SAP DB:ODBC Installation guide

mxODBC
ODBC Database Interface
for Python
Veersion
rsion 3
.3
3.3
Copyright  1997-2000 by IKDS Marc-André Lemburg, Langenfeld
Copyright  2000-2015 by eGenix.com GmbH, Langenfeld
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Printed in Germany.
Contents
Contents
1.
Introduction..........................................................1
1.1
Technical Overview............................................................. 1
1.2
Features............................................................................... 2
1.3
Requirements ...................................................................... 4
Windows.......................................................................................... 4
Unix ................................................................................................. 4
Mac OS X ......................................................................................... 5
2.
Installation ............................................................6
2.1
Download the Software....................................................... 6
2.1.1
Automatic download ............................................................................. 6
2.1.2
Manual Download ................................................................................. 6
Operating System Platform............................................................... 7
Python Build Version ........................................................................ 7
Python Build Architecture (32 bit or 64 bit) ...................................... 7
Unicode Variant (UCS2 or UCS4)..................................................... 7
2.2
Installation using Windows installers................................... 8
2.2.1
Prerequisites.......................................................................................... 8
2.2.2
Before You Start..................................................................................... 8
Upgrading ........................................................................................ 8
License Files ..................................................................................... 9
2.2.3
Step-by-step Installation Guide.............................................................. 9
Step 1............................................................................................... 9
mxODBC - Python ODBC Database Interface
Step 2 ............................................................................................. 10
Step 3 ............................................................................................. 10
Step 4 ............................................................................................. 10
2.2.4
Uninstall .............................................................................................. 10
2.3
Installation using egg package archives ............................. 11
Setuptools ...................................................................................... 11
2.3.2
Before You Start ................................................................................... 11
Upgrading....................................................................................... 11
License Files ................................................................................... 11
2.3.3
Step-by-step Installation Guide ............................................................ 12
Step 1 ............................................................................................. 12
Step 2 ............................................................................................. 12
Step 3 ............................................................................................. 13
Step 4 ............................................................................................. 13
2.3.4
Uninstall .............................................................................................. 14
2.4
Installation using prebuilt package archives ...................... 14
2.4.1
Before You Start ................................................................................... 14
Upgrading....................................................................................... 14
License Files ................................................................................... 14
2.4.2
Step-by-step Installation Guide ............................................................ 15
Step 1 ............................................................................................. 15
Step 2 ............................................................................................. 15
Step 3 ............................................................................................. 16
Step 4 ............................................................................................. 16
2.4.3
Uninstall .............................................................................................. 16
Automatic Uninstall ........................................................................ 16
Manual Uninstall ............................................................................ 17
3.
Access Databases using mxODBC ..................... 18
3.1
ODBC Application Stack ................................................... 18
3.1.1
Architecture: 32-bit vs. 64-bit .............................................................. 18
3.2
Accessing Databases from Windows................................. 19
Contents
3.2.1
Looking for Windows ODBC Drivers ? ................................................ 19
3.2.2
Installing Windows ODBC Drivers ...................................................... 20
3.2.3
Setting up an ODBC Data Source ........................................................ 20
ODBC on 64-bit Windows Versions ............................................... 20
3.2.4
ODBC Configuration Files ................................................................... 20
ODBC.INI - ODBC Data Source Configuration............................... 21
[ODBC]..................................................................................... 21
[ODBC Data Sources] ............................................................... 21
ODBCINST.INI - ODBC Driver Configuration................................. 21
[ODBC Drivers] ........................................................................ 21
Windows Registry Keys .................................................................. 21
HKEY_LOCAL_MACHINE\Software\ODBC\ODBC.INI ............... 21
HKEY_LOCAL_MACHINE\Software\ODBC\ODBCINST.INI........ 21
HKEY_CURRENT_USER\Software\ODBC\ODBC.INI .................. 21
3.2.5
Available Data Source Types (DSNs).................................................... 22
User Data Sources (User-DSN) ...................................................... 22
System Data Sources (System-DSN)............................................... 22
File Data Sources (File-DSN) .......................................................... 22
3.2.6
DSN-less Connections......................................................................... 23
Pros and Cons of using DSN-less Connections............................... 23
DNS-less Connection String ........................................................... 23
3.3
Accessing Databases from Unix ........................................ 24
3.3.1
Looking for Unix ODBC Drivers ?........................................................ 24
3.3.2
mxODBC Connect - a general purpose client-server solution .............. 24
3.3.3
Installing Unix ODBC Drivers.............................................................. 25
3.3.4
Setting up an ODBC Data Source ........................................................ 25
3.3.5
ODBC Configuration Files ................................................................... 26
/etc/odbc.ini - System ODBC Data Source Configuration ............... 26
[ODBC]..................................................................................... 26
[ODBC Data Sources] ............................................................... 27
~/.odbc.ini - User ODBC Data Source Configuration ..................... 27
/etc/odbcinst.ini - System ODBC Driver Configuration ................... 27
[ODBC]..................................................................................... 27
[ODBC Drivers] ........................................................................ 28
~/.odbcinst.ini - User ODBC Driver Configuration......................... 28
Environment Variables: ODBCINI and ODBCINSTINI .................... 28
ODBCINI .................................................................................. 28
ODBCINSTINI ........................................................................... 28
mxODBC - Python ODBC Database Interface
3.3.6
Available Data Source Types (DSNs).................................................... 29
User Data Sources (User-DSN)....................................................... 29
System Data Sources (System-DSN) ............................................... 29
File Data Sources (File-DSN)........................................................... 30
3.3.7
DSN-less Connections ......................................................................... 30
Pros and Cons of using DSN-less Connections ............................... 30
DNS-less Connection String............................................................ 31
4.
Accessing Popular Databases ............................ 32
4.1
MS SQL Server.................................................................. 32
4.1.1
Available ODBC Drivers ...................................................................... 32
MS SQL Server Native Client for SQL Server 2005, 2008 and later . 32
Finding the latest version of the SQL Server Native Client for
Windows ................................................................................... 32
Use mxODBC direct execution methods for better performance33
Optimizing SQL Server Native Client Access Method ................ 33
Configuring the SQL Server Native Client Network Protocol...... 33
Multiple active result sets (MARS) on a single connection ......... 34
Parameter Binding with SQL Server 2012 and later.................... 34
Stored procedures with output parameters and result sets ........ 34
MS SQL Server ODBC Driver for SQL Server 2000......................... 35
Configuring the SQL Server ODBC Driver Client Network
Protocol..................................................................................... 35
MS SQL Server Native Client for Linux............................................ 35
Driver Limitations ...................................................................... 36
Example Configuration for Unix................................................. 36
EasySoft ODBC Driver for SQL Server ............................................ 37
OpenLink ODBC Driver for SQL Server .......................................... 37
DataDirect ODBC Driver for SQL Server ........................................ 37
Actual Technologies Mac OS X ODBC Driver for SQL Server.......... 37
FreeTDS Unix ODBC Driver for SQL Server................................... 37
Driver Limitations ...................................................................... 37
Example Configuration for Unix................................................. 38
4.1.2
General Notes...................................................................................... 39
ODBC API Extensions and the SQL Server Native Client................. 39
Static vs. forward-only Cursors ....................................................... 39
Timestamp Resolution .................................................................... 39
Multiple Cursors on Connections / MARS....................................... 40
International Character Data........................................................... 40
Contents
Access Violations............................................................................ 41
Distributed Transaction Managers .................................................. 41
Kerberos / Windows Integrated Authentication............................... 41
MS SQL Server Native Client for Windows................................ 41
MS SQL Server Native Client for Linux ...................................... 42
EasySoft SQL Server Driver for Linux ......................................... 42
FreeTDS ODBC Driver for Linux................................................ 42
Kerberos on Linux ..................................................................... 42
Other Common Problems and Solutions ........................................ 42
4.2
MS Access Database ......................................................... 43
4.2.1
Available ODBC Drivers ...................................................................... 43
MS Access ODBC Driver................................................................ 43
MDBTools ODBC Driver ................................................................ 43
4.3
Oracle ............................................................................... 43
4.3.1
Available ODBC Drivers ...................................................................... 43
Oracle Instant Client ODBC driver ................................................. 43
Driver Notes ............................................................................. 44
Example Configuration for Unix................................................. 44
EasySoft ODBC Driver for Oracle................................................... 45
OpenLink ODBC Driver for Oracle................................................. 45
DataDirect ODBC Driver for Oracle............................................... 45
Actual Technologies Mac OS X ODBC Driver for Oracle ................ 45
4.3.2
General Notes ..................................................................................... 46
Oracle tnsnames.ora file................................................................. 46
4.4
IBM DB2 ........................................................................... 46
4.4.1
Available ODBC Drivers ...................................................................... 46
IBM ODBC Driver for Unix/Windows DB2 servers......................... 46
Example Configuration for Unix................................................. 46
IBM ODBC Driver for iSeries / AS/400 DB2 servers........................ 47
OpenLink ODBC Driver for DB2 .................................................... 47
DataDirect ODBC Driver for DB2 .................................................. 47
4.4.2
General Notes ..................................................................................... 47
ODBC API Extensions and the IBM CLI .......................................... 47
Configuring Database Access ......................................................... 47
Environment Variables on Unix ...................................................... 47
Linker Paths.................................................................................... 48
Database Setup for ODBC Access .................................................. 48
mxODBC - Python ODBC Database Interface
Static vs. forward-only Cursors ....................................................... 48
4.5
Sybase ASE........................................................................ 49
4.5.1
Available ODBC Drivers ...................................................................... 49
Sybase ASE ODBC driver ................................................................ 49
NULL issues with Sybase ASE ODBC driver ............................... 49
Segfaults with Sybase ASE ODBC driver 15.7 ............................ 49
BIGINT columns can cause data corruption ............................... 49
Driver Notes.............................................................................. 50
Example Configuration for Unix................................................. 50
EasySoft ODBC Driver for Sybase................................................... 51
OpenLink ODBC Driver for Sybase................................................. 51
DataDirect ODBC Driver for Sybase............................................... 51
Actual Technologies Mac OS X ODBC Driver for Sybase ................ 51
4.6
PostgreSQL ....................................................................... 51
4.6.1
Available ODBC Drivers ...................................................................... 51
PostgreSQL ODBC Driver............................................................... 51
Driver Notes.............................................................................. 51
Example Configuration for Unix................................................. 52
EasySoft ODBC Driver for PostgreSQL ........................................... 52
OpenLink ODBC Driver for PostgreSQL ......................................... 52
DataDirect ODBC Driver for PostgreSQL ....................................... 52
Actual Technologies Mac OS X ODBC Driver for PostgreSQL......... 53
4.7
MySQL.............................................................................. 53
4.7.1
Available ODBC Drivers ...................................................................... 53
MySQL ODBC Driver ..................................................................... 53
Driver Notes.............................................................................. 53
Example Configuration for Unix................................................. 54
OpenLink ODBC Driver for MySQL................................................ 54
DataDirect ODBC Driver for MySQL .............................................. 54
Actual Technologies Mac OS X ODBC Driver for MySQL ............... 55
4.7.2
General Notes...................................................................................... 55
4.8
SAP MaxDB / SAPDB......................................................... 55
4.8.1
Available ODBC Drivers ...................................................................... 55
MaxDB ODBC driver ...................................................................... 55
Example Configuration for Unix................................................. 55
4.8.2
General Database Notes ...................................................................... 56
Contents
Warnings when deleting/update more than one row at a time........ 56
4.9
Teradata ............................................................................ 56
4.9.1
Available ODBC Drivers ...................................................................... 56
Teradata ODBC Driver ................................................................... 56
Driver Notes ............................................................................. 57
Example Configuration for Unix................................................. 58
DataDirect ODBC Driver for Teradata ............................................ 59
4.10
Netezza ............................................................................. 59
4.10.1
Available ODBC Drivers ...................................................................... 59
Netezza ODBC Driver .................................................................... 59
Recommended Setup ................................................................ 59
Netezza and Unicode ................................................................ 60
Example Configuration for Unix................................................. 60
DataDirect ODBC Driver for Netezza............................................. 61
4.11
Other Databases ............................................................... 61
4.11.1
EasySoft ODBC Driver Packages.......................................................... 61
4.11.2
OpenLink............................................................................................. 61
4.11.3
DataDirect........................................................................................... 61
4.11.4
Other Vendors..................................................................................... 61
4.11.5
Alternative solution: mxODBC Connect .............................................. 62
5.
mxODBC Overview ............................................63
5.1
mxODBC and the Python Database API Specification ....... 63
5.1.1
Differences .......................................................................................... 63
5.1.2
Extensions ........................................................................................... 64
5.2
mxODBC and the ODBC Specification.............................. 64
5.2.1
Full access to most ODBC features...................................................... 64
5.3
Supported ODBC Versions................................................ 65
5.3.1
ODBC Managers ................................................................................. 65
5.3.2
Changes between ODBC 2.x and 3.x................................................... 65
mxODBC - Python ODBC Database Interface
5.4
Thread Safety & Thread Friendliness ................................. 66
5.4.1
Connections and Cursors..................................................................... 66
5.4.2
Unlocking the Python Global Interpreter Lock (GIL)............................. 66
5.4.3
Threading Support ............................................................................... 66
5.5
Transaction Support .......................................................... 66
5.5.1
Auto-Commit....................................................................................... 66
5.5.2
Manual Commit................................................................................... 67
Transaction Start and End ............................................................... 67
Data Sources without Transaction Support ..................................... 67
5.5.3
Adjusting the Connection Commit Mode............................................. 68
5.6
Stored Procedures............................................................. 68
5.6.1
Calling Stored Procedures with .callproc() ........................................... 68
Retrieving output parameters from stored procedures .................... 69
Retrieving result sets from stored procedures ................................. 69
5.6.2
Calling Stored Procedures with cursor.execute*() Methods ................. 69
Retrieving output parameters from stored procedures .................... 70
Retrieving result sets from stored procedures ................................. 71
5.6.3
Input/Output and Output Parameters .................................................. 71
parametertypes Parameter .............................................................. 71
SQL.PARAM_INPUT .................................................................. 72
SQL.PARAM_OUTPUT............................................................... 72
SQL.PARAM_INPUT_OUTPUT .................................................. 72
Dynamically determining the Parameter Type................................. 72
5.6.4
Special constraints of some ODBC drivers........................................... 73
Mixing output parameters and output result sets............................ 73
Using None as value for output parameters .................................... 73
5.6.5
Using Result Sets for passing back Output Data .................................. 74
Using result sets to pass back output data ...................................... 74
MS SQL Server and Sybase ASE Cursors in Stored Procedures........ 74
Oracle Ref Cursors as Output Parameters....................................... 75
IBM DB2 Cursors in Stored Procedures .......................................... 75
PostgreSQL Cursors in Stored Procedures ...................................... 75
5.6.6
SQL Output Statements in Stored Procedures...................................... 76
5.7
Introspection..................................................................... 76
Contents
5.7.1
Database Schema Introspection........................................................... 76
5.7.2
Result Set Introspection ....................................................................... 76
Introspection via cursor.execute() .................................................. 77
Introspection via cursor.prepare() .................................................. 77
The cursor.description attribute...................................................... 77
name [0] ................................................................................... 77
type_code [1] ............................................................................ 77
display_size [2] ......................................................................... 77
internal_size [3]......................................................................... 77
precision [4].............................................................................. 77
scale [5] .................................................................................... 77
null_ok [6]................................................................................. 78
The cursor.getcolattribute() method ............................................... 78
5.8
ODBC Cursor Types.......................................................... 78
5.8.1
Adjusting/Inspecting the ODBC Cursor Type ....................................... 78
SQL.CURSOR_FORWARD_ONLY.............................................. 78
SQL.CURSOR_STATIC............................................................... 79
SQL.CURSOR_KEYSET_DRIVEN ................................................ 79
SQL.CURSOR_DYNAMIC.......................................................... 79
5.8.2
Default Cursor Type ............................................................................ 79
5.8.3
Effects of the Cursor Type on cursor.rownumber ................................ 80
5.8.4
Database Specific Cursor Type Notes .................................................. 80
MS SQL Server ............................................................................... 80
Oracle ............................................................................................ 80
PostgreSQL..................................................................................... 81
IBM DB2 ........................................................................................ 81
5.9
Custom Cursor Row Objects and Row Factory Functions.. 81
5.9.1
Cursor Row Constructor: cursor.row................................................... 81
Attribute Inheritance: cursor.row and connection.row ................... 82
5.9.2
Cursor Row Factories: cursor.rowfactory............................................. 82
On-the-fly Creation of Row Classes................................................ 82
Row Factories and multiple Result Sets........................................... 83
Predefined Row Factories ............................................................... 83
RowFactory.TupleRowFactory ................................................... 83
RowFactory.ListRowFactory....................................................... 83
RowFactory.NamespaceRowFactory.......................................... 84
Factory created Row Classes and pickle ......................................... 85
Attribute Inheritance: cursor.rowfactory and connection.rowfactory85
mxODBC - Python ODBC Database Interface
5.10
mxODBC Subpackages ..................................................... 85
5.10.1
One API for all Subpackages ................................................................ 86
6.
mxODBC Connection Objects........................... 87
6.1
Subpackage Support ......................................................... 87
6.2
Connection Type Object ................................................... 87
6.3
Connection Object Constructors ...................................... 87
6.4
Default Transaction Settings.............................................. 89
6.4.1
Overriding the Default ......................................................................... 89
6.4.2
Errors due to missing Transaction Support........................................... 90
6.5
Connection objects as context managers .......................... 90
6.5.1
Introduction to Context Managers ....................................................... 90
6.5.2
Using connection objects as context object ......................................... 90
6.6
Unicode/ANSI Connections............................................... 91
6.6.1
Unicode ODBC Interface ..................................................................... 91
6.6.2
ANSI ODBC Interface .......................................................................... 91
6.7
Connection Object Methods............................................. 92
Connect(dsn, user='', password='', clear_auto_commit=1,
errorhandler=None, connection_options=())............................ 87
connect(dsn, user='', password='', clear_auto_commit=1,
errorhandler=None).................................................................. 88
DriverConnect(DSN_string, clear_auto_commit=1,
errorhandler=None).................................................................. 88
ODBC(dsn, user='', password='', clear_auto_commit=1,
errorhandler=None).................................................................. 89
.close() ...................................................................................... 92
.commit() .................................................................................. 92
.cursor(name=None, cursor_options=()).................................. 92
.getconnectoption(option) ......................................................... 92
.getinfo(info_id) ......................................................................... 92
.nativesql(command) ................................................................. 93
.rollback() .................................................................................. 93
Contents
.setconnectoption(option, value) ............................................... 93
.__enter__()............................................................................... 94
.__exit__(exc_type, exc_value, exc_tb) ...................................... 94
6.8
Connection Object Attributes............................................ 94
.autocommit.............................................................................. 94
.bindmethod ............................................................................. 94
.closed ...................................................................................... 94
.converter.................................................................................. 94
.cursortype ................................................................................ 95
SQL.CURSOR_FORWARD_ONLY.............................................. 95
SQL.CURSOR_STATIC............................................................... 95
SQL.CURSOR_KEYSET_DRIVEN ................................................ 95
SQL.CURSOR_DYNAMIC.......................................................... 95
.datetimeformat......................................................................... 95
DATETIME_DATETIMEFORMAT (default) .................................. 95
PYDATETIME_DATETIMEFORMAT ............................................ 95
TIMEVALUE_DATETIMEFORMAT .............................................. 95
TUPLE_DATETIMEFORMAT....................................................... 96
STRING_DATETIMEFORMAT .................................................... 96
.dbms_name ............................................................................. 96
.dbms_version........................................................................... 96
.decimalformat .......................................................................... 96
FLOAT_DECIMALFORMAT (default).......................................... 96
DECIMAL_DECIMALFORMAT ................................................... 96
.driver_name ............................................................................. 96
.driver_version .......................................................................... 96
.encoding .................................................................................. 96
.errorhandler ............................................................................. 97
.license...................................................................................... 97
.messages ................................................................................. 97
.paramstyle ............................................................................... 97
'qmark' (default) ........................................................................ 97
'named'...................................................................................... 98
.row .......................................................................................... 98
.rowfactory................................................................................ 98
.stringformat ............................................................................. 98
EIGHTBIT_STRINGFORMAT (default) ........................................ 98
MIXED_STRINGFORMAT .......................................................... 99
UNICODE_STRINGFORMAT..................................................... 99
NATIVE_UNICODE_STRINGFORMAT ....................................... 99
.timestampresolution .............................................................. 100
.warningformat........................................................................ 100
ERROR_WARNINGFORMAT (default)...................................... 101
WARN_WARNINGFORMAT .................................................... 101
IGNORE_WARNINGFORMAT ................................................. 101
mxODBC - Python ODBC Database Interface
6.8.1
Additional Attributes .......................................................................... 101
7.
mxODBC Cursor Objects................................. 102
7.1
Relationship between Cursors and Connections ............. 102
7.1.1
Dependency on the Connection Object ............................................. 102
7.1.2
Using multiple Cursor Objects on a single Connection ...................... 102
7.2
Subpackage Support ....................................................... 103
7.3
Cursor objects as context managers................................ 103
7.3.1
Using cursor objects as context objects ............................................. 103
7.4
Cursor Type Object......................................................... 103
7.5
Cursor Object Constructors ............................................ 104
7.6
Cursor Object Methods .................................................. 104
connection.cursor(name=None, cursor_options=()) .............. 104
.callproc(procname, parameters=(), parametertypes=None) .. 104
.close() .................................................................................... 104
.execute(sqlcmd, parameters=(), direct=-1,
parametertypes=None) ........................................................... 104
'qmark'(default)........................................................................ 105
'named' .................................................................................... 105
.executedirect(sqlcmd, parameters=(), parametertypes=None)106
.executemany(sqlcmd, batch=(), direct=0,
parametertypes=None) ........................................................... 106
.fetchall() ................................................................................. 106
.fetchmany([size=cursor.arraysize]) ........................................ 106
.fetchone()............................................................................... 107
.flush()..................................................................................... 107
.getcolattribute(position, info_id)............................................. 107
.getcursorname() ..................................................................... 109
.getcursoroption(option).......................................................... 109
.next()...................................................................................... 110
.nextset() ................................................................................. 110
.prepare(sqlcmd) ..................................................................... 111
.scroll(value, mode='relative').................................................. 111
.setconverter(converter) .......................................................... 111
.setcursorname(name)............................................................. 111
.setcursoroption(option, value)................................................ 112
Contents
.setinputsizes(sizes) ................................................................ 113
.setoutputsize(size[, column]) ................................................. 113
.__iter__()................................................................................ 113
.__enter__()............................................................................. 113
.__exit__(exc_type, exc_value, exc_tb) .................................... 113
7.6.1
Catalog Methods ............................................................................... 113
Common Interface ....................................................................... 114
Result Set Layouts ........................................................................ 114
Search Pattern Parameters............................................................ 114
Case-sensitivity of Search Patterns .......................................... 114
Switching between Search Patterns and Identifier Matching.... 115
Unicode ....................................................................................... 115
Available Catalog Methods ........................................................... 115
.columns(qualifier=None, owner=None, table=None,
column=None) ....................................................................... 115
.columnprivileges(qualifier=None, owner=None, table=None,
column=None) ....................................................................... 118
.foreignkeys(primary_qualifier=None, primary_owner=None,
pimary_table=None, foreign_qualifier=None,
foreign_owner=None, foreign_table=None) .......................... 119
primary_table .......................................................................... 119
foreign_table ........................................................................... 119
.gettypeinfo(sqltype) ............................................................... 120
.primarykeys(qualifier=None, owner=None, table=None)..... 123
.procedures(qualifier=None, owner=None, procedure=None)124
.procedurecolumns(qualifier=None, owner=None,
procedure=None, column=None).......................................... 125
.specialcolumns(qualifier=None, owner=None, table=None,
coltype=SQL.BEST_ROWID, scope=SQL.SCOPE_SESSION,
nullable=SQL.NO_NULLS) ..................................................... 128
SQL_BEST_ROWID ................................................................. 128
SQL_ROWVER ........................................................................ 128
SQL.SCOPE_CURROW ........................................................... 128
SQL.SCOPE_TRANSACTION ................................................... 128
SQL.SCOPE_SESSION ............................................................. 128
SQL.NO_NULLS ...................................................................... 128
SQL.NULLABLE ....................................................................... 128
.statistics(qualifier=None, owner=None, table=None,
unique=SQL.INDEX_ALL, accuracy=SQL.QUICK) .................. 130
SQL.INDEX_UNIQUE .............................................................. 130
SQL.INDEX_ALL ...................................................................... 130
SQL.ENSURE ........................................................................... 130
SQL.QUICK............................................................................. 130
.tables(qualifier=None, owner=None, table=None, type=None)132
.tableprivileges(qualifier=None, owner=None, table=None) . 133
mxODBC - Python ODBC Database Interface
7.7
Cursor Object Attributes................................................. 134
8.
Data Types supported by mxODBC ................ 139
8.1
mxODBC Parameter Binding .......................................... 139
8.1.1
Parameter Binding Styles ................................................................... 140
8.2
mxODBC Input Binding Modes ...................................... 141
8.2.1
Adjusting the Type Binding Mode ...................................................... 142
Per Connection Type Binding Setting ............................................ 142
Per Cursor Type Binding Setting ................................................... 142
Per-Statement Binding Mode ........................................................ 142
8.3
SQL Type Input Binding .................................................. 143
8.4
Python Type Input Binding.............................................. 147
8.5
Output Conversions........................................................ 149
.arraysize ................................................................................. 134
.bindmethod............................................................................ 134
.closed..................................................................................... 134
.colcount ................................................................................. 134
.command ............................................................................... 134
.connection ............................................................................. 135
.converter ................................................................................ 135
.cursortype .............................................................................. 135
.datetimeformat....................................................................... 135
.decimalformat ........................................................................ 135
.description ............................................................................. 135
.encoding ................................................................................ 136
.messages................................................................................ 136
.paramcount ............................................................................ 136
.paramstyle.............................................................................. 136
'qmark' (default)....................................................................... 136
'named' .................................................................................... 137
.row......................................................................................... 137
.rowfactory .............................................................................. 137
.rowcount................................................................................ 138
.rownumber ............................................................................ 138
.stringformat............................................................................ 138
.timestampresolution............................................................... 138
.warningformat ........................................................................ 138
Contents
8.6
Output Type Converter Functions ................................... 151
8.6.1
Converter Function Signatures........................................................... 152
position ................................................................................... 152
sqltype .................................................................................... 152
sqllen ...................................................................................... 152
binddata .................................................................................. 152
8.6.2
Adjusting/Querying the Converter Function....................................... 153
8.6.3
Example Converter Function.............................................................. 153
8.7
Auto-Conversions............................................................ 153
8.8
Unicode and String Data Encodings ................................ 154
8.9
Additional Comments...................................................... 155
9.
DB-API Type Objects and Constructors ...........156
10.
mxODBC Exceptions and Error Handling ........158
10.1
Exception Classes ............................................................ 158
Date(year,month,day) ............................................................. 156
Time(hour,minute,second) ...................................................... 156
Timestamp(year,month,day,hour,minute,second) ................... 156
DateFromTicks(ticks) .............................................................. 156
TimeFromTicks(ticks) .............................................................. 157
TimestampFromTicks(ticks)..................................................... 157
Binary(string)........................................................................... 157
STRING ................................................................................... 157
BINARY ................................................................................... 157
NUMBER................................................................................. 157
DATETIME............................................................................... 157
ROWID ................................................................................... 157
Error........................................................................................ 158
Warning .................................................................................. 159
InterfaceError .......................................................................... 159
DatabaseError ......................................................................... 159
DataError ................................................................................ 159
OperationalError ..................................................................... 159
IntegrityError ........................................................................... 159
InternalError ............................................................................ 159
mxODBC - Python ODBC Database Interface
ProgrammingError ................................................................... 159
NotSupportedError .................................................................. 159
10.2
SQL Error Mappings........................................................ 160
10.3
Exception Value Format .................................................. 160
10.4
Error Handlers ................................................................ 161
errorclass................................................................................. 160
sqlstate .................................................................................... 160
sqlcode.................................................................................... 160
messagetext............................................................................. 160
lineno ...................................................................................... 160
Error handler signature ................................................................. 161
Default error handler .................................................................... 161
Error processing ........................................................................... 161
10.4.2
Examples ........................................................................................... 162
10.5
Warning Classes ............................................................. 163
10.6
Database Warnings ......................................................... 163
10.6.1
Default Error Handler ........................................................................ 163
ERROR_WARNINGFORMAT (default)...................................... 164
WARN_WARNINGFORMAT .................................................... 164
IGNORE_WARNINGFORMAT.................................................. 164
10.6.2
Custom Warning Error Handler ......................................................... 164
11.
mxODBC Functions.......................................... 166
11.1
Subpackage Functions..................................................... 166
11.2
mx.ODBC Functions ....................................................... 167
DatabaseWarning .................................................................... 163
DataSources().......................................................................... 166
getenvattr(option).................................................................... 166
setenvattr(option, value).......................................................... 166
statistics() ................................................................................ 167
format_resultset(cursor, headers=None, colsep=' | ',
headersep='-', stringify=repr) ................................................. 167
print_resultset(cursor, headers=None) ................................... 167
Contents
12.
mxODBC Globals and Constants .....................168
12.1
Subpackage Globals and Constants ................................. 168
12.2
mx.ODBC Globals and Constants ................................... 170
13.
mx.ODBC.Misc.RowFactory Module................171
BIND_USING_SQLTYPE, BIND_USING_PYTHONTYPE ........... 168
CHAR, VARCHAR, LONGVARCHAR, BINARY, VARBINARY,
LONGVARBINARY, TINYINT, SMALLINT, INTEGER, BIGINT,
DECIMAL, NUMERIC, BIT, REAL, FLOAT, DOUBLE, DATE, TIME,
TIMESTAMP [, CLOB, BLOB, TYPE_DATE, TYPE_TIME,
TYPE_TIMESTAMP, UNICODE, UNICODE_LONGVARCHAR,
UNICODE_VARCHAR, WCHAR, WVARCHAR,
WLONGVARCHAR]................................................................. 168
DATETIME_DATETIMEFORMAT,
PYDATETIME_DATETIMEFORMAT,
TIMEVALUE_DATETIMEFORMAT, TUPLE_DATETIMEFORMAT,
STRING_DATETIMEFORMAT .................................................. 168
EIGHTBIT_STRINGFORMAT, MIXED_STRINGFORMAT,
UNICODE_STRINGFORMAT,
NATIVE_UNICODE_STRINGFORMAT ..................................... 169
ERROR_WARNINGFORMAT, WARN_WARNINGFORMAT,
IGNORE_WARNINGFORMAT ................................................. 169
FLOAT_DECIMALFORMAT, DECIMAL_DECIMALFORMAT ..... 169
HAVE_UNICODE_SUPPORT ................................................... 169
RowFactory ............................................................................. 169
SQL ......................................................................................... 169
apilevel.................................................................................... 169
errorclass ................................................................................ 169
license..................................................................................... 170
paramstyle .............................................................................. 170
sqltype .................................................................................... 170
threadsafety ............................................................................ 170
Error, Warning, InterfaceError, DatabaseError, DataError,
OperationalError, IntegrityError, InternalError, ProgrammingError,
NotSupportedError.................................................................. 170
Classes ......................................................................................... 171
Row......................................................................................... 171
Functions ..................................................................................... 171
TupleRowFactory(cursor) ........................................................ 171
ListRowFactory(cursor)............................................................ 171
NamespaceRowFactory(cursor)............................................... 171
mxODBC - Python ODBC Database Interface
14.
mx.ODBC Driver/Manager Packages............... 173
14.1
Driver/Manager Subpackage Notes ................................. 173
14.1.1
Windows Platform Notes ................................................................... 173
14.1.2
Unix Platform Notes .......................................................................... 173
14.2
mx.ODBC.Manager -- Generic ODBC Driver Manager ... 173
Windows Platforms ...................................................................... 174
Unix Platforms.............................................................................. 174
14.3
mx.ODBC.Windows -- Windows ODBC Driver Manager 174
14.3.1
Connecting to a Database .................................................................. 174
14.3.2
Supported Datatypes ......................................................................... 175
14.3.3
File Data Sources ............................................................................... 175
14.4
mx.ODBC.iODBC -- iODBC Driver Manager.................. 175
14.4.1
Notes................................................................................................. 175
General Recommendations........................................................... 175
64-bit Platforms ............................................................................ 176
14.5
mx.ODBC.unixODBC -- unixODBC Driver Manager ...... 176
14.5.1
Notes................................................................................................. 177
General Recommendations........................................................... 177
Debugging ODBC Configurations................................................. 177
Finding the cause using an ODBC trace................................... 177
Finding the cause using a custom error handler....................... 177
64-bit Platforms ............................................................................ 178
Threading ..................................................................................... 179
14.6
mx.ODBC.DataDirect -- DataDirect ODBC Manager...... 179
14.6.1
Notes................................................................................................. 180
General Recommendations........................................................... 180
64-bit Platforms ............................................................................ 180
14.7
ODBC Driver Subpackages ............................................. 180
Contents
15.
Hints & Links to other Resources.....................182
15.1
Running mxODBC from a CGI script............................... 182
15.2
Running mxODBC with mod_wsgi.................................. 182
mod_wsgi and Python 2.7 ............................................................ 182
Manifest work-around ............................................................. 183
15.3
Freezing mxODBC using py2exe ..................................... 183
15.4
More Sources of Information........................................... 183
16.
Examples ...........................................................185
17.
Testing the Database Connection ....................187
18.
mxODBC Package Structure ............................188
19.
Support .............................................................189
19.1
ODBC Call Level Tracing ................................................. 189
19.1.1
Windows ODBC Manager ................................................................. 189
19.1.2
iODBC Driver Manager ..................................................................... 190
19.1.3
unixODBC Driver Manager ............................................................... 190
19.1.4
DataDirect ODBC Driver Manager .................................................... 190
19.1.5
Mac OS X ODBC Driver Manager...................................................... 191
19.2
mxODBC Call Level Tracing ............................................ 191
20.
History & Changes ............................................192
mxODBC - Python ODBC Database Interface
21.
Copyright & License ......................................... 193
1. Introduction
1.
Introduction
mxODBC has proven to be the most stable and versatile ODBC interface available
for Python. It has been in active use for more than a decade and is actively
maintained by eGenix.com to meet the requirements of modern database
applications which our customers have built on top of mxODBC.
This manual will give you an in-depth overview of mxODBC's capabilities and
features. It is written as technical manual, so background in Python and database
programming is needed.
mxODBC tries to hide many of the complicated details of the ODBC specification
from the user, but does provide access to many of the introspection APIs defined
in that standard. If you don't need introspection for your applications, you can
easily make use of mxODBC without any further knowledge of the underlying
ODBC interface.
1.1 Technical Overview
The mxODBC package provides a Python Database API 2.0 compliant interface to
databases that are accessible via the ODBC application programming interface
(API). Since ODBC is the de-facto standard for connecting to databases, this
allows connecting Python to most available databases on the market today.
Accessing the databases can be done through an ODBC manager, e.g. the ODBC
manager that comes with Windows, iODBC or unixODBC which are free ODBC
managers available for Unix, or the DataDirect ODBC manager, which is a
proprietary ODBC manager for Unix.
The package supports parallel database interfacing, meaning that you can access
multiple different databases from within one process, e.g. one database through
the iODBC manager and another through unixODBC.
mxODBC is customizable to many different needs via configuration attributes, e.g.
you can use the Python datetime module or the eGenix.xom mxDateTime package
for handling date/time value, eliminating the problems you often face when
handling dates before 1.1.1970 and after 2038.
It also supports the Python decimal module, long integer interfacing, Unicode,
large binary and text data, as well as stored procedures, prepared statements,
database introspection and in-flight customization of connections and cursors.
1
mxODBC - Python ODBC Database Interface
1.2 Features
•
Python Database API 2.0 Compliance: the mxODBC API is fully Python
DB-API 2.0 compatible and implements a large number of powerful
extensions.
•
Support for all recent ODBC Version : mxODBC works with ODBC
drivers implementing the ODBC version specifications 2.0 - 3.8.
•
Uses ODBC 3 APIs: provided the ODBC driver/manager is capable of
using ODBC 3 APIs, mxODBC will use them for added efficiency.
•
32-bit and 64-bit ODBC: mxODBC supports both 32-bit and 64-bit
versions of the ODBC standard - including special 64-bit builds on Unix.
•
Supports all major ODBC driver managers: mxODBC can work with the
MS ODBC Driver Manager on Windows, unixODBC, iODBC and the
DataDirect ODBC Driver Manager on Unix and the Mac OS X ODBC
Driver Manager on Mac OS X. If needed, multiple ODBC managers can
be used at the same time, giving you full flexibility.
•
Stable, robust and reliable: the mxODBC API has been in active
production use since 1997.
•
Stored Procedure / Function Calls: mxODBC support calling stored
procedures and functions, using output and input/output parameters, as
well as result sets for passing back data to Python.
•
ODBC Catalog & Introspection Functions: mxODBC Client API provides
methods e.g. to list tables, find column specifications, query index
relationships, etc.
•
Support for Multiple Result Sets: call stored procedures and access all
returned result sets using an easy to API. Easily free up resources in case
result sets are no longer needed.
•
Support for custom Row objects: in addition to using standard Python
tuples, mxODBC can automatically return result set rows as custom
objects. mxODBC comes with a set of optimized row factories for:
TupleRows, ListRows and NamespaceRows. All of these provide both
index and attribute access to row column fields.
•
Dynamic ODBC Configuration: adjust ODBC connection parameters
dynamically, e.g. set timeouts, read-only access, auto-commit, etc.
•
Many useful DB-API Extensions:
o
2
Adjustable .paramstyle: mxODBC supports both the ODBC
question mark positional parameter binding style as well as the
named parameter styles used by e.g. Oracle.
1. Introduction
•
1
o
cursor.scroll() to scroll the cursor in result sets without actually
fetching data.
o
cursor.prepare() to prepare SQL statements for execution,
without actually running them. This allows creating pools of
cursors for dedicated purposes.
o
connection.autocommit
autocommit feature
o
cursor and connection objects usable as context managers
o
cursor.executemany() accepts iterators/generators as parameter
"sequence".
o
cursor.cursortype to easily adjust the used ODBC cursor type to
your application's needs.
o
ODBC cursor/connection option methods to adjust ODBC
cursors/connections to your application's needs and optimize
performance by e.g. declaring a connection read-only.
to
easily
turn
on/off
the
ODBC
Configurable Data Type Mappings:
o
Supports Python type binding and Database type binding for
efficient data exchange.
o
Supports mxDateTime and Python's time and datetime modules
for date/time value exchange.
o
Supports standard Python floats, integers, longs and Python's
decimal module for loss-less numeric value exchange.
o
Supports Python 2.7 memoryview objects.
o
Automatically handles and supports unknown data types and
user data types via string conversion.
•
Full Unicode Support: use Unicode for managing text data in your client
applications - even if the database does not natively support Unicode,
mxODBC will automatically provide the necessary conversions on-the-fly.
mxODBC supports both the Unicode or the ANSI ODBC APIs. You can
chose the optimal approach for your driver.
•
Multi-Version Python Support: mxODBC works with Python 2.4, 2.5, 2.6
and 2.7.1
•
Full 64-bit Support: mxODBC runs on the following 64-bit platforms
natively: Windows, Linux, FreeBSD and Mac OS X.
Please note that mxODBC 3.3 will be the last release to support Python 2.4, 2.5 and 2.6.
The next release will only support Python 2.7 and Python 3.
3
mxODBC - Python ODBC Database Interface
•
Highly Portable Codebase: in addition to the already supported platforms
for mxODBC, eGenix.com provides custom porting services for more
exotic platforms.
•
Easy installation: using Windows installers, .egg file package or our
Python distutils compatible prebuilt Python packages.
•
Easy configuration: use ODBC manager GUI tools for easy configuration
of ODBC data sources, then access these data sources by name from
Python, or use a connection-less way to connect to databases by
specifying the driver name and database details in the application.
1.3 Requirements
mxODBC needs these environment on Windows, Unix or Mac OS X for successful
installation:
Windows
•
All Windows platforms starting with Windows 2000 are supported.
•
Python 2.4 or later needs to be installed and working.
•
The Windows version of the mxODBC uses the Windows ODBC manager
as ODBC manager, so you have to configure your ODBC data sources
using its GUI interface which is available through the system settings
folder. Alternatively, you can choose to use a DSN-less setup which
defines all connection details in the connection string.
•
You should setup at least one configured and running ODBC data source
for testing purposes.
Unix
4
•
SuSE and RedHat Linux distributions for x86 and x86_64 (AMD64/EM64T)
processors, FreeBSD and Sun Solaris are supported Unix platforms.
eGenix.com can also provide custom builds for other Unix platforms on
request. Please write to sales@egenix.com for details.
•
Python 2.4 or later needs to be installed and working.
•
On Linux, FreeBSD and Solaris, the binary package includes support for
the iODBC, the unixODBC and the DataDirect managers. You must have
at least one of these installed in order to be able to connect to ODBC data
sources. Please use the ODBC manager GUI interfaces to configure the
data sources. Alternatively, you can choose to use a DSN-less setup
which defines all connection details in the connection string.
1. Introduction
mx.ODBC.Manager prefers iODBC over unixODBC over DataDirect if
more than one ODBC driver manager is installed.
•
You should setup at least one configured and running ODBC data source
for testing purposes.
Mac OS X
•
Mac OS X 10.4/10.5 Intel and PPC 32-bit and Mac OS X 10.6 Intel 64-bit
are supported.
•
Python 2.4 or later needs to be installed and working.
•
Mac OS X uses a variant of iODBC as system ODBC manager. On Mac
OS X 10.4 and 10.5 this comes pre-installed with the system. On Mac OS
X 10.6, the ODBC manager is available from Apple as separate download.
Please use the ODBC manager GUI interfaces to configure the data
sources. Alternatively, you can choose to use a DSN-less setup which
defines all connection details in the connection string.
•
If you want to use the unixODBC manager from MacPorts instead of the
system iODBC manager, you first have to install unixODBC from the
MacPorts and then tell the Mac OS X linker where to find the ports
libraries by adjusting the environment variable DYLD_LIBRARY_PATH
prior to starting Python:
export DYLD_LIBRARY_PATH=/opt/local/lib
•
5
You should setup at least one configured and running ODBC data source
for testing purposes.
mxODBC - Python ODBC Database Interface
2.
Installation
The mxODBC database package is distributed as add-on for the eGenix.com mx
Base Distribution (egenix-mx-base).
Please visit the eGenix.com web-site to download the latest versions of both the
eGenix.com mx Base Distribution and the eGenix.com mxODBC distribution for
your platform and Python version.
IMPORTANT NOTE:
Before installing the egenix-mxodbc package, you will have to install the
egenix-mx-base distribution which contains packages needed by mxODBC.
Even though both distributions use the same installation procedure, please refer
to the egenix-mx-base installation instructions on how to install that package.
2.1 Download the Software
2.1.1 Automatic download
If you want to use .egg package archives for the mxODBC installation, package
tools such as easy_install or zc.buildout will download the archives automatically
from a special package index on the eGenix.com website.
A separate manual download is normally not needed. However, you can still
download the files manually and point the package tools directly at the
downloaded .egg package files, if needed. This may be needed in case the package
tools cannot determine which .egg package files to download.
For installation using Windows installers or our distutils compatible prebuilt
package format, you will also have to manually download the files.
2.1.2 Manual Download
You can download the binary archives (Windows installers, .egg files or prebuilt
archives) for your combination of platform, Python version and Unicode variant
from the eGenix.com web-site at http://www.egenix.com/.
6
2. Installation
Please make sure that you download the right version for your Python
installation. If you get import errors or notices of failed initialization, you likely
have the wrong product version installed.
These parameters make a difference:
Operating System Platform
All recent versions of these operating systems are supported:
•
Windows
•
Linux
•
Mac OS X
•
FreeBSD
Please check the eGenix.com web-site for the detailed list of available downloads
for these platforms.
If your platform is not among those listed above or on the web-site, eGenix also
provides custom porting services to have mxODBC ported to your platform.
Please write to sales@egenix.com for details.
Python Build Version
To check which Python version you are using, startup the Python interpreter using
the –V option:
python –V
This will print out the Python version number.
mxODBC supports Python versions 2.4 - 2.7 on most platforms.
Python Build Architecture (32 bit or 64 bit)
On most platforms, eGenix.com supports x86 32-bit and x86_64 (AMD64/EM64T)
64-bit versions of Python.
To find out which Python version you are using, run the following command:
python -c 'import struct; print struct.calcsize("P")*8,"bit"'
This will print out “32 bit” or “64 bit”.
Unicode Variant (UCS2 or UCS4)
On Unix and Mac OS X, Python can be built using two different Unicode variants:
UCS2 and UCS4. Windows builds are always UCS2 builds.
7
mxODBC - Python ODBC Database Interface
To find out which variant your Python version was compiled with, run the
following command:
python -c 'print "UCS%s"%len(u"x".encode("unicode-internal"))'
This will either print out “UCS2” or “UCS4”.
2.2 Installation using Windows installers
The installers provided by eGenix.com for use on Windows only include the
mx.ODBC.Windows subpackage of mxODBC. This subpackage interfaces directly
to the Microsoft ODBC Manager, so you can use all available Windows system
tools to configure your ODBC data sources.
2.2.1 Prerequisites
•
Please make sure that you have a working installation of the egenix-mxbase distribution prior to continuing with the installation of the egenixmxodbc add-on. You can easily check this by checking the Windows
Software Setup dialog for an entry of the form "Python x.x eGenix.com mx
Base Distribution" or by running the following at the command prompt:
python –c "import mx.DateTime"
If you get an import error, please visit the eGenix.com web-site and install
the egenix-mx-base package first.
•
You will need ODBC drivers for all databases you wish to connect to.
Windows comes with a very complete set of such drivers, but if you can't
find the driver you are looking for, have a look at 15. Hints & Links to
other Resources.
2.2.2 Before You Start
Upgrading
When upgrading from a previous version of mxODBC, you can normally install
the new version in place of the previous one. If you want to be extra careful, you
can also uninstall the previous version using the standard Windows software
setup tool. See 2.2.4 Uninstall for details.
If you used a different packaging format for installing the previous version, please
see the relevant installation section of this guide for instructions on how to
uninstall that variant.
8
2. Installation
License Files
In order to use mxODBC, you will need license files from eGenix.com.
If you want to test the product before buying it, you can request evaluation
licenses via the eGenix.com web-site at http://www.egenix.com/.
When buying licenses from the eGenix.com online shop (http://shop.egenix.com/),
you will receive the license files immediately after purchase.
In both cases, the license files are sent to the email address you specified during
the purchase process or from which you wrote the evaluation license request in
form of a ZIP license archive attached to the license email – usually named
licenses.zip.
The license archive licenses.zip contains one subdirectory per license you bought.
The directories are named after the license key for each license. A typical license
archive will have these contents:
2100-8789-0322-0926-2568-6429/mxodbc_license.py
2100-8789-0322-0926-2568-6429/mxodbc_license.txt
2100-8089-0312-0926-2668-6529/mxodbc_license.py
2100-8089-0312-0926-2668-6529/mxodbc_license.txt
(in the above example, the license archive contains the files for two product
licenses).
In order to install the license files, please unzip the license archive to a temporary
directory.
In order for mxODBC to pick up the correct license files, please copy them to a
location on your sys.path or PYTHONPATH. If you installed Python to e.g.
C:\Python27, the typical location for installation of the license files would be
C:\Python27\Lib\site-packages\.
Use the following command to see the sys.path that your Python version uses:
python -c "import sys; print ':'.join(sys.path)"
2.2.3 Step-by-step Installation Guide
Step 1
After you have downloaded the Windows installer of the egenix-mxodbc
distribution, double-click on the .exe file to start the installer.
9
mxODBC - Python ODBC Database Interface
Note:
Depending on your Python installation, you may need admin privileges on
Windows to successfully complete the installation.
Step 2
The installer will then ask you to accept the license, choose the Python version
and then to start the install process.
If the listbox showing the installed Python versions is empty, it is likely that you
have chosen the wrong Windows installer for your Python version. Please go back
to the eGenix.com web-site and download the correct version for the installed
Python version.
Step 3
In case you are upgrading to a new mxODBC version, the installer will ask you
whether you want to overwrite existing files. Answer "yes" to this question. It is
safe to allow the installer overwrite files.
The installer will then install all the needed files. Note that it does not setup any
links on the desktop or in the start menu.
Step 4
Test the installation by trying to import mxODBC:
$ python
>>> import mx.ODBC.Manager
>>>
If you don't get any ImportError, you have successfully installed mxODBC.
2.2.4 Uninstall
The Windows installer will automatically register the installed software with the
standard Windows software setup tool.
To uninstall the distribution, run the Windows Software Setup tool and select the
"Python x.x eGenix mxODBC x.x" entry for deinstallation.
This will uninstall all files that can safely be removed from the system. It will not
remove files which were added to the subpackages after installation, nor will it
remove the license files you manually installed.
10
2. Installation
2.3 Installation using egg package archives
We assume that you have already have setuptools and easy_install installed in your
Python installation. The examples in this section refer to a Unix or Mac OS X
installation, but it is also possible to install .egg packages on Windows.
You can check this by searching for easy_install in the directory where you've
installed the Python interpreter binary:
python -c "import setuptools; print 'setuptools installed'"
If this reports an ImportError, you don't have setuptools installed. In that case,
please see the next section.
Note that you can also use the information from this section to create a
zc.buildout setup.
Setuptools
In order to be able to install eggs, you need to install a Python package called
setuptools.
To get this package installed, download the file ez_setup.py from the URL
http://peak.telecommunity.com/dist/ez_setup.py and run it using the Python
interpreter that you will be using with mxODBC:
python ez_setup.py
This will install setuptools into your Python site-packages/ directory as well as a
script called easy_install in your bin/ directory. The easy_install script is later
need to install the mxODBC.
2.3.2 Before You Start
Upgrading
When upgrading from a previous version of mxODBC, you should uninstall the
egenix-mxodbc package first. Please see section 2.3.4 Uninstall for instructions.
License Files
In order to use mxODBC, you will need license files from eGenix.com.
If you want to test the product before buying it, you can request evaluation
licenses via the eGenix.com web-site at http://www.egenix.com/.
When buying licenses from the eGenix.com online shop (http://shop.egenix.com/),
you will receive the license files immediately after purchase.
11
mxODBC - Python ODBC Database Interface
In both cases, the license files are sent to the email address you specified during
the purchase process or from which you wrote the evaluation license request in
form of a ZIP license archive attached to the license email – usually named
licenses.zip.
The license archive licenses.zip contains one subdirectory per license you bought.
The directories are named after the license key for each license. A typical license
archive will have these contents:
2100-8789-0322-0926-2568-6429/mxodbc_license.py
2100-8789-0322-0926-2568-6429/mxodbc_license.txt
2100-8089-0312-0926-2668-6529/mxodbc_license.py
2100-8089-0312-0926-2668-6529/mxodbc_license.txt
(in the above example, the license archive contains the files for two product
licenses).
In order to install the license files, please unzip the license archive to a temporary
directory.
In order for mxODBC to pick up the correct license files, please copy them to a
location on your sys.path or PYTHONPATH. If you installed Python to e.g.
C:\Python27 on Windows or /usr/local/bin/python on Unix or Mac OS X, the
typical location for installation of the license files would be C:\Python27\Lib\sitepackages\ or /usr/local/lib/python2.7/site-packages/.
Use the following command to see the sys.path that your Python version uses:
python -c "import sys; print ';'.join(sys.path)"
2.3.3 Step-by-step Installation Guide
Step 1
Determine whether you are using a UCS2 or UCS4 build of Python (Windows
users always need the UCS2 version, Mac OS X should also try the UCS2 version
first, Unix users will most likely need the UCS4 version).
To find out which variant your Python version was compiled with, run the
following command:
python -c 'print("UCS%s"%len(u"x".encode("unicode-internal")))'
This will either print out “UCS2” or “UCS4”.
Step 2
Next, install the egenix-mxodbc egg package in your Python installation.
12
2. Installation
Note that you may need to have admin or root privileges in order to successfully
complete the following step, unless you are using a virtualenv-based setup.
If you got UCS2 in step 1, run the following command using the easy_install
script from the Python installation you intend to use:
easy_install -i http://downloads.egenix.com/python/index/ucs2/ \
egenix-mxodbc
If you got UCS4 in step 1, use this command:
easy_install -i http://downloads.egenix.com/python/index/ucs4/ \
egenix-mxodbc
If you manually downloaded the egg archive from the eGenix.com website to a
temporary directory, pass the file name directly to easy_install to start the
installation:
easy_install \
/path-to-egg-file/egenix_mxodbc-3.3.0-py2.7-win32.egg
(replace the file name with the one of the file you downloaded)
After installation, the egg file can be removed from the temporary directory
without causing harm.
For more information on how to use easy_install, please see the easy_install
documentation.
Step 3
Now that you have installed the product code, you need to install the proper
licenses in order for the mxODBC to startup correctly.
Go to the temporary directory where you unzipped the license archive and change
to the license subdirectory which contains the license for the installation you are
currently working on.
Copy the two files mxodbc_license.py and mxodbc_license.txt from the license
subdirectory to the Python site-packages/ directory.
Step 4
Test the installation by trying to import mxODBC:
$ python
>>> import mx.ODBC.Manager
>>>
If you don't get any ImportError, you have successfully installed mxODBC.
13
mxODBC - Python ODBC Database Interface
2.3.4 Uninstall
Since setuptools doesn't provide an uninstall command you have to manually
remove the installation:
1. remove the egenix-mxodbc.* egg directory from your Python sitepackages/ directory and
2. edit the file easy-install.pth in that directory to remove the corresponding
egg entry.
2.4 Installation using prebuilt package
archives
Prebuilt package archives are standard distutils source distribution packages,
which have been built on the respective platforms without performing the
installation step. The source parts are also removed from those packages.
You can think of the prebuilt packages as source package installations that were
frozen just before running the install command.
When installing these , you just need to run the last step after unpacking the
package: the distutils install command.
No additional software is needed to install these packages.
2.4.1 Before You Start
Upgrading
When upgrading from a previous version of mxODBC, you can either install the
new version over the previous version or first uninstall the previous version. See
section 2.4.3 Uninstall for instructions.
License Files
In order to use mxODBC, you will need license files from eGenix.com.
If you want to test the product before buying it, you can request evaluation
licenses via the eGenix.com web-site at http://www.egenix.com/.
When buying licenses from the eGenix.com online shop (http://shop.egenix.com/),
you will receive the license files immediately after purchase.
14
2. Installation
In both cases, the license files are sent to the email address you specified during
the purchase process or from which you wrote the evaluation license request in
form of a ZIP license archive attached to the license email – usually named
licenses.zip.
The license archive licenses.zip contains one subdirectory per license you bought.
The directories are named after the license key for each license. A typical license
archive will have these contents:
2100-8789-0322-0926-2568-6429/mxodbc_license.py
2100-8789-0322-0926-2568-6429/mxodbc_license.txt
2100-8089-0312-0926-2668-6529/mxodbc_license.py
2100-8089-0312-0926-2668-6529/mxodbc_license.txt
(in the above example, the license archive contains the files for two product
licenses).
In order to install the license files, please unzip the license archive to a temporary
directory.
In order for mxODBC to pick up the correct license files, please copy them to a
location on your sys.path or PYTHONPATH. If you installed Python to e.g.
C:\Python27 on Windows or /usr/local/bin/python on Unix or Mac OS X, the
typical location for installation of the license files would be C:\Python27\Lib\sitepackages\ or /usr/local/lib/python2.7/site-packages/.
Use the following command to see the sys.path that your Python version uses:
python -c "import sys; print ';'.join(sys.path)"
2.4.2 Step-by-step Installation Guide
Step 1
Determine whether you are using a UCS2 or UCS4 build of Python (Windows
users always need the UCS2 version, Mac OS X should also try the UCS2 version
first, Unix users will most likely need the UCS4 version).
To find out which variant your Python version was compiled with, run the
following command:
python -c 'print("UCS%s"%len(u"x".encode("unicode-internal")))'
This will either print out “UCS2” or “UCS4”.
Step 2
Next, install the egenix-mxodbc prebuilt package in your Python installation.
15
mxODBC - Python ODBC Database Interface
Note that you may need to have admin or root privileges in order to successfully
complete the following step, unless you are using a virtualenv-based setup.
1. First, unzip the downloaded prebuilt package archive to a temporary
directory.
2. Then run the following command using the Python installation you intend
to use in the package directory egenix-mxodbc-3.3.*/:
python setup.py install
Note that you can use the standard distutils install command options, e.g. to
install the package to a different prefix (using --prefix) or a home directory
(using --home). For more information on the available options, please have a look
at the distutils install command documentation.
After installation, you can remove the temporary directory without causing harm.
Please keep the prebuilt package archive around, in case you want to uninstall the
package again.
Step 3
Now that you have installed the product code, you need to install the proper
licenses in order for the mxODBC to startup correctly.
Go to the temporary directory where you unzipped the license archive and change
to the license subdirectory which contains the license for the installation you are
currently working on.
Copy the two files mxodbc_license.py and mxodbc_license.txt from the license
subdirectory to the Python site-packages/ directory.
Step 4
Test the installation by trying to import mxODBC:
$ python
>>> import mx.ODBC.Manager
>>>
If you don't get any ImportError, you have successfully installed mxODBC.
2.4.3 Uninstall
Automatic Uninstall
In order to uninstall the mxODBC package, run the setup.py of the installation
package using the uninstall command and the same options you passed to the
install command when you installed the package:
16
2. Installation
python setup.py uninstall
Manual Uninstall
If you no longer have the older installation package, just remove the sitepackages/mx/ODBC directory with all its subdirectories.
17
mxODBC - Python ODBC Database Interface
3.
Access Databases using mxODBC
mxODBC provides an easy to use way of accessing the ODBC API of ODBC
managers and drivers from Python. Together with a suitable ODBC driver installed
on the machine where you are running the Python application, you can connect to
your databases with a single Python call.
3.1 ODBC Application Stack
The typical ODBC application setup looks like this:
Python Application
↓
mxODBC
↓
ODBC Manager (Windows, unixODBC, iODBC, DataDirect)
↓
ODBC Driver
↓
(Network, Local Connection, Pipe, Shared Memory)
↓
Database
The upper blue part in the diagram executes within the process of the Python
application. The green part usually runs in a separate process and possibly also on
a different machine.
3.1.1 Architecture: 32-bit vs. 64-bit
As a result of this process setup outlined in the previous section, it is important
that you choose the right ODBC driver type for your application:
18
3. Access Databases using mxODBC
•
If you are running a 64-bit Python application, you will also have to have a
64-bit ODBC manager and ODBC driver installed.
•
If you are running a 32-bit Python application, you need an 32-bit ODBC
manager and ODBC driver.
Note that the ODBC manager may be capable of translating 32-bit or 64-bit
function calls to whatever the ODBC driver supports (this is called thunking).
Please check the documentation of your ODBC manager for details.
3.2 Accessing Databases from Windows
Most database ship with ODBC drivers for Windows, so setting up database
access for Python applications on Windows is fairly straight forward.
Once you’ve installed the ODBC drivers on the machine you are running your
Python application on, you will need to setup an ODBC Data Source. This can be
done using the ODBC Manager on Windows.
To avoid problems with system permissions, eGenix.com recommends setting up
System Data Sources, as these are usually accessible by all accounts on a
Windows machine.
Using
the
mxODBC
connection
constructor
mx.ODBC.Windows.DriverConnect() you can then setup a connection to the
database.
3.2.1 Looking for Windows ODBC Drivers ?
Microsoft supports a whole range of (desktop) ODBC drivers for various
databases and file formats. These are available under the name "ODBC Desktop
Database Drivers" (search the MS web-site for the exact URL) [wx1350.exe] and
also included in the more up-to-date "Microsoft Data Access Components"
(MDAC) archive [mdac_typ.exe].
It includes ODBC drivers for: Access, dBase, Excel, Oracle, Paradox, Text (flat file
CSV), FoxPro, MS SQL Server.
If you need to connect to databases running on other hosts, please contact the
database vendor or check the SQLSummit list of ODBC drivers.
19
mxODBC - Python ODBC Database Interface
3.2.2 Installing Windows ODBC Drivers
Please consult the documentation of your database for ODBC driver installation
instructions. These are usually installed in the same way as any other application
on Windows, but their respective setup wizards and options are usually different
in layout and depend on the target database.
3.2.3 Setting up an ODBC Data Source
Data sources are setup using the Windows ODBC Manager on Windows. This can
be found in the in the Control Panel as Administrative Tools and is called Data
Sources (ODBC). See the Windows ODBC documentation for details.
Starting the ODBC manager will bring up a dialog with tabs for data source
creation, ODBC tracing and connection pooling as well as a few information tabs
showing the versions of installed drivers.
ODBC on 64-bit Windows Versions
On 64-bit versions of Windows, there are two separate ODBC managers which
also keep and manage different lists of ODBC data sources: the 64-bit version can
be found in C:\windows\system32\odbcad32.exe, the 32-bit version is located in
C:\windows\sysWOW64\odbcad32.exe.
64-bit applications can only use the 64-bit ODBC manager and drivers, whereas
32-bit applications can only use the 32-bit ODBC manager and drivers.
Please make sure that you use the right variant of the ODBC manager when
configuring ODBC data sources on 64-bit Windows. If not, you will get errors
from the ODBC manager mentioning problems in finding the given ODBC data
source or an architecture mismatch, e.g. [Microsoft][ODBC Driver
Manager] The specified DSN contains an architecture mismatch
between the Driver and Application
3.2.4 ODBC Configuration Files
On Windows, you should always use the Windows ODBC Manager to configure
ODBC data sources.
Even though the Windows ODBC Manager also exposes the standard ODBC
configuration files C:\Windows\ODBC.INI and C:\Windows\ODBCINST.INI, these
do not contain the full configuration information, since this is stored in the
Windows registry.
20
3. Access Databases using mxODBC
ODBC.INI - ODBC Data Source Configuration
This INI-file provides data source information using one INI-section per data
source.
In addition to the data source sections, there are also a number of higher-level
sections:
[ODBC]
This section is used to configure driver related ODBC manager settings such as
ODBC call tracing. The settings in this section apply to all data sources.
[ODBC Data Sources]
This section contains one entry per configured data source, mapping the data
source name to a description.
ODBCINST.INI - ODBC Driver Configuration
This INI-file provides one INI-section per installed ODBC driver.
In addition to the data source sections, there are also a number of higher-level
sections:
[ODBC Drivers]
This section contains one entry per configured and installed ODBC driver,
mapping the driver name to the string "Installed".
Windows Registry Keys
The following registry keys provide the ODBC configuration information in much
the same way the formerly used INI-files did:
HKEY_LOCAL_MACHINE\Software\ODBC\ODBC.INI
One entry per INI-section of the ODBC.INI file, used for system-wide settings
and system DSNs. See section 3.2.5 Available Data Source Types (DSNs) for
details on the different DSN types.
HKEY_LOCAL_MACHINE\Software\ODBC\ODBCINST.INI
One entry per INI-section of the ODBCINST.INI file, used for managing the
installed ODBC drivers.
HKEY_CURRENT_USER\Software\ODBC\ODBC.INI
One entry per INI-section of the ODBC.INI file, used for user specific settings
and user DSNs. See section 3.2.5 Available Data Source Types (DSNs) for
details on the different DSN types.
21
mxODBC - Python ODBC Database Interface
3.2.5 Available Data Source Types (DSNs)
There are three kinds of data sources that you can install on Windows machines:
1. User Data Sources (User-DSN)
2. System Data Sources (System-DSN)
3. File Data Sources (File-DSN)
User Data Sources (User-DSN)
User data sources are only visible to the user creating them. Other users normally
do not have access to these data source definitions.
When running an application that is meant to run as service, you have to make
sure that you create the user data source under the user name of the service.
If you intend a data source to be available for all users, or to avoid permissions
problems, creating a system data source is a better option.
When connecting to a user DSN, you have to specify the DSN name as part of the
connection string of mx.ODBC.Windows.DriverConnect() using the form
"DSN=mydsn". If you use the mx.ODBC.Windows.Connect() API to connect, pass
the DSN name as first parameter.
System Data Sources (System-DSN)
System data sources are available to all users of the system. This is the
recommended setup, if you run services that need to access the data sources from
more than just one account.
When connecting to a system DSN, you have to specify the DSN name as part of
the connection string of mx.ODBC.Windows.DriverConnect() using the form
"DSN=mydsn". If you use the mx.ODBC.Windows.Connect() API to connect, pass
the DSN name as first parameter.
File Data Sources (File-DSN)
File data sources are special in the sense that they store the data source
connection information and options in a dedicated file rather than in the registry.
This can be useful if you want to manage data sources across many servers and
keep the data source files on a central file server.
You create such DSN files using the ODBC manager.
In order to connect to such a data source, you have to use the
mx.ODBC.Windows.DriverConnect()
API
and
provide
a
"FILEDSN=c:\myfile.dsn" entry instead of the usual "DSN=mydsn" as part for
the connection string.
22
3. Access Databases using mxODBC
See the ODBC File Data Source documentation for more details.
3.2.6 DSN-less Connections
If you don't want to bother setting up a data source in the ODBC manager, you
can also use a DSN-less connection setup.
Pros and Cons of using DSN-less Connections
These setups include all required driver and connection information in the
connection string itself. All connection information is thus under the control of the
application, without any system ODBC manager being aware of the connection
setup.
This has both up- and downsides. The most important downside is that changes
to the server system can no longer be administered through the ODBC manager,
but instead have to be repeated in each application using a DSN-less setup. Even
you upgrade an ODBC driver to a newer version, you may have to change all
DSN-less connection setups due to changes in the ODBC driver name.
We recommend to only use DSN-less setups if absolutely necessary, or in cases
where access to the ODBC configuration files is otherwise not possible.
DNS-less Connection String
A DNS-less connection provides all configuration information you'd normally
configure in the ODBC manager for a data source. Instead of a DSN name, you
provide a textual representation of the driver name enclosed in curly brackets, e.g.
"Driver={MySQL ODBC 3.51 Driver}; Server=mysql.example.net;
Database=mydb"
The name given in curly brackets must match the driver name as listed in the
ODBC manager (under Name on the Driver tab). The ODBC manager will then
map the name to the registered driver.
A "DSN=mydsn" entry in the connection string is no longer needed.
For a list of common DSN-less connection strings, have a look at the
ConnectionStrings.com website.
In order to connect to a database using a DSN-less connection string, you simply
pass the string to the mx.ODBC.Windows.DriverConnect() API.
23
mxODBC - Python ODBC Database Interface
3.3 Accessing Databases from Unix
mxODBC is often used to access databases across a network. A very typical use
case is that of connecting to MS SQL Server, Oracle or DB2 from a Unix machine.
eGenix.com has collected some information in the next section 4. Accessing
Popular Databases which may help you in finding the right solution for this kind of
setup. We recommend that you always use an ODBC manager on Unix to access
these driver setups, e.g. unixODBC, iODBC, or the DataDirect ODBC manager.
Once you’ve installed the ODBC drivers on the machine you are running your
Python application on, you will need to setup an ODBC Data Source. This can be
done using the ODBC manager GUIs which try to mimic the Windows ODBC
Manager, or using a text editor by editing either the system wide ODBC
configuration files (usually /etc/odbc.ini and /etc/odbcinst.ini; Mac OS X uses
/Library/ODBC/odbc.ini and /Library/ODBC/odbcinst.ini) or the user home
directory versions (usually ~/.odbc.ini and ~/.odbcinst.ini).
To avoid problems with system permissions, eGenix.com recommends setting up
data sources as System Data Sources using the GUI tools or in the system
configuration file /etc/odbc.ini using a text editor, as these are usually accessible
by all accounts on a Unix server.
Using
the
mxODBC
connection
constructor
mx.ODBC.Manager.DriverConnect() you can then setup a connection to the
database.
3.3.1 Looking for Unix ODBC Drivers ?
Many database vendors also provide ODBC for various Unix platforms. If you are
looking for Linux drivers, the situation has cleared up a lot in recent years. On
other platforms such as Mac OS X, AIX, Solaris or the BSDs, the situation is a lot
less encouraging.
If you have trouble finding a suitable driver, you can contact the database vendor
or check the SQLSummit list of ODBC drivers.
eGenix.com also provides a generic solution to such problems in form of the
mxODBC Connect product, which helps you work around the problem of finding
a suitable ODBC driver for the client platform. See the next section for detail.
3.3.2 mxODBC Connect - a general purpose client-server
solution
Since finding good quality ODBC drivers for Unix platforms is sometimes difficult
and managing them on all client systems can introduce quite a bit of
24
3. Access Databases using mxODBC
administrative overhead, eGenix has developed a general solution to the problem
for Python applications, the client-server product called eGenix mxODBC
Connect.
eGenix mxODBC Connect provides a highly portable client side Python interface
module mxODBC Connect Client which connects to a server side service
application called mxODBC Connect Server.
On the client side, the mxODBC Connect Client provides an interface which is
almost fully compatible to the standard mxODBC Python interface, so you can
easily port applications using mxODBC or other DB-API compatible adapters to
the mxODBC Connect Client.
On the server side, the mxODBC Connect Server takes care of managing the
incoming network connections from the mxODBC Connect Clients and interfaces
directly to the database using an ODBC driver on the server machine. Since the
mxODBC Connect Server is typically installed on the database server itself, the
ODBC driver can communicate with the database using low-level and high
performance interfaces such as shared memory, pipes, etc.
Using the mxODBC Connect product, you no longer need to search and install
ODBC drivers for all your client platforms. Instead, you just need one ODBC
driver installation on the server which is then shared by all clients.
The mxODBC Connect also provides better performance, since it doesn't require
as many network roundtrips to the server as a low-level ODBC driver on the client
side needs in order to provide the database connectivity.
Please see our website http://www.egenix.com/ for more information on mxODBC
Connect.
3.3.3 Installing Unix ODBC Drivers
Please consult the documentation of your database for ODBC driver installation
instructions.
These often have to be installed by running a shell script or using the system
packaging manager.
There are no standards for the driver directory location. Some drivers install in
/opt, others in /usr/local, yet others can be unzipped anywhere in the system,
provided the linker is setup to find the driver files.
3.3.4 Setting up an ODBC Data Source
Data sources are setup using the ODBC manager GUI tools on Unix or by editing
the respective ODBC configuration files.
25
mxODBC - Python ODBC Database Interface
The GUI tools can typically be found in the System part of the menu.
For more details description please see the ODBC manager manuals:
•
unixODBC User Manual
•
iODBC User Manual
•
DataDirect User Manual
•
Mac OS X ODBC Administrator Manual2
Since the layout and operation of these tools is often similar to the Windows
ODBC manager, you can also have a look at the Windows ODBC documentation
for details.
Starting the ODBC manager will bring up a dialog with tabs for data source
creation, ODBC tracing and connection pooling as well as a few information tabs
showing the versions of installed drivers.
3.3.5 ODBC Configuration Files
On Windows, you should always use the Windows ODBC Manager to configure
ODBC data sources.
Even though the Windows ODBC Manager also exposes the standard ODBC
configuration files C:\Windows\ODBC.INI and C:\Windows\ODBCINST.INI, these
do not contain the full configuration information, since this is stored in the
Windows registry.
/etc/odbc.ini - System ODBC Data Source Configuration
Depending on your ODBC manager installation or OS, the file may also reside in a
different directory. Please consult your ODBC manager documentation for details.
On Mac OS X, the file is located in /Library/ODBC/odbc.ini.
This INI-file provides data source information using one INI-section per data
source.
In addition to the data source sections, there are also a number of higher-level
sections:
[ODBC]
This section is used to configure driver related ODBC manager settings such as
ODBC call tracing. The settings in this section apply to all data sources.
2
For Mac OS X 10.6 (Snow Leopard) you may have to install the ODBC Administrator
separately. It is available from Apple as disk image: http://support.apple.com/kb/DL895
26
3. Access Databases using mxODBC
iODBC needs this section in the odbc.ini file. unixODBC in the odbcinst.ini
file. More recent DataDirect ODBC manager versions accept the section in
both files, older version need it in the odbc.ini file.
[ODBC Data Sources]
This section contains one entry per configured data source, mapping the data
source name to a description.
Example:
[ODBC]
Trace = 0
TraceFile = /tmp/odbc.log
[ODBC Data Sources]
sybasease12 = Sybase ASE 12 on sybasease12.example.net
[sybasease12]
Driver
Description
Server
Port
Database
TextSize
#UseCursor
FileUsage
Trace
TraceFile
=
=
=
=
=
=
/opt/sybase/DataAccess/ODBC/lib/libsybdrvodb.so
Adaptive Server Enterprise
sybasease12.egenix.internal
5000
mydb
10000000
= 1
= -1
= 0
= /tmp/sybase.log
~/.odbc.ini - User ODBC Data Source Configuration
This INI-file provides data source information on a per user basis. It uses the same
structure as the system wide /etc/odbc.ini file.
The data sources defined in this file are only visible to the user account for which
it is defined.
/etc/odbcinst.ini - System ODBC Driver Configuration
Depending on your ODBC manager installation or OS, the file may also reside in a
different directory. Please consult your ODBC manager documentation for details.
On Mac OS X, the file is located in /Library/ODBC/odbcinst.ini.
This INI-file provides one INI-section per installed ODBC driver.
In addition to the data source sections, there are also a number of higher-level
sections:
[ODBC]
This section is used to configure driver related ODBC manager settings such as
ODBC call tracing. The settings in this section apply to all data sources.
27
mxODBC - Python ODBC Database Interface
iODBC needs this section in the odbc.ini file. unixODBC in the odbcinst.ini
file. More recent DataDirect ODBC manager versions accept the section in
both files, older version need it in the odbc.ini file.
[ODBC Drivers]
This section contains one entry per configured and installed ODBC driver,
mapping the driver name to the string "Installed".
Example:
[ODBC]
Trace = 0
TraceFile = /tmp/odbc.log
[ODBC Drivers]
OracleInstantClient = Installed
[OracleInstantClient]
Description = Oracle 11g ODBC Driver
Driver = /usr/local/oracle/instantclient_11_2/libsqora.so.11.1
Setup =
FileUsage =
CPTimeout =
CPReuse =
~/.odbcinst.ini - User ODBC Driver Configuration
This INI-file provides ODBC driver information on a per user basis. It uses the
same structure as the system wide /etc/odbcinst.ini file.
The drivers defined in this file are only visible to the user account for which it is
defined.
Environment Variables: ODBCINI and ODBCINSTINI
In order to override the default search path used by the ODBC manager for the
above configuration files, the ODBC managers honor a few environment variables
which can be used to direct them to specific alternate files:
ODBCINI
This environment is used by the ODBC manager to find the ODBC data source
configuration file, if set.
ODBCINSTINI
This environment is used by the ODBC manager to find the ODBC driver
configuration file, if set.
28
3. Access Databases using mxODBC
Note that some driver manager do not support this environment variable:
unixODBC and iODBC support the variable, the DataDirect ODBC manager
doesn't.
3.3.6 Available Data Source Types (DSNs)
There are three kinds of data sources that you can install on Windows machines:
1. User Data Sources (User-DSN)
2. System Data Sources (System-DSN)
3. File Data Sources (File-DSN)
User Data Sources (User-DSN)
User data sources are only visible to the user creating them. Other users normally
do not have access to these data source definitions.
The user DSNs can be defined via the ODBC manager GUI administration tools or
by editing the user ODBC configuration file ~/.odbc.ini. See section 3.3.5 ODBC
Configuration Files for details.
When running an application that is meant to run as service or daemon, you have
to make sure that you create the user data source under the user name of the
service or daemon.
If you intend a data source to be available for all users, or to avoid permissions
problems, creating a system data source is a better option.
When connecting to a user DSN, you have to specify the DSN name as part of the
connection string of mx.ODBC.Manager.DriverConnect() using the form
"DSN=mydsn". If you use the mx.ODBC.Manager.Connect() API to connect, pass
the DSN name as first parameter.
System Data Sources (System-DSN)
System data sources are available to all users of the system. This is the
recommended setup, if you run services that need to access the data sources from
more than just one account.
Systems DSNs can be defined via the ODBC manager GUI administration tools or
by editing the system ODBC configuration file /etc/odbc.ini. See section 3.3.5
ODBC Configuration Files for details.
When connecting to a system DSN, you have to specify the DSN name as part of
the connection string of mx.ODBC.Windows.DriverConnect() using the form
"DSN=mydsn". If you use the mx.ODBC.Windows.Connect() API to connect, pass
the DSN name as first parameter.
29
mxODBC - Python ODBC Database Interface
File Data Sources (File-DSN)
File data sources are special in the sense that they store the data source
connection information and options in a dedicated file rather than in the registry.
This can be useful if you want to manage data sources across many servers and
keep the data source files on a central file server.
You create such DSN files using the ODBC manager (if supported) or by using a
text editor.
A DSN file uses the same syntax as the ODBC connection strings, with the
difference that the file must start with the line [ODBC] and each keyword-value
pair must be on a separate line, e.g. postgresql.dns:
[ODBC]
Driver = /usr/local/postgresql/lib/psqlodbcw.so
Database = mydb
ServerName = postgresql.example.net
Port = 5432
#Debug = 0
#Optimizer = 0
#CommLog = 0
#ReadOnly = 0
#SSLmode = require
ByteaAsLongVarBinary = 1
TextAsLongVarchar = 1
Please see the FILEDSN MS Knowledge-Base article 165866 for details regarding
the file format.
In order to connect to such a data source, you have to use the
mx.ODBC.Manager.DriverConnect()
API
and
provide
a
"FILEDSN=/etc/postgresql.dns" entry instead of the usual "DSN=mydsn" as
part for the connection string.
See the ODBC File Data Source documentation for more details.
3.3.7 DSN-less Connections
If you don't want to bother setting up a data source in the ODBC manager, you
can also use a DSN-less connection setup.
Pros and Cons of using DSN-less Connections
These setups include all required driver and connection information in the
connection string itself. All connection information is thus under the control of the
application, without any system ODBC manager being aware of the connection
setup.
This has both up- and downsides. The most important downside is that changes
to the server system can no longer be administered through the ODBC manager,
but instead have to be repeated in each application using a DSN-less setup. Even
30
3. Access Databases using mxODBC
you upgrade an ODBC driver to a newer version, you may have to change all
DSN-less connection setups due to changes in the ODBC driver name.
We recommend to only use DSN-less setups if absolutely necessary or in cases
where access to the ODBC configuration files is otherwise not possible.
DNS-less Connection String
A DNS-less connection provides all configuration information you'd normally place
into the ~/.odbc.ini file, including a textual representation of the driver location
(based on the name used in ~/.odbcinst.ini), e.g.
"Driver={MySQL ODBC 3.51 Driver}; Server=mysql.example.net;
Database=mydb"
Note the curly brackets around the driver name. The name given here must match
the one used in the ~/.odbcinst.ini or /etc/odbcinst.ini file. The ODBC
manager will then map the name to the registered driver file location.
A "DSN=mydsn" entry in the connection string is no longer needed.
For a list of common DSN-less connection strings, have a look at the
ConnectionStrings.com website.
In order to connect to a database using a DSN-less connection string, you simply
pass the string to the mx.ODBC.Manager.DriverConnect() API.
31
mxODBC - Python ODBC Database Interface
4.
Accessing Popular Databases
This section provides information on available ODBC drivers for various popular
database as well as notes regarding setup, functionality or available workarounds
for compatibility problems eGenix.com found with the drivers.
We have also included the resp. version information of the drivers we have tested
successfully with mxODBC.
4.1 MS SQL Server
4.1.1 Available ODBC Drivers
MS SQL Server Native Client for SQL Server 2005, 2008 and later
Homepage: http://msdn.microsoft.com/en-us/sqlserver/connectivity.aspx
Tested with MS SQL Server Native Client for 2005, 2008, 2008R2 and 2012
SQL Server Native Client is the native database client and ODBC driver for SQL
Server 2005, 2008 and later on Windows. Versions for 32-bit and 64-bit Windows
are available.
Finding the latest version of the SQL Server Native Client for Windows
Microsoft always ships the SQL Server Native Client ODBC driver together with
the SQL Server database packages, but also makes it available as separate
download in the feature packs for each new SQL Server version.
Since the client can typically also be used with older SQL Server installations, it's
worth trying the latest available version in case of problems or to benefit from
new features. As of this writing, the latest version is SQL Server Native Client 11.
Here's a list of feature packs that include the SQL Server Native Client. You have
to look for an installation file called sqlncli.msi or msodbcsql.msi on the pages:
•
Microsoft ODBC Driver 11 for SQL Server
Supports SQL Server 2005, 2008, 2008 R2 and 2012, 2014 and Windows
Azure SQL Database.
•
32
Microsoft SQL Server 2012 SP2 Feature Pack
4. Accessing Popular Databases
Supports SQL Server 2005, 2008, 2008R2, 2012. This version no longer
supports SQL Server 2000.
•
Microsoft SQL Server 2008 R2 SP1 Feature Pack
Supports SQL Server 2000, 2005, 2008, 2008R2.
•
Microsoft SQL Server 2008 Service Pack 2 Feature Pack
Supports SQL Server 2000, 2005, 2008.
•
Microsoft SQL Server 2005 Feature Pack Downloads
Supports SQL Server 2000 and 2005.
Use mxODBC direct execution methods for better performance
Python applications using the SQL Server Native Client should try to make use of
the available direct execution interfaces in mxODBC, e.g.
•
cursor.executedirect()
•
cursor.executemany(…, direct=1)
•
cursor.execute(…, direct=1)
Our tests have shown that these interface can give a 2-5x better performance
with SQL Server than the normal APIs (e.g. cursor.execute() without
direct=1)
Optimizing SQL Server Native Client Access Method
When installing the SQL Server Native Client, please make sure that you choose
the most efficient database access method. If the ODBC driver resides on the
same server as the database, shared memory is the most efficient protocol
available. For most other purposes, TCP/IP is the best option. See
http://msdn.microsoft.com/en-us/library/ms187892.aspx for details.
Configuring the SQL Server Native Client Network Protocol
When configuring an ODBC data source using the SQL Server Native Client you
can choose the protocol by providing a server address with protocol prefix:
tcp:db.example.com,1434 - connect to the server db.example.com using
TCP/IP over port 1434 (the default SQL Server post is 1433)
lpc:LOCALHOST\SQLEXPRESS - connect to the instance SQLEXPRESS running on
the local host via shared memory
np:\\EXAMPLE\pipe\MSSQL$SQLEXPRESS\sql\query - connect to the instance
SQLEXPRESS running on the computer EXAMPLE via named pipe
33
mxODBC - Python ODBC Database Interface
See http://msdn.microsoft.com/en-us/library/ms188635.aspx for details on the
various formats and how to configure them.
Multiple active result sets (MARS) on a single connection
The SQL Server Native Client per default does not support having more than one
active result set per connection. This means that you cannot have two cursors on
the same connection, which both have active result sets.
Starting with SQL Server 2005, there is a connection option which can be used to
enable the MARS feature of SQL Server Native Client, which enables working with
multiple active result sets on the same connection:
from mx.ODBC.Manager import DriverConnect, SQL
# Enable MARS on this connection:
options = [(SQL.COPT_SS_MARS_ENABLED, SQL.MARS_ENABLED_YES)]
# Pass the options to the connection constructor:
db = DriverConnect('DSN=mssqlserver2008;UID=sa;PWD=sa-passwd',
connection_options=options)
This option is available on SQL Server Native Client for Windows and Linux. The
FreeTDS ODBC driver 0.91 does not support this option.
Parameter Binding with SQL Server 2012 and later
SQL Server 2012 and later have changed the SQL parser or optimizer to use a
more stringent method of determining the unkown parameter input types.
This results in SQL statements such as "WHERE col1 >= ? + ?" to fail with an
error such as mx.ODBC.Error.ProgrammingError: ('42000', 11503,
"[Microsoft][ODBC Driver 11 for SQL Server][SQL Server]The
parameter type cannot be deduced because a single expression
contains two untyped parameters, '@P1' and '@P2'.", 10191).
There are two solutions to this incompatibility between SQL Server 2008R2 and
SQL Server 2012:
1. use explicit casts to tell the SQL parser which type to expect from the
right hand side operation, e.g. "WHERE col1 >= ? + CAST(? as int)".
This gives the second argument an explicit type and allows the parser to
deduce the type of the result,
2. run the query using .executedirect() instead of .execute(). This
causes the parameter values to be embedded into the SQL command and
allows the SQL parser on the server side to determine the types at
preparation time by looking at the values, rather than just their
placeholders.
Stored procedures with output parameters and result sets
MS SQL Server stored procedures are fully supported by mxODBC, but there is
one important detail to know when using stored procedures which use both
output or input/output parameters and result sets.
34
4. Accessing Popular Databases
Due to the way the SQL Server Native Client works, the data from the result sets
is sent to the client before the data for the output parameters. See e.g. the IBM
Knowledge Center or StackOverflow for details.
Since mxODBC returns the output parameters immediately after executing a
statement
via
the
cursor.callproc(),
cursors.execute()
or
cursor.executedirect() APIs, the changes send to the client after the result
sets are not seen by mxODBC.
The Python DB-API 2.0 also does not allow for the output parameters to be
fetched later, e.g. after the result sets have been fetched using the
cursor.fetch*() APIs.
As a result, output and input/output parameters in stored procedures which
generate and return result sets are not updated.
Work-around:
The work-around for this is to return the output parameter values as additional
result sets and then using the cursor.nextset() method to switch through the
available result sets.
MS SQL Server ODBC Driver for SQL Server 2000
Tested with MS SQL Server ODBC driver from MDAC 2.8 SP1.
If you still use SQL Server 2000, please get the latest ODBC driver for SQL Server
from the Micrsoft MDAC package. MDAC 2.8 SP1 can be downloaded from this
page:
http://www.microsoft.com/downloads/details.aspx?familyid=78CAC895-EFC24F8E-A9E0-3A1AFBD5922E&displaylang=en
Configuring the SQL Server ODBC Driver Client Network Protocol
When configuring an ODBC data source using the MDAC SQL Server ODBC
Driver you can choose the protocol by clicking on the Client Configuration button
on the second wizard page.
Note that the MDAC ODBC drivers do not support shared memory access. Use
named pipes as best connectivity option when connecting to a database server
running on the same machine.
MS SQL Server Native Client for Linux
Homepage:
http://msdn.microsoft.com/en-us/library/hh477150%28v=sql.10%29.aspx
Tested with MS SQL Server Native Client 11 for Linux
35
mxODBC - Python ODBC Database Interface
The new Microsoft SQL Server Native Client for Linux is a port of the SQL Server
Native Client for Windows to Linux. It provides an ODBC driver for SQL Server
2008 R2 and 2012 on Linux, but also works with SQL Server 2005 and 2008. At
the moment, only a 64-bit version is available and then only for RedHat RHEL 5
and 6 systems.
Most of the comments for the Windows driver also apply to the Linux driver.
This driver also supports the MARS feature. See "Multiple active result sets (MARS)
on a single connection" further up for details.
Driver Limitations
•
The driver still has some issues and can produce segfaults (see below),
but it's already good enough for testing and simple setups.
•
The driver only works on 64-bit Linux distributions and requires the
unixODBC 2.3.2 ODBC manager (2.2 won't work due to ABI differences).
•
The mxODBC DriverConnect() API cannot be used with Unicode
connection strings when using this driver: the SQL Server Native Driver
for Linux causes a segfault when trying to connect using a Unicode
connection string (which triggers the use of Unicode ODBC APIs). We
have confirmed this for version 11.0.1790 and 11.0.2270 of the driver.
Unfortunately, we cannot add a work-around to mxODBC to guard
against this, since mxODBC only receives the driver name after the
connect.
Example Configuration for Unix
Here is a sample setup for the SQL Server Native Client for Linux:
•
Install the driver following the instructions given by Microsoft. Here's
quick version:
tar xvfz sqlncli-11.0.1790.0.tar.gz
cd sqlncli-11.0.1790.0/
mkdir -p /opt/microsoft/sqlncli/bin
mkdir -p /opt/microsoft/sqlncli/lib
./install.sh install --force --accept-license \
--bin-dir=/opt/microsoft/sqlncli/bin \
--lib-dir=/opt/microsoft/sqlncli/lib
You can ignore any warnings. Note that using the driver directly from the
untarred archive is not possible, since the installation location appears to
be hardwired in the driver.
•
Depending on your Linux distribution, you may have to add symlinks to
your OpenSSL libraries to match the ones used on RedHat:
cd /lib64
ln -sf libssl.so.1.0.0 libssl.so.10
ln -sf libcrypto.so.1.0.0 libcrypto.so.10
ldconfig
•
36
Add the driver to the /etc/odbcinst.ini (or ~/.odbcinst.ini):
4. Accessing Popular Databases
[ODBC Drivers]
MSNativeClient = Installed
[MSNativeClient]
Driver = /opt/microsoft/sqlncli/lib64/libsqlncli-11.0.so.1790.0
Description = MS SQL Server Native Client 11
Threading = 1
•
Add a data source to the /etc/odbc.ini (or ~/.odbc.ini):
[mssqlserver2008]
Driver = /opt/microsoft/sqlncli/lib64/libsqlncli-11.0.so.1790.0
Description = MS SQL Server 2008 running on Picasso (MS Native
Client)
Server = tcp:picasso\SQLSERVER2008,1436
Database = testdb
The syntax for the Server entry is described in the MSDN article SQL
Server Native Client ODBC Connection String Format.
EasySoft ODBC Driver for SQL Server
Homepage: http://www.easysoft.com/
OpenLink ODBC Driver for SQL Server
Homepage: http://www.openlinksw.com/
DataDirect ODBC Driver for SQL Server
Homepage: http://www.datadirect.com/
Actual Technologies Mac OS X ODBC Driver for SQL Server
Homepage: http://www.actualtech.com/
When using the driver on Mac OS X 10.6 (Snow Leopard), be sure to use version
3.0.9 or higher, since earlier versions had a problem with fetching data.
FreeTDS Unix ODBC Driver for SQL Server
Homepage: http://www.freetds.org/
Tested with FreeTDS 0.91 ODBC driver compiled against unixODBC 2.3.2.
The FreeTDS ODBC driver implements the client side of the TDS wire protocol
used by Sybase ASA and Microsoft SQL Server installations. It allows you to
directly connect to a SQL Server database from a Unix machine.
Driver Limitations
•
37
The FreeTDS ODBC driver version 0.91 introduces Unicode support for
the first time in its version history. The previous stable version 0.82 did
not have Unicode support. We've had most success using the
NATIVE_UNICODE_STRINGFORMAT mode.
mxODBC - Python ODBC Database Interface
•
Most other operations work as expected, but please note that the driver is
still under heavy development in some areas. You should test it
thoroughly before using it on a production system.
•
The FreeTDS website mentions that the driver has some restrictions.
Please see the FreeTDS user guide for details.
•
Be sure to use the same ODBC manager with FreeTDS as the one you
have compiled it with. If you mix e.g. unixODBC and iODBC, you can
easily run into Unicode data corruption issues. The two ODBC managers
use different default data types for Unicode data, so a FreeTDS ODBC
driver compiled against unixODBC (2-bytes Unicode data type) will not
return correct Unicode data when used with the iODBC ODBC manager
(4-bytes Unicode data type).
•
FreeTDS ODBC driver only works natively with DATETIME columns.
DATE and TIME column types introduced in SQL Server 2008 are only
supported via strings. FreeTDS 0.91 accepts them as strings and returns
them as strings. Using mxDateTime values for DATE and TIME fields does
not work. You can use the MS SQL Server Native Client for Linux, if you
need these column types supported, since it does not have this limitation.
•
There are other ODBC drivers available from commercial vendors which
implement the full ODBC3 API, including the free MS SQL Server Native
Client for Linux from Microsoft. Alternatively, you can use our mxODBC
Connect product to use the SQL Server Native Client on Windows from
all supported Python platforms and without the need for a client-side
ODBC driver.
•
The FreeTDS driver does not support the MARS feature3. Only one active
result set is allowed per connection. If you need the MARS feature, please
have a look at the MS SQL Server Native Client for Linux. This driver also
support the MARS feature. See "Multiple active result sets (MARS) on a
single connection" further up for details.
Example Configuration for Unix
Here is a sample setup for FreeTDS on Linux talking to MS SQL Server 2008 on
Windows:
•
Add this section to /usr/local/freetds/etc/freetds.conf (the freetds.conf
configuration file may be in a different location on your machine):
# MS SQL Server 2000 running on server MONET
[MONET]
host = monet.example.net
port = 1433
tds version = 8.0
•
3
Add this section to /etc/odbc.ini (the odbc.ini configuration file may be in
a different location on your machine ). It is also necessary to point
LD_LIBRARY_PATH to the directory where the driver itself is located.
There is work underway to add this feature. See the http://freetds.org/ website.
38
4. Accessing Popular Databases
[mssql]
Driver = /usr/local/freetds/lib/libtdsodbc.so
Description = MS SQL Server 2008 running on Monet
Trace = 0
Servername = MONET
Database = tempdb
Note that the libtdsodbc.so file may be located in a different directory on
your machine.
•
Using these settings, you can then connect to SQL Server using a simple
connection string such as:
"DSN=mssql;UID=username;PWD=password"
4.1.2 General Notes
ODBC API Extensions and the SQL Server Native Client
The ODBC API is the native MS SQL Server call level interface and provides the
best performance when interfacing to SQL Server.
Microsoft has also extended ODBC with various custom extensions they make
available in their SQL Server Native Client API. If you need support for those
extensions, please contact support@egenix.com.
Static vs. forward-only Cursors
MS SQL Server supports static ODBC cursors, but mxODBC defaults to forward
only cursors. 4
While static cursors allow scrolling through the result set and also provides ways
of accessing the correct .rowcount value, it does come with a significant
performance penalty. We have seen slow-downs in fetching rows of 2-3x times for
average queries, up to 300x for simple ones, so we recommend not using static
cursors on connections that do not need scroll support. To enable static cursors,
you can adjust the connection.cursortype:
connection = mx.ODBC.Windows.DriverConnect(…)
connection.cursortype = mx.ODBC.Windows.SQL.CURSOR_STATIC
# All cursors created on connection will then default to the static
# cursor type.
Please refer to section 5.8 ODBC Cursor Types for more details on cursor types.
Timestamp Resolution
Unlike many other databases which support nanosecond precision on
timestamps, MS SQL Server has a limitation when it comes to the seconds part of
timestamp values. Version of SQL Server earlier and including SQL Server 2005
only accept timestamp precisions of 1 millisecond, while version SQL Server 2008
and later work with precision of 100 nanoseconds.
4
Please note that in mxODBC 3.2, mxODBC used to default to static cursors.
39
mxODBC - Python ODBC Database Interface
mxODBC addresses this by defaulting to connection.timestampresolution =
1000000 for SQL Server 2005 and earlier. For SQL Server 2008 and later,
mxODBC uses connection.timestampresolution = 100.
This allows using timestamp values with SQL Server which use higher precision
values without running into errors from the database such as:
HY104 - [Microsoft][SQL
precision value.
Server
Native
Client
11.0]
Invalid
However, please be advised that reducing the precision of input values requires
rounding, which can lead to unexpected results. mxODBC does make sure that
the seconds whole value is not altered by the rounding to reduce unwanted
surprises. Please see the documentation on connection.timestampresolution
for details.
Multiple Cursors on Connections / MARS
If you have troubles with multiple cursors on connections to MS SQL Server the
MS Knowledge Base Article 140896 INF: Multiple Active Microsoft SQL Server
Statements has some valuable information for you.
You have to explicitly enable support for multiple active cursors (MARS) or force
the usage of server side cursors to be able to execute multiple statements on a
single connection to MS SQL Server. According to the article this is done by
setting
the
connection
option
SQL.CURSOR_TYPE
to
e.g.
SQL.CURSOR_DYNAMIC:
dbc.setconnectoption(SQL.CURSOR_TYPE, SQL.CURSOR_DYNAMIC)
If you are using the MS SQL Server Native Client, you can also enable the MARS
feature on the client side by setting a connect option during connect. Please see
the section "Multiple active result sets (MARS) on a single connection" further up
for details.
International Character Data
If you are experiencing problems with MS SQL Server not storing or fetching
international character data (Unicode, Asian encodings, etc.) correctly, please
have a look at the following MS Knowledge Base Articles:
•
232580 - INF: Storing UTF-8 Data in SQL Server
•
257668 - FIX: SQL Server ODBC Driver May Cause Incorrect Code
Conversion of Some Characters
•
234748 - PRB: SQL Server ODBC Driver Converts Language Events to
Unicode
More information about the MS SQL Server ODBC Driver and the various
connection parameters and options are available on the MSDN Library site: MS
SQL Server ODBC Driver Programmer's Guide.
40
4. Accessing Popular Databases
Access Violations
If you are experiencing problems related to access violations, like e.g.
ProgrammingError: ('37000', 0, '[Microsoft][ODBC
Driver]Syntax error or access violation', 4498)
SQL
Server
a possible reason could be that you are using a function or stored procedure
which is generating output using PRINT or that it uses RAISEERROR to report an
error with the parameters or values.
Another possible reason is that the ODBC driver for SQL Server does not support
the syntax you are using or that bound parameters are not allowed at that location
in the SQL statement. As work-around you can use Python string formatting to
insert the data verbatim directly into the SQL statement.
Distributed Transaction Managers
If you are using a transaction manager (e.g. MS DTC), you can sometimes get
warnings like the following:
mxODBC.Warning: ('01000', 7312, [Microsoft][ODBC SQL Server
Driver][SQL
Server][OLE/DB
provider
returned
message:
New
transaction
cannot
enlist
in
the
specified
transaction
coordinator.]', 4606)
This is a problem related to the used transaction manager rather than mxODBC or
the database. Please consult your DBA for help.
Note that even though the above exception is raised by the
cursor.execute()
method, the fact that it is a warning suggests that the executed operation was
indeed executed on the cursor.
Kerberos / Windows Integrated Authentication
In order to use Kerberos authentication the ODBC driver used by mxODBC has to
support this. mxODBC itself can help with the setup via connection options (see
Service Principal Names (SPNs) in Client Connections (ODBC)), but does not need
to be setup in a special way to support Kerberos.
We know of these ODBC drivers that support Kerberos Windows integrated
authentication with MS SQL Server:
MS SQL Server Native Client for Windows
On Windows, you simply have to replace the "UID=…;PWD=…" part of your
connection string with "Trusted_Connection=yes" in order to use Kerberos
authentication.
It may also be necessary to provide a Service Principal Name (SPN) for the server.
This can be done via the "ServerSPN=…" keyword parameter in the connection
41
mxODBC - Python ODBC Database Interface
string. Please see this article for details: Service Principal Name (SPN) Support in
Client Connections
MS SQL Server Native Client for Linux
Please see this article for details on how to setup the driver to use Kerberos
authentication: Using Integrated Authentication
Also see the EasySoft documentation below for some added details around the
setup of Kerberos authentication on Linux.
EasySoft SQL Server Driver for Linux
Please see the following page for details on how this driver is setup: Securing
Access to SQL Server from Linux with Kerberos
FreeTDS ODBC Driver for Linux
The FreeTDS ODBC driver can be built against the Kerberos libraries and provides
the same Trusted_Connection keyword connection parameter as the MS SQL
Server Native Client. Provided you have Kerberos working on the system, you
simply have to replace the "UID=…;PWD=…" part of your connection string with
"Trusted_Connection=yes" in order to use Kerberos authentication.
Kerberos on Linux
All of the above have some information about the setup of Kerberos on Linux. This
book chapter has all the information you need to complete the setup:
http://commons.oreilly.com/wiki/index.php/Linux_in_a_Windows_World/Centralize
d_Authentication_Tools/Kerberos_Configuration_and_Use
If you want to use an Active Directory, you will additionally have to use Samba to
integrate into the AD, hook winbind into PAM and have pam_winbind use
Kerberos authentication:
http://wiki.samba.org/index.php/Samba_&_Active_Directory
A user can then log in and authenticate against the AD and the Kerberos server
will provide the necessary credentials to the ODBC driver.
Other Common Problems and Solutions
A general description of the problems you might experience when accessing the
MS SQL Server using ODBC is described in the article Using ODBC with Microsoft
SQL Server. Even though it's dated September 1997 it provides some insights into
the design and workings of the MS SQL ODBC driver.
42
4. Accessing Popular Databases
4.2 MS Access Database
4.2.1 Available ODBC Drivers
MS Access ODBC Driver
Tested with MDAC 2.8 SP1 Access ODBC driver.
MS Access ships with an ODBC driver for the database which is then installed on
the same machine as MS Access (or Office). The drivers are also available
separately as part of the MDAC package.
MDAC 2.8 SP1 can be downloaded from this page:
http://www.microsoft.com/downloads/details.aspx?familyid=78CAC895-EFC24F8E-A9E0-3A1AFBD5922E&displaylang=en
MDBTools ODBC Driver
Homepage: http://mdbtools.sourceforge.net/
This package provides a very limited ODBC driver which allows accessing Access
database files directly without having to install or run MS Access. It is mostly used
on Unix platforms to extract data from existing MS Access database files.
4.3 Oracle
4.3.1 Available ODBC Drivers
Oracle Instant Client ODBC driver
Homepage: http://www.oracle.com/technology/tech/oci/instantclient/index.html
Tested with Oracle Instant Client ODBC driver 11.2.
The Oracle Instant Client ships with an ODBC driver (part of the ODBC
Supplement) for most supported platforms.
mxODBC works well when using the Oracle Instant Client 11.2 with the
unixODBC ODBC manager package mx.ODBC.unixODBC on Unix or the
mx.ODBC.Windows package on Windows.
43
mxODBC - Python ODBC Database Interface
Driver Notes
•
eGenix.com has had reports about memory leaks occurring with the
Oracle driver when used in long running applications. mxODBC itself
does not have any known memory leaks and there are no problems with
other available drivers for Oracle.
•
Oracle regards empty strings as NULL values. As a result inserting an
empty string into a VARCHAR column can result in the Oracle driver
returning NULL for that column when fetching data.
•
The Oracle driver returns numeric values as floats, even integers, so
unless you use a converter function, you will get floats when querying
integer columns.
•
The automatic reuse of prepared SQL commands does not work with the
Oracle driver, so the optimization for the cursor.execute() method
does not work with the Oracle driver.
•
The Oracle driver does not support scrollable cursors, meaning that
cursor.scroll() will only work using the built-in mxODBC emulation
for forward scrolling.
Example Configuration for Unix
•
To be able to use the Oracle Instant Client, you have to create a
~/.tnsnames.ora file providing the network configuration details of the
target database:
ORACLE11GR2 =
(DESCRIPTION =
(ADDRESS = (PROTOCOL = TCP)
(HOST = oracle11gr2.example.net)
(PORT = 1521))
(CONNECT_DATA =
(SERVER = DEDICATED)
(SERVICE_NAME = oracle11gr2.example.net)
)
)
•
Add an Oracle driver section to the ~/.odbcinst.ini file (the location of the
driver file may be different on your system):
[ODBC Drivers]
OracleInstantClient = Installed
[OracleInstantClient]
Description = Oracle 11g ODBC Driver
Driver = /opt/oracle/instantclient_11_2/libsqora.so.11.1
Setup =
FileUsage =
CPTimeout =
CPReuse =
•
Edit the ~/.odbc.ini file based on the above ~/.tnsnames.ora settings.
Note that the location of the driver file depends on your installation. It is
also necessary to point LD_LIBRARY_PATH to the directory where the
driver itself is located.
[oracle11gr2]
44
4. Accessing Popular Databases
Driver = /opt/oracle/instantclient_11_2/libsqora.so.11.1
ServerName = oracle11gr2
# DSN driver options
Application Attributes = T
Attributes = W
BatchAutocommitMode = IfAllSuccessful
BindAsFLOAT = F
CloseCursor = F
DisableDPM = F
DisableMTS = T
EXECSchemaOpt =
EXECSyntax = T
Failover = T
FailoverDelay = 10
FailoverRetryCount = 10
FetchBufferSize = 64000
ForceWCHAR = F
Lobs = T
Longs = T
MaxLargeData = 0
MetadataIdDefault = F
QueryTimeout = T
ResultSets = T
#SQLGetData extensions = F
SQLGetData extensions = T
Translation DLL =
Translation Option = 0
DisableRULEHint = T
#UserID =
StatementCache=F
CacheBufferSize=20
UseOCIDescribeAny=F
•
Using these settings, you can then connect to Oracle using a simple
connection string such as:
"DSN=oracle11gr2;UID=username;PWD=password"
EasySoft ODBC Driver for Oracle
Homepage: http://www.easysoft.com/
OpenLink ODBC Driver for Oracle
Homepage: http://www.openlinksw.com/
DataDirect ODBC Driver for Oracle
Homepage: http://www.datadirect.com/
Actual Technologies Mac OS X ODBC Driver for Oracle
Homepage: http://www.actualtech.com/
When using the driver on Mac OS X 10.6 (Snow Leopard), be sure to use version
3.0.9 or higher, since earlier versions had a problem with fetching data.
45
mxODBC - Python ODBC Database Interface
4.3.2 General Notes
Oracle tnsnames.ora file
When connecting to Oracle database you typically have to provide a
~/.tnsnames.ora file which has the network connection information of your
Oracle database servers.
If you want to use a different file location, be sure to set the environment variable
TNS_ADMIN to the path of the tnsnames.ora file.
4.4 IBM DB2
4.4.1 Available ODBC Drivers
IBM ODBC Driver for Unix/Windows DB2 servers
Tested with IBM DB2 9.7 ODBC driver.
IBM DB2 ships with ODBC drivers for DB2 on Windows, Linux and other Unix
systems. These can also be used to connect to DB2 database over a network.
Please see this page for more information:
http://publib.boulder.ibm.com/infocenter/db2luw/v9/index.jsp?topic=/com.ibm.db
2.udb.apdv.cli.doc/doc/c0023378.htm
Example Configuration for Unix
•
Setup the network details of your DB2 database in the ~/.db2cli.ini file:
[ibmdb2]
DBAlias=SAMPLE
Hostname=db2.example.net
•
Using the same section name, add a new section to your ~/.odbc.ini file.
[ibmdb2]
Driver = /usr/local/odbc-drivers/db2/clidriver/lib/libdb2.so
You will have to change the driver entry to the location where you copied
the ODBC driver and add the lib/ directory of the driver to your
LD_LIBRARY_PATH.
•
46
You can then connect to your database via the connection string
"DSN=ibmdb2;UID=username;PWD=password".
4. Accessing Popular Databases
IBM ODBC Driver for iSeries / AS/400 DB2 servers
IBM has a Linux ODBC driver which makes this setup possible. See their webpage on the "iSeries ODBC driver for Linux" for details:
http://www-03.ibm.com/systems/i/software/access/linux/guide/index.html
OpenLink ODBC Driver for DB2
Homepage: http://www.openlinksw.com/
DataDirect ODBC Driver for DB2
Homepage: http://www.datadirect.com/
4.4.2 General Notes
ODBC API Extensions and the IBM CLI
The ODBC API is the native IBM DB2 call level interface and provides the best
performance when interfacing to DB2.
IBM has also extended ODBC with various custom extensions they make available
as CLI interface. If you need support for those extensions, please contact
support@egenix.com.
Configuring Database Access
If you want to use the DriverConnect() API with IBM DB2, you'll have to
configure the IBM ODBC driver's data source INI file which is named ~/db2cli.ini
and usually found in the same directory as the above script files. The file is
needed in addition to the ~/.odbc.ini file and the entries must match.
If you place the db2cli.ini file into a different directory, make sure that you setup
the environment variable DB2CLIINIPATH to point to the full path of the file.
Environment Variables on Unix
If you don't use a db2cli.ini file, you can configure the access details using
environment variables:
In order to connect to the IBM DB2 database the DB2INSTANCE environment
variable must be set to the name of the DB2 instance you would like to connect
to.
There may be more environment variables needed, please check the scripts that
come with DB2 called db2profile (for bash) or db2cshrc (for C shell) which set
47
mxODBC - Python ODBC Database Interface
the environment variables. Without having these set, mxODBC will fail to load
and give you a traceback:
Traceback (most recent call last):
...
from mxODBC import *
ImportError: initialization of module mxODBC failed
(mxODBC.InterfaceError:failed to retrieve error information (line 6778,
rc=-1))
Linker Paths
Unfortunately, the provided db2profile / db2cshrs shell scripts are buggy in some
versions of DB2, so simply sourcing them won't necessarily work.
You will have to carefully create your own to work around these issues.
A typical problem is that the scripts set LIBPATH or LD_LIBRARY_PATH (without
paying attention to possibly existing settings) which then causes the following
linker-related traceback when trying to load mxODBC:
Traceback (most recent call last):
...
ImportError: from module mxODBC.so No such file or directory
Database Setup for ODBC Access
Unlike many other databases, DB2 needs to be explicitly told that you want to
connect to the database using ODBC.
This is done by binding the IBM CLI driver against the database in order to setup
ODBC related views and stored procedures. Please consult the IBM DB2
documentation for details on how this is done.
Static vs. forward-only Cursors
IBM DB2 supports static ODBC cursors, but mxODBC defaults to forward only
cursors. 5
While static cursors allow scrolling through the result set and also provides ways
of accessing the correct .rowcount value, it does come with a significant
performance penalty. We have seen slow-downs in fetching rows of around 2x
times for average queries, so we recommend not using static cursors on
connections that do not need scroll support. To enable static cursors, you can
adjust the connection.cursortype:
connection = mx.ODBC.Windows.DriverConnect(…)
connection.cursortype = mx.ODBC.Windows.SQL.CURSOR_STATIC
# All cursors created on connection will then default to the static
# cursor type.
Please refer to section 5.8 ODBC Cursor Types for more details on cursor types.
5
Please note that in mxODBC 3.2, mxODBC used to default to static cursors.
48
4. Accessing Popular Databases
4.5 Sybase ASE
4.5.1 Available ODBC Drivers
Sybase ASE ODBC driver
Homepage: http://www.sybase.com/
Tested with Sybase ASE 15.5 and 15.7 ODBC drivers
Sybase ASE ships with ODBC drivers for both 32-bit and 64-bit platforms. The
drivers are part of the ASE server packages.
The ASE 15.5 ODBC driver can also be used to connect to a Sybase ASE 12.x
server database. In fact, this setup is recommended, since the 15.5 version of the
driver fixes a couple of issues that are present in the 12.x ODBC driver.
NULL issues with Sybase ASE ODBC driver
We have had reports of the Sybase ODBC driver producing errors when trying to
set a character column to NULL (by passing None to mxODBC for that column),
esp. on 64-bit platforms.
mxODBC 3.3 now has a work-around for this problem in place, so this should no
longer be an issue.
Segfaults with Sybase ASE ODBC driver 15.7
On 64-bit platforms, we have observed occasional segfaults caused by the ODBC
driver. These occur in the malloc() routine of the glibc after running tests for a
while and seem to be caused by the driver corrupting the heap. In some cases,
glibc also detects invalid pointers in free() as a result of this.
The specific version of the driver where we found this problem was 15.7.0.104.
This may have been resolved in later versions.
The Sybase ASE ODBC driver for 15.5 does not have these issues.
BIGINT columns can cause data corruption
Even though Sybase ASE 15 does support a BIGINT column type, the Sybase ESD
3 ODBC driver has problems interfacing to it and data is corrupted. As example,
inserting a -2 to a BIGINT columns results in 1 being read back; inserting
-2147483648 results in 47493012874424 read from the column.
49
mxODBC - Python ODBC Database Interface
Since this is a bug in the ODBC driver, future ESDs may fix the issue. In any case,
please carefully check for this problem before using BIGINT columns with the
driver.
Driver Notes
•
In mxODBC 3.3, we switched the default parameter binding method from
Python type to SQL type. This resolves issues with the Sybase ODBC
driver complaining about the wrong Python object type being used for
certain database data types. Especially the Unicode support (UNICHAR,
UNIVARCHAR and UNITEXT database column types) now works much
better than before.
•
The
Sybase
ASE
driver
only
supports
forward
scrolling,
cursor.scroll() will just work with relative and positive increments.
so
•
There is no support for cursor.rownumber in the driver.
•
If you are using large text/binary data fields with more than 32k data, be
sure to add the connection parameter TextSize = 10000000 (or larger)
to the connection string or the data source definition in your ~/.odbc.ini.
Not doing so will otherwise result in data truncations.
Example Configuration for Unix
•
Add a Sybase driver section to the ~/.odbcinst.ini file (the location of the
driver file may be different on your system):
[ODBC Drivers]
SybaseASE = Installed
[SybaseASE]
Description = SybaseASE ODBC Driver
Driver = /opt/sybase/DataAccess/ODBC/lib/libsybdrvodb.so
Setup =
•
Edit the ~/.odbc.ini file based and add a sybasease section(the location
of the driver file may be different on your system). It is also necessary to
point LD_LIBRARY_PATH to the directory where the driver itself is
located.
[sybasease]
Driver = /opt/sybase/DataAccess/ODBC/lib/libsybdrvodb.so
Description = Adaptive Server Enterprise
Server = sybasease.example.net
Port = 5000
Database = mydb
TextSize = 10000000
#UseCursor = 1
FileUsage = -1
Trace = Off
TraceFile = /tmp/sybase.log
•
Using these settings, you can then connect to Sybase ASE using a simple
connection string such as:
"DSN=sybasease;UID=username;PWD=password"
50
4. Accessing Popular Databases
EasySoft ODBC Driver for Sybase
Homepage: http://www.easysoft.com/
OpenLink ODBC Driver for Sybase
Homepage: http://www.openlinksw.com/
DataDirect ODBC Driver for Sybase
Homepage: http://www.datadirect.com/
Actual Technologies Mac OS X ODBC Driver for Sybase
Homepage: http://www.actualtech.com/
When using the driver on Mac OS X 10.6 (Snow Leopard), be sure to use version
3.0.9 or higher, since earlier versions had a problem with fetching data.
4.6 PostgreSQL
4.6.1 Available ODBC Drivers
PostgreSQL ODBC Driver
Homepage: http://psqlodbc.projects.postgresql.org/
Tested with psqlodbc 09.03.0210.
The PostgreSQL driver is usually compiled against unixODBC on Unix platforms.
Please use the mx.ODBC.unixODBC subpackage to connect to PostgreSQL with it.
On Mac OS X, you may need to use the mx.ODBC.iODBC subpackage instead,
since the Mac OS X ODBC manager is derived from the iODBC manager.
Driver Notes
51
•
Because of limitations in the PostgreSQL ODBC drivers, mxODBC always
operates in Python type binding mode.
•
In mxODBC 3.3, we have added a work-around to make the driver work
with binary data and BYTEA columns.
mxODBC - Python ODBC Database Interface
•
Unicode
data
is
supported.
It
works
best
with
the
NATIVE_UNICODE_STRINGFORMAT mode. You can also use the autotranscoding feature of mxODBC with UTF-8 as encoding.
•
The driver only supports forward scrolling with relative increments of +1.
Other values result in a driver error. As a result, only
cursor.scroll(+1) can be used.
Example Configuration for Unix
•
Add a PostgreSQL driver section to the ~/.odbcinst.ini file (the location of
the driver file may be different on your system):
[ODBC Drivers]
PostgreSQL = Installed
[PostgreSQL]
Description = PostgreSQL ODBC Driver
Driver = /usr/local/postgresql/lib/psqlodbcw.so
Setup =
•
Edit the ~/.odbc.ini file based and add a postgresql section(the location of
the driver file may be different on your system; be sure to use the
Unicode variant which ends with '…w.so'). It is also necessary to point
LD_LIBRARY_PATH to the directory where the driver itself is located.
[postgresql]
Driver = /usr/local/postgresql/lib/psqlodbcw.so
Database = mydb
ServerName = postgresql.example.net
Port = 5432
#Debug = 0
#Optimizer = 0
#CommLog = 0
#ReadOnly = 0
#SSLmode = require
ByteaAsLongVarBinary = 1
TextAsLongVarchar = 1
# This currently doesn't appear to work:
#UseServerSidePrepare = 1
•
Using these settings, you can then connect to PostgreSQL using a simple
connection string such as:
"DSN=postgresql;UID=username;PWD=password"
EasySoft ODBC Driver for PostgreSQL
Homepage: http://www.easysoft.com/
OpenLink ODBC Driver for PostgreSQL
Homepage: http://www.openlinksw.com/
DataDirect ODBC Driver for PostgreSQL
Homepage: http://www.datadirect.com/
52
4. Accessing Popular Databases
Actual Technologies Mac OS X ODBC Driver for PostgreSQL
Homepage: http://www.actualtech.com/
When using the driver on Mac OS X 10.6 (Snow Leopard), be sure to use version
3.0.9 or higher, since earlier versions had a problem with fetching data.
4.7 MySQL
4.7.1 Available ODBC Drivers
MySQL ODBC Driver
Homepage: http://dev.mysql.com/downloads/connector/odbc/
Tested with MySQL ODBC driver 5.2.6 and MySQL 5.5 and 5.6.
Be sure to use the mxODBC ODBC manager subpackage against which the
MySQL driver was compiled. This will usually be mx.ODBC.unixODBC or
mx.ODBC.iODBC.
The MySQL ODBC driver documentation recommends using unixODBC with the
driver, i.e. the mx.ODBC.unixODBC subpackage.
Note that the MySQL 5.2 ODBC driver can connect to all recent versions of the
MySQL database server. It is usually best to use the latest available version, even if
your database server has a different version number.
Driver Notes
53
•
There is one particularity with the ODBC driver for MySQL: all input
parameters are being processed as strings -- even integers and floats. The
ODBC driver implements the necessary conversions. mxODBC therefore
defaults to Python Type binding mode for binding parameters; see the
Python Type Input Binding section 8.4 for more details.
•
Unicode data is supported, provided you use the Unicode ODBC driver
versions - on Unix these are identified with a small "w" at the end of the
driver lib name, e.g. libmyodbc5w.so. It works best with the
NATIVE_UNICODE_STRINGFORMAT mode. You can also use the autotranscoding feature of mxODBC with UTF-8 as encoding.
•
Using a MySQL 5 Windows ODBC driver character setting of 'utf-8'
(with hyphen) can cause the driver to segfaults, so care must be taken,
using the right spelling for the character set setting.
mxODBC - Python ODBC Database Interface
•
The MySQL ODBC driver does not always update the .rownumber to the
correct value, especially when using .scroll(). For client side cursors,
mxODBC corrects this using an emulation for .rownumber.
•
When using the ODBC driver RPMs available from www.mysql.com,
please be sure to also have the MySQL shared libs RPM and the MySQL
development RPM installed.
•
Some older MySQL + ODBC driver setups eGenix.com has tested
showed some serious memory leaks on Linux machines. Please check
your setup for such leaks before going into production. There are no
known leaks in mxODBC itself.
Example Configuration for Unix
•
Add a MySQL driver section to the ~/.odbcinst.ini file (the location of the
driver file may be different on your system):
[ODBC Drivers]
MySQL = Installed
[MySQL]
Description = MySQL ODBC Driver
Driver = /usr/local/lib/libmyodbc5w.so
Setup =
•
Edit the ~/.odbc.ini file based and add a mysql section(the location of
the driver file may be different on your system). It is also necessary to
point LD_LIBRARY_PATH to the directory where the driver itself is
located.
[myodbc]
Driver = /usr/local/lib/libmyodbc5w.so
Description = MySQL 5 Server
Server = mysql.example.net
Port =
# Specifying a database is necessary for MySQL, since you'll
# otherwise won't be able to connect
Database = mydb
# Allow big packets for BLOBs, etc.
option = 8
#Socket =
•
Using these settings, you can then connect to MySQL using a simple
connection string such as:
"DSN=mysql;UID=username;PWD=password"
OpenLink ODBC Driver for MySQL
Homepage: http://www.openlinksw.com/
DataDirect ODBC Driver for MySQL
Homepage: http://www.datadirect.com/
54
4. Accessing Popular Databases
Actual Technologies Mac OS X ODBC Driver for MySQL
Homepage: http://www.actualtech.com/
When using the driver on Mac OS X 10.6 (Snow Leopard), be sure to use version
3.0.9 or higher, since earlier versions had a problem with fetching data.
4.7.2 General Notes
Depending on whether you use a transactional MySQL storage backend or not,
clearing the auto-commit flag at connection time, which is normally done per
default by the connection constructors, will not work.
Be sure to set clear_auto_commit=0 if you know that the storage backend
cannot handle transactions. mxODBC will then default to auto-commit mode.
Rollback will not work in that mode.
4.8 SAP MaxDB / SAPDB
4.8.1 Available ODBC Drivers
MaxDB ODBC driver
Homepage: http://www.sdn.sap.com/irj/sdn/maxdb
Tested with MaxDB 7.7 ODBC driver
MaxDB ships with ODBC drivers for all supported platforms. The ODBC driver is
included in the distribution tar archive of the database as SDBODBC.TGZ.
You can use the drivers with both unixODBC and iODBC.
Note that the MaxDB 7.7 ODBC driver can also connect to a MaxDB 7.6 database
server. It is usually best to use the latest available version, even if your database
servers hasn't been upgraded yet.
Example Configuration for Unix
•
Edit your ~/.odbcinst.ini file and add the MaxDB driver (the location of
the driver and setup file may be different on your system):
[ODBC Drivers]
MaxDB = Installed
[MaxDB]
55
mxODBC - Python ODBC Database Interface
Driver = /usr/local/maxdb/lib/libsdbodbcw.so
Description = MaxDB ODBC Driver
•
Edit your ~/.odbc.ini file and add a MaxDB section (the location of the
driver may be different on your system; be sure to use the Unicode
variant which ends with '…w.so'). It is also necessary to point
LD_LIBRARY_PATH to the directory where the driver itself is located.
[maxdb]
DRIVER = /usr/local/maxdb/lib/libsdbodbcw.so
ServerDB = MYDB
ServerNode = maxdb.example.net
SQLMode =
IsolationLevel =
Trace
= 0
TraceFileName=/tmp/maxdb.log
•
Using these settings, you can then connect to MaxDB using a simple
connection string such as:
"DSN=maxdb;UID=username;PWD=password"
4.8.2 General Database Notes
Warnings when deleting/update more than one row at a time
MaxDB issues a mx.ODBC.Error.Warning:
('01001',
0,
'[SAP
AG][LIBSDBOD SO] Cursor operation conflict', 8416) warning whenever
you try to delete or update more than one row with a single database statement.
You can easily work around this by setting the cursor.warningformat to
IGNORE_WARNINGFORMAT,
restoring
it
afterwards
to
the
default
ERROR_WARNINGFORMAT, if you just want to ignore this particular warning case.
4.9 Teradata
4.9.1 Available ODBC Drivers
Teradata ODBC Driver
Homepage: http://www.teradata.com/downloadcenter/
Tested with Teradata 14.1 ODBC driver and DataDirect 7.1 ODBC manager.
The Teradata ODBC driver was developed by DataDirect and requires the
DataDirect ODBC manager, so you will need to use the mx.ODBC.DataDirect
package on Unix to work with the driver.
56
4. Accessing Popular Databases
Driver Notes
•
The mx.ODBC.DataDirect package is currently only available for Linux
32-bit and 64-bit systems. If you need the package on other platforms,
please write to support@egenix.com for assistance.
•
The DataDirect ODBC driver manager is included in the same directory
as the Teradata ODBC driver itself. If you setup LD_LIBRARY_PATH to
the directory where the driver is located, mxODBC will automatically use
the right DataDirect ODBC driver manager, e.g.
export LD_LIBRARY_PATH=\
/opt/teradata/client/14.10/odbc_64/lib:\
/opt/teradata/client/14.10/tdicu/lib64
•
The Teradata ODBC driver uses a separate file for loading error messages.
The path for this is set using the NLSPATH environment variable and
should be set up like this (the directory will have to be adapted to the
location of the tdodbc.cat file:
export NLSPATH=/opt/teradata/client/14.10/odbc_64/msg/%N.cat
If not set, you will get exceptions like this from the driver:
[Teradata][ODBC
string.
Teradata
Driver]
Unable
to
get
catalog
•
Native Unicode is supported by the driver/manager combination setup
with the CharacterSet = UTF16 setting in the ~/.odbc.ini section for
Teradata.
•
Trying to use the Teradata ODBC driver with unixODBC or iODBC
usually results in an immediate segfault.
•
If you use the Teradata ODBC driver in combination with the DataDirect
ODBC manager, be sure to keep the ~/.odbc.ini file short. With longer
~/.odbc.ini files, the combination will segfault.
•
The 14.10 version of the driver insists on having a section [ODBC Data
Sources] in the ~/.odbc.ini file. Without it, the driver doesn't connect
and fails with the following error message:
[Teradata][ODBC Teradata Driver] No DBCName entries were
found in DSN/connection-string
This does not happen with the 13.10 driver.
57
•
We found that it is apparently not possible to use multi-line SQL
statements with the Teradata ODBC drivers 13.10 and 14.10. The
Teradata SQL parser complains about newline characters in the strings.
Removing these results in syntax errors. This makes it difficult to e.g.
define stored procedures from a Python application. The problem appears
to be a driver limitation which may be fixed in future Teradata driver
versions.
•
The Teradata driver only supports relative forward scrolling in the result
set. Backwards scrolling is not supported.
mxODBC - Python ODBC Database Interface
•
Teradata has the tendency to return non-ordered result sets in random
order. This is due to the way the database works internally. If you need to
rely on a reproducible result set order, please add an ORDER BY clause to
the SELECT statements as necessary.
Example Configuration for Unix
•
Setup your OS environment so that the ODBC manager can find and load
the driver (this is for the version 14.1 of the driver, your installation
directories may be different):
export LD_LIBRARY_PATH=\
/opt/teradata/client/14.10/odbc_64/lib:\
/opt/teradata/client/14.10/tdicu/lib64
export NLSPATH=/opt/teradata/client/14.10/odbc_64/msg/%N.cat
This last setting is important to make sure the driver can find its error
messages. If not set, you will get exceptions like this from the driver:
[Teradata][ODBC
string.
•
Teradata
Driver]
Unable
to
get
catalog
Edit your ~/.odbcinst.ini file and add the Teradata driver (the location of
the driver and setup file may be different on your system):
[ODBC Drivers]
Teradata = Installed
[Teradata]
Driver=/opt/teradata/client/13.10/odbc_64/lib/tdata.so
APILevel=CORE
ConnectFunctions=YYY
DriverODBCVer=3.51
SQLLevel=1
•
Edit your ~/.odbc.ini file and add a Teradata section (the location of the
driver may be different on your system). It is also necessary to point
LD_LIBRARY_PATH to the directory where the driver itself is located.
[ODBC]
Trace = 0
TraceFile = /tmp/odbc.log
[ODBC Data Sources]
teradata = Teradata
[teradata]
Driver = /opt/teradata/client/14.10/odbc_64/lib/tdata.so
Description = Teradata ODBC
DBCName = 192.168.0.250
DefaultDatabase = mydb
RunInQuietMode = Yes
DSNTraceEnable = No
DSNTraceFilePath = /tmp/teradata.txt
DSNTraceOverwrite = Yes
CharacterSet = UTF16
DateTimeFormat = AAA
# Disable preparing statements
#DisablePREPARE = Yes
# Max. response packet size in bytes
MaxRespSize = 10000000
# Disable parsing of SQL statements by the driver; do not set to
Yes
# if using .callproc() in the application.
NoScan = No
58
4. Accessing Popular Databases
# SessionMode can be Teradata or ANSI
SessionMode =
# Cursor open checks
StCheckLevel = 0
# Enable TCP_NODELAY ?
TCPNoDelay = Yes
# Port to use on the database servers
TDMSTPortNumber =
# Use BLOB and CLOB ?
UseNativeLOBSupport = Yes
Also see the above driver notes regarding how to format the .odbc.ini file.
•
Using these settings, you can then connect to Teradata using a simple
connection string such as:
"DSN=teradata;UID=username;PWD=password"
DataDirect ODBC Driver for Teradata
Homepage: http://www.datadirect.com/
4.10 Netezza
4.10.1 Available ODBC Drivers
Netezza ODBC Driver
Homepage: http://www.netezza.com/
Tested with Netezza 4.6.6 ODBC driver.
The Netezza ODBC driver is available to Netezza customers or partners.
eGenix.com partnered up with Netezza to make sure that mxODBC performs well
with Netezza's driver.
Recommended Setup
The recommended setup is to use the mx.ODBC.unixODBC subpackage together
with a unixODBC 2.3 or later ODBC manager.
The Netezza driver will also work with the DataDirect ODBC manager that ships
with the Netezza driver. If you use this setup, please interface to the DataDirect
ODBC manager using the mx.ODBC.DataDirect subpackage.
Also note that when using the DataDirect ODBC Manager we have seen segfaults
related to the .odbc.ini file being too big. You can work around this by either
keeping the file short, or by setting up a separate netezza-odbc.ini file and
pointing the driver manager to it using the ODBCINI environment variable.
59
mxODBC - Python ODBC Database Interface
Netezza and Unicode
Unicode data exchange doesn't work well when using the Netezza driver with the
DataDirect manager.
The unixODBC manager interface does not have these issues and works fine with
Unicode if the Netezza driver is configured for UTF-16 data using the
UnicodeTranslationOption = utf16 driver configuration option.
Example Configuration for Unix
•
Edit your ~/.odbcinst.ini file and add the Netezza driver (the location of
the driver and setup file may be different on your system):
[ODBC Drivers]
NetezzaSQL = Installed
[NetezzaSQL]
Driver
= /usr/local/nz/lib64/libnzodbc.so
Setup
= /usr/local/nz/lib64/libnzodbc.so
APILevel
= 1
ConnectFunctions = YYN
Description
= Netezza ODBC driver
DriverODBCVer
= 03.00
DebugLogging
= false
LogPath
= /tmp
# For unixODBC, use the following setting:
UnicodeTranslationOption = utf16
# For DataDirect, use this setting:
#UnicodeTranslationOption = utf8
CharacterTranslationOption = all
PreFetch
= 256
Socket
= 8192
•
Edit your ~/.odbc.ini file and add a Netezza section (the location of the
driver may be different on your system). It is also necessary to point
LD_LIBRARY_PATH to the directory where the driver itself is located.
[netezza]
Driver
Description
Servername
Port
Database
Username
Password
ReadOnly
ShowSystemTables
LegacySQLTables
LoginTimeout
QueryTimeout
DateFormat
NumericAsChar
SQLBitOneZero
StripCRLF
securityLevel
caCertFile
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
/usr/local/nz/lib64/libnzodbc.so
NetezzaSQL ODBC
netezza.example.net
5480
mydb
false
false
false
0
0
1
false
true
false
preferredUnSecured
# Needed by the DataDirect ODBC manager, values:
# 1=UTF-16, 2=UTF-8
DriverUnicodeType = 1
•
Using these settings, you can then connect to Netezza using a simple
connection string such as:
"DSN=netezza;UID=username;PWD=password"
60
4. Accessing Popular Databases
DataDirect ODBC Driver for Netezza
Homepage: http://www.datadirect.com/
4.11 Other Databases
If you want to run mxODBC in a Unix environment and your database doesn't
provide an Unix ODBC driver, you can try the drivers sold by these ODBC driver
specialists:
4.11.1 EasySoft ODBC Driver Packages
Homepage: http://www.easysoft.com/
EasySoft also maintains the open source ODBC manager unixODBC.
4.11.2 OpenLink
Homepage: http://www.openlinksw.com/
OpenLink maintains the open source ODBC manager iODBC.
4.11.3 DataDirect
Homepage: http://www.datadirect.com/
DataDirect drivers ship their own ODBC manager. Since this ODBC manager is
not compatible with unixODBC or iODBC, please use the mx.ODBC.DataDirect
driver manager package when accessing the DataDirect drivers through the
DataDirect ODBC manager.
The mx.ODBC.DataDirect package is currently only available for Linux 32-bit
and 64-bit systems. If you need the package on other platforms, please write to
support@egenix.com for assistance.
4.11.4 Other Vendors
For a fairly large list of sources for ODBC drivers have a look on the SQLSummit
list of ODBC drivers.
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mxODBC - Python ODBC Database Interface
4.11.5 Alternative solution: mxODBC Connect
If you would like to connect to a database for which you don't have a Unix ODBC
driver, you can also try our mxODBC Connect Python Database Interface which
just needs an ODBC driver on the server side and provides a cross-platform
networked interface to this for the client side. This makes it very easy to connect
to e.g. a Windows-based database from Unix, BSD or Mac OS X.
62
5. mxODBC Overview
5.
mxODBC Overview
mxODBC is structured as Python package to support interfaces to many different
ODBC managers and drivers. Each of these interfaces is accessible as subpackage
of the mx.ODBC Python package, e.g. on Windows you'd normally use the
mx.ODBC.Windows subpackage to access the Windows ODBC manager; on Unix
this would typically be the mx.ODBC.iODBC, mx.ODBC.unixODBC or the
mx.ODBC.DataDirect package depending on which of these Unix ODBC
managers you have installed.
Each of these subpackages behaves as if it were a separate Python database
interface, so you actually get more than just one interface with mxODBC. The
advantage over other Python database interfaces is that all subpackages share the
same logic and programming interfaces, so you don't have to change your
application logic when moving from one subpackage to another. This enables
programs to run (more or less) unchanged on Windows and Unix, for example.
As you may know, there is a standard for Python database interfaces, the Python
Database API Specification or Python DB-API for short. Marc-André Lemburg, the
author of the mxODBC package, is the editor of this specification, so great care is
taken to make mxODBC as compatible to the Python DB-API as possible.
5.1 mxODBC and the Python Database API
Specification
The mxODBC package tries to adhere to the Python DB API Version 2.0 in most
details. Many features of the old Python DB API 1.0 are still supported to maintain
backwards compatibility and simplify porting old Python applications to the new
interface.
5.1.1 Differences
Here is a list of minor differences between mxODBC and the DB API 2.0
specifications:
•
63
cursor.description doesn't return display_size and internal_size; both
values are always None, since this information is not readily available
through ODBC interfaces used for result set processing, the information
can be expensive to determine and the values are not commonly used in
applications. If you do need to access this information, you can use the
cursor.getcolattribute()
method
with
info
ids
SQL.DESC_DISPLAY_SIZE and SQL.DESC_OCTET_LENGTH.
mxODBC - Python ODBC Database Interface
•
db.setinputsizes()
•
The type objects / constructors (formerly found in the dbi module
defined by DB API 1.0) are only needed if you want to write database
independent code.
•
The connection constructor is available under three different names:
ODBC() (DB API 1.0), connect() (DB API 2.0) and Connect() (mxODBC
specific). See the next section for details on the used parameters.
mxODBC also defines a DriverConnect() constructor which is available
for ODBC managers and some ODBC drivers. If you can, please use the
DriverConnect() API since this provides more flexibility in configuring
the connection.
and db.setoutputsizes()
functions; this is allowed by DB API 2.0.
are
dummy
5.1.2 Extensions
mxODBC extends the DB-API specification in a significant number of ways to
provide access to as many ODBC features as possible. If you want to stay
compatible to other Python DB-API compliant interface, you should only use
those interfaces which are mentioned in the Python DB-API specification
documents.
5.2 mxODBC and the ODBC Specification
Since ODBC is a widely supported standard for accessing databases, it should in
general be possible to use the package with any ODBC version 2.0 - 3.8
compliant ODBC database driver/manager. mxODBC prefers ODBC 3.x over 2.x
in case the driver/manager supports both versions of the standard.
5.2.1 Full access to most ODBC features
The ODBC API is very rich in terms of accessing information about what is stored
in the database. mxODBC makes most of these APIs available as additional
connection and cursor methods and these can be put to good use for database
and schema introspection.
Since many of the parameters and names of the ODBC function names were
mapped directly to Python method names (by dropping the SQL prefix and
converting them to lower-case), we kindly refer you to the Microsoft ODBC
Documentation and your ODBC driver documentation for low-level details on the
various APIs.
64
5. mxODBC Overview
You also can access the MS ODBC online reference from the Microsoft MDAC
web-site.
Please note that not all ODBC drivers and databases support the complete set of
available introspection parameters. When using them, please make sure that the
databases supported by your application do implement the parameters used in
your application.
5.3 Supported ODBC Versions
mxODBC can be configured to use ODBC 2.x or 3.x interfaces by setting the
ODBCVER symbol in mxODBC.h to the needed value. It uses the value provided by
the ODBC driver header files per default which usually is the latest ODBC
standard version available.
Most ODBC drivers today support ODBC 3.x and thus mxODBC will try to use
APIs from this version if available.
5.3.1 ODBC Managers
All supported ODBC managers (MS ODBC Manager, iODBC, unixODBC and
DataDirect) provide the ODBC 3.x interfaces and map these to ODBC 2.x
interfaces in case the driver for the database does not comply to ODBC 3.x.
However, some drivers only pretend to be ODBC 3.x compliant and raise
"Driver not capable" exceptions when using certain ODBC 3.x APIs or
features. If you run into such an situation, please contact support for help. The
only way to solve this problem currently lies in adding workarounds which are
specific to a database.
To find out which ODBC version is being supported by the ODBC driver, you can
use connection.getinfo(SQL.DRIVER_ODBC_VER)[1]. This will return a string
giving you the ODBC version number, e.g. '03.51.00'.
5.3.2 Changes between ODBC 2.x and 3.x
Please also note that there are some changes in behavior between ODBC 2.x and
3.x compatible drivers/managers which means that certain option settings differ
slightly between the two versions and that special cases are treated differently for
ODBC 3.x than for ODBC 2.x. See the ODBC Documentation for details.
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mxODBC - Python ODBC Database Interface
5.4 Thread Safety & Thread Friendliness
mxODBC itself is written in a thread safe way. There are no module globals being
used and thus no locking is necessary.
5.4.1 Connections and Cursors
In general when using a separate database connection for each thread, you
shouldn't run into threading problems. If you do, it is more likely that the ODBC
driver is not 100% thread safe and thus not 100% ODBC compatible. Note that
having threads share cursors is not a good idea: there are many very strange
transaction related problems you can then run into.
5.4.2 Unlocking the Python Global Interpreter Lock (GIL)
Many of the underlying ODBC SQL function calls are wrapped by macros
unlocking the global Python interpreter lock before the call and regaining that lock
directly afterwards. The most prominent of those are the connection APIs and the
execute and fetch APIs.
Unlocking the interpreter lock during long SQL function calls gives your
application more responsiveness. This is especially important for GUI based
applications, since no other Python thread can run when the global lock is
acquired by one thread.
5.4.3 Threading Support
mxODBC will only support threading if you have built Python itself with thread
support enabled. Python for Windows and most recent Python versions for Unix
have this enabled per default. Try: python -c "import threading" to find out.
If you get an exception, thread support is not available.
5.5 Transaction Support
5.5.1 Auto-Commit
ODBC uses auto-commit on new connections per default. This means that all SQL
statement executes will directly have an effect on the underlying database even in
66
5. mxODBC Overview
those cases where you would really back out of a certain modification, e.g. due to
an unexpected error in your program.
mxODBC turns off auto-commit whenever it creates a new connection, ie. it
runs the connection in manual commit mode -- unless the connection
constructor flag clear_auto_commit is set to 0 or the database does not
provide transactions.
You can adjust the connection's commit mode after creating it using the
connection.autocommit attribute. See 5.5.3 Adjusting the Connection Commit
Mode for details.
5.5.2 Manual Commit
Using a connection in manual commit mode means that all your commands are
grouped in transactions: only the connection will see the changes it has made to
the data in the database until an explicit connection.commit() is issued.
The commit informs the database to write all changes done during the last
transaction into the global data storage making it visible to all other users. A
connection.rollback() on the other hand, tells the database to discard all
modifications processed in the last transaction.
Transaction Start and End
New transactions are started implicitly in the following cases:
•
creation of a new connection,
•
on return from a .commit() and
•
after having issued a .rollback().
Unless you perform an explicit connection.commit() prior to deleting or closing
the connection, mxODBC will try to issue an implicit rollback on that connection
before actually closing it.
Errors are only reported in case you use the connection.close() method.
Implicit closing of the connection through Python's garbage collection will ignore
any errors occurring during rollback.
Data Sources without Transaction Support
Data sources that do not support transactions, such as flat file databases (e.g.
Excel or CSV files on Windows), cause calls to .rollback() to fail with an
NotSupportedError. mxODBC will not turn off auto-commit behavior for these
sources. The setting of the connection constructor flag clear_auto_commit has
no effect in this case.
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mxODBC - Python ODBC Database Interface
Some databases for which mxODBC provides special subpackages such as MySQL
don't have transaction support, since the database does not provide transaction
support. For these subpackages, the .rollback() connection method is not
available at all (i.e. calling it produces an AttributeError) and the
clear_auto_commit flag on connection constructors defaults to 0.
5.5.3 Adjusting the Connection Commit Mode
You can adjust the connection's commit mode after creating it using the
connection.autocommit attribute. Setting the attribute to True will cause the
connection to operate in auto-commit mode again. Setting it to False will have
the connection use manual commit. The attribute also allows querying the current
commit mode in the same way.
Alternatively, you can use a connection.setconnectoption(SQL.AUTOCOMMIT,
call
to
turn
on
auto
commit
and
SQL.AUTOCOMMIT_ON)
connection.setconnectoption(SQL.AUTOCOMMIT, SQL.AUTOCOMMIT_OFF) to
turn it off again. Similarly, connection.getconnectoption(SQL.AUTOCOMMIT)
will return the current option value (as tuple).
5.6 Stored Procedures
mxODBC provides several ways to call stored procedures in databases and
supports input, input/output and output parameters to make integration with
existing database systems easy:
1. directly using the .callproc() cursor method, or
2. using the standard ODBC syntax for calling stored procedures and using
the standard .execute*() cursor methods to initiate the calls.
5.6.1 Calling Stored Procedures with .callproc()
The .callproc() cursor method is very straight forward way of calling stored
procedures:
results = cursor.callproc("myprocedure", parameters)
When
using
this
notation,
mxODBC
will
call
the
procedure
named
"myprocedure" with the variables given in the sequence parameters and return
a list copy of the parameters as results.
Parameters are bound to the procedure parameters by position, just as is done for
the .execute*() methods when using the 'qmark' parameter style.
68
5. mxODBC Overview
Results can be retrieved through output parameter, input/output parameters, or
result sets. Depending on the database backend, it is also possible to combine
both.
Retrieving output parameters from stored procedures
When not providing the optional parametertypes parameter as in the above
example, all parameters are considered to be input parameters, so results will
be a list copy of parameters.
If you want to use input/output or output parameters, you have to specify the
parametertypes parameter to define how to bind the variables to the procedure
parameters:
results = cursor.callproc("myprocedure", parameters, parametertypes)
Please see section 5.6.3 Input/Output and Output Parameters for more details on
how to use parametertypes.
Values from input/output and output parameters will then be updated in the
results list copy as returned by the stored procedure.
Example:
from mx.ODBC.unixODBC import SQL
…
results = cursor.callproc('sp_params',
[1, 0],
parametertypes=(SQL.PARAM_INPUT,
SQL.PARAM_OUTPUT))
if results == [1, 3]:
print 'Works.'
Retrieving result sets from stored procedures
The cursor.callproc() method can also be used to call stored procedures
which generate result sets. These can then be fetched using the standard
cursor.fetch*() methods. If the stored procedure has generate multiple result
sets, skipping to the next result set is possible by calling the .nextset() cursor
method.
Please see section 5.6.5 Using Result Sets for passing back Output Data for
details.
Example:
cursor.callproc('sp_result_set', [1])
result_set = cursor.fetchall()
5.6.2 Calling Stored Procedures with cursor.execute*()
Methods
Stored procedures and functions can also be called indirectly using the following
standard ODBC syntax for calling stored procedures.
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mxODBC - Python ODBC Database Interface
The ODBC syntax for calling a stored procedure is as follows:
{call procedure-name [([parameter][,[parameter]]...)]}
For stored functions or procedures with return status, the ODBC syntax is as
follows:
{? = call function-name [([parameter][,[parameter]]...)]}
Using the above syntax, you can call stored procedures through one of the
.execute*() calls, e.g.
results = cursor.execute("{call myprocedure(?,?)}", parameters)
will call the stored procedure myprocedure with the given input parameters.
It is also possible to use the 'named' parameter style, e.g.
results = cursor.execute("{call myprocedure(:a, :b)}", parameters)
Results can be retrieved through output parameter, input/output parameters, or
result sets. Depending on the database backend, it is also possible to combine
both.
Retrieving output parameters from stored procedures
When not providing the optional parametertypes parameter as in the above
examples, all parameters are considered to be input parameters, so results will
be a tuple copy of parameters.6
If you want to use input/output or output parameters, you have to specify the
parametertypes parameter to define how to bind the variables to the procedure
parameters:
results = cursor.execute("{call myprocedure(?,?)}",
parameters, parametertypes)
Please see section 5.6.3 Input/Output and Output Parameters for more details on
how to use parametertypes.
Values from input/output and output parameters will then be updated in the
results tuple copy as returned by the stored procedure.
Example:
from mx.ODBC.unixODBC import SQL
…
results = cursor.execute(
'{call sp_params(?,?)}',
[1, 0],
parametertypes=(SQL.PARAM_INPUT, SQL.PARAM_OUTPUT))
if results == [1, 3]:
print 'Works.'
For stored functions or procedures with return status, the syntax is similar (note
the prepended "? =":
results = cursor.execute("{? = call myfunction(?,?)}",
6
Note that the results sequence is a tuple or list of tuples for the cursor.execute*()
methods, not a list as for cursor.callproc(). This is due to the DB-API requiring a list for
cursor.callproc().
70
5. mxODBC Overview
parameters, parametertypes)
The return value from the function will be passed back as first parameter.
Accordingly, the first entry in parametertypes must be set to
SQL.PARAM_OUTPUT.
Example:
from mx.ODBC.unixODBC import SQL
…
results = cursor.execute(
'{? = call function_params(?,?)}',
[0, 1, 0],
parametertypes=(SQL.PARAM_OUTPUT,
SQL.PARAM_INPUT,
SQL.PARAM_OUTPUT))
if results == (4, 1, 2):
print 'Works.'
Retrieving result sets from stored procedures
In case the stored procedure generates one or more result sets, these can be
fetched using the standard cursor.fetch*() methods. If the stored procedure
has generate multiple result sets, skipping to the next result set is possible by
calling the .nextset() cursor method.
Please see section 5.6.5 Using Result Sets for passing back Output Data for
details.
Example:
cursor.execute('{call sp_result_set(?)}', [1])
result_set = cursor.fetchall()
5.6.3 Input/Output and Output Parameters
The mxODBC default assumption for bound parameters is to use input
parameters. These don't require additional information to be processed by
mxODBC.
ODBC and several databases also support output parameters (parameters which
don't have an input value, but are used for sending output back to the caller) and
input/output parameters (which are read for input and send data as output).
parametertypes Parameter
In order to tell which parameters are input/output or output parameters, mxODBC
needs additional information in form of a parametertypes sequence. This
sequence defines the type of parameter for each bound parameter in the order
they appear in the executed command or stored procedure definition.
The following types of parameters are supported. They are defined through the
SQL lookup variable which is available in all mxODBC subpackages.
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mxODBC - Python ODBC Database Interface
SQL.PARAM_INPUT
The parameter is an input parameter. Output values are not allowed and may
raise a database error or simply be ignored (this depends on the ODBC driver
and database).
SQL.PARAM_OUTPUT
The parameter is an output parameter. Input values are ignored.
Since mxODBC does not always have an efficient possibility to query the
output type of the stored procedure, the type of the corresponding parameter
value in the input parameters sequence is used as hint to the output type. Even
though the value itself is ignored, it should therefore match the expected
output type of the output parameter7.
SQL.PARAM_INPUT_OUTPUT
The parameter is a combination of input and output parameter. Input values
are passed to the command/stored procedure parameters. After execution of
the command/stored procedure, the output values are read back from the
database.
Note: The parametertypes parameter and - as a result - output and
input/output parameters are not supported for 'named' parameter style mode.
This may change in future mxODBC versions.
Example for cursor.execute():
from mx.ODBC.unixODBC import SQL
…
results = cursor.execute('{call get_max_value(?, ?)}',
(1, 3),
parametertypes=(SQL.PARAM_INPUT,
SQL.PARAM_INPUT_OUTPUT))
Example for cursor.callproc():
from mx.ODBC.unixODBC import SQL
…
results = c.callproc('get_max_value',
(1, 3),
parametertypes=(SQL.PARAM_INPUT,
SQL.PARAM_INPUT_OUTPUT))
Dynamically determining the Parameter Type
In some situations it may not be possible to determine the parameters
beforehand, e.g. when dynamically creating a stored procedure call.
Fortunately, the cursor catalog methods provide a way to determine which
parameters are input, output or input/output parameters via the
cursor.procedurecolumns() method.
7
Some ODBC drivers/database backends can provide type information for output
parameters in stored procedures, but others fail to provide usable information. If you run
into problems with data type conversion errors, please try setting the cursor.bindmethod
to BIND_USING_PYTHONTYPE before running the procedure call.
72
5. mxODBC Overview
This generates a result set with column COLUMN_TYPE which has the needed
information.
Please
see
the
documentation
in
section
cursor.procedurecolumns() for details.
7.6.1
Catalog
Methods
for
5.6.4 Special constraints of some ODBC drivers
Mixing output parameters and output result sets
Some ODBC drivers, most notably, the MS SQL Server Native Client, send the
output parameter data only after any output result sets which the stored
procedure may have created.
Since the mxODBC cursor methods return the output parameter right after
executing the stored procedure and before fetching any result sets, the output
parameters are not yet updated. Furthermore, there is no method of accessing the
output parameters after those methods have returned.
As a result, you won't see output parameter updates in your application, if you
are using both output parameters and output result sets in your stored
procedures.
The work-around for this is to pass back the output parameter data using an
additional result set and then fetching this using the cursor.nextset() method
after the other result sets. Also see section 5.6.5 Using Result Sets for passing
back Output Data on this topic.
Example:
cursor.callproc('procname', parameters)
# Get the original output result set
output_result_set = cursor.fetchall()
# Switch to the new output parameter result set
cursor.nextset()
output_parameter_result_set = cursor.fetchall()
Using None as value for output parameters
mxODBC uses the value passed to the cursor execution method as hint for the
output type of the output parameter, in case the ODBC driver does not provide
this information.
If you pass in None as placeholder for the output parameter value, mxODBC is, in
some cases, unable to determine the correct output type. It then defaults to using
a VARCHAR(4000) output parameter value and sends back the data as character
string.
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mxODBC - Python ODBC Database Interface
Especially for numeric data, this may both be inefficient and inconvenient, so it's
better to pass in a value which matches the output parameter type such as 0 for
integer or 0.0 for floating point data.
5.6.5 Using Result Sets for passing back Output Data
It is also possible and to pass back data from the stored procedure via standard
result sets which can be fetched from mxODBC using the cursor.execute*()
methods.
This method is often preferred when dealing with larger data chunks, or table
data.
Using result sets to pass back output data
Passing back such data in form of one or more result sets allow for great flexibility
in exchanging data between stored procedures and your Python application, also
let's you implement variable length output parameter lists and special output value
conversions.
This can easily be done by adding a SELECT to the stored procedure which then
returns the data as additional result set:
SELECT OutputParam1, OutputParam2
or even using multiple result sets:
SELECT OutputParam1; SELECT OutputParam2
You
can
then
pick
cursor.fetchall():
up
the
data
using
cursor.nextset()
and
rs1 = c.fetchall()
c.nextset()
rs2 = c.fetchall()
c.nextset()
rs3 = c.fetchall()
Example:
>>> c.execute('select 1; select 2')
>>> c.fetchall()
[(1,)]
>>> c.nextset()
True
>>> c.fetchall()
[(2,)]
MS SQL Server and Sybase ASE Cursors in Stored Procedures
MS SQL Server and Sybase ASE both make the result sets from SELECTs in the
stored procedures available to the mxODBC cursor via cursor.fetch*().
Example:
CREATE PROCEDURE sp_result_set
@a INTEGER
AS
74
5. mxODBC Overview
SELECT @a * 3;
Oracle Ref Cursors as Output Parameters
Oracle has the concept of reference cursors, which provide a similar way to pass
cursors to the stored procedure caller. Instead of defining an output variable or a
set of output variables, you simply define a REF CURSOR as output variable in
your stored procedure.
You can then access the open cursor after calling the stored procedure by simply
using the standard .fetch*() and .nextset() APIs to access the results. The
key to making this work is by not passing in any variable for the output REF
CURSOR when calling the stored procedure. 8
Oracle Base has a more detailed article on this:
•
Using Ref Cursors To Return Recordsets
Example:
CREATE PROCEDURE sp_result_set
(a INTEGER,
rs OUT SYS_REFCURSOR)
AS
BEGIN
OPEN rs FOR
SELECT a * 3 FROM DUAL;
END;
Note that you don't need to call the procedure with the second parameter. The
result set will still be available.
IBM DB2 Cursors in Stored Procedures
IBM has a similar feature to the Oracle Ref Cursors. You simply declare a cursor
and open it before returning from the stored procedure. The cursor is then
available for reading in Python.
Example:
CREATE PROCEDURE sp_result_set
(a INTEGER)
RESULT SETS 1
BEGIN
DECLARE c1 CURSOR WITH RETURN FOR
SELECT a * 3 FROM SYSIBM.SYSDUMMY1;
OPEN c1;
END
PostgreSQL Cursors in Stored Procedures
PostgreSQL also allow opening cursors in stored procedures which are then
available in Python via mxODBC's cursor.fetch*() methods.
Example:
CREATE FUNCTION sp_result_set
8
Thanks to Etienne Desgagné for pointing out this solution.
75
mxODBC - Python ODBC Database Interface
(a INTEGER,
rs OUT refcursor)
AS $$
BEGIN
OPEN rs FOR
SELECT a * 3;
END;
$$ LANGUAGE plpgsql;
5.6.6 SQL Output Statements in Stored Procedures
You should not use any output SQL statements such as "PRINT" in the stored
procedures, since this will cause at least some ODBC drivers (notably the MS SQL
Server one) to turn the output into an SQL error which causes the execution to
fail.
On the other hand, these error messages can be useful to pass along error
conditions to the Python program, since the error message string will be the
output of the "PRINT" statement.
5.7 Introspection
5.7.1 Database Schema Introspection
mxODBC provides the full set of ODBC supported introspection cursor methods
which allows querying most database schema details without having to rely on
database specific internal system tables.
Usage is easy: Open a connection to the database, open a cursor on the
connection. Then call a catalog method on the cursor and inspect the generated
result set using the cursor.fetch*() methods.
Please see section 7.6.1 Catalog Methods for full details on the available catalog
methods and their generated result sets.
5.7.2 Result Set Introspection
When working with dynamically generated SQL statements, you often need to
check the result set layout in order to prepare for processing the result set.
76
5. mxODBC Overview
Introspection via cursor.execute()
In mxODBC this can be done right after executing a SQL statement using one of
the cursor.execute*() methods by looking at the cursor.description
attribute.
Introspection via cursor.prepare()
Alternatively, you can use the cursor.prepare() method to just prepare
execution of a SQL statement - without actually executing it. This may be desirable
in case the result set is not immediately needed or the query would require a long
time to execute.
The cursor.description attribute
This cursor attribute provides access to a sequence of tuples, each describing the
result set column at that position: (name, type_code, display_size,
internal_size, precision, scale, null_ok).
If no information is available the cursor.description is set to None.
The column tuple entries have the following meanings (index given in square
brackets):
name [0]
Name of the column as returned by the database.
type_code [1]
In mxODBC, this is the SQL type integer describing the database data type of
the result set column. These are described in the section 8 Supported Data
Types and are available through the SQL singleton defined at subpackage
module level for comparisons.
display_size [2]
mxODBC will always return None for this field. For database tables, this
information can be determined by using the
cursor.getcolattribute(position, SQL.DESC_DISPLAY_SIZE) method,
if needed.
internal_size [3]
mxODBC will always return None for this field. For database tables, this
information can be determined by using the
cursor.getcolattribute(position, SQL.DESC_OCTET_LENGTH) method,
if needed.
precision [4]
Precision of numeric columns.
scale [5]
Scale of numeric columns.
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mxODBC - Python ODBC Database Interface
null_ok [6]
Returns 1 if the column can contain NULL values (which are returned as None
in Python).
The cursor.getcolattribute() method
The cursor.getcolattribute() method provides more information about the
result set columns than the Python DB-API compatible cursor.description
sequence.
It also allows querying for auto-increment columns, the base column and table
name, the database specific type name, etc.
Please see the document for cursor.getcolattribute() in section 7.6 Cursor
Object Methods for details.
5.8 ODBC Cursor Types
Starting with mxODBC 3.2, mxODBC supports several different ODBC cursor
types. These types define how the cursors will be used by the application and
whether or not the application will see changes to the result set while fetching the
result set rows.
As with other cursor settings, the ODBC cursor type default value can be defined
on the mxODBC connection object and the setting is then inherited by the
mxODBC cursor objects created on that connection. Subsequent changes to the
cursor type on the cursor do not affect the setting on the connection.
5.8.1 Adjusting/Inspecting the ODBC Cursor Type
Both connections and cursors expose a read/write .cursortype attribute for this
purpose. The attribute uses the ODBC defined values for the cursor types.
The following values are defined in the ODBC standard:9
SQL.CURSOR_FORWARD_ONLY
The cursor only scrolls forward. This is the default setting used by
mxODBC for all databases.10
9
The SQL global refers to the mxODBC subpackage global of the same name, e.g. for
mx.ODBC.Windows, this is accessible as mx.ODBC.Windows.SQL.
10
Please note that in mxODBC 3.2, the default was database dependent.
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5. mxODBC Overview
SQL.CURSOR_STATIC
The result set is made static by creating a static copy of the result set after
opening the cursor. As a result, any changes to the result set after opening
the cursor will not be visible to the client. Databases typically require
setting the cursor type to static to support backwards scrolling in the result
set via the cursor.scroll() call. Please note that creating a static copy
can result in a significant performance degradation, esp. with MS SQL
Server and less so with IBM DB2.
SQL.CURSOR_KEYSET_DRIVEN
Keysets are sets of columns in the result set that provide unique keys to the
rows in the result set. Keyset driven cursors fix the memberships and order
of the rows in the result set using these keysets. Unlike static cursors, they
don't create a copy of the result set.
SQL.CURSOR_DYNAMIC
Dynamic cursors are the opposite of static cursors. All changes to the result
set after opening it are visible on the next fetch operation.
Please note that using cursor types other than SQL.CURSOR_FORWARD_ONLY may
have a significant effect on the performance of fetch operations. Not all databases
support all listed cursor types.
5.8.2 Default Cursor Type
mxODBC defaults to using forward-only cursors with all databases.11
Some databases also support other cursor types, which may be useful in certain
application settings, e.g. to make sure that the result set cannot change while
fetching it, or to enable backwards scrolling through a result set.
mxODBC therefore allows changing the cursor type on a per connection or cursor
basis using the connection.cursortype / cursor.cursortype attributes.
You can check the currently used cursor type by inspecting the .cursortype
attribute on a newly created connection/cursor objects:
if connection.cursortype == mx.ODBC.Windows.SQL.CURSOR_STATIC:
print "Connection uses static cursors."
elif connection.cursortype == mx.ODBC.Windows.SQL.CURSOR_FORWARD_ONLY:
print "Connection uses forward only cursors."
As with most connection attributes, the setting is inherited by the cursors created
on the connection at creation time. You can adjust the .cursortype on a cursor
prior to executing a statement by assigning to the cursor.cursortype attribute:
cursor.cursortype == mx.ODBC.Windows.SQL.CURSOR_STATIC
in case you need e.g. static cursor behavior for that cursor.
11
In mxODBC 3.2, mxODBC used to default to static cursors for some databases such as
MS SQL Server and IBM DB2, but this was found to cause performance problems.
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mxODBC - Python ODBC Database Interface
Backwards Compatibility Notice:
Please note that mxODBC 3.2 used to set the default cursor type depending on
whether the database supports static cursors or not. For those that do, it used
static cursors, for all others, it used forward-only cursors. In mxODBC 3.3, we
have changed this back to defaulting to forward-only cursors for all databases
due to performance issues with static cursors.
5.8.3 Effects of the Cursor Type on cursor.rownumber
Some databases do not provide accurate information for cursor.rownumber in
case forward-only cursors are used. Examples are MS Access, Teradata and
Oracle.
Since mxODBC 3.3 switched to forward-only cursors for all databases, we have
added a special client-side .rownumber emulation to mitigate this problem.
If the emulation cannot be provided or the value cannot be determined, the
cursor.rownumber attribute is set to None.
5.8.4 Database Specific Cursor Type Notes
MS SQL Server
MS SQL Server supports backwards scrolling and other more advanced scrolling
modes when using static cursors. With forward only cursors, these scrolling
capabilities are no longer available. The attribute .rownumber is emulated by
mxODBC, since SQL Server returns wrong results with forward cursors.
We still recommend setting the .cursortype to SQL.CURSOR_FORWARD_ONLY in
case result set scrolling is not needed by the application, since fetch operations on
static cursors can result in a significant slow-down compared to forward only
cursors.
Adjusting the default cursor type can be done on a per connection basis:
connection = mx.ODBC.Windows.DriverConnect(…)
connection.cursortype = mx.ODBC.Windows.SQL.CURSOR_STATIC
# All cursors created on connection will then default to static
# cursor type, allowing backwards scrolling.
Performance Hint:
In tests we have seen slow-downs from 2-3x for average queries, up to 300x for
simple ones, when using static cursors compared to forward only ones.
Oracle
mxODBC uses forward only cursors as default, since using other types can cause
segfaults in the ODBC driver.
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5. mxODBC Overview
PostgreSQL
mxODBC defaults to forward only cursors, since the driver becomes unusable
with other settings.
IBM DB2
Just like MS SQL Server, IBM DB2 supports static cursors as well, so you can
enable these, if you need scrolling support or .rowcount information.
There is a performance penalty of about 2x in using static cursors.
connection = mx.ODBC.Windows.DriverConnect(…)
connection.cursortype = mx.ODBC.Windows.SQL.CURSOR_STATIC
# All cursors created on connection will then default to static
# cursor type.
Note that with forward cursors, the .rowcount attribute does not always give
correct results with DB2.
5.9 Custom Cursor Row Objects and Row
Factory Functions
In some situation you may want to have mxODBC return a different Python object
type or class when fetching rows from the database, e.g. ones which offer not
only indexes based access to the row fields, but also named attribute or index
access.
mxODBC
3.3 introduced two new cursor attributes cursor.row and
cursor.rowfactory which can be used to customize the objects returned by
mxODBC in result sets when using the cursor.fetch*() methods.
Default is to return standard Python tuples for rows in the result, since this is the
most performant way of providing access to the data.
With the new attributes, it is possible to have mxODBC automatically return other
sequence types (e.g. lists), hybrids providing sequence/mapping/attribute access
to the columns or higher-level abstraction layer objects.
5.9.1 Cursor Row Constructor: cursor.row
In order to have mxODBC use a different row constructor than the tuple
constructor, set the cursor.row attribute to a function or class which takes a
single parameter, the row tuple, and returns an object for the row.
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mxODBC - Python ODBC Database Interface
Setting the value has an immediate effect on subsequent cursor.fetch*() calls.
mxODBC does not reset this attribute after the fetch operation, so the setting
persists until set to another constructor or None.
Setting cursor.row to None resets the row constructor to the mxODBC default of
using Python tuples.
Examples:
# Have mxODBC return lists for rows instead of tuples:
cursor.row = list
result_set = cursor.fetchall()
# Have mxODBC return tuples again:
cursor.row = None
result_set = cursor.fetchall()
# Have mxODBC return a custom object instead of tuples:
cursor.row = MyRow
result_set = cursor.fetchall()
Attribute Inheritance: cursor.row and connection.row
As with many other cursor attributes, the cursor.row attribute inherits its default
value from the connection on which the cursor was created. At creation time, the
cursor.row attribute is set to connection.row.
Adjusting connection.row after the cursor was created does not have an effect
on cursor.row anymore. The connection attribute setting is only used when
creating the cursor.
5.9.2 Cursor Row Factories: cursor.rowfactory
The cursor.row constructor attribute is useful for object types that don't depend
on the result set that is being returned or where you know that the result set rows
are going to have a specific layout before running the query.
On-the-fly Creation of Row Classes
In many cases, you will want to use custom row objects even for queries that
depend on external settings or where you don't want to create a specific object
class in advance.
This is where the cursor.rowfactory attribute comes in handy. It allows you to
specify a factory function which provides the row constructor depending on the
cursor that just executed a query or statement.
When set, the row factory function cursor.rowfactory is called with the cursor
as first parameter when calling the first cursor.fetch*() method on the cursor
to fetch a new result set, but before actually fetching the first row.
The return value is then assigned to cursor.row, which then results in the
cursor.row constructor to be used for fetching the rows of the result set.
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5. mxODBC Overview
This makes it easy to define your own factory functions to programmatically
define row classes based on the cursor.description or other cursor
parameters.
Row Factories and multiple Result Sets
If you are using multiple result sets, the cursor.rowfactory is called for the first
fetch in each of the result sets you are reading from the database.
Predefined Row Factories
mxODBC comes with a set of useful row factories which provide both sequence
index access as well as named attribute access. These are defined in the
mx.ODBC.Misc.RowFactory module, which is imported into all mxODBC
subpackages for convenience. See section 13 mx.ODBC.Misc.RowFactory Module
for the API documentation.
The module defines these row factories:
RowFactory.TupleRowFactory
This is a factory which is a subtype of the Python tuple type and provides a
standard tuple index based access to the row column values, as well as an
attribute based one which is derived from the lower-cased column names
found in cursor.description.
The row objects are immutable, just like standard tuples, but you can also slice
them or index them as usual.
Example:
from mx.ODBC.Windows import RowFactory
cursor.rowfactory = RowFactory.TupleRowFactory
cursor.execute('select x, Y, z from mytable')
row = cursor.fetchone()
print (row[0], row[1], row[2], row.x, row.y, row.z)
Because the row objects implement the sequence protocol, they are also
usable as input parameters to the cursor.execute*() methods.
Example:
cursor.execute('insert into mytable values (x, Y, z)', row)
RowFactory.ListRowFactory
This factory uses a subtype of the Python list type and also provides a
sequence index based access, as well as a named attribute access, just like the
TupleRowFactory.
Unlike for the TupleRowFactory, the row objects created by the
ListRowFactory are mutable lists, so you can assign to the indexes as well as
the attributes.
Example:
from mx.ODBC.unixODBC import RowFactory
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mxODBC - Python ODBC Database Interface
cursor.rowfactory = RowFactory.ListRowFactory
cursor.execute('select x, Y, z from mytable')
row = cursor.fetchone()
print (row[0], row[1], row[2], row.x, row.y, row.z)
row[0] = 10
row[1] = 'abc'
print (row[:2])
# will print [10, 'abc']
row.x = 20
row.y = 'def'
print (row[:2])
# will print [20, 'def']
The row objects are also usable as input for the cursor.execute*()
methods.
Example:
cursor.execute('insert into mytable values (x, Y, z)', row)
RowFactory.NamespaceRowFactory
The NamespaceRowFactory creates mx.Misc.Namespace.Namespace objects
as row objects. These provide a more complex namespace oriented API.
In addition to the sequence protocol, they also allow mapping access as well
as named attribute access based on the lower-cased column names read from
cursor.description.
Rows created by this factory are mutable.
Example:
from mx.ODBC.iODBC import RowFactory
cursor.rowfactory = RowFactory.NamespaceeRowFactory
cursor.execute('select x, Y, z from mytable')
row = cursor.fetchone()
print (row[0], row[1], row[2])
print (row.x, row.y, row.z)
print (row['x'], row['y'], row['z'])
row[0] = 10
row[1] = 'abc'
print (row[:2])
# will print [10, 'abc']
row.x = 20
row.y = 'def'
print (row[:2])
# will print [20, 'def']
row['x'] = 30
row['y'] = 'ghi'
print (row[0], row[1])
# will print [30, 'ghi']
The row objects are also usable as input for the cursor.execute*()
methods.
Example:
cursor.execute('insert into mytable values (x, Y, z)', row)
All factories create row classes on-the-fly, based on cursor.description.
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5. mxODBC Overview
Factory created Row Classes and pickle
Because of the way these row classes are dynamically created, they are by default
not pickleable.
In order to be pickleable, they would have to be saved to a module namespace, so
that pickle can recreate them at load time. Since the creation parameters depend
on the cursor state at creation time, this is not easily possible.
If you know that a cursor will use particular result set layout, you can statically
create the row class using the factory functions, register the class in a module and
then set the cursor.row directly to the row class.
Example:
# Create a cursor with information about the result set
cursor.execute('select * from mytable')
# Create the row class
MyTableRow = RowFactory.TupleRowFactory(cursor)
# Adjust the MyTableRow class so that pickle can find the right module
# (__name__) and class name ('MyTableRow')
MyTableRow.__name__ = 'MyTableRow'
MyTableRow.__module__ = __name__
# Fetch the data using MyTableRow objects
cursor.row = MyTableRow
rows = cursor.fetchall()
The resulting rows list is pickleable, since it can find the module and class name.
Attribute Inheritance: cursor.rowfactory and
connection.rowfactory
Just like for cursor.row, the cursor.rowfactory attribute inherits its default
value from the connection on which the cursor was created. At creation time, the
cursor.rowfactory attribute is set to connection.rowfactory.
Adjusting connection.rowfactory after the cursor was created does not have
an effect on cursor.rowfactory. The connection attribute setting is only used
when creating the cursor.
5.10 mxODBC Subpackages
The mxODBC package is organized in subpackages, with one package per support
ODBC driver manager and in custom builds, additional subpackages for specific
drivers/databases.
See section 14 mx.ODBC Driver/Manager Packages for details on available
subpackages.
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mxODBC - Python ODBC Database Interface
5.10.1 One API for all Subpackages
To make applications portable between ODBC database backends, each of these
subpackages use the same names and API signatures, in fact, the same mxODBC
implementation is used for each of the subpackages, customized to meet the
respective ODBC driver/manager's specific requirements.
As an example, say if you are using the mx.ODBC.Windows subpackage, then the
constructor to call would be mx.ODBC.Windows.DriverConnect(). When
porting the application to Unix you'd use e.g. the mx.ODBC.iODBC subpackage and
the constructor then becomes mx.ODBC.iODBC.DriverConnect().
In your application you'd just have to change the top-level import from
from mx.ODBC import Windows as Database
to
from mx.ODBC import iODBC as Database
The subpackage globals such as exception names, helper functions, connection
constructors, etc. remain the same, so no additional changes are necessary.
Of course, you will usually have to rely on different ODBC drivers when switching
from Windows to Unix or the other way around. While the mxODBC API names
and signatures don't change, you will likely have to make some application level
changes to accommodate for differences in the ODBC drivers you are using.
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6. mxODBC Connection Objects
6.
mxODBC Connection Objects
Connection objects provide the communication link between your Python
application and the database. They are also the scope of transactions you perform.
Each connection can be setup to your specific needs, multiple connections may be
opened at the same time.
6.1 Subpackage Support
Connection objects are supported by all subpackages included in mxODBC.
The extent to which the functionality and number of methods is supported may
differ from subpackage to subpackage, so you have to verify the functionality of
the used methods (esp. the catalog methods) for each subpackage and database
that you intend to use.
6.2 Connection Type Object
mxODBC uses a dedicated object type for connections. Each mxODBC
subpackage defines its own object type, but all share the same name:
ConnectionType.
6.3 Connection Object Constructors
Connect(dsn, user='', password='', clear_auto_commit=1,
errorhandler=None, connection_options=())
This constructor returns a connection object for the given data source. It
accepts keyword arguments. dsn indicates the data source to be used, user
and password are optional and used for database login.
errorhandler may be given to set the error handler for the Connection object
prior to actually connecting to the database. This is useful to mask e.g. certain
warnings which can occur at connection time. The errorhandler can be
changed after the connection has been established by assigning to the
.errorhandler attribute of the Connection object. The default error handler
raises exceptions for all database warnings and errors. See section 10.4 Error
Handlers for more details on how to use error handlers.
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mxODBC - Python ODBC Database Interface
If you connect to the database through an ODBC manager, you should use the
DriverConnect() API since this allows passing more configuration
information to the manager and thus provides more flexibility over this
interface.
See the following section 6.4 Default Transaction Settings for details on
clear_auto_commit.
connection_options may be given as list of (option, value) tuples to set
pre-connect ODBC connection options. The option and value arguments
must use the same format as the parameters for the .setconnectoption()
method. This list can be used to e.g. enable the MARS feature of SQL Server
Native Client, which enables working with multiple active result sets on the
same connection:
from mx.ODBC.Manager import DriverConnect, SQL
options = [(SQL.COPT_SS_MARS_ENABLED, SQL.MARS_ENABLED_YES)]
db = DriverConnect('DSN=mssqlserver2008;UID=sa;PWD=dbs0R-X9.rxD',
connection_options=options)
connect(dsn, user='', password='', clear_auto_commit=1,
errorhandler=None)
Is just an alias for Connect() needed for Python DB API 2.0 compliance.
DriverConnect(DSN_string, clear_auto_commit=1, errorhandler=None)
This constructor returns a connection object for the given data source which is
managed by an ODBC Driver Manager (e.g. the Windows ODBC Manager or
iODBC). It allows passing more information to the database than the standard
Connect() constructor.
errorhandler may be given to set the error handler for the Connection object
prior to actually connecting to the database. This is useful to mask e.g. certain
warnings which can occur at connection time. The errorhandler can be
changed after the connection has been established by assigning to the
.errorhandler attribute of the Connection object. The default error handler
raises exceptions for all database warnings and errors. See section 10.4 Error
Handlers for more details on how to use error handlers.
Please refer to the documentation of your ODBC manager and the database for
the exact syntax of the DSN_string. It typically has this formatting:
'DSN=datasource_name;UID=userid;PWD=password' (case can be
important and more entries may be needed to successfully connect to the data
source).
See the following section 6.4 Default Transaction Settings for details on
clear_auto_commit.
connection_options may be given as list of (option, value) tuples to set
pre-connect ODBC connection options. The option and value arguments
must use the same format as the parameters for the .setconnectoption()
method. This list can be used to e.g. enable the MARS feature of SQL Server
Native Client, which enables working with multiple active result sets on the
same connection:
from mx.ODBC.Manager import DriverConnect, SQL
options = [(SQL.COPT_SS_MARS_ENABLED, SQL.MARS_ENABLED_YES)]
db = DriverConnect('DSN=mssqlserver2008;UID=sa;PWD=dbs0R-X9.rxD',
connection_options=options)
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6. mxODBC Connection Objects
The DriverConnect() API is only available if the ODBC driver or ODBC
driver manager supports this. It is available on all supported ODBC driver
manager
subpackages
such
as
the
one
for
Windows
and
iODBC/unixODBC/DataDirect on Unix platforms. See the subpackages section
for details.
ODBC(dsn, user='', password='', clear_auto_commit=1,
errorhandler=None)
Is just an alias for Connect() needed for Python DB API 1.0 compliance.
6.4 Default Transaction Settings
ODBC usually defaults to auto-commit, meaning that all actions on the
connection are directly applied to the database. Since this can be dangerous,
mxODBC defaults to turning auto-commit off at connection initiation time
provided the database supports transactions.
All connection constructors implicitly start a new transaction when connecting to
a database in transactional mode.
When connecting to a database with transaction support, you should explicitly do
a .rollback() or .commit() prior to closing the connection. mxODBC does an
automatic rollback of the transaction when the connection is closed if the driver
supports transactions.
6.4.1 Overriding the Default
The value of the clear_auto_commit connection parameter overrides this default
behavior. Passing a 0 as value disables the clearing of the auto-commit flag and
lets the connection use the database's default commit behavior. Please see the
database documentation for details on its default transaction setting.
Use
the
connection
SQL.AUTOCOMMIT,
method
connection.setconnectoption(
to
adjust
the
SQL.AUTOCOMMIT_ON|OFF|DEFAULT)
connection's behavior to your needs after the connection has been established,
but before you have opened a database cursor.
With auto-commit turned on, transactions are effectively disabled. The
rollback() method will raise a NotSupportedError when used on such a
connection.
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mxODBC - Python ODBC Database Interface
6.4.2 Errors due to missing Transaction Support
If you get an exception during connect telling you that the driver is not capable or
does not support transactions, e.g. mxODBC.NotSupportedError: ('S1C00',
84, '[Microsoft][ODBC Excel Driver]Driver not capable ', 4226), try
to connect with clear_auto_commit set to 0. mxODBC will then keep autocommit switched on and the connection will operate in auto-commit mode.
6.5 Connection objects as context managers
6.5.1 Introduction to Context Managers
Python 2.5 introduced the new concept of context manager to Python. Context
managers are Python objects implementing the context manager API based on the
methods .__enter__() and .__exit__().
The context managers can be used together with the Python with-statement to
wrap sections of a program into a block (the context) that is entered and exited in
a controlled way:
with context_manager as context:
context.do_something()
When entering the block, the context_manager's .__enter__() method is
called and the returned object assigned to context. When exiting the block, the
context.__exit__() is called, either with the exception that caused the block to
be left or without exception in case the block was left normally.
6.5.2 Using connection objects as context object
Connection objects implement this API and use it to automatically commit or roll
back the current transaction.
from mx.ODBC.Manager import DriverConnect
connection = DriverConnect(…)
with connection:
cursor = connection.cursor()
cursor.execute('INSERT INTO table VALUES (?, ?)', (1, 2))
… other tasks …
cursor.close()
This code will automatically commit the INSERT to the database backend in cae
the with-block is left without exception. If the other tasks trigger an unhandled
transaction, the connection is rolled back when leaving the block.
For code which doesn't have to do more complex error handling, using the withstatement block can greatly simplify the resulting code. It also gives the
transaction section a visible resemblance in the code.
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6. mxODBC Connection Objects
Cursors also support the context manager API, so the above could be simplified
even more to:
with connection:
with connection.cursor() as cursor:
cursor.execute('INSERT INTO table VALUES (?, ?)', (1, 2))
… other tasks …
6.6 Unicode/ANSI Connections
Starting with mxODBC 3.1, it is possible to tell the ODBC driver manager whether
to use the Unicode ODBC interface of a supporting ODBC driver or the ANSI (8bit string) ODBC interface at connection time.
6.6.1 Unicode ODBC Interface
If the ODBC driver supports the ODBC Unicode interface and you select the
Unicode interface by using a Unicode string as connection parameter, the ODBC
manager will subsequently convert all ANSI-parameters to Unicode and then call
the Unicode APIs of the ODBC driver. Unicode parameters are passed through asis to the ODBC driver.
For ODBC drivers that natively support the ODBC Unicode interface, connecting
using a Unicode connection string and subsequently using Unicode parameters
for all execution and catalog methods may result in better performance or
improved compatibility.
Example:
# Use the Unicode ODBC API of the driver by using a Unicode connection
# string
db = mx.ODBC.Windows.DriverConnect(u'DSN=mydb;UID=uid;PWD=pwd')
6.6.2 ANSI ODBC Interface
If the ODBC driver does not support the ODBC Unicode interface, or you connect
using an ANSI (8-bit string), the ODBC driver manager will subsequently convert
all Unicode parameters to the connection's ANSI code page before calling the
ANSI API on the ODBC driver. ANSI parameters are passed through as-is to the
ODBC driver.
For ODBC drivers that do not support the ODBC Unicode interface, connecting
using an ANSI connection string and subsequently using ANSI parameters for all
execution and catalog methods may result in better performance or improved
compatibility.
Example:
# Use the ANSI ODBC API of the driver by using an 8-bit connection
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mxODBC - Python ODBC Database Interface
# string
db = mx.ODBC.Windows.DriverConnect('DSN=mydb;UID=uid;PWD=pwd')
6.7 Connection Object Methods
.close()
Close the connection now (rather than automatically at garbage collection
time). The connection will be unusable from this point on; an Error (or
subclass) exception will be raised if any operation is attempted with the
connection. The same applies to all cursor objects trying to use the
connection.
.commit()
Commit any pending changes and implicitly start a new transaction.
For connections which do not provide transaction support or operate in autocommit mode, this method does nothing.
.cursor(name=None, cursor_options=())
Constructs a new Cursor Object with the given name using the connection and
initializes any provided cursor options.
If no name is given, the ODBC driver or database backend will determine a
unique name on its own. You can query this name with
cursor.getcursorname() (see the Cursor Object section 7).
The cursor_options may be given as list of (option, value) tuples. These
are then passed to the cursor's cursor.setconnectoption() API (see the
Cursor Object section 7) and allow configuring the cursor upfront to a specific
need.
.getconnectoption(option)
Get information about the connection.
option must be an integer. Suitable option values are available through the
SQL object (see the Constants section 10.5 for details).
The method returns the data as 32-bit integer. It is up to the user to decode
the integer value using the SQL defines available through the SQL constant.
This API gives you a very wide range of information about the underlying
database and its capabilities. See the ODBC SQLGetConnectAttr API
Documentation for more information.
.getinfo(info_id)
Get general information about the database, the ODBC driver and the ODBC
driver manager.
The info_id must be an integer. Suitable values are available through the SQL
object (see the Constants section 10.5 for details).
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6. mxODBC Connection Objects
The method returns a tuple (integer, string) giving an integer decoding
(in native integer byte order) of the first bytes of the API's result as well as the
raw buffer data as string. It is up to the caller to decode the data (e.g. using the
struct module).
This API gives you a very wide range of information about the underlying
database and its capabilities. See the ODBC SQLGetInfo API Documentation for
more information.
.nativesql(command)
This method returns the command as it would have been modified by the driver
to pass to the database engine. It is a direct interface to the ODBC API
SQLNativeSql().
In many cases it simply returns the command string unchanged. Some drivers
unescape ODBC escape sequences in the command string. Syntax checking is
usually not applied by this method and errors are only raised in case of
command string truncation.
Not all mxODBC subpackages support this API.
.rollback()
In case the database connection has transactions enabled, this method causes
the database to roll back any changes to the start of the current transaction.
Closing a connection without committing the changes first will cause an
implicit rollback to be performed.
This method is only available if the ODBC driver database subpackage was
compiled with transaction support. For ODBC manager subpackages it is
always available, but may raise a NotSupportedError in case the connection
does not support transactions.
.setconnectoption(option, value)
This method lets you set some ODBC integer options to new values, e.g. to set
the transaction isolation level or to turn on auto-commit.
option must be an integer. Suitable option values are available through the
SQL object, e.g. SQL.ATTR_AUTOCOMMIT corresponds to the SQL option
SQL_ATTR_AUTOCOMMIT in C (see the Constants section 10.5 for details).
The method is a direct interface to the ODBC SQLSetConnectOption()
function. Please refer to the ODBC Documentation for more information.
Note that while the API function also supports setting character fields, the
method currently does not know how to handle these.
Note for ADABAS/SAP DB/MAX DB users:
Adabas, SAP DB and MAX DB can emulate several different SQL dialects. They
have introduced an option for this to be set. These are the values you can use:
1 = ADABAS, 2 = DB2, 3 = ANSI, 4 = ORACLE, 5 = SAPR3. The option code
is SQL.CONNECT_OPT_DRVR_START + 2 according to the Adabas
documentation. Please consult your driver documentation for details.
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.__enter__()
Returns the connection itself. This method makes connection objects usable as
context manager (together with the .__exit__() method) and is called when
entering a with-block (new in Python 2.5).
.__exit__(exc_type, exc_value, exc_tb)
Returns True in case exc_type is set to None (no exception set) and commits
the current transaction. Returns False in case exc_type is set to an exception
and rolls back the current transaction. This method is part of the context
manager API and is called when leaving a with-block (new in Python 2.5).
6.8 Connection Object Attributes
.autocommit
Writeable attribute to query and set the auto-commit status of the connection.
Returns True if the connection is operating in auto commit (non-transactional)
mode. Returns False is the connection is operating in manual commit
(transactional) mode.
Setting the attribute to True or False adjusts the connection's mode
accordingly.
This attribute is a shortcut to using
connection.setconnectoption(SQL.AUTO_COMMIT, value) and can raise
the same exceptions, e.g. in case of a closed connection.
.bindmethod
Attribute to query and set the input variable binding method used by the
connection. This can either be BIND_USING_PYTHONTYPE of
BIND_USING_SQLTYPE (see the Constants section 10.5 for details).
The attribute is inherited by cursors created on the connection at creation
time. Cursors may override the setting on a per cursor basis.
.closed
Read-only attribute that is true in case the connection is closed. Any action on
a closed connection will result in a ProgrammingError to be raised. This
variable can be used to conveniently test for this state.
.converter
Read/write attribute that sets the converter callback default for all newly
created cursors using the connection. It is None per default (meaning to use
the standard conversion mechanism). See the Supported Data Types section for
details.
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.cursortype
Read/write attribute that sets the default ODBC cursor type for cursors created
on this connection. Possible values are:
SQL.CURSOR_FORWARD_ONLY
The cursor only scrolls forward. This is the default setting for all
databases.12
SQL.CURSOR_STATIC
The result set is made static by creating a static copy of the result set after
opening the cursor. As a result, any changes to the result set after opening
the cursor will not be visible to the client. 12
SQL.CURSOR_KEYSET_DRIVEN
Keysets are sets of columns in the result set that provide unique keys to the
rows in the result set. Keyset driven cursors fix the memberships and order
of the rows in the result set using these keysets. Unlike static cursors, they
don't create a copy of the result set.
SQL.CURSOR_DYNAMIC
Dynamic cursors are the opposite of static cursors. All changes to the result
set after opening it are visible on the next fetch operation.
Please refer to section 5.8 ODBC Cursor Types for more details on cursor
types. Not all databases support all listed cursor types.
Performance Warning:
Please note that using cursor types other than SQL.CURSOR_FORWARD_ONLY
may have a significant effect on the performance of fetch operations.
.datetimeformat
Use this instance variable to set the default output format for
date/time/timestamp columns of all cursors created using this connection
object.
Possible values are (see the Constants section 10.5 for details):
DATETIME_DATETIMEFORMAT (default)
DateTime and DateTimeDelta instances.
PYDATETIME_DATETIMEFORMAT
datetime.date, datetime.time, datetime.datetime instances. Only
available using Python 2.4 and later.
TIMEVALUE_DATETIMEFORMAT
Ticks (number of seconds since the epoch) and tocks (number of
seconds since midnight).
12
Please note that in mxODBC 3.2, the default was database dependent.
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TUPLE_DATETIMEFORMAT
Python tuples as defined in the Supported Data Types section.
STRING_DATETIMEFORMAT
Python strings. The format used depends on the internal settings of the
database. See your database's manuals for the exact format and ways to
change it.
We strongly suggest always using the DateTime/DateTimeDelta instances.
Note that changing the values of this attribute will not change the date/time
format for existing cursors using this connection.
This value is inherited by all cursors created from the connection at creation
time. Note that changing the value of this attribute will not change the
date/time format for existing cursors using this connection.
.dbms_name
String identifying the database manager system.
.dbms_version
String identifying the database manager system version.
.decimalformat
Use this instance variable to set the default output format for decimal and
numeric columns of all cursors created using this connection object.
Possible values are (see the Constants section 10.5 for details):
FLOAT_DECIMALFORMAT (default)
Values are returned as Python floats.
DECIMAL_DECIMALFORMAT
Values are returned as Python decimal.Decimal instances. Only
available using Python 2.4 and later.
This value is inherited by all cursors created from the connection at creation
time. Note that changing the value of this attribute will not change the decimal
format for existing cursors using this connection.
.driver_name
String identifying the ODBC driver.
.driver_version
String identifying the ODBC driver version.
.encoding
Read/write attribute which defines the encoding to use for converting Unicode
to 8-bit strings and vice-versa. If set to None (default), Python's default
encoding will be used, otherwise it has to be a string providing a valid
encoding name, e.g. 'latin-1' or 'utf-8'.
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The connection.encoding is used on connection related APIs and also
passed to cursors created on the connection at creation time. Cursors store the
encoding in cursor.encoding and cursor related APIs will use the cursor
setting instead of the connection setting.
.errorhandler
Read/write attribute which defines the error handler function to use. If set to
None, the default handling is used, i.e. errors and warnings all raise an
exception and get appended to the .messages list.
An error handler must be a callable object taking the arguments
(connection, cursor, errorclass, errorvalue) where connection is
a reference to the connection, cursor a reference to the cursor (or None in
case the error does not apply to a cursor), errorclass is an error class which
to instantiate using errorvalue as construction argument.
See section 10.4 Error Handlers for more details on how to use error handlers.
.license
String with the license information of the installed mxODBC license.
.messages
This is a Python list object to which mxODBC appends tuples (exception
class, exception value) for all messages which the interfaces receives
from the underlying ODBC driver or manager for this connection.
The list is cleared automatically by all connection methods calls (prior to
executing the call) except for the info and connection option methods calls to
avoid excessive memory usage and can also be cleared by executing del
connection.messages[:].
All error and warning messages generated by the ODBC driver are placed into
this list, so checking the list allows you to verify correct operation of the
method calls.
.paramstyle
Sets the default parameter binding style for cursors created on this connection,
i.e. all cursors created on the connection will use connection.paramstyle as
their default cursor.paramstyle value.
The attribute can be set or queried and takes the following string values
(following the paramstyle module global as defined in the DB-API):
'qmark' (default)
This is the default ODBC parameter binding style and also used as native
database binding style by MS SQL Server and IBM DB2.
Parameters in SQL statements used on cursor.execute*() methods are
marked with the question mark letter ('?') and the variables are bound to
these parameter locations using a positional mapping. Parameter values for
a SQL statement must be specified as sequence, normally a list or a tuple.
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Example: 'SELECT * FROM MyTable WHERE A=? AND B=?' used with a
parameter tuple (1, 2) would result in the database executing the query
'SELECT * FROM MyTable WHERE A=1 AND B=2'.
'named'
The 'named' parameter binding style is used by the native database
interfaces of e.g. Oracle.
Parameters in SQL statements used on cursor.execute*() methods are
marked with a colon followed by a name, e.g. ':a' or ':1'. The variables
are bound to these parameter locations using a name based mapping.
Parameter values for a SQL statement must be specified as mapping,
normally a dictionary, and are bound to the locations based on the names
used in the SQL statement.
Example: 'SELECT * FROM MyTable WHERE A=:a AND B=:b' used with
a parameter dictionary {'a': 1, 'b': 2} would result in the database
executing the query 'SELECT * FROM MyTable WHERE A=1 AND B=2'.
.row
This attribute sets the default cursor.row object constructor to be used by all
newly created cursor objects on this connection.
The purpose of this attribute is to define a constructor for rows in result sets
fetched using the cursor.fetch*() methods.
Default is None, which means that mxODBC will use regular Python tuples for
returning row data in result sets.
Please see the cursor.row cursor attribute documentation in section 7.7 for
more details.
.rowfactory
This attribute sets the default cursor.rowfactory row object constructor
factory to be used by all newly created cursor objects on this connection.
The purpose of the row factory is to dynamically set the cursor.row attribute
after having executed a statement on the cursor.
Default is None, which means that mxODBC will not use a row factory
function and leave cursor.row untouched.
Please see the cursor.rowfactory cursor attribute documentation in section
7.7 for more details.
.stringformat
Use this attribute to set or query the default input and output handling for
string columns of all cursors created using this connection object. Data
conversion on input is dependent on the input binding type.
Possible values are (see the Constants section 10.5 for details):
EIGHTBIT_STRINGFORMAT (default)
This format tells mxODBC to convert all data passed to and read from
the ODBC driver to 8-bit strings.
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On input, Python 8-bit strings are passed to the ODBC driver as-is.
Unicode objects are converted to Python 8-bit strings assuming the
cursor's encoding setting (see the cursor.encoding attribute) prior to
passing them to the ODBC driver.
On output, all string columns are fetched as strings and passed back as
Python 8-bit string objects. Unicode data from the database is converted
to Python 8-bit string objects assuming the cursor's encoding setting
(see the cursor.encoding attribute).
This setting emulates the behavior of previous mxODBC versions and is
the default.
MIXED_STRINGFORMAT
This format lets the ODBC driver decide which string format to use for
the communication, providing the most efficient way of communicating
with the driver.
Input and output conversion is dependent on the data format the ODBC
driver expects or returns for a given column. If the driver returns a
string, a Python string is created; if it returns Unicode data, a Python
Unicode object is used.
UNICODE_STRINGFORMAT
This format can be used to emulate Unicode support with a database
backend that doesn't have a native Unicode data type or where the
ODBC driver cannot handle Unicode data.
On input, Python strings are passed to the ODBC driver as-is. Unicode
objects are converted to 8-bit strings using the cursor's encoding setting
(see the cursor.encoding attribute) and then passed to the ODBC
driver.
On output, string data is converted to Python Unicode objects, based on
the same conversion technique.
Use this setting if you plan to use Unicode objects with non-Unicode
aware databases (e.g. by setting the encoding to UTF-8 -- be careful
though: multibyte character encodings usually take up more space and
are not necessarily compatible with the database's string functions).
NATIVE_UNICODE_STRINGFORMAT
This format should be used for databases and applications that support
native Unicode data communication.
String columns are converted to Python Unicode objects assuming the
cursor's encoding setting (see the cursor.encoding attribute) and then
passed as Unicode to the ODBC driver.
On output, string data is always fetched as Unicode data from the
ODBC driver and returned using Python Unicode objects.
Note that even though mxODBC may report that Unicode support is enabled
(default in Python 2.0 and later; HAVE_UNICODE_SUPPORT is set to 1), the
ODBC driver may still reject Unicode data. In this case, an InternalError of
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type 'S1003' is raised whenever trying to read data from the database in this
.stringformat mode.
You can use the included mx/ODBC/Misc/test.pyc script to find out whether
the database backend support Unicode or not.
Binary and other plain data columns will still use 8-bit strings for interfacing,
since storing this data in Unicode objects would cause trouble. mxODBC will
eventually use buffer/memoryview or some form of binary objects to store
binary data in some future version, e.g. the new bytes type which was
introduced with Python 3.
This value is inherited by all cursors created from the connection at creation
time. Note that changing the value of this attribute will not change the string
format for existing cursors using this connection.
.timestampresolution
Use this attribute to adjust the rounding applied when passing second values
with fractions to the database, i.e. from Python to the database13. Some
databases complain about their data types not being capable of representing
the precision as given in the fraction value. With others, it is possible to get
rounding errors due to truncation, e.g. of 0.4999 to 0.49 instead of 0.50.
The attribute value must be given as integer and defines the resolution of the
timestamp values in nanoseconds (ns).
Setting the attribute to 1000 would result in Python seconds values to get
rounded to the nearest microsecond prior to passing the value to the database.
Setting it to 250*1000000 would result in seconds to get rounded to the
nearest ¼ second.
Note: Rounding to a full second is prevented to not cause possibly illegal time
values.
Default is 1 nanosecond (.timestampresolution = 1), with the following
exceptions to address limitations in the database engines, which otherwise
cause database errors or warnings:
•
MS SQL Server 2005 and earlier: 1 millisecond (.timetstampresolution
= 1000000)
•
MS SQL Server 2008 and later: 100 nanoseoncds
(.timestampresolution = 100)
This value is inherited by all cursors created from the connection at creation
time. Note that changing the value of this attribute will not change the
timestamp resolution for existing cursors using this connection.
.warningformat
Use this attribute to change the default warning reporting behavior of
mxODBC, in case you don't want to define your own .errorhandler.
13
mxODBC applies this rounding when using the ODBC timestamp interface structures and
also applies the rounding to mxDateTime input objects in case the database requests the
date/time value as string. It currently does not apply the rounding for strings in case Python
datetime objects are used on input.
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The DB-API 2.0 mandates that database warnings must raised as
mx.ODBC.Warning exception, but mostly because at the time of writing, the
Python warning module did not yet exist.
For some applications it may be more useful to report warnings via Python
warnings. The application could then use the standard Python warning filters
to report or filter the warnings in an appropriate way.
Another alternative is to simply ignore such warnings. Some ODBC are rather
verbose when it comes to warnings.
Note that a possibly registered .errorhandler will still be called in all these
cases, however, the mxODBC default error handler will use the
.warningformat to determine how to react to database warnings.
Possible values are (see the Constants section 10.5 for details):
ERROR_WARNINGFORMAT (default)
Report warnings in the usual DB-API 2.0 way and raise a Warning
exception.
WARN_WARNINGFORMAT
Instead of raising a Warning exception, issue a
mx.ODBC.DatabaseWarning which is a Python Warning subclass and
can be filtered using the standard Python warnings module mechanisms.
IGNORE_WARNINGFORMAT
Silently ignore the database warning.
The warning will still be added to the .message attribute, but no further
action is taken.
This value is inherited by all cursors created from the connection at creation
time. Note that changing the value of this attribute will not change the warning
format for existing cursors using this connection.
6.8.1 Additional Attributes
In addition to the above attributes, all exception objects used by the connection's
subpackage are also exposed on the connection objects as attributes, e.g.
connection.Error gives the Error exception of the subpackage which was used
to create the connection object.
See the Exceptions and Error Handling section 10 for details and names of these
error attributes.
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7.
mxODBC Cursor Objects
These objects represent a database cursor: an object which is used to manage the
context of a database query operation.
This includes preparing and parsing the query or command to be executed on the
connection, executing the query or command one or multiple times and providing
a pointer into the result set or sets generated by queries.
7.1 Relationship between Cursors and
Connections
7.1.1 Dependency on the Connection Object
Cursors are created through a database connection. As a result, cursor objects are
only usable as long as the connection object exists and the associated database
connection is open and working.
All operations of a cursor are done through the connection that was used to create
it. The scope and default settings of a cursor are defined by the connection. Once
created, you can change various settings of the cursor, e.g. the
cursor.datetimeformat. Such changes do not affect the connection or any
other cursor objects created on the connection.
Using cursors on a closed connection will result in a ProgrammingError to be
raised.
7.1.2 Using multiple Cursor Objects on a single Connection
Depending on the capabilities of the database and the used ODBC driver, you can
have multiple cursors open on a single connection and execute queries and
commands on each at will. This makes it possible to e.g. prepare and then cache
often used commands.
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7.2 Subpackage Support
Cursor objects are supported by all subpackages included in mxODBC.
The extent to which the functionality and number of methods is supported may
differ from subpackage to subpackage, so you have to verify the functionality of
the used methods (esp. the catalog methods) for each subpackage and database
that you intend to use.
7.3 Cursor objects as context managers
Please see section 6.5.1. Introduction to Context Managers for an introduction to
context managers and the Python with-statement.
7.3.1 Using cursor objects as context objects
Cursor objects implement this API and use it to automatically close the cursor and
freeing resources in the ODBC driver when leaving a with-block. Instead of
writing:
cursor = connection.cursor()
try:
cursor.execute('INSERT INTO table VALUES (?, ?)', (1, 2))
… other tasks …
finally:
cursor.close()
you can write:
with connection.cursor() as cursor:
cursor.execute('INSERT INTO table VALUES (?, ?)', (1, 2))
… other tasks …
This not only looks a lot better and also takes care of freeing the resources in case
of an error in the block.
7.4 Cursor Type Object
mxODBC uses a dedicated object type for cursors.
Each subpackage defines its own object type, but all share the same name:
CursorType.
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7.5 Cursor Object Constructors
Cursor objects are created using the connection method connection.cursor().
connection.cursor(name=None, cursor_options=())
Constructs a new Cursor Object with the given name using the connection and
initializes any provided cursor options. If no name is given, the ODBC driver or
database backend will create one dynamically.
Please see section 6.7 Connection Object Methods for details.
7.6 Cursor Object Methods
The following cursor methods are defined in the DB API:
.callproc(procname, parameters=(), parametertypes=None)
Call a stored database procedure with the given name.
The sequence of parameters must contain one entry for each argument that
the procedure expects.
The result of the call is returned as modified list copy of the input sequence.
Input parameters are left untouched, output and input/output parameters
replaced with possibly new values in the list copy.
If parametertypes is given, it defines the parameter types of the parameters
used in the sqlcmd. The sequence has to provide one integer entry per
parameter. Possible values are SQL.PARAM_INPUT (input parameter), SQL.
PARAM_OUTPUT (output parameter) and SQL.PARAM_INPUT_OUTPUT
(input/output parameter). If parametertypes is not given, default is to assume
input parameter types for all parameters.
The procedure may also provide one or more result sets as output. This can
then be fetched through the standard cursor.fetch*() methods.
Please see section 5.6 Stored Procedures for more details on how to call stored
procedures.
.close()
Close the cursor now (rather than automatically at garbage collection time).
The cursor will be unusable from this point forward; an Error (or subclass)
exception will be raised if any operation is attempted with the cursor.
.execute(sqlcmd, parameters=(), direct=-1, parametertypes=None)
Prepare and execute a database operation sqlcmd (query or command).
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Depending on the current .paramstyle setting, parameters must be
provided as sequence14 or mapping:
'qmark'(default)
With the 'qmark' parameter style (default) a sequence is expected and
parameters be bound to variables found in the sqlcmd string on a
positional basis. Variables in the sqlcmd string are specified using the
ODBC variable question mark placeholder '?', e.g. 'SELECT name,id
FROM table WHERE amount > ? AND amount < ?', and get bound in
the order they appear in the SQL statement sqlcmd from left to right.
'named'
With 'named' parameter style a mapping is expected and parameters be
bound to variables found in the sqlcmd string based on the values of the
referenced named entries in the mapping. Variables in the sqlcmd string
are specified using the Oracle style variable marks placeholder ':name',
e.g. 'SELECT name,id FROM table WHERE amount > :minamount AND
amount < :maxamount', and get bound to the values defined in the
parameters mapping. It is possible to use multiple references to the same
named parameter in sqlcmd.
A reference to the sqlcmd string will be retained by the cursor and made
available to Python as cursor.command. If the same sqlcmd object is passed
in again, the cursor will optimize its behavior by reusing the previously
prepared statement. This is most effective for algorithms where the same
sqlcmd is used, but different parameters are bound to it, e.g. in loops iterating
over input data items.
Use .executemany()if you want to apply the sqlcmd to a sequence or
iterator/generator of parameters in one call, e.g. to insert multiple rows in a
single call.
sqlcmd may be a Unicode object in case the ODBC driver and/or database
support this.
direct specifies whether to use direct, unprepared execution or not (see
.executedirect() for details). It defaults to -1, meaning that direct execution
is used if no parameters are given, non-direct otherwise.
If parametertypes is given, it defines the parameter types of the parameters
used in the sqlcmd. The sequence has to provide one integer entry per
parameter. Possible values are SQL.PARAM_INPUT (input parameter), SQL.
PARAM_OUTPUT (output parameter) and SQL.PARAM_INPUT_OUTPUT
(input/output parameter). If parametertypes is not given, default is to assume
input parameter types for all parameters. Please see section 5.6 Stored
Procedures for more details on how to use this parameter.
14
Note that in mxODBC 3.0 and earlier, the .execute() methods used to work like
.executemany() when passing a list of tuples as parameter (a feature inherited from
Python DB-API 1.0). Starting with mxODBC 3.1 this behavior was removed to avoid
confusion.
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If parametertypes are given, the method returns a tuple copy of the
parameters sequence, with output and input/output parameter values replaced
by the updated values from the database.
Without parametertypes, the method returns None.
.executedirect(sqlcmd, parameters=(), parametertypes=None)
This method works just like .execute(), except that no prepare step is issued
and the sqlcmd is not cached. This can result in better performance with some
ODBC driver setups, but also implies that Python type binding mode is used to
bind the parameters. All SQL command parsing is then pushed from the client
side to the server side.
sqlcmd may be a Unicode object in case the ODBC driver and/or database
support this.
Return values are the same as for cursor.execute().
.executemany(sqlcmd, batch=(), direct=0, parametertypes=None)
Prepare a database operation (query or command) and then execute it against
all parameter sequences found in the sequence, iterator or generator batch.
The same comments as for .execute() also apply accordingly to this method.
If the optional integer direct is given and true, mxODBC will not cache the
sqlcmd, but submit it for one-time execution to the database. This can result in
better performance with some ODBC driver setups, but also implies that
Python type binding mode is used to bind the parameters.
sqlcmd may be a Unicode object in case the ODBC driver and/or database
support this.
If parametertypes are given, the method returns a list of tuple copies of the
batch parameter sequence, with output and input/output parameter values
replaced by the updated values from the database.15
Without parametertypes, the method returns None.
.fetchall()
Fetch all (remaining) rows of a query result, returning them as a sequence of
sequences (e.g. a list of tuples).
An Error (or subclass) exception is raised if the previous call to .execute*()
did not produce any result set or no call was issued yet.
.fetchmany([size=cursor.arraysize])
Fetch the next set of rows of a query result, returning a sequence of sequences
(e.g. a list of tuples). An empty sequence is returned when no more rows are
available.
15
While this can be used to issue multiple stored procedure calls and retrieve data from the
database via output parameters, not all databases support multiple batched calls. The
database will then raise a function sequence error or similar as a result. PostgreSQL is one
such database.
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The number of rows to fetch per call is specified by the parameter. If it is not
given, the cursor's .arraysize determines the number of rows to be fetched.
The method will try to fetch as many rows as indicated by the size parameter.
If this is not possible due to the specified number of rows not being available,
fewer rows may be returned.
An Error (or subclass) exception is raised if the previous call to .execute*()
did not produce any result set or no call was issued yet.
.fetchone()
Fetch the next row of a query result set, returning a single sequence, or None
when no more data is available.
An Error (or subclass) exception is raised if the previous call to .execute*()
did not produce any result set or no call was issued yet.
mxODBC will move the associated database cursor forward by one row only.
.flush()
Frees any pending result set used by the cursor. If you only fetch some of the
rows of large result sets you can optimize memory usage by calling this
method.
Note that .execute*() and all the catalog methods do an implicit .flush()
prior to executing a new query.
.getcolattribute(position, info_id)
Get information about the result set column position. The column index
must be given as 0-based integer, i.e. the first result setup column has the
index 0.
info_id must be an integer and identifies the requested field information.
Suitable values are available through the SQL object (see the Constants section
10.5 for details).
The method returns a tuple (integer, string) giving an integer decoding
(in native integer byte order) of the first bytes of the API's result as well as the
raw buffer data as string. It is up to the caller to decode the data (e.g. using the
struct module).
This API gives you a wide range of information about the result set column. See
the ODBC SQLColAttribute API Documentation for more information.
Some of these values are also available through the cursor.description
attribute.
This is a list of useful info ids:
Option
Comment
SQL.DESC_AUTO_UNIQUE_VALUE Check whether the result set column refers to an
auto-increment column of the table.
The check only returns valid values for numeric
columns that can be defined as auto-increment
column in the database.
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Option
Comment
Returns an integer value:
SQL.TRUE - column is auto-increment
SQL.FALSE - column is not an auto-increment
column or not numeric
SQL.DESC_BASE_COLUMN_NAME
Base column name of the result set column. If the
base column name cannot be determined, e.g. for
expressions, an empty string is returned.
Returns a string..
SQL.DESC_BASE_TABLE_NAME
Base table name of the result set column. If the base
table name cannot be determined, e.g. for
expressions, an empty string is returned.
Returns a string..
SQL.DESC_DISPLAY_SIZE
Returns the maximum number of characters
needed to display the column data.
Returns an integer.
SQL.DESC_LENGTH
Returns the maximum length of the column data in
characters.
Returns an integer.
SQL.DESC_OCTET_LENGTH
Returns the maximum length of the column data in
bytes.
Returns an integer.
SQL.DESC_PRECISION
Returns the precision of a numeric column.
For date/time columns, this returns the precision of
the seconds fraction, if applicable.
Returns an integer.
SQL.DESC_SCALE
Returns the scale of a numeric column.
Returns an integer.
SQL.DESC_TABLE_NAME
Table name of the table containing the result set
column. If the table name cannot be determined,
e.g. for expressions, an empty string is returned.
Returns a string..
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Option
Comment
SQL.DESC_TYPE_NAME
Data source dependent type name of the result set
column or an empty string if the value cannot be
determined.
Returns a string..
SQL.DESC_UNSIGNED
Checks whether the result set column is unsigned
numeric data or not.
Returns an integer value:
SQL.TRUE - column data is unsigned or not
numeric
SQL.FALSE - column data is signed
If the ODBC driver doesn't support an info_id or cannot determine the
requested value, it either raises an exception, or returns an empty string where
applicable.
.getcursorname()
Returns the current cursor name associated with the cursor object. This may
either be the name given to the cursor at creation time or a name generated by
the ODBC driver for it to use.
.getcursoroption(option)
Returns the given cursor option. This method interfaces directly to the ODBC
function SQLGetCursorOption().
option must be an integer. Suitable option values are available through the
SQL object.
Possible values are:
Option
Comment
SQL.ATTR_QUERY_TIMEOUT
Returns the query timeout in seconds used for the
cursor.
Note that not all ODBC drivers support this option.
SQL.ATTR_ASYNC_ENABLE
Check whether asynchronous execution of commands is
enabled.
Possible values:
SQL.ASYNC_ENABLE_OFF (default)
SQL.ASYNC_ENABLE_ON
SQL.ASYNC_ENABLE_DEFAULT
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Option
Comment
SQL.ATTR_MAX_LENGTH
Returns the length limit for fetching column data.
Possible values:
Any positive integer or
SQL.MAX_LENGTH_DEFAULT (no limit)
SQL.ATTR_MAX_ROWS
Returns the maximum number of rows a .fetchall()
command would return from the result set.
Possible values:
Any positive integer or
SQL.MAX_ROWS_DEFAULT (no limit)
SQL.ATTR_NOSCAN
Check whether the ODBC driver will scan the SQL
commands for ODBC escape sequences or not.
Possible values:
SQL.NOSCAN_OFF (default)
SQL.NOSCAN_ON
SQL.NOSCAN_DEFAULT
SQL.ROW_NUMBER
Returns the row number of the current row in the result
set or 0 if it cannot be determined.
The method returns the data as 32-bit integer. It is up to the caller to decode
the integer using the SQL defines.
.next()
Works like .fetchone() to make cursors compatible to the iterator interface
(new in Python 2.2). Raises a StopIteration at the end of a result set.
.nextset()
This method will make the cursor skip to the next available set, discarding any
remaining rows from the current set.
If there are no more sets, the method returns None. Otherwise, it returns a
true value and subsequent calls to the fetch methods will return rows from the
next result set.
An Error (or subclass) exception is raised if the previous call to .execute*()
did not produce any result set or no call was issued yet.
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7. mxODBC Cursor Objects
.prepare(sqlcmd)
Prepare a database operation (query or command) statement for later
execution and set cursor.command. To later execute a prepared statement,
pass cursor.command to one of the .execute*() methods.
cursor.prepare(sqlcmd) can also be used to check sqlcmd for syntax
errors, or to inspect the result set structure of a query without executing the
sqlcmd operation, by looking at cursor.description after calling
cursor.prepare().
sqlcmd may be a Unicode object in case the ODBC driver and/or database
support this.
Return values are not defined.
This method is may not be available in all mxODBC subpackages. Even if it is
available, the used ODBC driver or database may not support preparing
database operations for later reuse.
.scroll(value, mode='relative')
Scroll the cursor in the result set according to mode.
If mode is 'relative' (default), value is taken as offset to the current position
in the result set, if set to 'absolute', value gives the absolute position.
An IndexError is raised in case the scroll operation leaves the result set. In
this case, the cursor position is not changed.
This method will use native scrollable cursors, if the data source provides
these, or revert to an emulation for forward-only scrollable cursors. Please
check whether the data source supports this method using the included
mx/ODBC/Misc/test.pyc script.
Warning:
Some ODBC drivers have trouble scrolling in result sets which use BLOBs or
other data types for which the data size cannot be determined at prepare time.
mxODBC currently raises a NotSupportedError in case a request for
backward scrolling is made in such a result set. Hopefully, this will change as
ODBC drivers become more mature.
.setconverter(converter)
This method sets the converter function to use for subsequent fetches. Passing
None as converter will reset the converter mechanism to its default setting. See
the Supported Data Types section 8 for details on how user-defined converters
work.
The current converter function used on the cursor can be queried through the
read-only cursor.converter attribute.
.setcursorname(name)
Sets the name to be associated with the cursor object.
There is a length limit for names in SQL at 18 characters. An InternalError
will be raised if the name is too long or otherwise not useable.
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.setcursoroption(option, value)
Sets a cursor option to a new value.
Only a subset of the possible option values defined by ODBC are available
since this method could otherwise easily cause mxODBC to segfault – it makes
changes possible which effect the way mxODBC interfaces to the ODBC
driver.
Only options with numeric values are currently supported.
Option
Comment
SQL.ATTR_QUERY_TIMEOUT
Sets the query timeout in seconds used for the cursor.
Queries that take longer raise an exception after the
timeout is reached.
Possible values:
Any positive integer or
SQL.QUERY_TIMEOUT_DEFAULT
Note that not all ODBC drivers support this option.
SQL.ATTR_ASYNC_ENABLE
Enable asynchronous execution of commands.
Possible values:
SQL.ASYNC_ENABLE_OFF (default)
SQL.ASYNC_ENABLE_ON
SQL.ASYNC_ENABLE_DEFAULT
SQL.ATTR_MAX_LENGTH
Maximum length of any fetched column. Default is no
limit.
Possible values:
Any positive integer or
SQL.MAX_LENGTH_DEFAULT (no limit)
SQL.ATTR_MAX_ROWS
Limit the maximum number of rows to fetch in a result
set. Default is no limit.
Possible values:
Any positive integer or
SQL.MAX_ROWS_DEFAULT (no limit)
SQL.ATTR_METADATA_ID
112
Tell the ODBC driver to interpret the catalog method
parameters as case-insensitive identifiers. Default is to
7. mxODBC Cursor Objects
Option
Comment
interpret them as case-sensitive SQL search patterns.
Possible values:
SQL.TRUE - case-insensitive identifers
SQL.FALSE - case-sensitive search patterns (default)
SQL.ATTR_NOSCAN
Tell the ODBC driver not to scan the SQL commands
and unescape (expand) any ODBC escape sequences it
finds. Default is to scan for them.
Possible values:
SQL.NOSCAN_OFF (default)
SQL.NOSCAN_ON
SQL.NOSCAN_DEFAULT
.setinputsizes(sizes)
This methods does nothing in mxODBC, it is just needed for DB API
compliance.
.setoutputsize(size[, column])
This methods does nothing in mxODBC, it is just needed for DB API
compliance.
.__iter__()
Returns the cursor itself. This method makes cursor objects usable as iterators
(new in Python 2.2).
.__enter__()
Returns the cursor itself. This method makes cursor objects usable as context
manager (together with the .__exit__() method) and is called when entering a
with-block (new in Python 2.5).
.__exit__(exc_type, exc_value, exc_tb)
Returns True in case exc_type is set to None (no exception set) and closes the
cursor. Returns False in case exc_type is set to an exception and also closes
the cursor. This method is part of the context manager API and is called when
leaving a with-block (new in Python 2.5).
7.6.1 Catalog Methods
Catalog methods allow you to access meta-level and structural information about
a data source in a portable way.
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Some ODBC drivers do not support all of these methods or return unusable
data. As a result, you should verify correct operation for your target data sources
prior to relying on these methods.
Common Interface
All of the following catalog methods use the same interface: they do an implicit
call to cursor.execute() and return their output in form of a list of rows which
that can be fetched with the cursor.fetch*() methods in the usual way. The
number of available rows is available via cursor.rowcount16. All catalog methods
support keywords and use the indicated default values for parameters which are
omitted in the call.
Please refer to the ODBC Documentation for more detailed information about
parameters (if you pass None as a value where a string would be expected, that
entry is converted to NULL before passing it to the underlying ODBC API).
Result Set Layouts
Note that the result set layouts described here may not apply to your data source.
Some databases do not provide all the information given here and thus generate
slightly different result sets. Expect column additions and even omissions and do
not rely on the column names used in the result set descriptions.
Search Pattern Parameters
The standard catalog method parameters qualifier, owner and table accept
SQL search patterns as input, e.g. table='SYS%' would return all tables whose
name starts with SYS.
In some cases, the catalog functions provide additional search parameters such as
procedure or column. These parameters then also accept SQL search pattern
strings.
Case-sensitivity of Search Patterns
The search patterns given as parameters to these catalog methods are usually
interpreted in a case-sensitive way. This means that even if the database itself
behaves case-insensitive for identifiers, you may still not find what you're looking
for if you don't use the case which the database internally uses to store the
identifier.
As an example take the SAP DB: it stores all unquoted identifiers using uppercase
letters. Trying to fetch e.g. information about a table using a lowercase version of
the name will result in an empty result set. You can use
connection.getinfo(SQL.IDENTIFIER_CASE) to determine how the database
stores identifiers. See the ODBC Documentation for details.
16
Note that this was changed in mxODBC 3.0. Previously the catalog methods used to
return the number of rows in the result set.
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7. mxODBC Cursor Objects
Switching between Search Patterns and Identifier Matching
Some ODBC drivers support adjusting the catalog method interface to interpret
the parameters as case-insensitive identifiers instead.
In mxODBC, this can be enabled using:
cursor.setcursoroption(SQL.ATTR_METADATA_ID, SQL.TRUE)
The setting persists on the cursor. It can be switched off again using:
cursor.setcursoroption(SQL.ATTR_METADATA_ID, SQL.FALSE)
which then causes the catalog methods to interpret the parameters as casesensitive search patterns again.
Whether this really helps with the problem described above depends on the
application.
Unicode
All catalog methods accept Unicode parameters, if the ODBC drivers provide the
necessary support for this.
Available Catalog Methods
Please note that the drivers may not implement all catalog methods that
mxODBC supports. In such a case, you will get a NotSupportedError or
AttributeError exception when trying to use a method that is not supported
by the ODBC driver.
The following catalog methods are supported by mxODBC:
.columns(qualifier=None, owner=None, table=None, column=None)
Query the database schema for information on table columns.
column allows restricting the results to a single column of a table.
Depending on the used query options, the result set will contain information
for only one table, the whole database or just a single column.
The catalog method generates a result set having the following schema:
115
Column Name
Column Datatype
Comment
TABLE_CAT
VARCHAR(128)
Always NULL.
TABLE_SCHEMA
VARCHAR(128)
The name of the schema containing
TABLE_NAME.
TABLE_NAME
VARCHAR(128) not
NULL
The name of the table, or view, or alias, or
synonym.
mxODBC - Python ODBC Database Interface
Column Name
Column Datatype
Comment
COLUMN_NAME
VARCHAR(128) not
NULL
Name of the column of the specified table,
view, alias, or synonym.
DATA_TYPE
SMALLINT not NULL
SQL data type of column identified by
COLUMN_NAME.
TYPE_NAME
VARCHAR(128) not
NULL
Character string representing the name of
the data type corresponding to DATA_TYPE.
COLUMN_SIZE
INTEGER
If the DATA_TYPE column value denotes a
character or binary string, then this column
contains the maximum length in characters
for the column.
For date, time, timestamp data types, this is
the total number of characters required to
display the value when converted to
character.
For numeric data types, this is either the
total number of digits, or the total number of
bits allowed in the column, depending on
the value in the NUM_PREC_RADIX column
in the result set.
BUFFER_LENGTH
INTEGER
The maximum number of bytes for the
associated C buffer to store data from this
column if SQL_C_DEFAULT were specified
on the SQLBindCol(),
SQLGetData() and
SQLBindParameter() calls. This
length does not include any null-terminator.
For exact numeric data types, the length
accounts for the decimal and the sign.
DECIMAL_DIGITS
SMALLINT
The scale of the column. NULL is returned
for data types where scale is not applicable.
NUM_PREC_RADIX
SMALLINT
Either 10 or 2 or NULL. If DATA_TYPE is an
approximate numeric data type, this column
contains the value 2, then the
COLUMN_SIZE column contains the
number of bits allowed in the column.
If DATA_TYPE is an exact numeric data type,
this column contains the value 10 and the
COLUMN_SIZE contains the number of
decimal digits allowed for the column.
For numeric data types, the database can
return a NUM_PREC_RADIX of either 10 or
2.
NULLABLE
116
SMALLINT not NULL
SQL.NO_NULLS if the column does not
7. mxODBC Cursor Objects
Column Name
Column Datatype
Comment
accept NULL values.
REMARKS
VARCHAR(254)
May contain descriptive information about
the column or NULL.
It is possible that no usable information is
returned in this column (due to
optimizations).
COLUMN_DEF
VARCHAR(254)
The column's default value. If the default
value is a numeric literal, then this column
contains the character representation of the
numeric literal with no enclosing single
quotes. If the default value is a character
string, then this column is that string
enclosed in single quotes. If the default value
a pseudo-literal, such as for DATE, TIME,
and TIMESTAMP columns, then this column
contains the keyword of the pseudo-literal
(e.g. CURRENT DATE) with no enclosing
quotes.
If NULL was specified as the default value,
then this column returns "NULL". If the
default value cannot be represented without
truncation, then this column contains
"TRUNCATED" with no enclosing single
quotes. If no default value was specified,
then this column is NULL.
It is possible that no usable information is
returned in this column (due to
optimizations).
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SQL_DATA_TYPE
SMALLINT not NULL
SQL data type. This column is the same as
the DATA_TYPE column.
SQL_DATETIME_SUB
SMALLINT
The subtype code for datetime data types:
SQL.CODE_DATE, SQL.CODE_TIME,
SQL.CODE_TIMESTAMP. For all other data
types this column returns NULL.
CHAR_OCTET_LENGTH INTEGER
Contains the maximum length in octets for a
character data type column. For Single Byte
character sets, this is the same as
COLUMN_SIZE. For all other data types it is
NULL.
ORDINAL_POSITION
INTEGER not NULL
The ordinal position of the column in the
table. The first column in the table is number
1.
IS_NULLABLE
VARCHAR(254)
Contains the string "NO" if the column is
known to be not nullable; and "YES"
mxODBC - Python ODBC Database Interface
Column Name
Column Datatype
Comment
otherwise.
.columnprivileges(qualifier=None, owner=None, table=None,
column=None)
Query the database schema for information on column privileges for the given
table. This is useful to determine the authorizations granted to a table or
column.
column allows restricting the results to a single column of a table.
Note that the table parameter is mandatory.
The catalog method generates a result set having the following schema:
118
Column Name
Column Datatype
Comment
TABLE_CAT
VARCHAR(128)
Always NULL.
TABLE_SCHEMA
VARCHAR(128)
The name of the schema containing TABLE_NAME.
TABLE_NAME
VARCHAR(128) not
NULL
The name of the table, or view, or alias, or
synonym.
COLUMN_NAME VARCHAR(128) not
NULL
Name of the column of the specified table, view,
alias, or synonym.
GRANTOR
VARCHAR(128)
Authorization ID of the user who granted the
privilege.
GRANTEE
VARCHAR(128)
Authorization ID of the user to whom the privilege
is granted.
PRIVILEGE
VARCHAR(128)
The table privilege. This may be one of the
following strings: "INSERT", "REFERENCES",
"SELECT", "UPDATE".
IS_GRANTABLE
VARCHAR(3)
Indicates whether the grantee is permitted to grant
the privilege to other users. This can be "YES", "NO"
or NULL.
7. mxODBC Cursor Objects
.foreignkeys(primary_qualifier=None, primary_owner=None,
pimary_table=None, foreign_qualifier=None, foreign_owner=None,
foreign_table=None)
Query the database schema for information on foreign keys. The method has
two modes of operation, depending on which parameter is set:
primary_table
The method returns a list of foreign key columns in other tables that refer
to the primary key column of the given table and the primary key column of
the given table itself.
foreign_table
The method returns a list of foreign key columns in a table that refer to the
primary keys of other tables and the primary key columns of those other
tables.
This is useful to determine the relationships between the tables in a database
schema.
The catalog method generates a result set having the following schema:
119
Column Name
Column Datatype
Comment
PKTABLE_CAT
VARCHAR(128)
Always NULL.
PKTABLE_SCHEMA
VARCHAR(128)
The name of the schema containing
PKTABLE_NAME.
PKTABLE_NAME
VARCHAR(128) not
NULL
Name of the table containing the primary key.
PKCOLUMN_NAME
VARCHAR(128) not
NULL
Primary key column name.
FKTABLE_CAT
VARCHAR(128)
Always NULL.
FKTABLE_SCHEMA
VARCHAR(128)
The name of the schema containing
FKTABLE_NAME.
FKTABLE_NAME
VARCHAR(128) not
NULL
Name of the table containing the foreign key.
FKCOLUMN_NAME
VARCHAR(128) not
NULL
Foreign key column name.
ORDINAL_POSITION SMALLINT not NULL
The ordinal position of the column in the key,
starting at 1.
UPDATE_RULE
Action to be applied to the foreign key when
SMALLINT
mxODBC - Python ODBC Database Interface
Column Name
Column Datatype
Comment
the SQL operation is UPDATE: SQL.RESTRICT,
SQL.NO_ACTION, SQL.CASCADE,
SQL.SET_NULL.
DELETE_RULE
SMALLINT
Action to be applied to the foreign key when
the SQL operation is DELETE: SQL.CASCADE,
SQL.NO_ACTION, SQL.RESTRICT,
SQL.SET_DEFAULT, SQL.SET_NULL
FK_NAME
VARCHAR(128)
Foreign key identifier. NULL if not applicable to
the data source.
PK_NAME
VARCHAR(128)
Primary key identifier. NULL if not applicable to
the data source.
DEFERRABILITY
SMALLINT
Possible values: SQL.INITIALLY_DEFERRED,
SQL.INITIALLY_IMMEDIATE,
SQL.NOT_DEFERRABLE.
.gettypeinfo(sqltype)
Query the data source for information on a supported data type sqltype.
sqltype must be one of the SQL type codes as returned in
cursor.description[1]. See section 8. Data Types supported by mxODBC
for a list of SQL type codes and details about their use.
This method is useful to determine characteristics of the given SQL data type
and how it is defined in the SQL dialect supported by the data source.
The catalog method generates a result set having the following schema:
Column Name
Column Datatype
Comment
TYPE_NAME
VARCHAR(128) not
NULL
Character representation of the SQL data
type name, e.g. "VARCHAR", "DATE",
"INTEGER".
DATA_TYPE
SMALLINT not NULL
SQL data type of column identified by
COLUMN_NAME.
COLUMN_SIZE
INTEGER
If the DATA_TYPE column value denotes a
character or binary string, then this column
contains the maximum length in characters
for the column.
For date, time, timestamp data types, this is
the total number of characters required to
display the value when converted to
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7. mxODBC Cursor Objects
Column Name
Column Datatype
Comment
character.
For numeric data types, this is either the
total number of digits, or the total number
of bits allowed in the column, depending on
the value in the NUM_PREC_RADIX column
in the result set.
LITERAL_PREFIX
VARCHAR(128)
Prefix for a literal of this data type. This
column is NULL for data types where a
literal prefix is not applicable.
LITERAL_SUFFIX
VARCHAR(128)
Suffix for a literal of this data type. This
column is NULL for data types where a
literal prefix is not applicable.
CREATE_PARAMS
VARCHAR(128)
The text of this column contains a list of
keywords, separated by commas,
corresponding to each parameter the
application may specify in parenthesis when
using the name in the TYPE_NAME column
as a data type in SQL.
The keywords in the list can be any of the
following: "LENGTH", "PRECISION",
"SCALE". They appear in the order that the
SQL syntax requires that they be used.
NULL is returned if there are no parameters
for the data type definition, (such as
INTEGER).
Note: The intent of CREATE_PARAMS is to
enable an application to customize the
interface for a DDL builder.
NULLABLE
SMALLINT not NULL
Indicates whether the data type accepts a
NULL value
SQL.NO_NULLS - NULL values are
disallowed.
SQL.NULLABLE - NULL values are allowed.
CASE_SENSITIVE
SMALLINT not NULL
Indicates whether the data type can be
treated as case sensitive for collation
purposes; valid values are SQL.TRUE and
SQL.FALSE.
SEARCHABLE
SMALLINT not NULL
Indicates how the data type is used in a
WHERE clause. Valid values are:
SQL.UNSEARCHABLE: if the data type
cannot be used in a WHERE clause.
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Column Name
Column Datatype
Comment
SQL.LIKE_ONLY: if the data type can be
used in a WHERE clause only with the LIKE
predicate.
SQL.ALL_EXCEPT_LIKE: if the data type can
be used in a WHERE clause with all
comparison operators except LIKE.
SQL.SEARCHABLE: if the data type can be
used in a WHERE clause with any
comparison operator.
UNSIGNED_ATTRIBUTE SMALLINT
Indicates where the data type is unsigned.
The valid values are: SQL.TRUE, SQL.FALSE
or NULL. A NULL indicator is returned if
this attribute is not applicable to the data
type.
FIXED_PREC_SCALE
SMALLINT not NULL
Contains the value SQL.TRUE if the data
type is exact numeric and always has the
same precision and scale; otherwise, it
contains SQL.FALSE.
AUTO_INCREMENT
SMALLINT
Contains SQL.TRUE if a column of this data
type is automatically set to a unique value
when a row is inserted; otherwise, contains
SQL.FALSE.
LOCAL_TYPE_NAME
VARCHAR(128)
This column contains any localized (native
language) name for the data type that is
different from the regular name of the data
type. If there is no localized name, this
column is NULL.
This column is intended for display only.
The character set of the string is localedependent and is typically the default
character set of the database.
122
MINIMUM_SCALE
INTEGER
The minimum scale of the SQL data type. If
a data type has a fixed scale, the
MINIMUM_SCALE and MAXIMUM_SCALE
columns both contain the same value.
NULL is returned where scale is not
applicable.
MAXIMUM_SCALE
INTEGER
The maximum scale of the SQL data type.
NULL is returned where scale is not
applicable. If the maximum scale is not
defined separately in the database, but is
defined instead to be the same as the
maximum length of the column, then this
column contains the same value as the
COLUMN_SIZE column.
7. mxODBC Cursor Objects
Column Name
Column Datatype
Comment
SQL_DATA_TYPE
SMALLINT not NULL
SQL data type. This column is the same as
the DATA_TYPE column.
SQL_DATETIME_SUB
SMALLINT
The subtype code for datetime data types:
SQL.CODE_DATE, SQL.CODE_TIME,
SQL.CODE_TIMESTAMP. For all other data
types this column returns NULL.
NUM_PREC_RADIX
SMALLINT
Either 10 or 2 or NULL. If DATA_TYPE is an
approximate numeric data type, this
column contains the value 2, then the
COLUMN_SIZE column contains the
number of bits allowed in the column.
If DATA_TYPE is an exact numeric data
type, this column contains the value 10 and
the COLUMN_SIZE contains the number of
decimal digits allowed for the column.
For numeric data types, the database can
return a NUM_PREC_RADIX of either 10 or
2.
INTERVAL_PRECISION
SMALLINT
Datetime interval precision or NULL is
interval types are not supported by the
database.
.primarykeys(qualifier=None, owner=None, table=None)
Query the data source for information on the primary keys of a given table.
The table parameter is mandatory.
The method is useful when inspecting unknown database schemas. It only
supports returning the primary key column(s) for a single table.
The catalog method generates a result set having the following schema:
123
Column Name
Column Datatype
Comment
TABLE_CAT
VARCHAR(128)
Always NULL.
TABLE_SCHEMA
VARCHAR(128)
The name of the schema containing
TABLE_NAME.
TABLE_NAME
VARCHAR(128) not
NULL
The name of the table, or view, or alias, or
synonym.
COLUMN_NAME
VARCHAR(128) not
Primary Key column name.
mxODBC - Python ODBC Database Interface
Column Name
Column Datatype
Comment
NULL
ORDINAL_POSITION SMALLINT not NULL
Column sequence number in the primary key,
starting with 1.
PK_NAME
Primary key identifier. NULL if not applicable to
the data source.
VARCHAR(128)
.procedures(qualifier=None, owner=None, procedure=None)
Query the data source for information on procedures stored in a data source.
procedure can be used to limit the results to a set of procedures or a single
procedure.
The method is useful for determining the availability of stored procedures and
also for database schema introspection purposes. It can be used to check
whether a stored requires output parameters or fetching result sets.
The catalog method generates a result set having the following schema:
Column Name
Column Datatype
Comment
PROCEDURE_CAT
VARCHAR(128)
Always NULL.
PROCEDURE_SCHEMA
VARCHAR(128)
The name of the schema containing
PROCEDURE_NAME.
PROCEDURE_NAME
VARCHAR(128) not
NULL
The name of the procedure.
NUM_INPUT_PARAMS
INTEGER not NULL
Number of input parameters.
NUM_OUTPUT_PARAMS
INTEGER not NULL
Number of output parameters.
NUM_RESULT_SETSNUM INTEGER not NULL
_RESULT_SETS
Number of result sets returned by the
procedure.
REMARKS
VARCHAR(254)
Contains the descriptive information about
the procedure.
PROCEDURE_TYPE
SMALLINT
Defines the procedure type:
SQL.PT_UNKNOWN: It cannot be
determined whether the procedure
returns a value.
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7. mxODBC Cursor Objects
Column Name
Column Datatype
Comment
SQL.PT_PROCEDURE: The returned object
is a procedure; that is, it does not have a
return value.
SQL.PT_FUNCTION: The returned object
is a function; that is, it has a return value.
.procedurecolumns(qualifier=None, owner=None, procedure=None,
column=None)
Query the data source for information on parameter details of procedures
stored in a data source.
procedure can be used to limit the results to a set of procedures or a single
procedure. column allows restricting the results to a single procedure
parameter.
The method can be used to e.g. determine whether a parameter is an input,
output or input/output parameter. The COLUMN_TYPE column information can
directly be passed to the parametertypes parameter in cursor.callproc()
and the cursor.execute*() methods.
The catalog method generates a result set having the following schema (the
term "column" used here refers to the procedure's call parameters):
Column Name
Column Datatype
Comment
PROCEDURE_CAT VARCHAR(128)
Always NULL.
PROCEDURE_
SCHEMA
VARCHAR(128)
The name of the schema containing
PROCEDURE_NAME.
PROCEDURE_
NAME
VARCHAR(128)
The name of the table, or view, or alias, or
synonym.
COLUMN_NAME
VARCHAR(128)
Name of the column of the specified table, view,
alias, or synonym.
COLUMN_TYPE
SMALLINT not NULL
Identifies the type information associated with
this column. Possible values:
SQL.PARAM_TYPE_UNKNOWN: the parameter
type is unknown.
SQL.PARAM_INPUT: this parameter is an input
parameter.
SQL.PARAM_INPUT_OUTPUT: this parameter is
an input / output parameter.
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mxODBC - Python ODBC Database Interface
Column Name
Column Datatype
Comment
SQL.PARAM_OUTPUT: this parameter is an
output parameter.
SQL.RETURN_VALUE: the procedure column is
the return value of the procedure.
SQL.RESULT_COL: this parameter is actually a
column in the result set.
DATA_TYPE
SMALLINT not NULL
SQL data type of column.
TYPE_NAME
VARCHAR(128) not
NULL
Character string representing the name of the
data type corresponding to DATA_TYPE.
COLUMN_SIZE
INTEGER
If the DATA_TYPE column value denotes a
character or binary string, then this column
contains the maximum length in characters for
the column.
For date, time, timestamp data types, this is the
total number of characters required to display
the value when converted to character.
For numeric data types, this is either the total
number of digits, or the total number of bits
allowed in the column, depending on the value in
the NUM_PREC_RADIX column in the result set.
BUFFER_LENGTH
INTEGER
The maximum number of bytes for the
associated C buffer to store data from this
column if SQL.C_DEFAULT were specified on the
SQLBindCol(), SQLGetData() and
SQLBindParameter() ODBC calls used
internally by mxODBC. This length does not
include any null-terminator. For exact numeric
data types, the length accounts for the decimal
and the sign.
Note: This column is of little value to Python
applications.
DECIMAL_DIGITS
SMALLINT
The scale of the column. NULL is returned for
data types where scale is not applicable.
NUM_PREC_
RADIX
SMALLINT
Either 10 or 2 or NULL. If DATA_TYPE is an
approximate numeric data type, this column
contains the value 2, then the COLUMN_SIZE
column contains the number of bits allowed in
the column.
If DATA_TYPE is an exact numeric data type, this
column contains the value 10 and the
COLUMN_SIZE contains the number of decimal
digits allowed for the column.
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7. mxODBC Cursor Objects
Column Name
Column Datatype
Comment
For numeric data types, the database can return a
NUM_PREC_RADIX of either 10 or 2.
NULLABLE
SMALLINT not NULL
SQL.NO_NULLS if the column does not accept
NULL values.
REMARKS
VARCHAR(254)
May contain descriptive information about the
column or NULL.
It is possible that no usable information is
returned in this column (due to optimizations).
COLUMN_DEF
VARCHAR(3)
The column's default value. If the default value is
a numeric literal, then this column contains the
character representation of the numeric literal
with no enclosing single quotes. If the default
value is a character string, then this column is
that string enclosed in single quotes. If the
default value a pseudo-literal, such as for DATE,
TIME, and TIMESTAMP columns, then this
column contains the keyword of the pseudoliteral (e.g. CURRENT DATE) with no enclosing
quotes.
If NULL was specified as the default value, then
this column returns "NULL". If the default value
cannot be represented without truncation, then
this column contains "TRUNCATED" with no
enclosing single quotes. If no default value was
specified, then this column is NULL.
It is possible that no usable information is
returned in this column (due to optimizations).
127
SQL_DATA_TYPE
SMALLINT not NULL
ODBC3 SQL data type. This column is the same
as the DATA_TYPE column, except for date/time
types.
SQL_DATETIME_
SUB
SMALLINT
The subtype code for datetime data types:
SQL.CODE_DATE, SQL.CODE_TIME,
SQL.CODE_TIMESTAMP. For all other data types
this column returns NULL.
CHAR_OCTET_
LENGTH
INTEGER
Contains the maximum length in octets for a
character data type column. For Single Byte
character sets, this is the same as
COLUMN_SIZE. For all other data types it is
NULL.
ORDINAL_
POSITION
INTEGER not NULL
The ordinal position of the parameter column in
the procedure call. The first column has an
ordinal position of 1.
mxODBC - Python ODBC Database Interface
Column Name
Column Datatype
Comment
IS_NULLABLE
VARCHAR(254)
Contains the string "NO" if the column is known
to be not nullable, "" if this cannot be
determined, or "YES" if it is known to be nullable.
.specialcolumns(qualifier=None, owner=None, table=None,
coltype=SQL.BEST_ROWID, scope=SQL.SCOPE_SESSION,
nullable=SQL.NO_NULLS)
Query the data source for information on "special" columns of a given table.
The table parameter is mandatory.
Special columns in this sense are columns which can be used to uniquely
identify a row in the table (e.g. primary keys) or which are automatically
updated by the database (e.g. auto-increment columns).
Possible input values for coltype:
SQL_BEST_ROWID
Return the optimal column or set of columns for uniquely identifying a row
in the table (the rowid).
SQL_ROWVER
Return columns that are automatically updated by the database when the
row is updated.
Possible input values for scope:
SQL.SCOPE_CURROW
The rowid column(s) are only guaranteed to be valid as long as the rows
remain unchanged.
SQL.SCOPE_TRANSACTION
The rowid is guaranteed to be valid for the duration of the current
transaction.
SQL.SCOPE_SESSION
The rowid is guaranteed to be valid for the duration of the connection.
Possible input values for nullable:
SQL.NO_NULLS
Exclude special columns that nullable. Using this option can result in an
empty result set, if the table, driver or database don't support such
requirements.
SQL.NULLABLE
Return special columns, even if they can have NULL values.
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7. mxODBC Cursor Objects
The method is useful to determine columns that can be used as to determine
query columns that allow retrieving rows which have been inserted in a table
without primary key or in a table with a primary key which is defined as autoincrement column.
The catalog method generates a result set having the following schema:
Column Name
Column Datatype
Comment
SCOPE
SMALLINT
The duration for which the name in
COLUMN_NAME is guaranteed to point to the
same row. Contains one of the following
values: SQL.SCOPE_CURROW,
SQL.SCOPE_TRANSACTION,
SQL.SCOPE_SESSION.
COLUMN_NAME
VARCHAR(128) not
NULL
Name of the column that is (or part of) the
table's primary key.
DATA_TYPE
SMALLINT not NULL
SQL data type of column identified by
COLUMN_NAME.
TYPE_NAME
VARCHAR(128) not
NULL
Character string representing the name of the
data type corresponding to DATA_TYPE.
COLUMN_SIZE
INTEGER
If the DATA_TYPE column value denotes a
character or binary string, then this column
contains the maximum length in characters for
the column.
For date, time, timestamp data types, this is the
total number of characters required to display
the value when converted to character.
For numeric data types, this is either the total
number of digits, or the total number of bits
allowed in the column, depending on the value
in the NUM_PREC_RADIX column in the result
set.
BUFFER_LENGTH
INTEGER
The maximum number of bytes for the
associated C buffer to store data from this
column if SQL.C_DEFAULT were specified on
the SQLBindCol(), SQLGetData() and
SQLBindParameter() ODBC calls used
internally by mxODBC. This length does not
include any null-terminator. For exact numeric
data types, the length accounts for the decimal
and the sign.
Note: This column is of little value to Python
applications.
DECIMAL_DIGITS
129
SMALLINT
The scale of the column. NULL is returned for
mxODBC - Python ODBC Database Interface
Column Name
Column Datatype
Comment
data types where scale is not applicable.
PSEUDO_COLUMN SMALLINT
Indicates whether or not the column is a
pseudo-column. Possible values:
SQL.PC_NOT_PSEUDO, SQL.PC_UNKNOWN,
SQL.PC_PSEUDO.
.statistics(qualifier=None, owner=None, table=None,
unique=SQL.INDEX_ALL, accuracy=SQL.QUICK)
Query the data source for information on statistics and available indexes for a
given table. The table parameter is mandatory.
Possible input values for unique:
SQL.INDEX_UNIQUE
Return only unique indexes.
SQL.INDEX_ALL
Return all indexes.
Possible input values for accuracy:
SQL.ENSURE
The data returned for CARDINALITY and PAGES must be current and
accurate. This mode is not widely supported and its use is discouraged.
SQL.QUICK
The data for CARDINALITY and PAGES is returned if available, but must not
be current.
This method is mainly useful for identifying the indexes of a table in a database
schema.
The catalog method generates a result set having the following schema:
130
Column Name
Column Datatype
Comment
TABLE_CAT
VARCHAR(128)
Always NULL.
TABLE_SCHEMA
VARCHAR(128)
The name of the schema containing
TABLE_NAME.
TABLE_NAME
VARCHAR(128) not
NULL
The name of the table, or view, or alias, or
synonym.
7. mxODBC Cursor Objects
Column Name
Column Datatype
Comment
NON_UNIQUE
SMALLINT
Indicates whether the index prohibits duplicate
values. Returns:
SQL.TRUE if the index allows duplicate values.
SQL.FALSE if the index values must be unique.
NULL is returned if the TYPE column indicates
that this row is SQL.TABLE_STAT (statistics
information on the table itself).
INDEX_QUALIFIER
VARCHAR(128)
The string that would be used to qualify the
index name in the DROP INDEX statement.
Appending a period (.) plus the INDEX_NAME
results in a full specification of the index.
INDEX_NAME
VARCHAR(128)
The name of the index. If the TYPE column has
the value SQL.TABLE_STAT, this column has
the value NULL.
TYPE
SMALLINT not NULL
Indicates the type of information contained in
this row of the result set:
SQL.TABLE_STAT - Indicates this row contains
statistics information on the table itself.
SQL.INDEX_CLUSTERED - Indicates this row
contains information on an index, and the index
type is a clustered index.
SQL.INDEX_HASHED - Indicates this row
contains information on an index, and the index
type is a hashed index.
SQL.INDEX_OTHER - Indicates this row
contains information on an index, and the index
type is other than clustered or hashed.
131
ORDINAL_POSITION SMALLINT
Ordinal position of the column within the index
whose name is given in the INDEX_NAME
column. A NULL value is returned for this
column if the TYPE column has the value of
SQL.TABLE_STAT.
COLUMN_NAME
VARCHAR(128)
Name of the column in the index. A NULL value
is returned for this column if the TYPE column
has the value of SQL.TABLE_STAT.
ASC_OR_DESC
CHAR(1)
Sort sequence for the column; "A" for
ascending, "D" for descending. NULL value is
returned if the value in the TYPE column is
SQL.TABLE_STAT.
mxODBC - Python ODBC Database Interface
Column Name
Column Datatype
Comment
CARDINALITY
INTEGER
If the TYPE column contains the value
SQL.TABLE_STAT, this column contains the
number of rows in the table.
If the TYPE column value is not
SQL.TABLE_STAT, this column contains the
number of unique values in the index.
A NULL value is returned if the information
cannot be determined.
PAGES
INTEGER
If the TYPE column contains the value
SQL.TABLE_STAT, this column contains the
number of pages used to store the table.
If the TYPE column value is not
SQL.TABLE_STAT, this column contains the
number of pages used to store the indexes.
A NULL value is returned if the information
cannot be determined.
FILTER_CONDITION
VARCHAR(128)
If the index is a filtered index, this is the filter
condition. NULL is returned if TYPE is
SQL.TABLE_STAT or the database does not
support filtered indexes.
.tables(qualifier=None, owner=None, table=None, type=None)
Query the data source for information on tables stored in the database.
type may be set to a comma-separated string of database table types using all
uppercase characters. The exact list of available types is data source
dependent. Common types include: TABLE, VIEW, SYSTEM TABLE, GLOBAL
TEMPORARY, LOCAL TEMPORARY, ALIAS, SYNONYM.
This method is useful for checking whether a table exists and is accessible by
the current user or not. It also aids in database schema introspection.
The catalog method generates a result set having the following schema:
Column Name
Column
Datatype
Comment
TABLE_CAT
VARCHAR(128) The name of the catalog containing TABLE_SCHEM. This
column contains a NULL value.
TABLE_SCHEMA VARCHAR(128) The name of the schema containing TABLE_NAME.
TABLE_NAME
132
VARCHAR(128) The name of the table, or view, or alias, or synonym.
7. mxODBC Cursor Objects
Column Name
Column
Datatype
Comment
TABLE_TYPE
VARCHAR(128) Identifies the type given by the name in the TABLE_NAME
column. It can have the string values "TABLE", "VIEW",
"INOPERATIVE VIEW", "SYSTEM TABLE", "ALIAS", or
"SYNONYM".
REMARKS
VARCHAR(254) Contains the descriptive information about the table.
.tableprivileges(qualifier=None, owner=None, table=None)
Query the data source for information on table privileges associated with
database tables.
The method is useful for determining and extracting table access permissions
from the database.
The catalog method generates a result set having the following schema:
133
Column Name
Column Datatype
Comment
TABLE_CAT
VARCHAR(128)
Always NULL.
TABLE_SCHEMA VARCHAR(128)
The name of the schema containing TABLE_NAME.
TABLE_NAME
VARCHAR(128) not
NULL
The name of the table, or view, or alias, or synonym.
GRANTOR
VARCHAR(128)
Authorization ID of the user who granted the
privilege.
GRANTEE
VARCHAR(128)
Authorization ID of the user to whom the privilege is
granted.
PRIVILEGE
VARCHAR(128)
The table privilege. This may be one of the following
strings: "ALTER", "CONTROL", "INDEX", "DELETE",
"INSERT", "REFERENCES", "SELECT", "UPDATE".
IS_GRANTABLE
VARCHAR(3)
Indicates whether the grantee is permitted to grant
the privilege to other users. This can be "YES", "NO"
or NULL.
mxODBC - Python ODBC Database Interface
7.7 Cursor Object Attributes
.arraysize
This read/write attribute specifies the number of rows to fetch at a time with
.fetchmany(). It defaults to 1 meaning to fetch a single row at a time.
mxODBC uses this value as default for the number of rows to fetch with
.fetchmany() method.
.bindmethod
Attribute to query and set the input variable binding method used by the
cursor. This can either be BIND_USING_PYTHONTYPE of BIND_USING_SQLTYPE
(see the Constants section 10.5 for details).
The attribute is inherited by cursors from their connections at creation time.
Cursors may override the setting on a per cursor basis without affecting the
connection that was used to create them.
.closed
This read-only attribute is true if the cursor or the underlying connection was
closed by calling the .close() method.
Any action on a closed connection or cursor will result in a
ProgrammingError to be raised. This variable can be used to conveniently test
for this state.
.colcount
This read-only attribute specifies the number of columns in the current result
set.
The attribute is -1 in case no .execute*() has been performed on the cursor.
Please note that accessing this attribute may result in database errors in case it
is used on cursors with prepared but not yet executed statements.
One of the reasons for this is that the ODBC drivers have not yet seen the
parameter values which will be bound to the parameter markers in the
statement, e.g. "[Microsoft][ODBC SQL Server Driver][SQL
Server]Procedure or function 'myfunc' expects parameter
'@param1', which was not supplied."
.command
Provides access to the last SQL command string or Unicode object that was
passed to .prepare() or .execute*(). If no such command is available,
None is returned.
It is set by .prepare() and .execute*() and reset by calling one of the
catalog methods or .close() on the cursor.
Note that .command may be a Unicode object in case a Unicode object was
passed to one of the above methods.
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7. mxODBC Cursor Objects
.connection
Connection object on which the cursor operates.
.converter
Read-only access to the converter function set using the
cursor.setconverter()method or inherited from the
connection.converter attribute at cursor creation time.
The attribute is None in case no converter function was set or inherited.
mxODBC will then use the default type conversions when fetching data from
the database. See section 8.5 Output Conversions for details.
.cursortype
Read/write attribute that sets the ODBC cursor type this cursor. It takes the
same values as the connection.cursortype instance variable and defaults to
the creating connection object's settings for connection.cursortype. For
possible values, please see the connection .cursortype attribute in section
6.8 Connection Object Attributes.
Changes to the cursor type must be made before opening the cursor, ie. before
executing a statement on it.
Please refer to section 5.8 ODBC Cursor Types for more details on cursor
types.
.datetimeformat
Attribute to set the output format for date/time/timestamp columns on a per
cursor basis. It takes the same values as the connection.datetimeformat
instance variable and defaults to the creating connection object's settings for
connection.datetimeformat.
.decimalformat
Attribute to set the output format for decimal/numeric columns on a per cursor
basis. It takes the same values as the connection.decimalformat instance
variable and defaults to the creating connection object's settings for
connection.decimalformat.
.description
This read-only attribute is a sequence of 7-item sequences for operations that
produce a result set (which may be empty).
Each of these sequences contains information describing one result column:
(name, type_code, display_size, internal_size, precision,
scale, null_ok).
This attribute will be None for operations that do not return rows or if the
cursor has not had an operation invoked via the .execute*() method yet.
mxODBC always returns None for display_size and internal_size. This
information can be obtained via connection.gettypeinfo(), if needed.
The type_code can be interpreted by comparing it to the type objects
specified in the section 8 Type Objects and Constructors below. mxODBC
returns the SQL type integers in this field. These are described in the section 8
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mxODBC - Python ODBC Database Interface
Supported Data Types and are available through the SQL singleton defined at
module level.
Please see section 5.7.2 Result Set Introspection for more information on this
attribute and how to use it.
.encoding
Read/write attribute which defines the encoding to use for converting Unicode
to 8-bit strings and vice-versa. If set to None (default), Python's default
encoding will be used, otherwise it has to be a string providing a valid
encoding name, e.g. 'latin-1' or 'utf-8'.
The setting is inherited from the connection.encoding at cursor creation
time, but can be adjust independently from the connection after its creation.
All cursor related APIs such cursor.execute*() and cursor.fetch*()
methods use the cursor.encoding for Unicode conversions.
.messages
This is a Python list object to which the standard mxODBC error handler
appends tuples (exception class, exception value) for all messages
which the interfaces receives from the underlying ODBC driver or manager for
this cursor. See section 10. Error Handlers for details.
The list is cleared by all cursor methods calls (prior to executing the call)
except for the .fetch*() calls to avoid excessive memory usage and can also
be cleared explicitly by executing del cursor.messages[:].
An application can use the information in this list to verify correct operation of
the method calls. This is particularly useful if the ODBC driver or database
splits the error information across multiple error messages. In such a case,
only one of the messages will be used to raise the exception by mxODBC
(usually the top-most), but this message may not provide enough information
to track down the problem.
.paramcount
This read-only attribute specifies the number of parameters in the current
prepared command.
The attribute is -1 in case this information is not available.
.paramstyle
Sets the default parameter binding style of the cursor. The value is initially set
to the value of connection.paramstyle of the creating connection. The value
takes affect on the next call to a cursor.execute*() method.
The attribute can be set or queried and takes the following string values
(following the paramstyle module global as defined in the DB-API):
'qmark' (default)
This is the default ODBC parameter binding style and also used as native
database binding style by MS SQL Server and IBM DB2.
Parameters in SQL statements used on cursor.execute*() methods are
marked with the question mark letter ('?') and the variables are bound to
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7. mxODBC Cursor Objects
these parameter locations using a positional mapping. Parameter values for
a SQL statement must be specified as sequence, normally a list or a tuple.
Example: 'SELECT * FROM MyTable WHERE A=? AND B=?' used with a
parameter tuple (1, 2) would result in the database executing the query
'SELECT * FROM MyTable WHERE A=1 AND B=2'.
'named'
The 'named' parameter binding style is used by the native database
interfaces of e.g. Oracle.
Parameters in SQL statements used on cursor.execute*() methods are
marked with a colon followed by a name, e.g. ':a' or ':1'. The variables
are bound to these parameter locations using a name based mapping.
Parameter values for a SQL statement must be specified as mapping,
normally a dictionary, and are bound to the locations based on the names
used in the SQL statement.
Example: 'SELECT * FROM MyTable WHERE A=:a AND B=:b' used with
a parameter dictionary {'a': 1, 'b': 2} would result in the database
executing the query 'SELECT * FROM MyTable WHERE A=1 AND B=2'.
.row
This attribute sets the default cursor.row object constructor to be used by all
newly created cursor objects on this connection.
If set to an object constructor taking a row tuple as argument (i.e.
cursor.row(row_tuple)), mxODBC will use the constructor to wrap all rows
fetched through one of the .fetch*() methods. Instead of row tuples, the
.fetch*() methods will then return the objects created by this constructor.
Default is None, which means that mxODBC will use regular Python tuples for
returning row data in result sets.
Please see section 5.9 Custom Cursor Row Objects and Row Factory Functions
for details on how to use cursor.row and cursor.rowfactory.
.rowfactory
This attribute sets the default cursor.rowfactory row object constructor
factory to be used by all newly created cursor objects on this connection.
If set to a factory function, mxODBC will call this factory function with the
cursor as argument when starting to fetch a result set and set the cursor.row
attribute to the object returned by the factory function (i.e. cursor.row =
cursor.rowfactory(cursor)).
The purpose of the row factory is to dynamically set the cursor.row attribute
after having executed a statement on the cursor. This allows the factory
function to use the cursor.description for building a row object
constructor customized to the available result set.
Default is None, which means that mxODBC will not use a row factory
function and leave cursor.row untouched.
Please see section 5.9 Custom Cursor Row Objects and Row Factory Functions
for details on how to use cursor.row and cursor.rowfactory.
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.rowcount
This read-only attribute specifies the number of rows that the last
.execute*() produced (for DQL statements like select) or affected (for SQL
DML statements like update or insert).
The attribute is -1 in case no .execute*() has been performed on the cursor
or the rowcount of the last operation is not determinable by the interface or
the database.
You should check whether the database you are interfacing to supports
.rowcount before writing code which relies on it. Many databases such as MS
Access and Oracle do not provide this information to the ODBC driver, so
.rowcount will always be –1.
.rownumber
This read-only attribute provides the current 0-based row position of the
cursor in the result set. The next .fetch*() will return rows starting at the
given position.
The row position is automatically updated whenever the cursor moves through
the result set, either due to fetches or scrolls.
The attribute is None in case no .execute*() has been performed on the
cursor or the cursor position cannot be determined.
mxODBC provides a .rownumber emulation on the client-side for databases
that do not implement the ODBC feature, such as e.g. MS Access, Teradata or
Oracle. If the emulation cannot be provided, the attribute will return None.
.stringformat
Attribute to set the conversion format for string columns on a per cursor basis.
It takes the same values as the connection.stringformat instance variable
and defaults to the creating connection object's settings for
connection.stringformat.
.timestampresolution
Attribute to set the timestamp resolution for timestamp input columns on a per
cursor basis. It works in the same ways as the
connection.timestampresolution instance variable and defaults to the
creating connection object's settings for connection.timestampresolution.
.warningformat
Attribute to set the database warning reporting method used by the mxODBC
default error handler. It takes the same values as the
connection.warningformat instance variable and defaults to the creating
connection object's settings for connection.warningformat.
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8. Data Types supported by mxODBC
8.
Data Types supported by mxODBC
mxODBC tries to maintain as much of the available information across the
Python-ODBC bridge as possible. In order to implement this, mxODBC converts
between the ODBC and the Python world by using native data types in both
worlds.
You should note however, that some ODBC drivers return data using different
types than the ones accepted for input, e.g. a database might accept a time value,
convert it internally to a timestamp and then return it in a subsequent SELECT as
timestamp value.
mxODBC cannot know that the value only contains valid time information and no
date information and thus converts the output data into an mxDateTime DateTime
instance instead of an mx.DateTime.DateTimeDelta instance (which would
normally be returned for time values).
The included mx/ODBC/Misc/test.pyc can help to check for this behavior. It tests
many common column types and other database features which are useful to
know when writing applications for a particular database backend.
8.1 mxODBC Parameter Binding
When defining SQL statements that use parameters, mxODBC provides a way to
bind Python values to those parameters called parameter binding.
Instead of using the literal parameter values in the SQL statement passed to the
cursor.execute*() methods, you can use a parameter binding character or
character sequence to define the parameter locations in the SQL statement and
then pass the Python parameter values to the cursor.execute*() methods as
additional parameter. The ODBC driver or the database backend will then take the
values and use them to run the SQL statement.
Example:
Use "SELECT * FROM MyTable WHERE A=? AND B=?" and (1, 2)
(parameter binding) instead of "SELECT * FROM MyTable WHERE A=1 AND
B=2" (embedding parameters literally).
This has both a performance and a security advantage.
Performance is much better if the database backend can easily identify whether it
has already created an access plan for a SQL statement by simply looking at the
parameterized version of the statement, than first having to convert a SQL
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mxODBC - Python ODBC Database Interface
statement with embedded literal parameters to a normalized form and then find
that it already has an access plan.
If you plan to run the same statement over and over again or use
cursor.executemany(), then the ODBC driver only has to pass the SQL
statement and the list of parameters to the database, rather than build and send
hundreds of statements across the wire to the database.
Security is better since the ODBC driver or database backend based building of
the final SQL statement prevents the popular SQL injection attack on applications.
With this attack method, an attacker tries to trick an application into inserting a
specially prepared SQL statement string sequence into an application defined SQL
statement template. Say the application uses "SELECT * FROM MyTable WHERE
A=%s". An attacker could then try to send the parameter value "1; DROP TABLE
MyTable" to the application, which would then result in the SQL statement
"SELECT * FROM MyTable WHERE A=1; DROP TABLE MyTable" to be executed
- in case the application doesn't very carefully check, parse and quote the
parameter value for A.
8.1.1 Parameter Binding Styles
mxODBC uses the ODBC parameter style as binding parameter marker style per
default. This style is called 'qmark' because it uses positional question mark
markers ('?') to locate the parameters, e.g. 'SELECT * FROM MyTable WHERE
A=?'.
Starting with mxODBC 3.2, mxODBC also provides a way to adjust the parameter
style on a per connection and per cursor basis. In addition of the 'qmark'
parameter style, mxODBC also supports the Oracle style 'named' parameter
style.
The
default style is still the 'qmark' style, but you can set the
connection.paramstyle to 'named' to have all new cursors created on the
connection default to the 'named' style. The default cursor.paramstyle is set
to the value connection.paramstyle of the connection on which the cursor was
created.
It is also possible to adjust existing cursors to use the 'named' parameter style for
all subsequent cursor.execute*() method calls by simply setting
cursor.paramstyle to 'named'. This has no affect on other cursors created on
the same connection.
Example:
cursor.paramstyle = 'qmark'
cursor.execute("SELECT * FROM MyTable WHERE A=? AND B=?",
(1, 2))
print cursor.fetchall()
cursor.paramstyle = 'named'
cursor.execute("SELECT * FROM MyTable WHERE A=:a AND B=:b",
{'a': 1, 'b': 2})
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8. Data Types supported by mxODBC
print cursor.fetchall()
More information about the connection and cursor attribute .paramstyle is
available in section 6.8 Connection Object Attributesand 7.7 Cursor Object
Attributes.
8.2 mxODBC Input Binding Modes
When passing parameters to the .execute*() methods of a cursor, mxODBC
has to apply type conversions to the parameters in order to send them to the
database in an appropriate form. This process is called binding a variable.
mxODBC implements two different input variable binding modes depending on
what the ODBC driver can deliver. The currently used binding mode can be
determined by looking at the cursor.bindmethod (which is inherited from the
connection.bindmethod at cursor creation time).
Binding Mode
Value of .bindmethod
Comments
SQL type binding
BIND_USING_SQLTYPE
The database is asked for the
appropriate data type and mxODBC
tries to convert the input variable
into that type.
This is the preferred binding mode
since it allows to choose the right
conversion before passing the data
to the ODBC driver.
Python type
binding
BIND_USING_PYTHONTYPE
mxODBC looks at the type of the
input variable and passes its value
to the database directly; conversion
is done by the ODBC
driver/manager as necessary.
The default depends on the capabilities of the ODBC driver being used on the
connection. mxODBC will always try to use the SQL type binding mode
(BIND_USING_SQLTYPE), since this offers more flexibility than Python type
binding.
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mxODBC - Python ODBC Database Interface
Please note that mxODBC will try to use SQL type binding if possible, but
always falls back to Python type binding mode in case it cannot access the
needed type information from the ODBC driver or database. This even applies if
the binding mode is set to SQL type binding.
8.2.1 Adjusting the Type Binding Mode
As for many other attributes, mxODBC provide ways of defining the binding
method on a per connection or a per cursor basis.
Per Connection Type Binding Setting
If you run into problems when using mxODBC in SQL type binding mode, please
try to use Python type binding mode by configuring the connections to use Python
type binding mode:
connection.bindmethod = BIND_USING_PYTHONTYPE
After setting the connection.bindmethod all cursors created on the connection
will use the new bind method as default.
Per Cursor Type Binding Setting
If you want to adjust the bind method on a per-cursor basis, this is possible as
well, by setting the cursor.bindmethod attribute.
cursor.bindmethod = BIND_USING_PYTHONTYPE
Doing so will not affect the connection the cursor was created on or any other
cursors created on the connection.
Per-Statement Binding Mode
With some database drivers, it is also possible to trigger the Python type binding
mode in a more fine-grained way on a per statement basis.
This is done by using cursor.executedirect() method or the direct=1
parameters on other execution methods for running SQL statements against the
database.
mxODBC will then send the statements as-is to the database server and apply
Python type binding for the parameters.
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8. Data Types supported by mxODBC
8.3 SQL Type Input Binding
The following data types are used for SQL type input binding mode cursor.bindmethod (inherited from connection.bindmethod) set to
BIND_USING_SQLTYPE.
The SQL type is what the database ODBC driver expects from mxODBC. The
interface then tries to convert the Python input objects to the Python type given in
the table before passing it on to the ODBC driver.
SQL Type
Python Type
Comments
SQL.CHAR,
SQL.VARCHAR,
SQL.LONGVARCHAR (TEXT,
BLOB or LONG in SQL)
String or
Unicode or
stringified object
The conversion truncates the string
at the SQL field length. The handling
of special characters depends on the
codepage the database uses.
Some database drivers/managers
can't handle binary data in these
column types, so you better check
the database's capabilities with the
included mx/ODBC/Misc/test.pyc
first before using them.
The handling of Unicode depends on
the setting of the .stringformat
attribute.
In NATIVE_UNICODE_
STRINGFORMAT mode, Unicode is
passed to the ODBC driver as native
Unicode. Strings are converted to
Unicode using the
cursor.encoding setting.
In all other modes, Unicode is
converted to an 8-bit string before
passing it to the ODBC driver using
the cursor.encoding setting.
Strings are passed as-is.
Note that for DateTime input objects,
seconds rounding is applied just like
for SQL.TIMESTAMP SQL types. For
DateTimeDelta input objects,
seconds are truncated to whole
seconds.
SQL.WCHAR,
SQL.WVARCHAR,
143
String or
Unicode or
The conversion truncates the string
at the SQL field length.
mxODBC - Python ODBC Database Interface
SQL Type
Python Type
SQL.WLONGVARCHAR
(TEXT, BLOB or LONG in
SQL)
stringified object
Comments
Non-string objects are passed
through unicode(obj,
cursor.encoding) to convert
them to Unicode objects, except
numbers, which are passed through
unicode(obj), i.e. without using
the connection encoding.
The handling of Unicode depends on
the setting of the .stringformat
attribute.
In EIGHTBIT_STRINGFORMAT and
UNICODE_STRINGFORMAT
mode, Unicode is converted to an 8bit string before passing it to the
ODBC driver using the
cursor.encoding setting. Strings
are passed as-is.
In all other modes, Unicode is
passed to the ODBC driver as native
Unicode. Strings are converted to
Unicode before passing them to the
ODBC driver using the
cursor.encoding setting.
Note that for mxDateTime input
objects, seconds rounding is applied
just like for SQL.TIMESTAMP SQL
types. For DateTimeDelta input
objects, seconds are truncated to
whole seconds.
SQL.BINARY,
SQL.VARBINARY,
SQL.LONGVARBINARY
(BLOB or LONG BYTE in
SQL)
buffer, memoryview or String
Truncation at the SQL field length.
These columns can contain
embedded 0-bytes and other special
characters.
Handling of these column types is
database dependent. Please refer to
the database's documentation for
details.
Many databases store the passed in
data as-is and thus make these
columns types useable as storage
facility for arbitrary binary data.
Note that for mxDateTime input
objects, seconds rounding is applied
just like for SQL.TIMESTAMP SQL
types. For DateTimeDelta input
objects, seconds are truncated to
whole seconds.
SQL.TINYINT,
SQL.SMALLINT,
144
Integer or
any other object which can be
Conversion from the Python integer
(a C long) to the SQL type is left to
8. Data Types supported by mxODBC
SQL Type
Python Type
Comments
SQL.INTEGER,
SQL.BIT
converted to a Python integer
the ODBC driver/manager, so expect
the usual truncations.
SQL.BIGINT
Long integer or
any other object which can be
converted to a Python long
integer
Conversion to and from the Python
long integer is done directly, if
possible, or via the string
representation if the C data types are
not sufficient to hold the numeric
data.
If mxODBC has to use the string
representation for interfacing, you
may receive errors indicating
truncation or errors because the
database sent string data that cannot
be converted to a Python long
integer.
Not all SQL databases implement
this type or impose size limits.
SQL.DECIMAL,
SQL.NUMERIC
Python decimal.Decimal or
Float or
any other object which can be
converted to a Python float
Conversion from the Python float (a
C double) to the SQL type is left to
the ODBC driver/manager, so expect
the usual truncations.
Python decimals are passed to that
database as strings, so no truncation
or loss of precision occurs.
SQL.REAL,
SQL.FLOAT,
SQL.DOUBLE
Float or
any other object which can be
converted to a Python float
Conversion from the Python float (a
C double) to the SQL type is left to
the ODBC driver/manager, so expect
the usual truncations.
SQL.DATE
DateTime instance or
datetime.date instance or
a tuple
(year,month,day) or
String/Unicode or
a ticks value as Python
number
While you should use DateTime
instances, the module also accepts
Python datetime.date instances,
ticks (Python numbers indicating the
number of seconds since the Unix
Epoch; these are converted to local
time and then stored in the database)
and tuples (year,month,day) on
input.
SQL.TIME
DateTimeDelta instance or
datetime.time instance or
a tuple
(hour,minute,second) or
String/Unicode or
a tocks value as Python
number
While you should use DateTimeDelta
instances, the module also accepts
Python datetime.time instances,
tocks (Python numbers indicating the
number of seconds since 0:00:00.00)
and tuples
(hour,minute,second) on
input.
Seconds are rounded to the nearest
nanosecond in order to avoid issues
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SQL Type
Python Type
Comments
with float second values which
sometimes cannot be represented
with full accuracy.
SQL.TIMESTAMP
DateTime instance or
datetime.datetime instance or
datetime.date instance or
a tuple (year,month,day,
hour,minute,second) or
String/Unicode or
a ticks value as Python
number
While you should use DateTime
instances, the module also accepts
Python datetime.datetime instances,
datetime.date instances (the time
part is then set to 00:00:00), ticks
(Python numbers indicating the
number of seconds since the epoch;
these are converted to local time and
then stored in the database) and
tuples (year,month,day,
hour,minute,second) on input.
Seconds are rounded according to
the setting of the
.timestampresolution setting, which
defines the resolution of the
timestamps in nanoseconds.
mxODBC will round the timestamp's
second value to the nearest
nanosecond fraction defined by this
setting in order to avoid issues with
float second values which sometimes
cannot be represented with full
accuracy. If not set, the
.timestampresolution attribute
defaults to 1 nanosecond, so
rounding usually is done to the
nearest nanosecond, which is also
the smallest fraction supported by
the ODBC standard.
Any nullable column
None
The Python None singleton is
converted to the special SQL NULL
value.
Unsupported Type
String or
stringified object
Input binding to these columns is
done via strings (or stringified
versions of the input data).
Note that for mxDateTime input
objects, seconds rounding is applied
just like for SQL.TIMESTAMP SQL
types.
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8. Data Types supported by mxODBC
8.4 Python Type Input Binding
The following mappings are used for input variables in Python type input binding
mode - cursor.bindmethod (inherited from connection.bindmethod) set to
BIND_USING_PYTHONTYPE. The table shows how the different Python types are
converted to SQL types.
Python Type
SQL Type
Comments
String
SQL.VARCHAR,
SQL.LONGVARCHAR,
SQL.VARBINARY,
SQL.LONGVARBINARY
The conversion truncates the string at the SQL
field length. If the string contains binary data,
SQL.VARBINARY is used for passing the data to
the ODBC driver/manager.
(char *)
Unicode
SQL.WVARCHAR,
SQL.WLONGVARCHAR
(wchar_t *)
The long variants are used for strings longer
than 256 characters.
The conversion truncates the string at the SQL
field length. Note that not all ODBC
drivers/managers support Unicode data at C
level.
This binding is used for all cursors which do
not have the .stringformat attribute set
to EIGHTBIT_STRINGFORMAT or
UNICODE_STRINGFORMAT.
In EIGHTBIT_STRINGFORMAT mode
(default) and UNICODE_STRINGFORMAT
mode, Unicode objects are converted to a 8-bit
strings first and then passed to the ODBC
driver/manager.
The long variant is used for Unicode data
longer than 256 code points.
buffer or
memoryview
SQL.VARBINARY,
SQL.LONGVARBINARY
(char *)
The conversion truncates the string at the SQL
field length. The string may contain binary
data.
If the ODBC driver/manager doesn't support
processing binary data using strings, wrap the
data object using Python buffers (via the
buffer() constructor) or Python memory
views (via the memoryview()constructor)
to have mxODBC use a binary SQL type for
interfacing to the driver/manager. The Oracle
ODBC drivers usually need this.
The long variant is used for binary data longer
than 256 bytes.
Integer
147
SQL.SLONG
Conversion from the signed long to the SQL
column type is left to the ODBC
mxODBC - Python ODBC Database Interface
Python Type
Long Integer
SQL Type
Comments
(signed long)
driver/manager, so expect the usual
truncations.
SQL.CHAR
Conversion from the Python long integer is
done via the string representation since there
usually is no C type with enough precision to
hold the value.
SQL.DOUBLE
Conversion from the Python float (a C double)
to the SQL column type is left to the ODBC
driver/manager, so expect the usual
truncations.
SQL.VARCHAR,
SQL.LONGVARCHAR
(char *)
Conversion from a Python decimal.Decimal
instance is done via the string representation to
avoid losing precision.
(char *)
Float
(double)
decimal.Decimal
The long variant is used for decimal
representations longer than 256 characters.
DateTime
SQL.TIMESTAMP
or
SQL.DATE
Converts the DateTime instance into a
TIMESTAMP or DATE struct defined by the
ODBC standard.
The ODBC driver may use the time part of the
instance or not depending on the SQL column
type (DATE or TIMESTAMP).
Seconds are rounded according to the setting
of the .timestampresolution setting, which
defines the resolution of the timestamps in
nanoseconds.
mxODBC will round the timestamp's second
value to the nearest nanosecond fraction
defined by this setting in order to avoid issues
with float second values which sometimes
cannot be represented with full accuracy. If not
set, the .timestampresolution attribute defaults
to 1 nanosecond, so rounding usually is done
to the nearest nanosecond, which is also the
smallest fraction supported by the ODBC
standard.
DateTimeDelta
SQL.TIME
Converts the DateTimeDelta instance into a
TIME struct defined by the ODBC standard.
Fractions of a second will be lost in this
conversion.
datetime.date
SQL.DATE
Converts the datetime.date instance into a
DATE struct defined by the ODBC standard.
Note that some database backends don't
support date column types and give an error
when using datetime.date objects. MS SQL
Server 2000 and 2005 are examples. MS SQL
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8. Data Types supported by mxODBC
Python Type
SQL Type
Comments
Server 2008 introduced a date column type.
datetime.time
SQL.TIME
Converts the datetime.time instance into a
TIME struct defined by the ODBC standard.
datetime.datetime
SQL.TIMESTAMP
Converts the datetime.datetime instance into a
TIMESTAMP struct defined by the ODBC
standard.
Seconds are rounded to the nearest
nanosecond in order to avoid issues with float
second values which sometimes cannot be
represented with full accuracy.
None
Any nullable column
The Python None singleton is converted to the
special SQL NULL value.
Any other type
SQL.VARCHAR,
SQL.LONGVARCHAR,
SQL.VARBINARY,
SQL.LONGVARBINARY
Conversion is done by calling str(variable) and
then passing the resulting string value to the
ODBC driver/manager.
(char *)
Same notes as for strings apply.
See the ODBC Documentation and your ODBC driver's documentation for more
information on how these C data types are mapped to SQL column types.
8.5 Output Conversions
The
following
data
types
are
used
per
default
for
output
variable:
SQL Type
Python Type
Comments
SQL.CHAR,
SQL.VARCHAR,
SQL.LONGVARCHAR
(TEXT, BLOB or LONG
in SQL)
String
The handling of special characters
depends on the codepage the database
uses.
In
NATIVE_UNICODE_STRINGFORMAT
and UNICODE_STRINGFORMAT
mode, the string data is converted to a
Python Unicode object based on the
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mxODBC - Python ODBC Database Interface
SQL Type
Python Type
Comments
connection's encoding setting.
SQL.WCHAR,
SQL.WVARCHAR,
SQL.WLONGVARCHAR
(TEXT, BLOB or LONG
in SQL)
String or
Unicode
Whether a Python string or Unicode
object is returned depends on the setting
of the .stringformat attribute of the
cursor fetching the data.
In EIGHTBIT_STRINGFORMAT
mode, the Unicode data is converted to a
Python string object based on the
connection's encoding setting.
SQL.BINARY,
String
SQL.VARBINARY,
SQL.LONGVARBINARY
(BLOB or LONG BYTE
in SQL)
These can contain embedded 0-bytes and
other special characters.
Handling of these column types is
database dependent. Please refer to the
database's documentation for details.
SQL.TINYINT,
SQL.SMALLINT,
SQL.INTEGER,
SQL.BIT
Integer or
Long Integer
Bits are converted to Python integers 0
and 1 resp.
SQL.BIGINT
Long Integer
mxODBC tries to fetch the long integer
data directly and falls back to using string
interfacing, if the platform does not
provide the necessary C types for this.
SQL.DECIMAL,
SQL.NUMERIC
Float or
decimal.Decimal
In FLOAT_DECIMALFORMAT mode
(default), mxODBC will fetch the numeric
data as Python float. Since Python stores
floats as double precision C float,
rounding errors may occur during the
conversion.
Unsigned short integers are fetched as
Python integers, unsigned integers as
Python long integers.
In DECIMAL_DECIMALFORMAT mode,
mxODBC will fetch the numeric data as
string and create a Python
decimal.Decimal instance from it which is
then returned. This avoids any rounding
errors.
150
SQL.REAL,
SQL.FLOAT,
SQL.DOUBLE
Float
Python stores floats as double precision C
float, so rounding errors may occur during
the conversion.
SQL.DATE
DateTime instance or
datetime.date instance or
ticks or
(year,month,day) or
String
The type of the return values depends on
the setting of
cursor.datetimeformat and
whether the ODBC driver/manager does
return the value with proper type
8. Data Types supported by mxODBC
SQL Type
Python Type
Comments
information.
Default is to return DateTime instances.
SQL.TIME
DateTimeDelta instance or
datetime.time instance or
tocks or
(hour,minute,second) or
String
The type of the return values depends on
the setting of
cursor.datetimeformat and
whether the ODBC driver/manager does
return the value with proper type
information.
Default is to return DateTimeDelta
instances.
SQL.TIMESTAMP
DateTime instance or
datetime.datetime instance or
ticks or
(year,month,day,
hour,minute,second) or
String
The type of the return values depends on
the setting of
cursor.datetimeformat and
whether the ODBC driver/manager does
return the value with proper type
information.
Default is to return DateTime instances.
SQL NULL value
None
The Python None singleton is used to
represent the special SQL NULL value in
Python.
Unsupported Type
String
mxODBC will try to fetch data from
columns using unsupported SQL data
types as strings.
This is likely to always work but may
cause unwanted conversions and or
truncations or loss of precision.
Output bindings can only be applied using the above mapping by mxODBC if the
database correctly identifies the type of the output variables.
The SQL type given in the above table is also made available though the cursor's
.description tuple as type_code entry (position 1) for result set generating
SQL commands. You can compare this value directly to the appropriate SQL
object values, e.g. test for SQL.CHAR or SQL.VARCHAR.
8.6 Output Type Converter Functions
The last section defined the standard mapping mxODBC applies when fetching
output data from the database.
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8.6.1 Converter Function Signatures
You can modify this mapping on-the-fly by defining a cursor converter function
which takes three arguments and has to return a 2-tuple:
def converter(position,sqltype,sqllen):
# modify sqltype and sqllen as appropriate
return sqltype,sqllen
# Now tell the cursor to use this converter:
cursor.setconverter(converter)
or 3-tuple:
def converter(position,sqltype,sqllen):
# modify sqltype and sqllen as appropriate, provide binddata as
# input (e.g. for file names which should be used for file
# binding)
return sqltype,sqllen,binddata
# Now tell the cursor to use this converter:
cursor.setconverter(converter)
The converter function is called for each output column prior to the first
.fetch*() operation executed on the cursor. The returned values are then
interpreted as defined in the table in section 8.3 Output Conversions and SQL
Type Input Binding.
The parameters have the following meanings:
position
identifies the 0-based position of the column in the result set.
sqltype
is usually one of the SQL data type constants, e.g. SQL.CHAR for string data,
but could also have database specific values. mxODBC only understands the
ones defined in the above table, so this gives you a chance to map user defined
types to ones that Python can process.
sqllen
is only used for string data and defines the maximum length of strings that can
be read in that column (mxODBC allocates a memory buffer of this size for the
data transfer).
Returning 0 as sqllen will result in mxODBC dynamically growing the data
transfer buffer when fetching the column data. This is sometimes handy in
case you want to fetch data that can vary in size.
binddata
is optional and only needed for some special sqltypes. It will be used in
future versions to e.g. allow binding output columns to files which some
ODBC drivers support (the column data is transferred directly to a file instead
of copied into memory).
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8. Data Types supported by mxODBC
8.6.2 Adjusting/Querying the Converter Function
Cursor objects will use the connection's .converter attribute as default
converter. It defaults to None, meaning that no converter function is in effect.
None can also be used to disable the converter function on a cursor:
# Don't use a converter function on the cursor
cursor.setconverter(None)
You can switch converter functions even in between fetches. mxODBC will then
reallocate and rebind the column buffers for you.
The currently used converter function can be queried through the read-only
cursor.converter attribute, e.g. to check whether the default mxODBC
conversions are being used or not.
8.6.3 Example Converter Function
Example (always return INTEGER values as FLOATS):
def converter(position,sqltype,sqllen):
if sqltype == SQL.INTEGER:
sqltype = SQL.FLOAT
return sqltype,sqllen
# Now tell the cursor to use this converter:
cursor.setconverter(converter)
8.7 Auto-Conversions
While you should always try to use the above Python types for passing input
values to the respective columns, the package will try to automatically convert the
types you give into the ones the database expects when using the SQL Type bind
method, e.g. an integer literal '123' will be converted into an integer 123 by
mxODBC if the database ODBC driver requests an integer.
The
situation
is
different
in
Python
type
binding
mode
(BIND_USING_PYTHONTYPE): the Python type used in the parameter is passed
directly to the database, thus passing '123' or 123 does make a difference and
could result in an error from the database.
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mxODBC - Python ODBC Database Interface
8.8 Unicode and String Data Encodings
mxODBC also supports Unicode objects to interface with databases. As more
databases and ODBC drivers support Unicode natively, using Unicode for text
data stored in database becomes more attractive than ever and allows you to
avoid the problems you typically face when having to deal with different text
encodings and code pages in databases.
Even if you don't have access to an ODBC capable of dealing with Unicode
natively, you can still take advantage of the auto-conversion mechanisms in
mxODBC to simulate Unicode capabilities.
mxODBC provides several different run-time configurations to deal with passing
Unicode to and fetching it from an ODBC driver. The .stringformat attribute of
connection and cursor objects allows defining how to convert string data into
Python objects and vice-versa.
Unicode conversions to and from 8-bit strings in Python usually assume the
Python default encoding (which is ASCII unless you modify the Python
installation). Since the database may be using a different encoding, mxODBC
allows defining the encoding to be used on a per-connection basis.
The .encoding attribute of connection and cursor objects is writeable for this
purpose. Its default value is None, meaning that Python's default encoding (usually
ASCII) is to be used. You can change the encoding by simply assigning a valid
encoding name to the attribute. Make sure that Python supports the encoding
(you can test this using the unicode() built-in).
The default conversion mechanism used in mxODBC is EIGHTBIT_STRINGFORMAT
(Unicode gets converted to 8-bit strings before passing the data to the driver,
output is always an 8-bit string), the default encoding Python's default encoding.
To
store
Unicode
in
a
database,
one
possibility
is
to
use
the
UNICODE_STRINGFORMAT and set the encoding attribute to e.g. 'utf-8'.
mxODBC will then convert the Unicode input data to UTF-8, store this in the
database and convert it back to Unicode during fetch operations. Note however
that UTF-8 encoded data usually takes up more room in the database than the
Unicode equivalent, so may experience data truncations which then cause the
decoding process to fail.
Another possibility is to use the MIXED_STRINGFORMAT which allows mxODBC to
interface to the database using the best suitable data type. For e.g. MS SQL Server
this usually means passing all string data as Unicode data to and from the
database. In MIXED_STRINGFORMAT mode mxODBC will return string data in the
default format of the database driver, leaving the conversion to the Python
program.
Note:
mxODBC only supports Unicode objects at the data storage interface level
meaning that it can insert and fetch Unicode data from a database provided that
the database can handle Unicode and that the used mxODBC subpackage was
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8. Data Types supported by mxODBC
configured with Unicode support. It also supports SQL commands given as
Unicode data. However, it does not handle Unicode at the schema interface level,
that is e.g. cursor.description will not return Unicode objects for the column
names. This may be added to a future version of mxODBC, but is currently not
supported by the package.
8.9 Additional Comments
The above SQL types are provided by each subpackage in form of SQL type code
integers through attributes of the singleton object SQL, e.g. SQL.CHAR is the type
integer for a CHAR column.
You can decode the type_code value in the cursor.description tuple by
comparing it to one of those constants. A reverse mapping of integer codes to
code names is provided by the dictionary sqltype which is provided by all
subpackages.
Note:
You may run into problems when using the tuple versions for
date/time/timestamp arguments. This is because some databases (notably MySQL)
want these arguments to be passed as strings. mxODBC does the conversion
internally but tuples turn out as: '(1998,4,6)' which it will refuse to accept. The
solution: use DateTime[Delta] instances instead. These convert themselves to ISO
dates/times which most databases (including MySQL) do understand.
To check the ODBC driver/manager capabilities and support for the above column
types, run the included mx/ODBC/Misc/test.pyc test script.
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mxODBC - Python ODBC Database Interface
9.
DB-API Type Objects and Constructors
Since many database have problems recognizing some column's or parameter's
type beforehand (e.g. for LONGs and date/time values), the Python DB-API
provides a set of standard constructors to create objects that can hold special
values. When passed to the cursor methods, the module can then detect the
proper type of the input parameter and bind it accordingly.
In mxODBC these constructors are not needed: it uses the objects defined in
mxDateTime for date/time values and is able to pass strings, buffer and
memoryview objects to LONG and normal CHAR columns without problems. You
only need them to write code that is portable across database interfaces.
A Cursor Object's description attribute returns information about each of the
result columns of a query. The type_code compares equal to one of Type Objects
defined below. Type Objects may be equal to more than one type code (e.g.
DATETIME could be equal to the type codes for date, time and timestamp
columns).
mxODBC returns more detailed description about type codes in the description
attribute. See the section 8 Supported Data Types for details. The type objects are
only defined for compatibility with the DB API standard and other database
interfaces.
Each subpackage exports the following constructors and singletons:
Date(year,month,day)
This function constructs an mxDateTime DateTime object holding the given
date value. The time is set to 0:00:00.
Time(hour,minute,second)
This function constructs an mxDateTime DateTimeDelta object holding the
given time value.
Timestamp(year,month,day,hour,minute,second)
This function constructs an mxDateTime DateTime object holding a time
stamp value.
DateFromTicks(ticks)
This function constructs an mxDateTime DateTime object holding the date
value from the given ticks value (number of seconds since the epoch; see the
documentation of the standard Python time module for details).
Usage of Unix ticks (number of seconds since the Epoch) for date/time
database interfacing can cause troubles because of the limited date range they
cover.
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9. DB-API Type Objects and Constructors
TimeFromTicks(ticks)
This function constructs an mxDateTime DateTimeDelta object holding a time
value from the given ticks value (number of seconds since the epoch; see the
documentation of the standard Python time module for details).
TimestampFromTicks(ticks)
This function constructs an mxDateTime DateTime object holding a time
stamp value from the given ticks value (number of seconds since the epoch;
see the documentation of the standard Python time module for details).
Usage of Unix ticks (number of seconds since the Epoch) for date/time
database interfacing can cause troubles because of the limited date range they
cover.
Binary(string)
This function constructs a buffer object pointing to the (long) string value. On
Python versions without buffer objects (prior to 1.5.2), the string is taken as is.
STRING
This type object is used to describe columns in a database that are stringbased: SQL.CHAR, SQL.BINARY.
BINARY
This type object is used to describe (long) binary columns in a database:
SQL.LONGVARCHAR, SQL.LONGVARBINARY (e.g. LONG, RAW, BLOB, TEXT).
NUMBER
This type object is used to describe numeric columns in a database:
SQL.DECIMAL, SQL.NUMERIC, SQL.DOUBLE, SQL.FLOAT, SQL.REAL,
SQL.DOUBLE, SQL.INTEGER, SQL.TINYINT, SQL.SMALLINT, SQL.BIT,
SQL.BIGINT.
DATETIME
This type object is used to describe date/time columns in a database:
SQL.DATE, SQL.TIME, SQL.TIMESTAMP.
ROWID
This type object is used to describe the "Row ID" column in a database.
mxODBC does not support this special column type and thus no type code is
equal to this type object.
SQL NULL values are represented by the Python None singleton on input and
output.
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10. mxODBC Exceptions and Error
Handling
The mxODBC package and all its subpackages use the DB API 2.0 exceptions
layout. All exceptions are defined in the submodule mx.ODBC.Error but also
imported into the top-level package module mx.ODBC as well as all sub-packages.
Note that all sub-packages use the same exception classes, so writing crossdatabase applications is simplified this way.
The exception values are either
•
a single string, or
•
a tuple having the format (sqlstate, sqltype, errortext, lineno)
SQL state (sqlstate) and type (sqltype) are defined by the ODBC standard and
may be extended by the specific ODBC driver handling the connection. Please see
the ODBC driver manual for details. lineno refers to the line number in the
mxODBC.c file to ease debugging the package.
Note on the mx.ODBC.Error Module
If you want to import the exception classes from the mx.ODBC.Error submodule,
you have to use the from…import form:
from mx.ODBC.Error import ProgrammingError
The reason is that the Error base class is imported into the top-level mx.ODBC
package when loading it, shadowing the module of the same name. With the
above form, Python will lookup mx.ODBC.Error in the module dictionary instead
of the mx.ODBC package and find the module instead of the mx.ODBC.Error
exception class.
10.1 Exception Classes
These exceptions are defined in the modules scope and also available as attributes
of the connection objects to easy writing applications using different mxODBC
sub-packages.
Error
Baseclass for all other exceptions related to database or interface errors.
You can use this class to catch all errors related to database or interface
failures. error is just an alias to Error needed for DB-API 1.0 compatibility.
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Error is a subclass of exceptions.StandardError.
Warning
Exception raised for important warnings like data truncations while inserting,
etc.
Warning is a subclass of exceptions.StandardError. This may change in a
future release to some other baseclass indicating warnings.
InterfaceError
Exception raised for errors that are related to the interface rather than the
database itself.
DatabaseError
Exception raised for errors that are related to the database.
DataError
Exception raised for errors that are due to problems with the processed data
like division by zero, numeric out of range, etc.
OperationalError
Exception raised for errors that are related to the database's operation and not
necessarily under the control of the programmer, e.g. an unexpected
disconnect occurs, the data source name is not found, a transaction could not
be processed, a memory allocation error occurred during processing, etc.
IntegrityError
Exception raised when the relational integrity of the database is affected, e.g. a
foreign key check fails.
InternalError
Exception raised when the database encounters an internal error, e.g. the
cursor is not valid anymore, the transaction is out of sync, etc.
ProgrammingError
Exception raised for programming errors, e.g. table not found or already exists,
syntax error in the SQL statement, wrong number of parameters specified,
performing operations on closed connections etc.
NotSupportedError
Exception raised in case a method or database API was used which is not
supported by the database, e.g. requesting a .rollback() on a connection that
does not support transaction or has transactions turned off.
This is the exception inheritance layout:
StandardError
|__Warning
|__Error
|__InterfaceError
|__DatabaseError
|__DataError
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|__OperationalError
|__IntegrityError
|__InternalError
|__ProgrammingError
|__NotSupportedError
10.2 SQL Error Mappings
If you are interested in the exact mapping of SQL error codes to exception classes,
have a look at the errorclass dictionary which is defined at subpackage scope,
e.g. mx.ODBC.Windows.errorclass.
errorclass
The errorclass dictionary maps SQLSTATE strings to error classes and is
used by mxODBC to determine which Python exception class to use for
reporting the database error within the Python application.
If you need to specify your own SQLSTATE to exception mappings, you can
assign to the errorclass dictionary.
10.3 Exception Value Format
All ODBC driver generated exceptions use a standard exception value layout.
The error value will always be a tuple (sqlstate, sqlcode, messagetext,
lineno) with the following meanings:
sqlstate
SQL state as string; these values are defined in the ODBC Documentation and
by the ODBC driver/manager.
sqlcode
Numeric SQL error code as integer; these values are defined in the ODBC
Documentation and by the ODBC driver/manager.
messagetext
Message text as string explaining the error. These strings usually have the
format "[Vendor][Driver][Database] Message Text".
lineno
Line number in the mxODBC source code which generated the message. This
is very useful for support purposes.
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10.4 Error Handlers
If you want to provide your own error handler, e.g. to mask database warnings or
debug connection setups, you can do so by assigning to the .errorhandler
attribute of connections and cursors or passing a callback function to the
connection constructors at connection creation time using the errorhandler
keyword argument.
Error handlers are inherited from connections to cursors, so it normally suffices to
set an error handler on the connection object to have it take affect for all
subsequently created cursors.
Cursors created prior to setting the error handler on the connection will not see
or use the new error handler.
Error handler signature
An error handler has to be a callable object taking the arguments (connection,
cursor, errorclass, errorvalue) where connection is a reference to the
connection (or None in case the connection has not yet been setup), cursor a
reference to the cursor (or None in case the error does not apply to a cursor or the
cursor has not yet been setup), errorclass is an error class which to instantiate
using errorvalue as construction argument.
Return values are currently not defined.
This a typical error handler function:
from mx.ODBC.Windows import Warning
# Error handler function
def myerrorhandler(connection, cursor, errorclass, errorvalue):
if issubclass(errorclass, Warning):
print ('Ignoring warning %s' % errorvalue)
else:
raise errorclass(*errorvalue)
Default error handler
The default mxODBC error handler will append the tuple (errorclass,
errorvalue) to the .messages list of the cursor or connection (if cursor is None)
and then raise the exception by instantiating errorclass with errorvalue.
Error processing
Note that only database and ODBC driver/manager related errors are processed
through the error handlers. Other errors such as mxODBC internal or
AttributeErrors are not processed by these handlers.
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10.4.2 Examples
Here's an example of an error handler that allows to flexibly ignore warnings or
only record messages.
# Error handler configuration
record_messages_only = 0
ignore_warnings = 0
# Error handler function
def myerrorhandler(connection, cursor, errorclass, errorvalue):
""" Default mxODBC error handler.
The default error handler reports all errors and warnings
using exceptions and also records these in
connection.messages as list of tuples (errorclass,
errorvalue).
"""
# Append to messages list
if cursor is not None:
cursor.messages.append((errorclass, errorvalue))
elif connection is not None:
connection.messages.append((errorclass, errorvalue))
# Ignore warnings
if (record_messages_only or
(ignore_warnings and
issubclass(errorclass, mx.ODBC.Error.Warning))):
return
# Raise the exception
raise errorclass, errorvalue
# Installation of the error handler on the connection
connection.errorhandler = myerrorhandler
In case the connection or one of the cursors created from it cause an error,
mxODBC will call the myerrorhandler() function to let it decide what to do
about the error situation.
Possible error resolutions are to raise an exception, log the error in some way,
ignore it or to apply a work-around.
Typical use-cases for error handlers are situations where warnings need to be
masked or an application requires an on-demand reconnect.
If you need to catch errors or warnings at connection time, you can use the
optional keyword argument errorhandler to have the error handler installed
early enough to be able to deal with such errors or warnings:
connection = mx.ODBC.Windows.DriverConnect('DSN=test',
errorhandler=myerrorhandler)
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10.5 Warning Classes
The Python DB-API 2.0 does not define a warning class hierarchy. At the time the
DB-API 2.0 was defined, the Python warning was not yet in existence. It is
expected that a future revision will add such a hierarchy.
Until then mxODBC uses it's own warning hierarchy which currently just has one
warning class:
DatabaseWarning
Warning issued for important warnings like data truncations while inserting,
etc., if the mxODBC default error handler is active and the
connection.warningformat or cursor.warningformat as set to
WARN_WARNINGFORMAT.
DatabaseWarning is a subclass of the standard Python Warning base class.
This may change in a future release if the DB-API is changed to provide a
warning class hierarchy as well.
10.6 Database Warnings
The default behavior of mxODBC is to raise all errors, including Warnings, which
many ODBC drivers issue for truncations, loss of precision in data conversions,
etc.
This may not always be desirable. For this reason, mxODBC provides a way to
handle database warnings in different ways.
10.6.1 Default Error Handler
The mxODBC default error handler can be adjusted to handle database warnings
in three different ways:
1. raise a Warning exception for all database warnings (this is the default),
2. issue a Python Warning for all database warnings (compatible with the
warning framework in Python),
3. ignore all database warnings.
Adjusting
mxODBC
behavior
is
possible
using
the
connection.warningformat or cursor.warningformat attributes. As always
for these format settings, the cursors inherit the setting from the connection they
were created from using the value set on the connection at creation time.
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These mx.ODBC constants are available for the .warningformat attribute:
ERROR_WARNINGFORMAT (default)
Report warnings in the usual DB-API 2.0 way and raise a Warning
exception.
WARN_WARNINGFORMAT
Instead of raising a Warning exception, issue a
mx.ODBC.DatabaseWarning which is a Python Warning subclass and can
be filtered using the standard Python warnings module mechanisms.
IGNORE_WARNINGFORMAT
Silently ignore the database warning.
The warning will still be added to the .message attribute, but no further
action is taken.
10.6.2 Custom Warning Error Handler
If you need a more fine-grained approach to dealing with warnings, you can also
setup a special error handler which then overrides the behavior of the default
handler.
If
you want to mask only certain Warnings, simply set a
connection.errorhandler like the one below to disable raising exceptions for
database warnings:
# Error handler function
def myerrorhandler(connection, cursor, errorclass, errorvalue):
""" This error handler ignores (but logs) 01000 warnings issued
by the database.
"""
# Append to messages list
if cursor is not None:
cursor.messages.append((errorclass, errorvalue))
elif connection is not None:
connection.messages.append((errorclass, errorvalue))
# Ignore 01000 database warning
if (issubclass(errorclass, connection.Warning) and
errorvalue[0] == '01000'):
return
# Raise all other database errors and warnings
raise errorclass, errorvalue
# Installation of the error handler
connection.errorhandler = myerrorhandler
If you need to catch errors or warnings at connection time, you can use the
optional keyword argument errorhandler to have the error handler installed
early enough to be able to deal with such errors or warnings:
connection = mx.ODBC.Windows.DriverConnect('DSN=test',
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errorhandler=myerrorhandler)
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11. mxODBC Functions
mxODBC includes a few helper functions and generic APIs which aid in everyday
ODBC database programming or allow introspection at the ODBC manager level.
The next sections describe these functions in detail.
11.1 Subpackage Functions
For some subpackages, mxODBC also defines a few helpers which you can use to
query additional information from the ODBC driver or manager. These are
available through the subpackage, e.g. as mx.ODBC.Windows.DataSources().
DataSources()
This helper function is only available for ODBC managers and some ODBC
drivers which have internal ODBC manager support, e.g. IBM's DB2 ODBC
driver, and allows you to query the available data sources.
It returns a dictionary mapping data source names to descriptions
Notes:
Older versions of unixODBC had a bug in some versions which makes the
manager only return information about data sources on the first call to this
function. Older versions of iODBC truncated the descriptions to two
characters.
getenvattr(option)
Returns the given ODBC environment option. This method interfaces directly
to the ODBC function SQLGetEnvAttr().
option must be an integer. Suitable option values are available through the
SQL singleton object.
The method returns the data as 32-bit integer. It is up to the caller to decode
the integer using the SQL defines.
This function is only available for ODBC 3.x compatible managers and ODBC
drivers.
setenvattr(option, value)
This function lets you set ODBC environment attributes which are encoded as
32-bit integers.
This method interfaces directly to the ODBC function SQLSetEnvAttr().
option must be an integer. Suitable option values are available through the
SQL singleton object.
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11. mxODBC Functions
This function is only available for ODBC 3.x compatible managers and ODBC
drivers.
Note:
The function allows setting environment attributes which mxODBC itself uses
to define the way it interfaces to the database. Changing these attributes can
result in unwanted behavior or even segmentation faults. USE AT YOUR OWN
RISK !
statistics()
Returns a tuple (connections, cursors) stating the number currently open
connections and cursors for this subpackage.
Note that broken connections or cursors are not correctly counted.
11.2 mx.ODBC Functions
In addition to subpackage specific helpers, mxODBC also provides a few
additional functions available through the top-level mx.ODBC package. These are:
format_resultset(cursor, headers=None, colsep=' | ', headersep='', stringify=repr)
Fetch the result set from cursor and format it into a list of strings (one for each
row):
-header-headersep-row1-row2...
headers may be given as list of strings. It defaults to the header names from
cursor.description. The function will add numbered columns as
appropriate if it finds more columns than given in headers.
Columns are separated by colsep; the header is separated from the result set
by a line of headersep characters.
The function calls stringify to format the value data returned by the driver into
a string. It defaults to repr().
print_resultset(cursor, headers=None)
Pretty-prints the current result set available through cursor.
See format_resultset() for details on formatting.
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12. mxODBC Globals and Constants
12.1 Subpackage Globals and Constants
Each mxODBC subpackage exports the following globals and constants:
BIND_USING_SQLTYPE, BIND_USING_PYTHONTYPE
Integer values returned by or used for setting connection.bindmethod and
cursor.bindmethod.
SQL type binding means that the interface queries the database to find out
which conversion to apply and which input type to expect, while Python type
binding looks at the parameters you pass to the methods to find out the type
information and then lets the database apply any conversions.
The bind method default is database dependent, but can also be adjusted on a
per connection or cursor basis.
CHAR, VARCHAR, LONGVARCHAR, BINARY, VARBINARY, LONGVARBINARY,
TINYINT, SMALLINT, INTEGER, BIGINT, DECIMAL, NUMERIC, BIT,
REAL, FLOAT, DOUBLE, DATE, TIME, TIMESTAMP [, CLOB, BLOB,
TYPE_DATE, TYPE_TIME, TYPE_TIMESTAMP, UNICODE,
UNICODE_LONGVARCHAR, UNICODE_VARCHAR, WCHAR, WVARCHAR,
WLONGVARCHAR]
ODBC 2.0 type code integers for the various natively supported SQL types.
These map to integers as returned in the type field of cursor.description.
They are also available through the SQL singleton, e.g. SQL.CHAR. The
dictionary sqltype provides the inverse mapping.
The codes mentioned in square brackets are optional and only available if the
ODBC driver/manager supports a later ODBC version than 2.5.
Note that mxODBC has support for unknown SQL types: it returns these types
converted to strings. The conversion is done by the ODBC driver and may be
driver dependent.
DATETIME_DATETIMEFORMAT, PYDATETIME_DATETIMEFORMAT,
TIMEVALUE_DATETIMEFORMAT, TUPLE_DATETIMEFORMAT,
STRING_DATETIMEFORMAT
Integer values which are used by connection.datetimeformat and
cursor.datetimeformat.
mxODBC can handle different output formats for date/time values on a per
connection and per cursor basis. See the documentation of the two attributes
for more information.
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12. mxODBC Globals and Constants
EIGHTBIT_STRINGFORMAT, MIXED_STRINGFORMAT, UNICODE_STRINGFORMAT,
NATIVE_UNICODE_STRINGFORMAT
Integer values which are used by connection.stringformat and
cursor.stringformat.
mxODBC can handle different string conversion methods on a per connection
and per cursor basis. See the documentation of the two attributes for more
information.
ERROR_WARNINGFORMAT, WARN_WARNINGFORMAT, IGNORE_WARNINGFORMAT
Integer values which are used by connection.warningformat and
cursor.warningformat.
mxODBC can use different ways of reporting database warnings on a per
connection and per cursor basis. See the documentation of the two attributes
for more information.
FLOAT_DECIMALFORMAT, DECIMAL_DECIMALFORMAT
Integer values which are used by connection.decimalformat and
cursor.decimalformat.
mxODBC can handle different output formats for numeric and decimal
database column types on a per connection and per cursor basis. See the
documentation of the two attributes for more information.
HAVE_UNICODE_SUPPORT
Integer flag which is either 0 or 1 depending on whether mxODBC was
compiled with Unicode support or not. Unicode support is always available in
mxODBC 3.1 and later so this flag is always set to 1.
RowFactory
A reference to the mx.ODBC.Misc.RowFactory module which provides access
to a set of standard row factory functions which can be used for
cursor.rowfactory. See section 13 mx.ODBC.Misc.RowFactory Module for
details on the available API and section 5.9 Custom Cursor Row Objects and
Row Factory Functions for usage examples.
SQL
Singleton object which defines nearly all values available in the ODBC 3.5
header files. The "SQL_" part of the ODBC symbols is omitted, e.g.
SQL_AUTOCOMMIT is available as SQL.AUTOCOMMIT.
apilevel
String constant stating the supported DB API level. This is set to '2.0', since
mxODBC supports the features of the DB API 2.0 standard. Many DB API 1.0
features are still supported too for backward compatibility.
errorclass
Writeable dictionary mapping SQL error code strings (ODBC's SQLSTATE) to
exception objects used by the module.
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If you need to specify your own SQLSTATE to exception class mappings, you
can assign to this dictionary. Changes will become visible immediately.
license
String with the license information for the installed mxODBC license.
paramstyle
String constant stating the type of parameter marker formatting expected by
the interface. This is set to 'qmark', since the ODBC default is to use '?' to
be used as positional placeholder for variables in an SQL statement.
Parameters are bound to these placeholders in the order they appear in the
SQL statement, e.g. the first parameter is bound to the first question mark, the
second to the second and so on.
Note that the parameter style can be changes on a per-connection or percursor basis using the connection.paramstyle and cursor.paramstyle
read/write attributes.
sqltype
Dictionary mapping SQL type codes (these are returned in the type field of
cursor.description) to type strings. All natively supported SQL type codes
are included in this dictionary. The contents may vary depending on whether
the ODBC driver/manager defines these types or not.
threadsafety
Integer constant stating the level of thread safety the interface supports. It is
always set to 1, meaning that each thread must use its own connection.
Some ODBC drivers also support sharing connections and even cursors
between threads. Please have a look at your ODBC driver documentation for
details.
12.2 mx.ODBC Globals and Constants
At the top-level, the mx.ODBC package defines these globals and constants:
Error, Warning, InterfaceError, DatabaseError, DataError,
OperationalError, IntegrityError, InternalError,
ProgrammingError, NotSupportedError
Exception objects used by the mxODBC subpackages. See section 10.
mxODBC Exceptions and Error Handling for details.
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13. mx.ODBC.Misc.RowFactory Module
13. mx.ODBC.Misc.RowFactory Module
This module defines a set of factory functions which can be used together with
cursor.rowfactory to customize the row objects returned by the cursor.fetch*()
methods in mxODBC.
This section describes the available module APIs. Please see section 5.9 Custom
Cursor Row Objects and Row Factory Functions for details on how to use these
row factory functions.
Classes
Row
Common base class of all Row classes built by the factory functions in this
module.
This is useful to have in order to easily type check Row classes via
isinstance().
Base class(es): object
Functions
TupleRowFactory(cursor)
This is a factory which is a subtype of the Python tuple type and provides a
standard tuple index based access to the row column values, as well as an
attribute based one which is derived from the lower-cased column names
found in cursor.description.
The row objects are immutable, just like standard tuples, but you can also slice
them or index them as usual.
cursor has to be an mxODBC Cursor object.
ListRowFactory(cursor)
This factory uses a subtype of the Python list type and also provides a
sequence index based access, as well as a named attribute access, just like the
TupleRowFactory.
Unlike for the TupleRowFactory, the row objects created by the
ListRowFactory are mutable lists, so you can assign to the indexes as well as
the attributes.
cursor has to be an mxODBC Cursor object.
NamespaceRowFactory(cursor)
This row factory function creates mx.Misc.Namespace.Namespace objects as
row objects. These provide a more complex namespace oriented API.
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In addition to the sequence protocol, they also allow mapping access as well
as named attribute access based on the lower-cased column names read from
cursor.description.
Rows created by this factory are mutable.
cursor has to be an mxODBC Cursor object.
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14. mx.ODBC Driver/Manager Packages
This section includes specific notes for preconfigured subpackages and setups.
14.1 Driver/Manager Subpackage Notes
The following sections provide hints that apply to all mx.ODBC subpackages.
Please read carefully.
14.1.1 Windows Platform Notes
You should always use the mx.ODBC.Windows subpackage and access the
databases through the MS ODBC Driver Manager. The other packages provide
Unix based interfaces to the databases.
14.1.2 Unix Platform Notes
Even though there are many subpackages for specific databases which then
sometimes provide more functionality for that particular database, we would like
to encourage the use of ODBC managers such as the iODBC, unixODBC or
DataDirect ODBC managers, since these provide the best flexibility in terms of
database setup and configuration.
Using ODBC managers also enables you to easily switch from local databases to
cross-network databases by adding additional tiers in-between.
The binary distributions of mxODBC for Unix platforms usually only contain the
mx.ODBC.unixODBC and mx.ODBC.iODBC subpackages. For some platforms, the
mx.ODBC.DataDirect subpackage is also included, e.g. Linux x86 and x86_64.
14.2 mx.ODBC.Manager -- Generic ODBC
Driver Manager
In order to make writing cross-platform application easier with mxODBC, the
package provides a meta-subpackage to access the default platform ODBC driver
manager.
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Windows Platforms
mxODBC selects the subpackage by trying to import the available ODBC driver
subpackages in the following order:
1. mx.ODBC.Windows
No other subpackage is currently tried, since the Windows ODBC manager is
always present in all recent Windows versions.
Unix Platforms
mxODBC selects the subpackage by trying to import the available ODBC driver
subpackages in the following order:
1. mx.ODBC.unixODBC
2. mx.ODBC.iODBC
3. mx.ODBC.DataDirect
The mx.ODBC.Manager package then behaves just like the driver manager chosen
by this process.
Please note: The order was changed in mxODBC 3.2. Previous mxODBC
versions preferred iODBC over unixODBC. Since unixODBC is widely
supported nowadays and provides better Unicode support, selecting unixODBC
over iODBC when both are present provides a better user experience.
14.3 mx.ODBC.Windows -- Windows ODBC
Driver Manager
Tested with Windows XP, Vista, 7.
mxODBC links against the Windows ODBC driver manager on Windows. This is
the only mxODBC interface subpackage available on Windows.
14.3.1 Connecting to a Database
Always use the DriverConnect() API to connect to the data source if you need
to pass in extra configuration information such as names of log files, etc.
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14.3.2 Supported Datatypes
The subpackage defaults to SQL type binding mode (see the Datatypes section for
details), but reverts to Python type binding in case the connection does not
support the ODBC SQLDescribeParam() API. MS Access is one candidate for
which this API is not useable.
14.3.3 File Data Sources
If you want to connect to a file data source (without having to configure it using
the ODBC manager), you can do so by using the FILEDSN= parameter instead of
the DSN= parameter:
DriverConnect('FILEDSN=test.dsn;UID=test;PWD=test')
This is sometimes useful when you want to dynamically setup a data source, e.g. a
MS Access database.
For more information about the FILEDSN-keyword and the other Windows ODBC
manager features, see the Microsoft SQLDriverConnect() documentation.
Also note that ODBC drivers working on single files, e.g. the MS Excel file driver,
usually do not support transactions. mxODBC will not clear auto-commit for
these drivers (it may sometimes still be necessary to set the clear_auto_commit
flag in the connect constructors to 0).
14.4 mx.ODBC.iODBC -- iODBC Driver
Manager
Tested with iODBC 3.52.7.
iODBC is an Open Source ODBC manager for Unix maintained by OpenLink. It
compiles against mxODBC without problems and is the preferred way of talking
to an ODBC data source from Unix using mxODBC.
14.4.1 Notes
General Recommendations
•
175
Please always use the DriverConnect() API to connect to the data
source if you need to pass in extra configuration information such as
names of log files, etc.
mxODBC - Python ODBC Database Interface
•
When interfacing to MySQL using the MySQL ODBC driver, we have
observed problems with using Unicode statements passed to
cursor.execute() when using iODBC 3.52.5. These problems appear
to be related to iODBC. As work-around, you can use unixODBC, which
works fine with Unicode statements.
•
You may experience problems when trying to connect to MySQL via
MyODBC hooked to iODBC in case you are using the binary RPMs
available. For some reason, the MyODBC driver does not reference the
MySQL shared libraries it needs to connect to the MySQL server and
there's no way to tell iODBC to load two shared libraries. Here's a trick
which will allow you to create an import lib which solves the problem on
Linux:
rm -f /usr/local/lib/libmyodbc.so
ld -shared --whole-archive \
/usr/local/lib/libmyodbc-2.50.34.so \
/usr/lib/libmysqlclient.so.10 \
-o /usr/local/lib/libmyodbc.so
ldconfig
64-bit Platforms
•
You may run into problems with iODBC since it uses 64-bit SQL Unicode
types. Most ODBC drivers follow the Windows standard of using 32-bit
Unicode types. Support for Unicode with iODBC is therefore limited.
•
You may also run into problems with ODBC drivers compiled against
unixODBC. While iODBC follows the ODBC standard of using 64-bit SQL
length types, unixODBC has only recently (starting with version 2.2.13)
switched to these longer types. As a result ODBC drivers compiled
against older versions of unixODBC will not work reliably with iODBC.
•
Commercial ODBC drivers for Unix are often compiled using 64-bit SQL
length types and 32-bit Unicode types. iODBC uses 64-bit types for both.
14.5 mx.ODBC.unixODBC -- unixODBC Driver
Manager
Tested with unixODBC 2.3.2.
unixODBC is an alternative Open Source ODBC manager for originally designed
for Linux and later extended to other Unixes maintained by EasySoft. It compiles
against mxODBC without problems.
Many open-source ODBC drivers are compiled against this driver manager per
default, so it may provide better support for those drivers than iODBC.
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14. mx.ODBC Driver/Manager Packages
14.5.1 Notes
General Recommendations
•
Please always use the DriverConnect() API to connect to the data
source if you need to pass in extra configuration information such as
names of log files, etc.
•
Between unixODBC 2.3.0 and unixODBC 2.3.1, the unixODBC project
switched the library name of the ODBC manager library from
libodbc.so.1 to libodbc.so.2 to signal the change in their ABI on 64-bit
platforms (see below). This renaming affects both 32- and 64-bit versions
of unixODBC.
Since eGenix.com compiles against unixODBC 2.3.1 (or later), mxODBC
will look for a libodbc.so.2 library file and this may not be available if your
system comes with unixODBC 2.3.0. If you have unixODBC 2.3.0
installed you can safely create a symlink from the libodbc.so.1 library to
the new name libodbc.so.2 to overcome this problem. Please see the
unixODBC website for instructions.
Debugging ODBC Configurations
A common error you can see when trying to configure a database connection or
ODBC driver installation is mx.ODBC.Error.OperationalError: ('08003',
0, '[unixODBC][Driver Manager]Connnection does not exist', 11593).
Unfortunately, this doesn't tell you much about the true cause of the problem only that the connection could not be established.
The reason is that unixODBC does not report the true cause of the problem as
error, but instead only issues a warning and these warnings are ignored by
mxODBC during connect, since they would prevent successful connects with
some popular drivers that regularly issues context switch warnings during
connects.
Finding the cause using an ODBC trace
If you run an ODBC trace and look at the log file, you'd see that unixODBC
reports a warning such as this during the connection attempt:
[01000][unixODBC][Driver
Manager]Can't
'/usr/…/libodbcdriver.so' : file not found]
open
lib
For details on how to setup an ODBC trace, please have a look at section 19.1
ODBC Call Level Tracing.
Finding the cause using a custom error handler
Alternatively, you can use a custom error handler to debug such situations during
connects.
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Example:
def debug_errorhandler(connection, cursor, errorclass, errorvalue):
sys.stderr.write('debug_errorhandler: %s: %r\n' %
(errorclass, errorvalue))
db = DriverConnect('DSN=drivernotfound;UID=sa;PWD=test',
errorhandler=debug_errorhandler)
The error handler will be called for all messages coming from the ODBC driver
and manager, including warnings which are then ignored by mxODBC, and print
these to stderr for review.
Depending on how the ODBC driver is written, the above may result in lengthy
output or even cause more severe problems, because the error handler does not
raise an exception which would cause the connect processing to stop. mxODBC
will continue setting up the connection as if it were existing and this can result in
segfaults with some drivers.
A safer variant looks like this:
errors = 0
def debug_errorhandler(connection, cursor, errorclass, errorvalue):
global errors
errors += 1
sys.stderr.write('debug_errorhandler: %s: %r\n' %
(errorclass, errorvalue))
if errors > 5:
raise errorclass(*errorvalue)
64-bit Platforms
•
On 64-bit platforms you may run into problems with unixODBC since it
uses 32-bit SQL length types for versions prior to 2.2.13. Some ODBC
drivers on Unix instead use 64-bit SQL length values and will therefore
not return correct results when used with unixODBC.
The binary version eGenix.com ships was compiled against unixODBC
2.3.1 (or later) and expects 64-bit SQL length types. If you need a version
for unixODBC 2.2.12 or earlier, please either use our older mxODBC 3.0
release or write to support@egenix.com for help.
178
•
Commercial ODBC drivers for Unix are often compiled using 64-bit SQL
length types and 32-bit Unicode types. unixODBC uses the same types
starting with version 2.3.
•
You may run into problems with ODBC drivers compiled against iODBC.
While unixODBC follows the ODBC standard of using 32-bit Unicode
types, iODBC defaults to using the Unix 64-bit standard. As a result,
ODBC drivers compiled against iODBC will not work reliably with
Unicode data when used with unixODBC.
14. mx.ODBC Driver/Manager Packages
Threading
•
In unixODBC versions 2.3.0 and below, the ODBC manager used a little
known odbc.ini setting called "Threading" which determined the default
thread level protection of the ODBC data source.
•
The default used to be lock level 3 (the ODBC driver does not allow
multiple threads to use it and everything is serialized). This could result in
the application using mxODBC and unixODBC to hang during long
running queries. Fixing this was easy, but not well documented in
unixODBC. Setting the thread lock level to 0 (driver is fully thread safe)
allowed the application to run other queries in parallel, e.g.
[PostgreSQL]
Description
Driver
Setup
Threading
=
=
=
=
PostgreSQL driver for Linux & Win32
/usr/local/lib/libodbcpsql.so
/usr/local/lib/libodbcpsqlS.so
0
•
Starting with unixODBC 2.3.1, the default thread lock level now is 0, so
the above is no longer necessary.
•
These are the available thread lock levels (from unixODBC's __handle.c):
Level 0 - Only the DM internal structures are protected
the driver is assumed to take care of it's self
Level 1 - The driver is protected
each statement will be protected,
level for connect functions, note
equal to statements when it comes
down to the statement level
and the same for the connect
that descriptors are considered
to thread protection.
Level 2 - The driver is protected at the connection level. only
one thread can be in a particular driver at one time
Level 3 - The driver is protected at the env level, only one thing
at a time.
By default the driver open connections with a lock level of 3,
this can be changed by adding the line
Threading = N
to the driver entry in odbcinst.ini, where N is the locking level
(0-3)
14.6 mx.ODBC.DataDirect -- DataDirect ODBC
Manager
Tested with DataDirect ODBC Manager 7.1
DataDirect is a proprietary ODBC manager for Unix developed by DataDirect. It is
used by a number of ODBC drivers available for Unix platforms.
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mxODBC - Python ODBC Database Interface
eGenix.com provides binary subpackages for this ODBC driver manager only on
Linux x86 and x64 platforms. If you need the subpackage on other platforms as
well, please contact support@egenix.com for help.
14.6.1 Notes
General Recommendations
•
Please always use the DriverConnect() API to connect to the data
source if you need to pass in extra configuration information such as
names of log files, etc.
•
The DataDirect ODBC manager may not work correctly with Unicode
data,
even
though
the
driver
may
support
Unicode.
This is due to the fact that the DataDirect manager provides three
different options of encoding Unicode data: UTF-8, UTF-16 (ODBC
standard on Windows) and UTF-32. Most drivers assume UTF-16, but
don't necessarily implement the special call needed to configure the
DataDirect manager to assume this as well. The manager then defaults to
UTF-8 and this causes the Unicode transport to fail.
You can try to work around this by adding an entry
# Needed by the DataDirect ODBC manager,
# possible values: 1=UTF-16, 2=UTF-8
DriverUnicodeType = 1
to the driver section in your .odbc.ini file. See this page for details:
http://web.datadirect.com/resources/odbc/unicode/unix.html
•
In some cases we have observed segfaults when using ODBC drivers with
the DataDirect ODBC manager. These were related to the ~/.odbc.ini
being to large. Reducing the size of the ODBC configuration file resolved
the problem. It is not clear whether the segfaults was caused by the driver
or the driver manager or just a specific combination of both.
64-bit Platforms
•
There are no known issues regarding 64-bit platforms.
14.7 ODBC Driver Subpackages
In previous mxODBC releases, eGenix.com included a limited set of additional
subpackages with support for directly linking against specific ODBC drivers on
Unix platforms.
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14. mx.ODBC Driver/Manager Packages
Since these setups caused a lot of support requests due to configuration problems
and version mismatches between the driver versions we used to build the binary
mxODBC distribution and the ones deployed at customer sites, we have decided
to drop general support for these additional subpackages.
It is usually better to use one of the available ODBC driver manager packages to
configure and manage the data sources. These driver managers also provide a
further abstraction layer between ODBC applications and the drivers, removing
ODBC level compatibility issues, which makes the ODBC setup a lot less error
prone.
eGenix.com can still provide specific subpackages or build custom ones on
request, if there is a need. Please contact support@egenix.com for details.
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15. Hints & Links to other Resources
15.1 Running mxODBC from a CGI script
ODBC drivers and managers are usually compiled as a shared library. When
running CGI scripts most HTTP daemons (or web servers) don't pass through the
path for the dynamic loader (e.g. LD_LIBRARY_PATH) to the script, thus importing
the mxODBC C extension will fail with unresolved symbols because the loader
doesn't find the ODBC driver/manager's libs.
To have the loader find the path to those shared libs you can either wrap the
Python script with a shell script that sets the path according to your system
configuration or tell the HTTP daemon to set or pass these through (see the
daemon's documentation for information on how to do this; for Apache the
directives are named SetEnv and PassEnv).
On Windows, you also have to take into account that the ODBC data sources
defined in the ODBC manager are usually restricted to specific user accounts. You
can work around this by either setting up the ODBC data sources for the web
server service account or by configuring the data as system data sources.
15.2 Running mxODBC with mod_wsgi
Using mxODBC with mod_wsgi is generally possible. However, since the script
will run under a restricted user account, some care has to be taken to make the
setup work. Please see 15.1 Running mxODBC from a CGI script for more details
on getting ODBC drivers to work in such an environment.
mod_wsgi and Python 2.7
On Windows, there is also another issue to consider when running the
combination Apache, mod_wsgi and Python 2.7. Due to changes in Python 2.7,
manifests for the Visual C++ runtime environment, needed by Windows to find
the right DLL to load, are no longer added to Python extensions, since this caused
problems with loading them into Python processes (see Python Issue 4120).
Unfortunately, neither mod_wsgi nor Apache appear to include the required
manifests either. This causes an import error when trying to load mxODBC into a
mod_wsgi run process, since Windows cannot resolve the DLL references in
mxODBC without the manifest.
182
15. Hints & Links to other Resources
Since this affects not only mxODBC, but other Python C extensions as well, you
may want to use a work-around until either Apache or the mod_wsgi team solves
the problem:
Manifest work-around
Adding the VC++ manifests to the Apache process is explained in this posting.
You will also have to install the MS VC++ 2008 CRT SP1 redistributable package
on the server running Apache.
With those changes in place, mxODBC should load without problems.
15.3 Freezing mxODBC using py2exe
Thomas Heller has written a great tool which is based on distutils. The tool allows
you to freeze your application into a single standalone Windows application and is
called py2exe.
Note:
Freezing mxODBC together with an application and redistributing the resulting
executables requires that you have obtained developer licenses from
eGenix.com permitting you to redistribute mxODBC along with a product.
Please see the License section for more information.
When freezing mxODBC you may experience problems with py2exe related to
py2exe not finding the DLLs needed by mxODBC. In this case you have to help
py2exe to find the correct subpackage for Windows, ie. mx.ODBC.Windows and
mx.DateTime. This can be done by adding -i mx.ODBC.Windows,mx.DateTime
to the py2exe command line:
python py2exe -i mx.ODBC.Windows,mx.DateTime yourapp.py
After doing so, py2exe should have no problem finding the files mxODBC.pyd and
mxDateTime.pyd needed by mx.ODBC.Windows and mx.DateTime.
mxODBC also uses the md5 or hashlib module (depending on the Python version)
and the license module mxodbc_license internally. You will have to add them to
the above list, if you run into license verification problems when running the
py2exe compiled application.
15.4 More Sources of Information
There are several resources available online that should help you getting started
with ODBC. Here is a small list of links useful for further reading:
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mxODBC - Python ODBC Database Interface
Microsoft MDAC Site
Microsoft is constantly developing new forms of database access. For a close up
on what they have come up recently take a look at their ODBC site. Note that
they now call their ODBC SDK "Microsoft Data Access Components SDK"
(MDAC). It does not only focus on ODBC but also on OLE DB and ADO.
Note: If you are not happy about the size of the SDK download (over 31MB), you
can also grab the older 3.0 SDK which might still be available from a FTP server.
Look for "odbc3sdk.exe" using e.g. FTP Search.
Microsoft also supports a whole range of (desktop) ODBC drivers for various
databases and file formats. These are available under the name "ODBC Desktop
Database Drivers" (search the MS web-site for the exact URL) [wx1350.exe] and
also included in the more up-to-date "Microsoft Data Access Components"
(MDAC) archive [mdac_typ.exe].
Microsoft ODBC Portal
This portal page has a few interesting links into the Microsoft ODBC site. If you're
looking for the latest SQL Server or Oracle ODBC drivers this is the place to look
first.
ODBC Documentation
The ODBC documentation is included in the free MS MDAC SDK which you can
download from their ODBC site.
SQLSummit List of ODBC drivers
A collection of available ODBC driver packages. This should be the first place to
look in case you are searching for OBDC connectivity to your database.
184
16. Examples
16. Examples
Here is a very simple example of how to use mxODBC. More elaborate examples
of using Python Database API compatible database interfaces can be found in the
Database Topic Guide on http://www.python.org/. Andrew Kuchling's introduction
to the Python Database API is an especially good reading. There are also a few
books on using Python DB API compatible interfaces, some of them cover
mxODBC explicitly.
On Unix:
>>> import mx.ODBC.iODBC
>>> db = mx.ODBC.iODBC.DriverConnect('DSN=database;UID=user;PWD=passwd')
>>> c = db.cursor()
>>> c.execute('select count(*) from test')
>>> c.fetchone()
(305,)
>>> c.tables(None,None,None,None)
8
>>> mx.ODBC.print_resultset(c)
Column 1 | Column 2 | Column 3
| Column 4 | Column 5
--------------------------------------------------------------''
| ''
| 'test'
| 'TABLE' | 'MySQL table'
''
| ''
| 'test1'
| 'TABLE' | 'MySQL table'
''
| ''
| 'test4'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testblobs'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testblobs2'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testdate'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testdates'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testdatetime' | 'TABLE' | 'MySQL table'
>>> c.close()
>>> db.close()
>>>
On Windows:
>>> import mx.ODBC.Windows
>>> db =
mx.ODBC.Windows.DriverConnect('DSN=database;UID=user;PWD=passwd')
>>> c = db.cursor()
>>> c.execute('select count(*) from test')
>>> c.fetchone()
(305,)
>>> c.tables(None,None,None,None)
8
>>> mx.ODBC.print_resultset(c)
Column 1 | Column 2 | Column 3
| Column 4 | Column 5
--------------------------------------------------------------''
| ''
| 'test'
| 'TABLE' | 'MySQL table'
''
| ''
| 'test1'
| 'TABLE' | 'MySQL table'
''
| ''
| 'test4'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testblobs'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testblobs2'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testdate'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testdates'
| 'TABLE' | 'MySQL table'
''
| ''
| 'testdatetime' | 'TABLE' | 'MySQL table'
>>> c.close()
>>> db.close()
>>>
As you can see, mxODBC has the same interface on Unix and Windows which
makes it an ideal basis for writing cross-platform database applications.
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mxODBC - Python ODBC Database Interface
Note:
When connecting to a database with transaction support, you should explicitly
do a .rollback() or .commit() prior to closing the connection. In the
example this was omitted since the used MySQL database backend does not
support transactions and we were only reading from the database.
186
17. Testing the Database Connection
17. Testing the Database Connection
The package includes a test script that checks some of the database's features. As
side effect this also provides a good regression test for the mxODBC interface.
To start the test, simply run the script in mx/ODBC/Misc/test.pyc.
python mx/ODBC/Misc/test.pyc
The script will generate a few temporary tables (named mxODBC0001,
mxODBC0002, etc; no existing tables will be overwritten) and then test the interface
- database communication including many database related features such as data
types and support of various SQL dialects. The tables are automatically removed
after the tests have run through.
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mxODBC - Python ODBC Database Interface
18. mxODBC Package Structure
This is the Python package structure setup when installing mxODBC:
[ODBC]
Doc/
[Misc]
proc.py
test.pyc
[DataDirect]
dbi.py
dbtypes.py
[Manager]
[Windows]
dbi.py
dbtypes.py
[iODBC]
dbi.py
dbtypes.py
[unixODBC]
dbi.py
dbtypes.py
LazyModule.py
ODBC.py
Entries enclosed in brackets are packages (i.e. they are directories that include a
__init__.py file). Ones with slashes are just simple subdirectories that are not
accessible via import.
188
19. Support
19. Support
eGenix.com is provides commercial support for this package, including adapting it
to special needs for use in customer projects. If you are interested in receiving
information about this service please contact support@egenix.com for details.
This section describes methods which are useful to track down interoperability
problems with ODBC drivers. eGenix support may ask you to apply some of the
methods when working with you to resolve driver-related problems.
19.1 ODBC Call Level Tracing
In support some cases, eGenix may ask you to create an ODBC trace of a session
demonstrating a problem you may have with a particular ODBC driver. This
section explains how to enable ODBC call level tracing.
The ODBC trace log is a text file that ODBC managers (and some drivers) can
generate in order to help with debugging the interaction between the driver, the
driver manager and the application.
The method of how to enable tracing depends on the used ODBC driver manager.
19.1.1 Windows ODBC Manager
Open the Windows ODBC Data Source Administrator on Windows. This can be
found in the in the Control Panel as Administrative Tools and is called Data Sources
(ODBC). See the Windows ODBC documentation for details.
Go to the Tracing tab and select a trace output file under Log File Path and then
click on Start Tracing to enable ODBC tracing output.
After that is done, start you application or script using mxODBC and run the code
that is causing problems with the driver in question.
After you've run the application or script, open the ODBC administrator again and
click on the same button, now called Stop Tracing.
Finally, pick up the ODBC trace file from the location you've chosen and email it
to support@egenix.com.
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mxODBC - Python ODBC Database Interface
19.1.2 iODBC Driver Manager
To enable ODBC level tracing, open the /etc/odbc.ini or ~/.odbc.ini file and add
this section to it:
[ODBC]
Trace = 1
TraceFile = /tmp/odbc.log
If you already have such entries in the [ODBC] section, make sure that the settings
are correct and that Trace is set to 1.
After that is done, start you application or script using mxODBC and run the code
that is causing problems with the driver in question.
After you've run the application or script, open the odbc.ini file again and set Trace
to 0. This will disable ODBC call level tracing.
Finally, pick up the ODBC trace file from the location you've chosen
(/tmp/odbc.log in the example) and email it to support@egenix.com.
19.1.3 unixODBC Driver Manager
To enable ODBC level tracing, open the /etc/odbcinst.ini or ~/.odbcinst.ini file
and add this section to it:
[ODBC]
Trace = 1
TraceFile = /tmp/odbc.log
If you already have such entries in the [ODBC] section, make sure that the settings
are correct and that Trace is set to 1.
After that is done, start you application or script using mxODBC and run the code
that is causing problems with the driver in question.
After you've run the application or script, open the odbcinst.ini file again and set
Trace to 0. This will disable ODBC call level tracing.
Finally, pick up the ODBC trace file from the location you've chosen
(/tmp/odbc.log in the example) and email it to support@egenix.com.
19.1.4 DataDirect ODBC Driver Manager
Please use the same approach as for the iODBC Driver Manager.
190
19. Support
19.1.5 Mac OS X ODBC Driver Manager
Open the Mac OS X ODBC Administrator. This can be found under
Applications/Utilities.
Go to the Tracing tab and select a trace output file under Log File and then click
the checkbox Enable Tracing to enable ODBC tracing output. Click on Apply have
the change take effect.
After that is done, start you application or script using mxODBC and run the code
that is causing problems with the driver in question.
After you've run the application or script, open the ODBC administrator again and
disable the Enable Tracing checkbox.
Finally, pick up the ODBC trace file from the location you've chosen and email it
to support@egenix.com.
19.2 mxODBC Call Level Tracing
To simplify debugging the mxODBC package can generate debugging output in
several important places. The feature is only enabled if the mxODBC package was
compiled with debug support and output is only generated if Python is run in
debugging mode (use the Python interpreter flag -d):
python –d script.py
The resulting log file is named mxODBC.log. It will be created in the current
working directory; messages are always appended to the file so no trace is lost
until you explicitly erase the log file. If the log file can not be opened, the module
will use stderr for reporting.
To obtain a debugging version of mxODBC, please contact support@egenix.com
for help.
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20. History & Changes
Please visit the change log on the mxODBC product page for a list of changes in
the various product versions.
192
21. Copyright & License
21. Copyright & License
© 1997-2000, Copyright by IKDS Marc-André Lemburg; All Rights Reserved.
mailto: mal@lemburg.com
© 2000-2015, Copyright by eGenix.com Software GmbH, Langenfeld, Germany;
All Rights Reserved. mailto: info@egenix.com
This software is covered by the eGenix.com Commercial License Agreement,
which is included in the following section. The text of the license is also included
as file "LICENSE" in the package's main directory.
Please note that using this software in a commercial environment is not free of
charge. You may use the software during an evaluation period as specified in the
license, but subsequent use requires the ownership of a "Proof of Authorization"
which you can buy online from eGenix.com.
Please see the eGenix.com mx Extensions Page for details about the license
ordering process.
By downloading, copying, installing or otherwise using the software, you agree to
be bound by the terms and conditions of the following eGenix.com Commercial
License Agreement.
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mxODBC - Python ODBC Database Interface
EGENIX.COM COMMERCIAL LICENSE AGREEMENT
Version 1.3.0
1.
Introduction
This “License Agreement” is between eGenix.com Software, Skills and Services
GmbH (“eGenix.com”), having an office at Pastor-Loeh-Str. 48, D-40764
Langenfeld, Germany, and the Individual or Organization (“Licensee”) accessing
and otherwise using this software in source or binary form and its associated
documentation (“the Software”).
2.
Terms and Definitions
The “Software” covered under this License Agreement includes without limitation,
all object code, source code, help files, publications, documentation and other
programs, products or tools that are included in the official “Software
Distribution” available from eGenix.com.
The “Proof of Authorization” for the Software is a written and signed notice from
eGenix.com providing evidence of the extent of authorizations the Licensee has
acquired to use the Software and of Licensee’s eligibility for future upgrade
program prices (if announced) and potential special or promotional opportunities.
As such, the Proof of Authorization becomes part of this License Agreement.
Installation of the Software (“Installation”) refers to the process of unpacking or
copying the files included in the Software Distribution to an Installation Target.
“Installation Target” refers to the target of an installation operation. Targets are
defined, among other parameters, in terms of the following definitions:
1) “CPU” refers to a central processing unit which is able to store and/or
execute the Software (a server, personal computer, virtual machine, or
other computer-like device) using at most two (2) processors,
2) “Site” refers to a single site of a company,
3) “Corporate” refers to an unlimited number of sites of the company,
4) “Developer CPU” refers to a single CPU used by at most one (1) developer.
Additional terms may be defined as part of the Proof of Authorization.
When installing the Software on a server CPU for use by other CPUs in a network,
Licensee must obtain a License for the server CPU and for all client CPUs attached
to the network which will make use of the Software by copying the Software in
binary or source form from the server into their CPU memory. If a CPU makes use
of more than two (2) processors, Licensee must obtain additional CPU licenses to
cover the total number of installed processors. The number of cores per processor
does not count towards this license limitation. Virtual machines always count as
one (1) CPU. If a Developer CPU is used by more than one developer, Licensee
must obtain additional Developer CPU licenses to cover the total number of
developers using the CPU.
194
21. Copyright & License
“Commercial Environment” refers to any application environment which is aimed
at directly or indirectly generating profit. This includes, without limitation, forprofit organizations, private educational institutions, work as independent
contractor, consultant and other profit generating relationships with organizations
or individuals. Governments and related agencies or organizations are also
regarded as being Commercial Environments.
“Non-Commercial Environments” are all those application environments which do
not directly or indirectly generate profit. Public educational institutions and
officially acknowledged private non-profit organizations are regarded as being
Non-Commercial Environments in the aforementioned sense.
“Educational Environments“ are all those application environments which directly
aim at educating children, pupils or students. This includes, without limitation,
class room installations and student server installations which are intended to be
used by students for educational purposes. Installations aimed at administrational
or organizational purposes are not regarded as Educational Environment.
3.
License Grant
Subject to the terms and conditions of this License Agreement, eGenix.com
hereby grants Licensee a non-exclusive, world-wide license to
1) use the Software to the extent of authorizations Licensee has acquired and
2) distribute, make and install copies to support the level of use authorized,
providing Licensee reproduces this License Agreement and any other
legends of ownership on each copy, or partial copy, of the Software.
If Licensee acquires this Software as a program upgrade, Licensee’s authorization
to use the Software from which Licensee upgraded is terminated.
Licensee will ensure that anyone who uses the Software does so only in
compliance with the terms of this License Agreement.
Licensee may not
1) use, copy, install, compile, modify, or distribute the Software except as
provided in this License Agreement;
2) reverse assemble, reverse engineer, reverse compile, or otherwise translate
the Software except as specifically permitted by law without the possibility
of contractual waiver; or
3) rent, sublicense or lease the Software.
4.
Authorizations
The extent of authorization depends on the ownership of a Proof of Authorization
for the Software.
Usage of the Software for any other purpose not explicitly covered by this License
Agreement or granted by the Proof of Authorization is not permitted and requires
the written prior permission from eGenix.com.
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mxODBC - Python ODBC Database Interface
5.
Modifications
Software modifications may only be distributed in form of patches to the original
files contained in the Software Distribution.
The patches must be accompanied by a legend of origin and ownership and a
visible message stating that the patches are not original Software delivered by
eGenix.com, nor that eGenix.com can be held liable for possible damages related
directly or indirectly to the patches if they are applied to the Software.
6.
Experimental Code or Features
The Software may include components containing experimental code or features
which may be modified substantially before becoming generally available.
These experimental components or features may not be at the level of
performance or compatibility of generally available eGenix.com products.
eGenix.com does not guarantee that any of the experimental components or
features contained in the eGenix.com will ever be made generally available.
7.
Expiration and License Control Devices
Components of the Software may contain disabling or license control devices that
will prevent them from being used after the expiration of a period of time or on
Installation Targets for which no license was obtained.
Licensee will not tamper with these disabling devices or the components. Licensee
will take precautions to avoid any loss of data that might result when the
components can no longer be used.
8.
NO WARRANTY
eGenix.com is making the Software available to Licensee on an “AS IS” basis.
SUBJECT TO ANY STATUTORY WARRANTIES WHICH CAN NOT BE EXCLUDED,
EGENIX.COM MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, EGENIX.COM MAKES
NO AND DISCLAIMS ANY REPRESENTATION OR WARRANTY OF
MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE
USE OF THE SOFTWARE WILL NOT INFRINGE ANY THIRD PARTY RIGHTS.
9.
LIMITATION OF LIABILITY
TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, IN NO EVENT
SHALL EGENIX.COM BE LIABLE TO LICENSEE OR ANY OTHER USERS OF THE
SOFTWARE FOR (I) ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL
DAMAGES OR LOSS (INCLUDING, WITHOUT LIMITATION, DAMAGES FOR
LOSS OF BUSINESS PROFITS, BUSINESS INTERRUPTION, LOSS OF BUSINESS
INFORMATION, OR OTHER PECUNIARY LOSS) AS A RESULT OF USING,
MODIFYING OR DISTRIBUTING THE SOFTWARE, OR ANY DERIVATIVE
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THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF; OR (II) ANY
AMOUNTS IN EXCESS OF THE AGGREGATE AMOUNTS PAID TO EGENIX.COM
UNDER THIS LICENSE AGREEMENT DURING THE TWELVE (12) MONTH PERIOD
PRECEEDING THE DATE THE CAUSE OF ACTION AROSE.
SOME JURISDICTIONS DO NOT ALLOW THE EXCLUSION OR LIMITATION OF
INCIDENTAL OR CONSEQUENTIAL DAMAGES, SO THE ABOVE EXCLUSION OR
LIMITATION MAY NOT APPLY TO LICENSEE.
10.
Termination
This License Agreement will automatically terminate upon a material breach of its
terms and conditions if not cured within thirty (30) days of written notice by
eGenix.com. Upon termination, Licensee shall discontinue use and remove all
installed copies of the Software.
11.
Indemnification
Licensee hereby agrees to indemnify eGenix.com against and hold harmless
eGenix.com from any claims, lawsuits or other losses that arise out of Licensee’s
breach of any provision of this License Agreement.
12.
Third Party Rights
Any software or documentation in source or binary form provided along with the
Software that is associated with a separate license agreement is licensed to
Licensee under the terms of that license agreement. This License Agreement does
not apply to those portions of the Software. Copies of the third party licenses are
included in the Software Distribution.
13.
High Risk Activities
The Software is not fault-tolerant and is not designed, manufactured or intended
for use or resale as on-line control equipment in hazardous environments
requiring fail-safe performance, such as in the operation of nuclear facilities,
aircraft navigation or communication systems, air traffic control, direct life support
machines, or weapons systems, in which the failure of the Software, or any
software, tool, process, or service that was developed using the Software, could
lead directly to death, personal injury, or severe physical or environmental
damage (“High Risk Activities”).
Accordingly, eGenix.com specifically disclaims any express or implied warranty of
fitness for High Risk Activities.
Licensee agree that eGenix.com will not be liable for any claims or damages
arising from the use of the Software, or any software, tool, process, or service that
was developed using the Software, in such applications.
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14.
General
Nothing in this License Agreement affects any statutory rights of consumers that
cannot be waived or limited by contract.
Nothing in this License Agreement shall be deemed to create any relationship of
agency, partnership, or joint venture between eGenix.com and Licensee.
If any provision of this License Agreement shall be unlawful, void, or for any
reason unenforceable, such provision shall be modified to the extent necessary to
render it enforceable without losing its intent, or, if no such modification is
possible, be severed from this License Agreement and shall not affect the validity
and enforceability of the remaining provisions of this License Agreement.
This License Agreement shall be governed by and interpreted in all respects by the
law of Germany, excluding conflict of law provisions. It shall not be governed by
the United Nations Convention on Contracts for International Sale of Goods.
This License Agreement does not grant permission to use eGenix.com trademarks
or trade names in a trademark sense to endorse or promote products or services
of Licensee, or any third party.
The controlling language of this License Agreement is English. If Licensee has
received a translation into another language, it has been provided for Licensee’s
convenience only.
15.
Agreement
By downloading, copying, installing or otherwise using the Software, Licensee
agrees to be bound by the terms and conditions of this License Agreement.
For question regarding this License Agreement, please write to:
eGenix.com Software, Skills and Services GmbH
Pastor-Loeh-Str. 48
D-40764 Langenfeld
Germany
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21. Copyright & License
EGENIX.COM PROOF OF AUTHORIZATION
1 CPU License (Example)
This is an example of a "Proof of Authorization" for a 1 CPU License. These proofs
are either wet-signed by the eGenix.com staff or digitally PGP-signed using an
official eGenix.com PGP-key.
1.
License Grant
eGenix.com Software, Skills and Services GmbH (“eGenix.com”), having an office
at Pastor-Loeh-Str. 48, D-40764 Langenfeld, Germany, hereby grants the
Individual or Organization (“Licensee”)
Licensee:
<name of the licensee>
a non-exclusive, world-wide license to use the software listed below in source or
binary form and its associated documentation (“the Software”) under the terms
and conditions of this License Agreement and to the extent authorized by this
Proof of Authorization.
2.
Covered Software
Software Name:
<product name>
Software Version:
<product version>
(including all patch level releases)
Software Distribution: As officially made available by
eGenix.com on http://www.egenix.com/
Operating System:
3.
any compatible operating system
Authorizations
eGenix.com hereby authorizes Licensee to copy, install, compile, modify and use
the Software on the following Installation Targets under the terms of this License
Agreement.
Installation Targets:
one (1) CPU
Use of the Software for any other purpose or redistribution IS NOT PERMITTED
BY THIS PROOF OF AUTHORIZATION.
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4.
Proof
This Proof of Authorization was issued by
<name>, <title>
Langenfeld, <date>
Proof of Authorization Key:
<license key>
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21. Copyright & License
EGENIX.COM PROOF OF AUTHORIZATION
1 Developer CPU License (Example)
This is an example of a "Proof of Authorization" for a 1 Developer CPU License.
These proofs are either wet-signed by the eGenix.com staff or digitally PGP-signed
using an official eGenix.com PGP-key.
5.
License Grant
eGenix.com Software, Skills and Services GmbH (“eGenix.com”), having an office
at Pastor-Loeh-Str. 48, D-40764 Langenfeld, Germany, hereby grants the
Individual or Organization (“Licensee”)
Licensee:
<name of the licensee>
a non-exclusive, world-wide license to use the software listed below in source or
binary form and its associated documentation (“the Software”) under the terms
and conditions of this License Agreement and to the extent authorized by this
Proof of Authorization.
6.
Covered Software
Software Name:
<product name>
Software Version:
<product version>
(including all patch level releases)
Software Distribution: As officially made available by
eGenix.com on http://www.egenix.com/
Operating System:
7.
any compatible operating system
Authorizations
7.1
Application Development
eGenix.com hereby authorizes Licensee to copy, install, compile, modify and use
the Software on the following Developer Installation Targets for the purpose of
developing products using the Software as integral part.
Developer Installation Targets:
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7.2
Redistribution
eGenix.com hereby authorizes Licensee to redistribute the Software bundled with
a product developed by Licensee on the Developer Installation Targets ("the
Product") subject to the terms and conditions of this License Agreement for
installation and use in combination with the Product on the following
Redistribution Installation Targets, provided that:
1. Licensee shall not and shall not permit or assist any third party to sell or
distribute the Software as a separate product;
2. Licensee shall not and shall not permit any third party to
i.
market, sell or distribute the Software to any end user except
subject to the terms and conditions of this License Agreement,
ii.
rent, sell, lease or otherwise transfer the Software or any part
thereof or use it for the benefit of any third party,
iii.
use the Software outside the Product or for any other purpose
not expressly licensed hereunder;
3. the Product does not provide functions or capabilities similar to those of
the Software itself, i.e. the Product does not introduce commercial
competition for the Software as sold by eGenix.com;
4. Licensee has obtained Developer CPU Licenses for all developers and
CPUs used in developing the Product.
Redistribution Installation Targets:
any number of CPUs capable of running the Product and the Software
8.
Proof
This Proof of Authorization was issued by
<name>, <title>
Langenfeld, <date>
Proof of Authorization Key:
<license key>
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