PL/Python Python The PL/Python procedural language allows PostgreSQL functions to be written in the Python language. The current version of PL/Python functions as a trusted language only; access to the file system and other local resources is disabled. Specifically, PL/Python uses the Python restricted execution environment, further restricts it to prevent the use of the file open call, and allows only modules from a specific list to be imported. Presently, that list includes: array, bisect, binascii, calendar, cmath, codecs, errno, marshal, math, md5, mpz, operator, pcre, pickle, random, re, regex, sre, sha, string, StringIO, struct, time, whrandom, and zlib. In the current version, any database error encountered while running a PL/Python function will result in the immediate termination of that function by the server. It is not possible to trap error conditions using Python try ... catch constructs. For example, a syntax error in an SQL statement passed to the plpy.execute() call will terminate the function. This behavior may be changed in a future release. To build PL/Python, the --with-python option needs to be specified when running configure. If after building and installing you have a file called plpython.so (possibly a different extension), then everything went well. Otherwise you should have seen a notice like this flying by: *** Cannot build PL/Python because libpython is not a shared library. *** You might have to rebuild your Python installation. Refer to *** the documentation for details. That means you have to rebuild (part of) your Python installation to supply this shared library. The catch is that the Python distribution or the Python maintainers do not provide any direct way to do this. The closest thing we can offer you is the information in Python FAQ 3.30. On some operating systems you don't really have to build a shared library, but then you will have to convince the PostgreSQL build system of this. Consult the Makefile in the src/pl/plpython directory for details. There are sample functions in plpython_function.sql. The Python code you write gets transformed into a function. E.g., CREATE FUNCTION myfunc(text) RETURNS text AS 'return args[0]' LANGUAGE 'plpython'; gets transformed into def __plpython_procedure_myfunc_23456(): return args[0] where 23456 is the Oid of the function. If you do not provide a return value, Python returns the default None which may or may not be what you want. The language module translates Python's None into SQL NULL. PostgreSQL function variables are available in the global args list. In the myfunc example, args[0] contains whatever was passed in as the text argument. For myfunc2(text, integer), args[0] would contain the text variable and args[1] the integer variable. The global dictionary SD is available to store data between function calls. This variable is private static data. The global dictionary GD is public data, available to all python functions within a backend. Use with care. Each function gets its own restricted execution object in the Python interpreter, so that global data and function arguments from myfunc are not available to myfunc2. The exception is the data in the GD dictionary, as mentioned above. When a function is used in a trigger, the dictionary TD contains transaction related values. The trigger tuples are in TD["new"] and/or TD["old"] depending on the trigger event. TD["event"] contains the event as a string (INSERT, UPDATE, DELETE, or UNKNOWN). TD["when"] contains one of (BEFORE, AFTER, or UNKNOWN). TD["level"] contains one of ROW, STATEMENT, or UNKNOWN. TD["name"] contains the trigger name, and TD["relid"] contains the relation id of the table on which the trigger occurred. If the trigger was called with arguments they are available in TD["args"][0] to TD["args"][(n -1)]. If the trigger when is BEFORE, you may return None or "OK" from the Python function to indicate the tuple is unmodified, "SKIP" to abort the event, or "MODIFIED" to indicate you've modified the tuple. The PL/Python language module automatically imports a Python module called plpy. The functions and constants in this module are available to you in the Python code as plpy.foo. At present plpy implements the functions plpy.debug("msg"), plpy.log("msg"), plpy.info("msg"), plpy.notice("msg"), plpy.warning("msg"), plpy.error("msg"), and plpy.fatal("msg"). They are mostly equivalent to calling elog(LEVEL, "msg"). plpy.error and plpy.fatal actually raise a Python exception which, if uncaught, causes the PL/Python module to call elog(ERROR, msg) when the function handler returns from the Python interpreter. Long jumping out of the Python interpreter is probably not good. raise plpy.ERROR("msg") and raise plpy.FATAL("msg") are equivalent to calling plpy.error or plpy.fatal. Additionally, the plpy module provides two functions called execute and prepare. Calling plpy.execute with a query string, and an optional limit argument, causes that query to be run, and the result returned in a result object. The result object emulates a list or dictionary object. The result object can be accessed by row number, and field name. It has these additional methods: nrows() which returns the number of rows returned by the query, and status which is the SPI_exec return variable. The result object can be modified. rv = plpy.execute("SELECT * FROM my_table", 5) returns up to 5 rows from my_table. Ff my_table has a column my_field it would be accessed as foo = rv[i]["my_field"] The second function plpy.prepare is called with a query string, and a list of argument types if you have bind variables in the query. plan = plpy.prepare("SELECT last_name FROM my_users WHERE first_name = $1", [ "text" ]) text is the type of the variable you will be passing as $1. After preparing you use the function plpy.execute to run it. rv = plpy.execute(plan, [ "name" ], 5) The limit argument is optional in the call to plpy.execute. When you prepare a plan using the PL/Python module it is automatically saved. Read the SPI documentation () for a description of what this means. The take home message is if you do plan = plpy.prepare("SOME QUERY") plan = plpy.prepare("SOME OTHER QUERY") you are leaking memory, as I know of no way to free a saved plan. The alternative of using unsaved plans it even more painful (for me).