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' LANGUAGE 'plpython';
gets transformed into
def __plpython_procedure_myfunc_23456(): return args
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
list. In the
args contains whatever was passed
in as the text argument. For myfunc2(text,
args would contain
the text variable and
args the integer
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
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"] 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.error("msg"), plpy.fatal("msg"), plpy.debug("msg"), and plpy.notice("msg"). They are mostly equivalent to
calling elog(LEVEL, "msg"), where LEVEL is DEBUG, ERROR, FATAL or NOTICE.
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
Additionally, the plpy module
provides two functions called
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
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
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
When you prepare a plan using the PL/Python module it is automatically saved. Read the SPI documentation (Chapter 21) 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).