postgresql/doc/src/sgml/plpython.sgml

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<chapter id="plpython">
 <title>PL/Python - Python Procedural Language</title>

 <note>
  <para>
   This chapter is not fully developed yet.
  </para>
 </note>

 <sect1 id="plpython-install">
  <title>Installation</title>

  <para>
   ... needs to be worked out.
  </para>
 </sect1>

 <sect1 id="plpython-using">
  <title>Using</title>

  <para>
   There are sample functions in
   <filename>plpython_function.sql</filename>.  The Python code you
   write gets transformed into a function.  E.g.,
<programlisting>
CREATE FUNCTION myfunc(text) RETURNS text AS
'return args[0]'
LANGUAGE 'plpython';
</programlisting>

   gets transformed into

<programlisting>
def __plpython_procedure_myfunc_23456():
	return args[0]
</programlisting>

   where 23456 is the Oid of the function.
  </para>

  <para>
   If you do not provide a return value, Python returns the default
   <symbol>None</symbol> which may or may not be what you want.  The
   language module translates Python's None into SQL NULL.
  </para>

  <para>
   PostgreSQL function variables are available in the global
   <varname>args</varname> list.  In the <function>myfunc</function>
   example, <varname>args[0]</> contains whatever was passed in as the text
   argument.  For <literal>myfunc2(text, integer)</literal>, <varname>args[0]</>
   would contain the <type>text</type> variable and <varname>args[1]</varname> the <type>integer</type> variable.
  </para>

  <para>
   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.
  </para>

  <para>
   Each function gets its own restricted execution object in the
   Python interpreter, so that global data and function arguments from
   <function>myfunc</function> are not available to
   <function>myfunc2</function>.  The exception is the data in the GD
   dictionary, as mentioned above.
  </para>

  <para>
   When a function is used in a trigger, the dictionary TD contains
   transaction related values.  The trigger tuples are in <literal>TD["new"]</>
   and/or <literal>TD["old"]</> depending on the trigger event.  <literal>TD["event"]</>
   contains the event as a string (<literal>INSERT</>, <literal>UPDATE</>, <literal>DELETE</>, or
   <literal>UNKNOWN</>).  TD["when"] contains one of (<literal>BEFORE</>, <literal>AFTER</>, or
   <literal>UNKNOWN</>).  <literal>TD["level"]</> contains one of <literal>ROW</>, <literal>STATEMENT</>, or
   <literal>UNKNOWN</>.  <literal>TD["name"]</> contains the trigger name, and <literal>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 <literal>TD["args"][0]</> to <literal>TD["args"][(n -1)]</>.
  </para>

  <para>
   If the trigger <quote>when</quote> is <literal>BEFORE</>, you may return <literal>None</literal> or <literal>"OK"</literal>
   from the Python function to indicate the tuple is unmodified,
   <literal>"SKIP"</> to abort the event, or <literal>"MODIFIED"</> to indicate you've
   modified the tuple.
  </para>

  <para>
   The PL/Python language module automatically imports a Python module
   called <literal>plpy</literal>.  The functions and constants in
   this module are available to you in the Python code as
   <literal>plpy.<replaceable>foo</replaceable></literal>.  At present
   <literal>plpy</literal> implements the functions
   <literal>plpy.error("msg")</literal>,
   <literal>plpy.fatal("msg")</literal>,
   <literal>plpy.debug("msg")</literal>, and
   <literal>plpy.notice("msg")</literal>.  They are mostly equivalent
   to calling <literal>elog(<replaceable>LEVEL</>, "msg")</literal>,
   where <replaceable>LEVEL</> is DEBUG, ERROR, FATAL or NOTICE.
   <function>plpy.error</function> and <function>plpy.fatal</function>
   actually raise a Python exception which, if uncaught, causes the
   PL/Python module to call <literal>elog(ERROR, msg)</literal> when
   the function handler returns from the Python interpreter.  Long
   jumping out of the Python interpreter is probably not good.
   <literal>raise plpy.ERROR("msg")</literal> and <literal>raise
   plpy.FATAL("msg")</literal> are equivalent to calling
   <function>plpy.error</function> or <function>plpy.fatal</function>.
  </para>

  <para>
   Additionally, the <literal>plpy</literal> module provides two functions called
   <function>execute</function> and <function>prepare</function>.
   Calling <function>plpy.execute</function> 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:
   <function>nrows()</function> which returns the number of rows
   returned by the query, and <function>status</function> which is the
   <function>SPI_exec</function> return variable.  The result object
   can be modified.

<programlisting>
rv = plpy.execute("SELECT * FROM my_table", 5)
</programlisting>
   returns up to 5 rows from my_table.  Ff my_table has a column
   my_field it would be accessed as
<programlisting>
foo = rv[i]["my_field"]
</programlisting>
   The second function <function>plpy.prepare</function> is called
   with a query string, and a list of argument types if you have bind
   variables in the query.
<programlisting>
plan = plpy.prepare("SELECT last_name FROM my_users WHERE first_name = $1", [ "text" ])
</programlisting>
   text is the type of the variable you will be passing as $1.  After
   preparing you use the function <function>plpy.execute</function> to
   run it.
<programlisting>
rv = plpy.execute(plan, [ "name" ], 5)
</programlisting>
   The limit argument is optional in the call to
   <function>plpy.execute</function>.
  </para>

  <para>
   When you prepare a plan using the PL/Python module it is
   automatically saved.  Read the SPI documentation (<xref
   linkend="spi">) for a description of what this means.  The take
   home message is if you do
<programlisting>
plan = plpy.prepare("SOME QUERY")
plan = plpy.prepare("SOME OTHER QUERY")
</programlisting>
   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).
  </para>
 </sect1>

</chapter>