1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
|
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/plpython.sgml,v 1.1 2001/05/12 17:49:32 petere Exp $ -->
<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, args[0] contains whatever was passed in as the text
argument. For <literal>myfunc2(text, int4)</literal>, args[0]
would contain the text variable and args[1] the int4 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. When the function is used in a
trigger, the triggers tuples are in TD["new"] and/or TD["old"]
depending on the trigger event. 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. If the trigger was called with arguments they are available
in TD["args"][0] to TD["args"][(n -1)]
</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>
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 plpy 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>
|
