Generally speaking, the aim of PL/Python is to provide a “natural” mapping between the PostgreSQL and the Python worlds. This informs the data mapping rules described below.
When a PL/Python function is called, its arguments are converted from their PostgreSQL data type to a corresponding Python type:
PostgreSQL boolean
is converted to Python bool
.
PostgreSQL smallint
and int
are
converted to Python int
.
PostgreSQL bigint
and oid
are converted
to long
in Python 2 and to int
in
Python 3.
PostgreSQL real
and double
are converted to
Python float
.
PostgreSQL numeric
is converted to
Python Decimal
. This type is imported from
the cdecimal
package if that is available.
Otherwise,
decimal.Decimal
from the standard library will be
used. cdecimal
is significantly faster
than decimal
. In Python 3.3 and up,
however, cdecimal
has been integrated into the
standard library under the name decimal
, so there is
no longer any difference.
PostgreSQL bytea
is converted to
Python str
in Python 2 and to bytes
in Python 3. In Python 2, the string should be treated as a
byte sequence without any character encoding.
All other data types, including the PostgreSQL character string
types, are converted to a Python str
. In Python
2, this string will be in the PostgreSQL server encoding; in
Python 3, it will be a Unicode string like all strings.
For nonscalar data types, see below.
When a PL/Python function returns, its return value is converted to the function's declared PostgreSQL return data type as follows:
When the PostgreSQL return type is boolean
, the
return value will be evaluated for truth according to the
Python rules. That is, 0 and empty string
are false, but notably 'f'
is true.
When the PostgreSQL return type is bytea
, the
return value will be converted to a string (Python 2) or bytes
(Python 3) using the respective Python built-ins, with the
result being converted to bytea
.
For all other PostgreSQL return types, the return value is converted
to a string using the Python built-in str
, and the
result is passed to the input function of the PostgreSQL data type.
(If the Python value is a float
, it is converted using
the repr
built-in instead of str
, to
avoid loss of precision.)
Strings in Python 2 are required to be in the PostgreSQL server encoding when they are passed to PostgreSQL. Strings that are not valid in the current server encoding will raise an error, but not all encoding mismatches can be detected, so garbage data can still result when this is not done correctly. Unicode strings are converted to the correct encoding automatically, so it can be safer and more convenient to use those. In Python 3, all strings are Unicode strings.
For nonscalar data types, see below.
Note that logical mismatches between the declared PostgreSQL return type and the Python data type of the actual return object are not flagged; the value will be converted in any case.
If an SQL null value is passed to a
function, the argument value will appear as None
in
Python. For example, the function definition of pymax
shown in Section 46.2 will return the wrong answer for null
inputs. We could add STRICT
to the function definition
to make PostgreSQL do something more reasonable:
if a null value is passed, the function will not be called at all,
but will just return a null result automatically. Alternatively,
we could check for null inputs in the function body:
CREATE FUNCTION pymax (a integer, b integer) RETURNS integer AS $$ if (a is None) or (b is None): return None if a > b: return a return b $$ LANGUAGE plpythonu;
As shown above, to return an SQL null value from a PL/Python
function, return the value None
. This can be done whether the
function is strict or not.
SQL array values are passed into PL/Python as a Python list. To return an SQL array value out of a PL/Python function, return a Python list:
CREATE FUNCTION return_arr() RETURNS int[] AS $$ return [1, 2, 3, 4, 5] $$ LANGUAGE plpythonu; SELECT return_arr(); return_arr ------------- {1,2,3,4,5} (1 row)
Multidimensional arrays are passed into PL/Python as nested Python lists. A 2-dimensional array is a list of lists, for example. When returning a multi-dimensional SQL array out of a PL/Python function, the inner lists at each level must all be of the same size. For example:
CREATE FUNCTION test_type_conversion_array_int4(x int4[]) RETURNS int4[] AS $$ plpy.info(x, type(x)) return x $$ LANGUAGE plpythonu; SELECT * FROM test_type_conversion_array_int4(ARRAY[[1,2,3],[4,5,6]]); INFO: ([[1, 2, 3], [4, 5, 6]], <type 'list'>) test_type_conversion_array_int4 --------------------------------- {{1,2,3},{4,5,6}} (1 row)
Other Python sequences, like tuples, are also accepted for backwards-compatibility with PostgreSQL versions 9.6 and below, when multi-dimensional arrays were not supported. However, they are always treated as one-dimensional arrays, because they are ambiguous with composite types. For the same reason, when a composite type is used in a multi-dimensional array, it must be represented by a tuple, rather than a list.
Note that in Python, strings are sequences, which can have undesirable effects that might be familiar to Python programmers:
CREATE FUNCTION return_str_arr() RETURNS varchar[] AS $$ return "hello" $$ LANGUAGE plpythonu; SELECT return_str_arr(); return_str_arr ---------------- {h,e,l,l,o} (1 row)
Composite-type arguments are passed to the function as Python mappings. The
element names of the mapping are the attribute names of the composite type.
If an attribute in the passed row has the null value, it has the value
None
in the mapping. Here is an example:
CREATE TABLE employee ( name text, salary integer, age integer ); CREATE FUNCTION overpaid (e employee) RETURNS boolean AS $$ if e["salary"] > 200000: return True if (e["age"] < 30) and (e["salary"] > 100000): return True return False $$ LANGUAGE plpythonu;
There are multiple ways to return row or composite types from a Python function. The following examples assume we have:
CREATE TYPE named_value AS ( name text, value integer );
A composite result can be returned as a:
Returned sequence objects must have the same number of items as the composite result type has fields. The item with index 0 is assigned to the first field of the composite type, 1 to the second and so on. For example:
CREATE FUNCTION make_pair (name text, value integer) RETURNS named_value AS $$ return ( name, value ) # or alternatively, as list: return [ name, value ] $$ LANGUAGE plpythonu;
To return an SQL null for any column, insert None
at
the corresponding position.
When an array of composite types is returned, it cannot be returned as a list, because it is ambiguous whether the Python list represents a composite type, or another array dimension.
The value for each result type column is retrieved from the mapping with the column name as key. Example:
CREATE FUNCTION make_pair (name text, value integer) RETURNS named_value AS $$ return { "name": name, "value": value } $$ LANGUAGE plpythonu;
Any extra dictionary key/value pairs are ignored. Missing keys are
treated as errors.
To return an SQL null value for any column, insert
None
with the corresponding column name as the key.
__getattr__
)This works the same as a mapping. Example:
CREATE FUNCTION make_pair (name text, value integer) RETURNS named_value AS $$ class named_value: def __init__ (self, n, v): self.name = n self.value = v return named_value(name, value) # or simply class nv: pass nv.name = name nv.value = value return nv $$ LANGUAGE plpythonu;
Functions with OUT
parameters are also supported. For example:
CREATE FUNCTION multiout_simple(OUT i integer, OUT j integer) AS $$ return (1, 2) $$ LANGUAGE plpythonu; SELECT * FROM multiout_simple();
Output parameters of procedures are passed back the same way. For example:
CREATE PROCEDURE python_triple(INOUT a integer, INOUT b integer) AS $$ return (a * 3, b * 3) $$ LANGUAGE plpythonu; CALL python_triple(5, 10);
A PL/Python function can also return sets of scalar or composite types. There are several ways to achieve this because the returned object is internally turned into an iterator. The following examples assume we have composite type:
CREATE TYPE greeting AS ( how text, who text );
A set result can be returned from a:
CREATE FUNCTION greet (how text) RETURNS SETOF greeting AS $$ # return tuple containing lists as composite types # all other combinations work also return ( [ how, "World" ], [ how, "PostgreSQL" ], [ how, "PL/Python" ] ) $$ LANGUAGE plpythonu;
__iter__
and
next
methods)
CREATE FUNCTION greet (how text) RETURNS SETOF greeting AS $$ class producer: def __init__ (self, how, who): self.how = how self.who = who self.ndx = -1 def __iter__ (self): return self def next (self): self.ndx += 1 if self.ndx == len(self.who): raise StopIteration return ( self.how, self.who[self.ndx] ) return producer(how, [ "World", "PostgreSQL", "PL/Python" ]) $$ LANGUAGE plpythonu;
yield
)
CREATE FUNCTION greet (how text) RETURNS SETOF greeting AS $$ for who in [ "World", "PostgreSQL", "PL/Python" ]: yield ( how, who ) $$ LANGUAGE plpythonu;
Set-returning functions with OUT
parameters
(using RETURNS SETOF record
) are also
supported. For example:
CREATE FUNCTION multiout_simple_setof(n integer, OUT integer, OUT integer) RETURNS SETOF record AS $$ return [(1, 2)] * n $$ LANGUAGE plpythonu; SELECT * FROM multiout_simple_setof(3);