Data Values

43.3.1. Data Type Mapping

Function arguments are converted from their PostgreSQL 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, 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.

Function return values are converted to the 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 bytea .

• For all other PostgreSQL return types, the returned Python 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.

  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.

43.3.2. Null, None

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 43.2 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.

43.3.3. Arrays, Lists

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 sequence, for example a list or tuple:

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)

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)

43.3.4. Composite Types

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:

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();

43.3.5. Set-returning Functions

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:

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);