Postgresql – How to create Select query function in the Postgresql

The approach you're using is unnecessarily complex - and very inefficient. Instead of the first function use:

create or replace function compute_pair_id_value(id bigint, value integer)
    returns setof pair_id_value
as $$
SELECT $1, generate_series(0,$2);
$$                          
language sql;

or better, get rid of it entirely and write the whole operation like this:

-- Sample data creation:
CREATE TABLE my_obj(id bigint, obj_value integer);
insert into my_obj(id,obj_value) VALUES (1712437,2),(17000,5);

-- and the query:
SELECT id, generate_series(0,obj_value) FROM my_obj;

Resulting in:

regress=> SELECT id, generate_series(0,obj_value) FROM my_obj;
   id    | generate_series 
---------+-----------------
 1712437 |               0
 1712437 |               1
 1712437 |               2
   17000 |               0
   17000 |               1
   17000 |               2
   17000 |               3
   17000 |               4
   17000 |               5
(9 rows)

This exploits PostgreSQL's behaviour with set-returning functions called in the SELECT list. Once PostgreSQL 9.3 comes out it can be replaced with a standards-compliant LATERAL query.

Since it turns out your question was a simplified version of the real problem, let's tackle that. I'll work with the simplified compute_pair_id_value above to avoid the hassle of plpython3. Here's how to do what you want:

SELECT (compute_pair_id_value(id,obj_value)).* FROM my_obj;

Result:

regress=> SELECT (compute_pair_id_value(id,obj_value)).* FROM my_obj;
   id    | value 
---------+-------
 1712437 |     0
 1712437 |     1
 1712437 |     2
   17000 |     0
   17000 |     1
   17000 |     2
   17000 |     3
   17000 |     4
   17000 |     5
(9 rows)

but again, be warned that compute_pair_id_value will be called more than once. This is a limitation of PostgreSQL's query executor that can be avoided in 9.3 with LATERAL support, but as far as I know you're stuck with it in 9.2 and below. Observe:

create or replace function compute_pair_id_value(id bigint, value integer)
    returns setof pair_id_value
as $$
BEGIN
  RAISE NOTICE 'compute_pair_id_value(%,%)',id,value;
  RETURN QUERY SELECT $1, generate_series(0,$2);
END;
$$             
language plpgsql;

output:

regress=> SELECT (compute_pair_id_value(id,obj_value)).* FROM my_obj;
NOTICE:  compute_pair_id_value(1712437,2)
NOTICE:  compute_pair_id_value(1712437,2)
NOTICE:  compute_pair_id_value(17000,5)
NOTICE:  compute_pair_id_value(17000,5)
   id    | value 
---------+-------
 1712437 |     0
 1712437 |     1
 1712437 |     2
   17000 |     0
   17000 |     1
   17000 |     2
   17000 |     3
   17000 |     4
   17000 |     5
(9 rows)

See how compute_pair_id_value is called once per output column?

There is a workaround: Another layer of subquery to unpack the composite type result. See:

regress=> SELECT (val).* FROM (SELECT compute_pair_id_value(id,obj_value) FROM my_obj) x(val);
NOTICE:  compute_pair_id_value(1712437,2)
NOTICE:  compute_pair_id_value(17000,5)
   id    | value 
---------+-------
 1712437 |     0
 1712437 |     1
 1712437 |     2
   17000 |     0
   17000 |     1
   17000 |     2
   17000 |     3
   17000 |     4
   17000 |     5
(9 rows)

You can use the same technique in your code if you really must LOOP over the results (it's slow to do that, so avoid it if you can).

Assuming current Postgres version 9.5, since it has not been defined.
Best solved with a LATERAL join (Postgres 9.3+).

The minimal working form:

INSERT INTO table_output
SELECT f.*
FROM   table_input t, my_func(t.id) f;

The same, more explicit:

INSERT INTO table_output (foo, bar)
SELECT f.foo, f.bar
FROM   table_input t
CROSS  JOIN LATERAL my_func(t.id) AS f;

Or, since exactly one result row is guaranteed in this case, a plain function call in a subquery does the same, probably cheaper:

INSERT INTO table_output
SELECT f.*
FROM  (SELECT my_func(id) AS f FROM table_input) t;

It's wise to declare target columns in a persisted INSERT, even if the row types of function and table currently match. This is more robust against later changes.

CROSS JOIN LATERAL is just the verbose equivalent of a simple comma before a set-returning function in the FROM list. (Binding more closely, but that's not relevant in this query.)

Detailed explanation for LATERAL and how to avoid repeated function evaluation in this recent, related answer on SO - with links to more:

• Split function-returned record into multiple columns