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Simple PostgreSQL database wrapper - provides wrapper over psycopg2 supporting a Python API for common sql functions (supports py2/py3)

Project description

pgwrap - simple PostgreSQL database wrapper

The 'pgwrap' module provides a simple wrapper over psycopg2 supporting a
Python API for common sql functions.

This is not intended to provide ORM-like functionality, just to make it
easier to interact with PostgreSQL from python code for simple use-cases
and allow direct SQL access for more complex operations.

The module wraps the excellent 'psycopg2' library and most of the
functionality is provided by this behind the scenes.

The module provides:

* Simplified handling of connections/cursor
* Connection pool (provided by psycopg2.pool)
* Cursor context handler
* Python API to wrap basic SQL functionality
* Simple select,update,delete,join methods extending the cursor
context handler (also available as stand-alone methods which
create an implicit cursor for simple queries)
* Query results as dict (using psycopg2.extras.DictCursor)
* Callable prepared statements
* Logging support
* Supports Python 2/3

Basic usage

>>> import pgwrap
>>> db = pgwrap.connection(url='postgres://localhost')
>>> with db.cursor() as c:
... c.query('select version()')
>>> v = db.query_one('select version()')
>>> v
>>> v.items()
[('version', 'PostgreSQL...')]
>>> v['version']


The connection class initialises an internal connection pool and provides
methods to return a cursor object or execute SQL queries directly (using an
implicit cursor).

The intention is that a single instance of this class is created at
application start up.


The module provides a cursor context handler wrapping the psycopg2 cursor.

Entering the cursor context handler will obtain a connection from the
connection pool and create a cursor using this connection. When the context
handler is exited the associated transaction will be committed, cursor
closed, and the connection released back to the connection pool.

The cursor object uses the psycopg2 'DictCursor' by default (which
returns rows as a pseudo python dictionary) however this can be overridden
by providing a 'cursor_factory' parameter to the constructor.

>>> db = pgwrap.connection(url='postgres://localhost')
>>> with db.cursor() as c:
... c.query('select version()')

The cursor context provides the following basic methods:

execute - execute SQL query and return rowcount
query - execute SQL query and fetch results
query_one - execute SQL query and fetch first result
query_dict - execute SQL query and return results as dict
keyed on specified key (which should be unique)
commit - Commit transaction (called implicitly on exiting
context handler)
rollback - Rollback transaction

In addition the cursor can use the SQL API methods described below or
access the underlying psycopg2 cursor (via the self.cursor attribute).

The cursor methods are also available as standalone functions which
run inside an implicit cursor object.


The cursor class also provides a simple Python API for common SQL
operations. The basic methods provides are:

select - single table select (with corresponding select_one,
select_dict methods)
join - two table join (with corresponding join_one,
join_dict methods)
insert - SQL insert
update - SQL update
delete - SQL delete

The methods can be parameterised to customise the associated query
(see db module for detail):

where - 'where' clause as dict (column operators can be
specified using the colunm__operator format)

where = {'name':'abc','status__in':(1,2,3)}

columns - list of columns to be returned - these can
be real columns or expressions. If spefified
as a tuple the column is explicitly named
using the AS operator

columns = ('name',('status > 1','updated'))

order - sort order as list (use 'column__desc' to
reverse order)

order = ('name__desc',)

limit - row limit (int)

offset - offset (int)

on - join columns (as tuple)

values - insert data as dict

returning - columns to return (string)

The methods are also available as standalone functions which create an
implicit cursor object.

Basic usage:

>>> db.create_table('t1','id serial,name text,count int')
>>> db.create_table('t2','id serial,t1_id int,value text')
>>> db.log = sys.stdout
>>> db.insert('t1',{'name':'abc','count':0},returning='id,name')
INSERT INTO t1 (name) VALUES ('abc') RETURNING id,name
[1, 'abc']
>>> db.insert('t2',{'t1_id':1,'value':'t2'})
INSERT INTO t2 (t1_id,value) VALUES (1,'t2')
[[1, 'abc', 0]]
>>> db.select_one('t1',where={'name':'abc'},columns=('name','count'))
SELECT name, count FROM t1 WHERE name = 'abc'
['abc', 0]
>>> db.join(('t1','t2'),columns=('','t2.value'))
SELECT, t2.value FROM t1 JOIN t2 ON = t2.t1_id
[[1, 't2']]
>>> db.insert('t1',{'name':'abc'},returning='id')
>>> db.update('t1',{'name':'xyz'},where={'name':'abc'})
UPDATE t1 SET name = 'xyz' WHERE name = 'abc'
>>> db.update('t1',{'count__func':'count + 1'},where={'count__lt':10},returning="id,count")
UPDATE t1 SET count = count + 1 WHERE count < 10 RETURNING id,count
[[1, 1]]

Prepared Statements

Prepared statements can be created using the


stmt : prepared statement (with parameters identified
in the statement using the psql $1,$2... notation)
params : list of optional parameter types (usually not
needed - infered by psql)
name : name for the prepared statement (usually
call_type : method used when instance called as method
(defaults to 'query')

The constructor returns a PreparedStatement object which can be used
instead of an sql statement in the connection.execute and
connection.query_xxx methods.

>>> p = db.prepare('UPDATE t1 SET name = $2 WHERE id = $1')
PREPARE _pstmt_001 AS UPDATE t1 SET name = $2 WHERE id = $1
>>> with db.cursor() as c:
... c.execute(p,(1,'xxx'))
EXECUTE _pstmt_001 (1,'xxx')

The PreparedStatement object can also be called directly using the
execute/query/query_one/query_dict methods. The instance is also
directly callable using the method type identified in 'call_type'

>>> p = db.prepare('UPDATE t1 SET name = $2 WHERE id = $1')
PREPARE _pstmt_001 AS UPDATE t1 SET name = $2 WHERE id = $1
>>> p.execute(1,'xxx')
EXECUTE _pstmt_001 (1,'xxx')
>>> p(1,'xxx')
EXECUTE _pstmt_001 (1,'xxx')


To enable logging the connection.log attribute can be set to either an
instance of logging.Logger or a file-like object (supporting the write

The log message is generated using the self.logf function (called with
the cursor object as a parameter). By default this just returns the
query string however can be customised as needed. A cursor.timestamp
attribute is available to allow execution time to be tracked.

>>> db.log = sys.stdout
>>> db.logf = lambda c : '[%f] %s' % (time.time() - c.timestamp,c.query)
>>> db.query('SELECT * FROM t1')
[0.000536] SELECT * FROM t1


* 0.1 19-10-2012 Initial import
* 0.2 20-10-2012 Remove psycopg2 dep in
* 0.3 20-10-2012 Remove hstore default for cursor
* 0.4 21-10-2012 Add logging support
* 0.5 22-12-2012 Refactor connection class / remove globals
* 0.6 23-12-2012 Add support for prepared statements
* 0.7 26-12-2012 Add callable prepared statements & named cursor
* 0.8 02-02-2019 Support Python 3 (finally)


* Paul Chakravarti (

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