pgwrap

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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()') [['PostgreSQL...']] v = db.query_one('select version()') v ['PostgreSQL...'] v.items() [('version', 'PostgreSQL...')] v['version'] 'PostgreSQL...'

Connection

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.

Cursor

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()') [['PostgreSQL...']]

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.

SQL API

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
>>> db.select('t1')
SELECT * FROM t1
[[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=('t1.id','t2.value'))
SELECT t1.id, t2.value FROM t1 JOIN t2 ON t1.id = t2.t1_id
[[1, 't2']]
>>> db.insert('t1',{'name':'abc'},returning='id')
INSERT INTO t1 (name) VALUES ('abc') RETURNING id
[2]
>>> db.update('t1',{'name':'xyz'},where={'name':'abc'})
UPDATE t1 SET name = 'xyz' WHERE name = 'abc'
2
>>> 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

    connection.prepare(stmt,params,name,call_type) 

    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
                autogenerated)
    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')

Logging

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
method).

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

Changelog

*   0.1     19-10-2012  Initial import
*   0.2     20-10-2012  Remove psycopg2 dep in setup.py
*   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)

Author

*   Paul Chakravarti ([email protected])

Master Repository/Issues

*   https://github.com/paulchakravarti/pgwrap