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556b4d461e
Added several links to the Python documentation using the 'intersphinx' extension.
492 lines
18 KiB
ReStructuredText
492 lines
18 KiB
ReStructuredText
More advanced topics
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====================
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.. sectionauthor:: Daniele Varrazzo <daniele.varrazzo@gmail.com>
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.. testsetup:: *
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import re
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import select
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cur.execute("CREATE TABLE atable (apoint point)")
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conn.commit()
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def wait(conn):
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while 1:
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state = conn.poll()
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if state == psycopg2.extensions.POLL_OK:
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break
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elif state == psycopg2.extensions.POLL_WRITE:
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select.select([], [conn.fileno()], [])
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elif state == psycopg2.extensions.POLL_READ:
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select.select([conn.fileno()], [], [])
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else:
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raise psycopg2.OperationalError("poll() returned %s" % state)
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aconn = psycopg2.connect(database='test', async=1)
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wait(aconn)
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acurs = aconn.cursor()
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.. index::
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double: Subclassing; Cursor
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double: Subclassing; Connection
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.. _subclassing-connection:
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.. _subclassing-cursor:
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Connection and cursor factories
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-------------------------------
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Psycopg exposes two new-style classes that can be sub-classed and expanded to
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adapt them to the needs of the programmer: `psycopg2.extensions.cursor`
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and `psycopg2.extensions.connection`. The `connection` class is
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usually sub-classed only to provide an easy way to create customized cursors
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but other uses are possible. `cursor` is much more interesting, because
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it is the class where query building, execution and result type-casting into
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Python variables happens.
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.. index::
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single: Example; Cursor subclass
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An example of cursor subclass performing logging is::
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import psycopg2
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import psycopg2.extensions
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import logging
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class LoggingCursor(psycopg2.extensions.cursor):
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def execute(self, sql, args=None):
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logger = logging.getLogger('sql_debug')
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logger.info(self.mogrify(sql, args))
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try:
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psycopg2.extensions.cursor.execute(self, sql, args)
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except Exception, exc:
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logger.error("%s: %s" % (exc.__class__.__name__, exc))
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raise
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conn = psycopg2.connect(DSN)
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cur = conn.cursor(cursor_factory=LoggingCursor)
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cur.execute("INSERT INTO mytable VALUES (%s, %s, %s);",
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(10, 20, 30))
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.. index::
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single: Objects; Creating new adapters
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single: Adaptation; Creating new adapters
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single: Data types; Creating new adapters
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.. _adapting-new-types:
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Adapting new Python types to SQL syntax
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---------------------------------------
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Any Python class or type can be adapted to an SQL string. Adaptation mechanism
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is similar to the Object Adaptation proposed in the :pep:`246` and is exposed
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by the `psycopg2.extensions.adapt()` function.
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The `~cursor.execute()` method adapts its arguments to the
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`~psycopg2.extensions.ISQLQuote` protocol. Objects that conform to this
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protocol expose a `!getquoted()` method returning the SQL representation
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of the object as a string (the method must return `!bytes` in Python 3).
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Optionally the conform object may expose a
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`~psycopg2.extensions.ISQLQuote.prepare()` method.
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There are two basic ways to have a Python object adapted to SQL:
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- the object itself is conform, or knows how to make itself conform. Such
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object must expose a `__conform__()` method that will be called with the
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protocol object as argument. The object can check that the protocol is
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`!ISQLQuote`, in which case it can return `!self` (if the object also
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implements `!getquoted()`) or a suitable wrapper object. This option is
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viable if you are the author of the object and if the object is specifically
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designed for the database (i.e. having Psycopg as a dependency and polluting
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its interface with the required methods doesn't bother you). For a simple
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example you can take a look at the source code for the
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`psycopg2.extras.Inet` object.
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- If implementing the `!ISQLQuote` interface directly in the object is not an
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option (maybe because the object to adapt comes from a third party library),
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you can use an *adaptation function*, taking the object to be adapted as
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argument and returning a conforming object. The adapter must be
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registered via the `~psycopg2.extensions.register_adapter()` function. A
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simple example wrapper is `!psycopg2.extras.UUID_adapter` used by the
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`~psycopg2.extras.register_uuid()` function.
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A convenient object to write adapters is the `~psycopg2.extensions.AsIs`
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wrapper, whose `!getquoted()` result is simply the `!str()`\ ing conversion of
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the wrapped object.
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.. index::
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single: Example; Types adaptation
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Example: mapping of a `!Point` class into the |point|_ PostgreSQL
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geometric type:
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.. doctest::
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>>> from psycopg2.extensions import adapt, register_adapter, AsIs
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>>> class Point(object):
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... def __init__(self, x, y):
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... self.x = x
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... self.y = y
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>>> def adapt_point(point):
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... return AsIs("'(%s, %s)'" % (adapt(point.x), adapt(point.y)))
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>>> register_adapter(Point, adapt_point)
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>>> cur.execute("INSERT INTO atable (apoint) VALUES (%s)",
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... (Point(1.23, 4.56),))
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.. |point| replace:: :sql:`point`
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.. _point: http://www.postgresql.org/docs/9.0/static/datatype-geometric.html#DATATYPE-GEOMETRIC
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The above function call results in the SQL command::
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INSERT INTO atable (apoint) VALUES ((1.23, 4.56));
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.. index:: Type casting
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.. _type-casting-from-sql-to-python:
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Type casting of SQL types into Python objects
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---------------------------------------------
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PostgreSQL objects read from the database can be adapted to Python objects
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through an user-defined adapting function. An adapter function takes two
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arguments: the object string representation as returned by PostgreSQL and the
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cursor currently being read, and should return a new Python object. For
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example, the following function parses the PostgreSQL :sql:`point`
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representation into the previously defined `!Point` class:
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>>> def cast_point(value, cur):
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... if value is None:
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... return None
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...
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... # Convert from (f1, f2) syntax using a regular expression.
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... m = re.match(r"\(([^)]+),([^)]+)\)", value)
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... if m:
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... return Point(float(m.group(1)), float(m.group(2)))
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... else:
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... raise InterfaceError("bad point representation: %r" % value)
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In order to create a mapping from a PostgreSQL type (either standard or
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user-defined), its OID must be known. It can be retrieved either by the second
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column of the `cursor.description`:
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>>> cur.execute("SELECT NULL::point")
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>>> point_oid = cur.description[0][1]
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>>> point_oid
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600
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or by querying the system catalog for the type name and namespace (the
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namespace for system objects is :sql:`pg_catalog`):
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>>> cur.execute("""
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... SELECT pg_type.oid
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... FROM pg_type JOIN pg_namespace
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... ON typnamespace = pg_namespace.oid
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... WHERE typname = %(typename)s
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... AND nspname = %(namespace)s""",
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... {'typename': 'point', 'namespace': 'pg_catalog'})
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>>> point_oid = cur.fetchone()[0]
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>>> point_oid
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600
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After you know the object OID, you can create and register the new type:
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>>> POINT = psycopg2.extensions.new_type((point_oid,), "POINT", cast_point)
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>>> psycopg2.extensions.register_type(POINT)
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The `~psycopg2.extensions.new_type()` function binds the object OIDs
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(more than one can be specified) to the adapter function.
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`~psycopg2.extensions.register_type()` completes the spell. Conversion
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is automatically performed when a column whose type is a registered OID is
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read:
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>>> cur.execute("SELECT '(10.2,20.3)'::point")
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>>> point = cur.fetchone()[0]
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>>> print type(point), point.x, point.y
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<class 'Point'> 10.2 20.3
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.. index::
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pair: Asynchronous; Notifications
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pair: LISTEN; SQL command
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pair: NOTIFY; SQL command
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.. _async-notify:
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Asynchronous notifications
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--------------------------
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Psycopg allows asynchronous interaction with other database sessions using the
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facilities offered by PostgreSQL commands |LISTEN|_ and |NOTIFY|_. Please
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refer to the PostgreSQL documentation for examples about how to use this form of
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communication.
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Notifications are instances of the `~psycopg2.extensions.Notify` object made
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available upon reception in the `connection.notifies` list. Notifications can
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be sent from Python code simply executing a :sql:`NOTIFY` command in an
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`~cursor.execute()` call.
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Because of the way sessions interact with notifications (see |NOTIFY|_
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documentation), you should keep the connection in :ref:`autocommit
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<autocommit>` mode if you wish to receive or send notifications in a timely
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manner.
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.. |LISTEN| replace:: :sql:`LISTEN`
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.. _LISTEN: http://www.postgresql.org/docs/9.0/static/sql-listen.html
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.. |NOTIFY| replace:: :sql:`NOTIFY`
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.. _NOTIFY: http://www.postgresql.org/docs/9.0/static/sql-notify.html
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Notifications are received after every query execution. If the user is
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interested in receiving notifications but not in performing any query, the
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`~connection.poll()` method can be used to check for new messages without
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wasting resources.
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A simple application could poll the connection from time to time to check if
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something new has arrived. A better strategy is to use some I/O completion
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function such as :py:func:`~select.select` to sleep until awaken from the kernel when there is
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some data to read on the connection, thereby using no CPU unless there is
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something to read::
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import select
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import psycopg2
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import psycopg2.extensions
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conn = psycopg2.connect(DSN)
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conn.set_isolation_level(psycopg2.extensions.ISOLATION_LEVEL_AUTOCOMMIT)
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curs = conn.cursor()
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curs.execute("LISTEN test;")
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print "Waiting for notifications on channel 'test'"
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while 1:
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if select.select([conn],[],[],5) == ([],[],[]):
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print "Timeout"
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else:
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conn.poll()
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while conn.notifies:
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notify = conn.notifies.pop()
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print "Got NOTIFY:", notify.pid, notify.channel, notify.payload
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Running the script and executing a command such as :sql:`NOTIFY test, 'hello'`
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in a separate :program:`psql` shell, the output may look similar to::
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Waiting for notifications on channel 'test'
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Timeout
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Timeout
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Got NOTIFY: 6535 test hello
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Timeout
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...
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Note that the payload is only available from PostgreSQL 9.0: notifications
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received from a previous version server will have the
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`~psycopg2.extensions.Notify.payload` attribute set to the empty string.
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.. versionchanged:: 2.3
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Added `~psycopg2.extensions.Notify` object and handling notification
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payload.
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.. index::
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double: Asynchronous; Connection
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.. _async-support:
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Asynchronous support
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--------------------
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.. versionadded:: 2.2.0
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Psycopg can issue asynchronous queries to a PostgreSQL database. An asynchronous
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communication style is established passing the parameter *async*\=1 to the
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`~psycopg2.connect()` function: the returned connection will work in
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*asynchronous mode*.
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In asynchronous mode, a Psycopg connection will rely on the caller to poll the
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socket file descriptor, checking if it is ready to accept data or if a query
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result has been transferred and is ready to be read on the client. The caller
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can use the method `~connection.fileno()` to get the connection file
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descriptor and `~connection.poll()` to make communication proceed according to
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the current connection state.
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The following is an example loop using methods `!fileno()` and `!poll()`
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together with the Python :py:func:`~select.select` function in order to carry on
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asynchronous operations with Psycopg::
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def wait(conn):
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while 1:
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state = conn.poll()
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if state == psycopg2.extensions.POLL_OK:
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break
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elif state == psycopg2.extensions.POLL_WRITE:
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select.select([], [conn.fileno()], [])
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elif state == psycopg2.extensions.POLL_READ:
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select.select([conn.fileno()], [], [])
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else:
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raise psycopg2.OperationalError("poll() returned %s" % state)
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The above loop of course would block an entire application: in a real
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asynchronous framework, `!select()` would be called on many file descriptors
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waiting for any of them to be ready. Nonetheless the function can be used to
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connect to a PostgreSQL server only using nonblocking commands and the
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connection obtained can be used to perform further nonblocking queries. After
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`!poll()` has returned `~psycopg2.extensions.POLL_OK`, and thus `!wait()` has
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returned, the connection can be safely used:
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>>> aconn = psycopg2.connect(database='test', async=1)
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>>> wait(aconn)
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>>> acurs = aconn.cursor()
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Notice that there are a few other requirements to be met in order to have a
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completely non-blocking connection attempt: see the libpq documentation for
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|PQconnectStart|_.
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.. |PQconnectStart| replace:: `!PQconnectStart()`
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.. _PQconnectStart: http://www.postgresql.org/docs/9.0/static/libpq-connect.html#LIBPQ-PQCONNECTSTART
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The same loop should be also used to perform nonblocking queries: after
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sending a query via `~cursor.execute()` or `~cursor.callproc()`, call
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`!poll()` on the connection available from `cursor.connection` until it
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returns `!POLL_OK`, at which point the query has been completely sent to the
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server and, if it produced data, the results have been transferred to the
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client and available using the regular cursor methods:
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>>> acurs.execute("SELECT pg_sleep(5); SELECT 42;")
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>>> wait(acurs.connection)
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>>> acurs.fetchone()[0]
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42
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When an asynchronous query is being executed, `connection.isexecuting()` returns
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`!True`. Two cursors can't execute concurrent queries on the same asynchronous
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connection.
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There are several limitations in using asynchronous connections: the
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connection is always in :ref:`autocommit <autocommit>` mode and it is not
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possible to change it using `~connection.set_isolation_level()`. So a
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transaction is not implicitly started at the first query and is not possible
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to use methods `~connection.commit()` and `~connection.rollback()`: you can
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manually control transactions using `~cursor.execute()` to send database
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commands such as :sql:`BEGIN`, :sql:`COMMIT` and :sql:`ROLLBACK`.
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With asynchronous connections it is also not possible to use
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`~connection.set_client_encoding()`, `~cursor.executemany()`, :ref:`large
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objects <large-objects>`, :ref:`named cursors <server-side-cursors>`.
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:ref:`COPY commands <copy>` are not supported either in asynchronous mode, but
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this will be probably implemented in a future release.
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.. index::
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single: Greenlet
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single: Coroutine
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single: Eventlet
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single: gevent
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single: Wait callback
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.. _green-support:
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Support to coroutine libraries
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------------------------------
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.. versionadded:: 2.2.0
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Psycopg can be used together with coroutine_\-based libraries, and participate
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to cooperative multithreading.
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Coroutine-based libraries (such as Eventlet_ or gevent_) can usually patch the
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Python standard library in order to enable a coroutine switch in the presence of
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blocking I/O: the process is usually referred as making the system *green*, in
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reference to the `green threads`_.
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Because Psycopg is a C extension module, it is not possible for coroutine
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libraries to patch it: Psycopg instead enables cooperative multithreading by
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allowing the registration of a *wait callback* using the
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`psycopg2.extensions.set_wait_callback()` function. When a wait callback is
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registered, Psycopg will use `libpq non-blocking calls`__ instead of the regular
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blocking ones, and will delegate to the callback the responsibility to wait
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for the socket to become readable or writable.
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Working this way, the caller does not have the complete freedom to schedule the
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socket check whenever they want as with an :ref:`asynchronous connection
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<async-support>`, but has the advantage of maintaining a complete |DBAPI|
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semantics: from the point of view of the end user, all Psycopg functions and
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objects will work transparently in the coroutine environment (blocking the
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calling green thread and giving other green threads the possibility to be
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scheduled), allowing non modified code and third party libraries (such as
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SQLAlchemy_) to be used in coroutine-based programs.
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.. warning::
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Psycopg connections are not *green thread safe* and can't be used
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concurrently by different green threads. Each connection has a lock
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used to serialize requests from different cursors to the backend process.
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The lock is held for the duration of the command: if the control switched
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to a different thread and the latter tried to access the same connection,
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the result would be a deadlock.
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Therefore, programmers are advised to either avoid sharing connections
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between coroutines or to use a library-friendly lock to synchronize shared
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connections, e.g. for pooling.
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Coroutine libraries authors should provide a callback implementation (and
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possibly a method to register it) to make Psycopg as green as they want. An
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example callback (using `!select()` to block) is provided as
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`psycopg2.extras.wait_select()`: it boils down to something similar to::
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def wait_select(conn):
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while 1:
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state = conn.poll()
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if state == extensions.POLL_OK:
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break
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elif state == extensions.POLL_READ:
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select.select([conn.fileno()], [], [])
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elif state == extensions.POLL_WRITE:
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select.select([], [conn.fileno()], [])
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else:
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raise OperationalError("bad state from poll: %s" % state)
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Providing callback functions for the single coroutine libraries is out of
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psycopg2 scope, as the callback can be tied to the libraries' implementation
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details. You can check the `psycogreen`_ project for further informations and
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resources about the topic.
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.. _coroutine: http://en.wikipedia.org/wiki/Coroutine
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.. _greenlet: http://pypi.python.org/pypi/greenlet
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.. _green threads: http://en.wikipedia.org/wiki/Green_threads
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.. _Eventlet: http://eventlet.net/
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.. _gevent: http://www.gevent.org/
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.. _SQLAlchemy: http://www.sqlalchemy.org/
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.. _psycogreen: http://bitbucket.org/dvarrazzo/psycogreen/
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.. __: http://www.postgresql.org/docs/9.0/static/libpq-async.html
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.. warning::
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:ref:`COPY commands <copy>` are currently not supported when a wait callback
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is registered, but they will be probably implemented in a future release.
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:ref:`Large objects <large-objects>` are not supported either: they are
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not compatible with asynchronous connections.
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.. testcode::
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:hide:
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aconn.close()
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conn.rollback()
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cur.execute("DROP TABLE atable")
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conn.commit()
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cur.close()
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conn.close()
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