More advanced topics — Psycopg 2.5.2 documentation

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# More advanced topics

## Connection and cursor factories

Psycopg exposes two new-style classes that can be sub-classed and expanded to adapt them to the needs of the programmer: `psycopg2.extensions.cursor` and `psycopg2.extensions.connection`. The `connection` class is usually sub-classed only to provide an easy way to create customized cursors but other uses are possible. `cursor` is much more interesting, because it is the class where query building, execution and result type-casting into Python variables happens.

The `extras` module contains several examples of connection and cursor sublcasses.

Note

If you only need a customized cursor class, since Psycopg 2.5 you can use the `cursor_factory` parameter of a regular connection instead of creating a new `connection` subclass.

An example of cursor subclass performing logging is:

    import psycopg2
    import psycopg2.extensions
    import logging

    class LoggingCursor(psycopg2.extensions.cursor):
        def execute(self, sql, args=None):
            logger = logging.getLogger('sql_debug')
            logger.info(self.mogrify(sql, args))

            try:
                psycopg2.extensions.cursor.execute(self, sql, args)
            except Exception, exc:
                logger.error("%s: %s" % (exc.__class__.__name__, exc))
                raise

    conn = psycopg2.connect(DSN)
    cur = conn.cursor(cursor_factory=LoggingCursor)
    cur.execute("INSERT INTO mytable VALUES (%s, %s, %s);",
                 (10, 20, 30))

## Adapting new Python types to SQL syntax

Any Python class or type can be adapted to an SQL string. Adaptation mechanism is similar to the Object Adaptation proposed in the PEP 246 and is exposed by the `psycopg2.extensions.adapt()` function.

The `execute()` method adapts its arguments to the `ISQLQuote` protocol. Objects that conform to this protocol expose a `getquoted()` method returning the SQL representation of the object as a string (the method must return `bytes` in Python 3). Optionally the conform object may expose a `prepare()` method.

There are two basic ways to have a Python object adapted to SQL:

- the object itself is conform, or knows how to make itself conform. Such object must expose a `__conform__()` method that will be called with the protocol object as argument. The object can check that the protocol is `ISQLQuote`, in which case it can return `self` (if the object also implements `getquoted()`) or a suitable wrapper object. This option is viable if you are the author of the object and if the object is specifically designed for the database (i.e. having Psycopg as a dependency and polluting its interface with the required methods doesn’t bother you). For a simple example you can take a look at the source code for the `psycopg2.extras.Inet` object.
- If implementing the `ISQLQuote` interface directly in the object is not an option (maybe because the object to adapt comes from a third party library), you can use an adaptation function, taking the object to be adapted as argument and returning a conforming object. The adapter must be registered via the `register_adapter()` function. A simple example wrapper is `psycopg2.extras.UUID_adapter` used by the `register_uuid()` function.

A convenient object to write adapters is the `AsIs` wrapper, whose `getquoted()` result is simply the `str()`ing conversion of the wrapped object.

Example: mapping of a `Point` class into the `point` PostgreSQL geometric type:

    >>> from psycopg2.extensions import adapt, register_adapter, AsIs

    >>> class Point(object):
    ...    def __init__(self, x, y):
    ...        self.x = x
    ...        self.y = y

    >>> def adapt_point(point):
    ...     return AsIs("'(%s, %s)'" % (adapt(point.x), adapt(point.y)))

    >>> register_adapter(Point, adapt_point)

    >>> cur.execute("INSERT INTO atable (apoint) VALUES (%s)",
    ...             (Point(1.23, 4.56),))

The above function call results in the SQL command:

    INSERT INTO atable (apoint) VALUES ('(1.23, 4.56)');

## Type casting of SQL types into Python objects

PostgreSQL objects read from the database can be adapted to Python objects through an user-defined adapting function. An adapter function takes two arguments: the object string representation as returned by PostgreSQL and the cursor currently being read, and should return a new Python object. For example, the following function parses the PostgreSQL `point` representation into the previously defined `Point` class:

    >>> def cast_point(value, cur):
    ...    if value is None:
    ...        return None
    ...
    ...    # Convert from (f1, f2) syntax using a regular expression.
    ...    m = re.match(r"\(([^)]+),([^)]+)\)", value)
    ...    if m:
    ...        return Point(float(m.group(1)), float(m.group(2)))
    ...    else:
    ...        raise InterfaceError("bad point representation: %r" % value)

In order to create a mapping from a PostgreSQL type (either standard or user-defined), its OID must be known. It can be retrieved either by the second column of the `cursor.description`:

    >>> cur.execute("SELECT NULL::point")
    >>> point_oid = cur.description[0][1]
    >>> point_oid
    600

or by querying the system catalog for the type name and namespace (the namespace for system objects is `pg_catalog`):

    >>> cur.execute("""
    ...    SELECT pg_type.oid
    ...      FROM pg_type JOIN pg_namespace
    ...             ON typnamespace = pg_namespace.oid
    ...     WHERE typname = %(typename)s
    ...       AND nspname = %(namespace)s""",
    ...    {'typename': 'point', 'namespace': 'pg_catalog'})
    >>> point_oid = cur.fetchone()[0]
    >>> point_oid
    600

After you know the object OID, you can create and register the new type:

    >>> POINT = psycopg2.extensions.new_type((point_oid,), "POINT", cast_point)
    >>> psycopg2.extensions.register_type(POINT)

The `new_type()` function binds the object OIDs (more than one can be specified) to the adapter function. `register_type()` completes the spell. Conversion is automatically performed when a column whose type is a registered OID is read:

    >>> cur.execute("SELECT '(10.2,20.3)'::point")
    >>> point = cur.fetchone()[0]
    >>> print type(point), point.x, point.y
    <class 'Point'> 10.2 20.3

A typecaster created by `new_type()` can be also used with `new_array_type()` to create a typecaster converting a PostgreSQL array into a Python list.

## Asynchronous notifications

Psycopg allows asynchronous interaction with other database sessions using the facilities offered by PostgreSQL commands `LISTEN` and `NOTIFY`. Please refer to the PostgreSQL documentation for examples about how to use this form of communication.

Notifications are instances of the `Notify` object made available upon reception in the `connection.notifies` list. Notifications can be sent from Python code simply executing a `NOTIFY` command in an `execute()` call.

Because of the way sessions interact with notifications (see `NOTIFY` documentation), you should keep the connection in `autocommit` mode if you wish to receive or send notifications in a timely manner.

Notifications are received after every query execution. If the user is interested in receiving notifications but not in performing any query, the `poll()` method can be used to check for new messages without wasting resources.

A simple application could poll the connection from time to time to check if something new has arrived. A better strategy is to use some I/O completion function such as `select()` to sleep until awaken from the kernel when there is some data to read on the connection, thereby using no CPU unless there is something to read:

    import select
    import psycopg2
    import psycopg2.extensions

    conn = psycopg2.connect(DSN)
    conn.set_isolation_level(psycopg2.extensions.ISOLATION_LEVEL_AUTOCOMMIT)

    curs = conn.cursor()
    curs.execute("LISTEN test;")

    print "Waiting for notifications on channel 'test'"
    while 1:
        if select.select([conn],[],[],5) == ([],[],[]):
            print "Timeout"
        else:
            conn.poll()
            while conn.notifies:
                notify = conn.notifies.pop()
                print "Got NOTIFY:", notify.pid, notify.channel, notify.payload

Running the script and executing a command such as `NOTIFY test, 'hello'` in a separate psql shell, the output may look similar to:

    Waiting for notifications on channel 'test'
    Timeout
    Timeout
    Got NOTIFY: 6535 test hello
    Timeout
    ...

Note that the payload is only available from PostgreSQL 9.0: notifications received from a previous version server will have the `payload` attribute set to the empty string.

Changed in version 2.3: Added `Notify` object and handling notification payload.

## Asynchronous support

New in version 2.2.0.

Psycopg can issue asynchronous queries to a PostgreSQL database. An asynchronous communication style is established passing the parameter async=1 to the `connect()` function: the returned connection will work in asynchronous mode.

In asynchronous mode, a Psycopg connection will rely on the caller to poll the socket file descriptor, checking if it is ready to accept data or if a query result has been transferred and is ready to be read on the client. The caller can use the method `fileno()` to get the connection file descriptor and `poll()` to make communication proceed according to the current connection state.

The following is an example loop using methods `fileno()` and `poll()` together with the Python `select()` function in order to carry on asynchronous operations with Psycopg:

    def wait(conn):
        while 1:
            state = conn.poll()
            if state == psycopg2.extensions.POLL_OK:
                break
            elif state == psycopg2.extensions.POLL_WRITE:
                select.select([], [conn.fileno()], [])
            elif state == psycopg2.extensions.POLL_READ:
                select.select([conn.fileno()], [], [])
            else:
                raise psycopg2.OperationalError("poll() returned %s" % state)

The above loop of course would block an entire application: in a real asynchronous framework, `select()` would be called on many file descriptors waiting for any of them to be ready. Nonetheless the function can be used to connect to a PostgreSQL server only using nonblocking commands and the connection obtained can be used to perform further nonblocking queries. After `poll()` has returned `POLL_OK`, and thus `wait()` has returned, the connection can be safely used:

    >>> aconn = psycopg2.connect(database='test', async=1)
    >>> wait(aconn)
    >>> acurs = aconn.cursor()

Note that there are a few other requirements to be met in order to have a completely non-blocking connection attempt: see the libpq documentation for `PQconnectStart()`.

The same loop should be also used to perform nonblocking queries: after sending a query via `execute()` or `callproc()`, call `poll()` on the connection available from `cursor.connection` until it returns `POLL_OK`, at which point the query has been completely sent to the server and, if it produced data, the results have been transferred to the client and available using the regular cursor methods:

    >>> acurs.execute("SELECT pg_sleep(5); SELECT 42;")
    >>> wait(acurs.connection)
    >>> acurs.fetchone()[0]
    42

When an asynchronous query is being executed, `connection.isexecuting()` returns `True`. Two cursors can’t execute concurrent queries on the same asynchronous connection.

There are several limitations in using asynchronous connections: the connection is always in `autocommit` mode and it is not possible to change it. So a transaction is not implicitly started at the first query and is not possible to use methods `commit()` and `rollback()`: you can manually control transactions using `execute()` to send database commands such as `BEGIN`, `COMMIT` and `ROLLBACK`. Similarly `set_session()` can’t be used but it is still possible to invoke the `SET` command with the proper `default_transaction_...` parameter.

With asynchronous connections it is also not possible to use `set_client_encoding()`, `executemany()`, large objects, named cursors.

COPY commands are not supported either in asynchronous mode, but this will be probably implemented in a future release.

## Support for coroutine libraries

New in version 2.2.0.

Psycopg can be used together with coroutine-based libraries and participate in cooperative multithreading.

Coroutine-based libraries (such as Eventlet or gevent) can usually patch the Python standard library in order to enable a coroutine switch in the presence of blocking I/O: the process is usually referred as making the system green, in reference to the green threads.

Because Psycopg is a C extension module, it is not possible for coroutine libraries to patch it: Psycopg instead enables cooperative multithreading by allowing the registration of a wait callback using the `psycopg2.extensions.set_wait_callback()` function. When a wait callback is registered, Psycopg will use libpq non-blocking calls instead of the regular blocking ones, and will delegate to the callback the responsibility to wait for the socket to become readable or writable.

Working this way, the caller does not have the complete freedom to schedule the socket check whenever they want as with an asynchronous connection, but has the advantage of maintaining a complete DB API 2.0 semantics: from the point of view of the end user, all Psycopg functions and objects will work transparently in the coroutine environment (blocking the calling green thread and giving other green threads the possibility to be scheduled), allowing non modified code and third party libraries (such as SQLAlchemy) to be used in coroutine-based programs.

Warning

Psycopg connections are not green thread safe and can’t be used concurrently by different green threads. Trying to execute more than one command at time using one cursor per thread will result in an error (or a deadlock on versions before 2.4.2).

Therefore, programmers are advised to either avoid sharing connections between coroutines or to use a library-friendly lock to synchronize shared connections, e.g. for pooling.

Coroutine libraries authors should provide a callback implementation (and possibly a method to register it) to make Psycopg as green as they want. An example callback (using `select()` to block) is provided as `psycopg2.extras.wait_select()`: it boils down to something similar to:

    def wait_select(conn):
        while 1:
            state = conn.poll()
            if state == extensions.POLL_OK:
                break
            elif state == extensions.POLL_READ:
                select.select([conn.fileno()], [], [])
            elif state == extensions.POLL_WRITE:
                select.select([], [conn.fileno()], [])
            else:
                raise OperationalError("bad state from poll: %s" % state)

Providing callback functions for the single coroutine libraries is out of psycopg2 scope, as the callback can be tied to the libraries’ implementation details. You can check the psycogreen project for further informations and resources about the topic.

Warning

COPY commands are currently not supported when a wait callback is registered, but they will be probably implemented in a future release.

Large objects are not supported either: they are not compatible with asynchronous connections.

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