psycopg2.extras – Miscellaneous goodies for Psycopg 2 — Psycopg v2.4.2 documentation

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# `psycopg2.extras` – Miscellaneous goodies for Psycopg 2

This module is a generic place used to hold little helper functions and classes until a better place in the distribution is found.

## Connection and cursor subclasses

A few objects that change the way the results are returned by the cursor or modify the object behavior in some other way. Typically `connection` subclasses are passed as connection_factory argument to `connect()` so that the connection will generate the matching `cursor` subclass. Alternatively a `cursor` subclass can be used one-off by passing it as the cursor_factory argument to the `cursor()` method of a regular `connection`.

### Dictionary-like cursor

The dict cursors allow to access to the retrieved records using an iterface similar to the Python dictionaries instead of the tuples.

    >>> dict_cur = conn.cursor(cursor_factory=psycopg2.extras.DictCursor)
    >>> dict_cur.execute("INSERT INTO test (num, data) VALUES(%s, %s)",
    ...                  (100, "abc'def"))
    >>> dict_cur.execute("SELECT * FROM test")
    >>> rec = dict_cur.fetchone()
    >>> rec['id']
    1
    >>> rec['num']
    100
    >>> rec['data']
    "abc'def"

The records still support indexing as the original tuple:

    >>> rec[2]
    "abc'def"

class `psycopg2.extras.` `DictCursor`(*args, **kwargs)

  A cursor that keeps a list of column name -> index mappings.

class `psycopg2.extras.` `DictConnection`

  A connection that uses `DictCursor` automatically.

class `psycopg2.extras.` `DictRow`(cursor)

  A row object that allow by-colmun-name access to data.

### Real dictionary cursor

class `psycopg2.extras.` `RealDictCursor`(*args, **kwargs)

  A cursor that uses a real dict as the base type for rows.

  Note that this cursor is extremely specialized and does not allow the normal access (using integer indices) to fetched data. If you need to access database rows both as a dictionary and a list, then use the generic `DictCursor` instead of `RealDictCursor`.

class `psycopg2.extras.` `RealDictConnection`

  A connection that uses `RealDictCursor` automatically.

class `psycopg2.extras.` `RealDictRow`(cursor)

  A `dict` subclass representing a data record.

### `namedtuple` cursor

New in version 2.3.

These objects require `collections.namedtuple()` to be found, so it is available out-of-the-box only from Python 2.6. Anyway, the namedtuple implementation is compatible with previous Python versions, so all you have to do is to download it and make it available where we expect it to be...

    from somewhere import namedtuple
    import collections
    collections.namedtuple = namedtuple
    from psycopg.extras import NamedTupleConnection
    # ...

class `psycopg2.extras.` `NamedTupleCursor`

  A cursor that generates results as `namedtuple`.

  `fetch*()` methods will return named tuples instead of regular tuples, so their elements can be accessed both as regular numeric items as well as attributes.

      >>> nt_cur = conn.cursor(cursor_factory=psycopg2.extras.NamedTupleCursor)
      >>> rec = nt_cur.fetchone()
      >>> rec
      Record(id=1, num=100, data="abc'def")
      >>> rec[1]
      100
      >>> rec.data
      "abc'def"

class `psycopg2.extras.` `NamedTupleConnection`

  A connection that uses `NamedTupleCursor` automatically.

### Logging cursor

class `psycopg2.extras.` `LoggingConnection`

  A connection that logs all queries to a file or logger object.

  `initialize`(logobj)

    Initialize the connection to log to `logobj`.

    The `logobj` parameter can be an open file object or a Logger instance from the standard logging module.

  `filter`(msg, curs)

    Filter the query before logging it.

    This is the method to overwrite to filter unwanted queries out of the log or to add some extra data to the output. The default implementation just does nothing.

class `psycopg2.extras.` `LoggingCursor`

  A cursor that logs queries using its connection logging facilities.

class `psycopg2.extras.` `MinTimeLoggingConnection`

  A connection that logs queries based on execution time.

  This is just an example of how to sub-class `LoggingConnection` to provide some extra filtering for the logged queries. Both the `inizialize()` and `filter()` methods are overwritten to make sure that only queries executing for more than `mintime` ms are logged.

  Note that this connection uses the specialized cursor `MinTimeLoggingCursor`.

class `psycopg2.extras.` `MinTimeLoggingCursor`

  The cursor sub-class companion to `MinTimeLoggingConnection`.

## Additional data types

### Hstore data type

New in version 2.3.

The `hstore` data type is a key-value store embedded in PostgreSQL. It has been available for several server versions but with the release 9.0 it has been greatly improved in capacity and usefulness with the addiction of many functions. It supports GiST or GIN indexes allowing search by keys or key/value pairs as well as regular BTree indexes for equality, uniqueness etc.

Psycopg can convert Python `dict` objects to and from `hstore` structures. Only dictionaries with string/unicode keys and values are supported. `None` is also allowed as value but not as a key. Psycopg uses a more efficient `hstore` representation when dealing with PostgreSQL 9.0 but previous server versions are supported as well. By default the adapter/typecaster are disabled: they can be enabled using the `register_hstore()` function.

`psycopg2.extras.` `register_hstore`(conn_or_curs, globally=False, unicode=False, oid=None)

  Register adapter and typecaster for `dict`-`hstore` conversions.

  Parameters: | conn_or_curs – a connection or cursor: the typecaster will be registered only on this object unless globally is set to `True` globally – register the adapter globally, not only on conn_or_curs unicode – if `True`, keys and values returned from the database will be `unicode` instead of `str`. The option is not available on Python 3 oid – the OID of the `hstore` type if known. If not, it will be queried on conn_or_curs

  The connection or cursor passed to the function will be used to query the database and look for the OID of the `hstore` type (which may be different across databases). If querying is not desirable (e.g. with asynchronous connections) you may specify it in the oid parameter (it can be found using a query such as `SELECT 'hstore'::regtype::oid;`).

  Note that, when passing a dictionary from Python to the database, both strings and unicode keys and values are supported. Dictionaries returned from the database have keys/values according to the unicode parameter.

  The `hstore` contrib module must be already installed in the database (executing the `hstore.sql` script in your `contrib` directory). Raise `ProgrammingError` if the type is not found.

  Changed in version 2.4: added the oid parameter. If not specified, the typecaster is installed also if `hstore` is not installed in the `public` schema.

### Composite types casting

New in version 2.4.

Using `register_composite()` it is possible to cast a PostgreSQL composite type (e.g. created with `CREATE TYPE` command) into a Python named tuple, or into a regular tuple if `collections.namedtuple()` is not found.

    >>> cur.execute("CREATE TYPE card AS (value int, suit text);")
    >>> psycopg2.extras.register_composite('card', cur)
    <psycopg2.extras.CompositeCaster object at 0x...>

    >>> cur.execute("select (8, 'hearts')::card")
    >>> cur.fetchone()[0]
    card(value=8, suit='hearts')

Nested composite types are handled as expected, but the type of the composite components must be registered as well.

    >>> cur.execute("CREATE TYPE card_back AS (face card, back text);")
    >>> psycopg2.extras.register_composite('card_back', cur)
    <psycopg2.extras.CompositeCaster object at 0x...>

    >>> cur.execute("select ((8, 'hearts'), 'blue')::card_back")
    >>> cur.fetchone()[0]
    card_back(face=card(value=8, suit='hearts'), back='blue')

Adaptation from Python tuples to composite types is automatic instead and requires no adapter registration.

`psycopg2.extras.` `register_composite`(name, conn_or_curs, globally=False)

  Register a typecaster to convert a composite type into a tuple.

  Parameters: | name – the name of a PostgreSQL composite type, e.g. created using the `CREATE TYPE` command conn_or_curs – a connection or cursor used to find the type oid and components; the typecaster is registered in a scope limited to this object, unless globally is set to `True` globally – if `False` (default) register the typecaster only on conn_or_curs, otherwise register it globally
  Returns: | the registered `CompositeCaster` instance responsible for the conversion

class `psycopg2.extras.` `CompositeCaster`(name, oid, attrs)

  Helps conversion of a PostgreSQL composite type into a Python object.

  The class is usually created by the `register_composite()` function.

  `name`

    The name of the PostgreSQL type.

  `oid`

    The oid of the PostgreSQL type.

  `type`

    The type of the Python objects returned. If `collections.namedtuple()` is available, it is a named tuple with attributes equal to the type components. Otherwise it is just the `tuple` object.

  `attnames`

    List of component names of the type to be casted.

  `atttypes`

    List of component type oids of the type to be casted.

### UUID data type

New in version 2.0.9.

Changed in version 2.0.13: added UUID array support.

    >>> psycopg2.extras.register_uuid()
    <psycopg2._psycopg.type object at 0x...>

    >>> # Python UUID can be used in SQL queries
    >>> import uuid
    >>> my_uuid = uuid.UUID('{12345678-1234-5678-1234-567812345678}')
    >>> psycopg2.extensions.adapt(my_uuid).getquoted()
    "'12345678-1234-5678-1234-567812345678'::uuid"

    >>> # PostgreSQL UUID are transformed into Python UUID objects.
    >>> cur.execute("SELECT 'a0eebc99-9c0b-4ef8-bb6d-6bb9bd380a11'::uuid")
    >>> cur.fetchone()[0]
    UUID('a0eebc99-9c0b-4ef8-bb6d-6bb9bd380a11')

`psycopg2.extras.` `register_uuid`(oids=None, conn_or_curs=None)

  Create the UUID type and an uuid.UUID adapter.

class `psycopg2.extras.` `UUID_adapter`(uuid)

  Adapt Python’s uuid.UUID type to PostgreSQL’s uuid.

### `inet` data type

New in version 2.0.9.

    >>> psycopg2.extras.register_inet()
    <psycopg2._psycopg.type object at 0x...>

    >>> cur.mogrify("SELECT %s", (Inet('127.0.0.1/32'),))
    "SELECT E'127.0.0.1/32'::inet"

    >>> cur.execute("SELECT '192.168.0.1/24'::inet")
    >>> cur.fetchone()[0].addr
    '192.168.0.1/24'

`psycopg2.extras.` `register_inet`()

  Create the INET type and an Inet adapter.

class `psycopg2.extras.` `Inet`(addr)

  Wrap a string to allow for correct SQL-quoting of inet values.

  Note that this adapter does NOT check the passed value to make sure it really is an inet-compatible address but DOES call adapt() on it to make sure it is impossible to execute an SQL-injection by passing an evil value to the initializer.

## Fractional time zones

`psycopg2.extras.` `register_tstz_w_secs`(oids=None, conn_or_curs=None)

  The function used to register an alternate type caster for `TIMESTAMP WITH TIME ZONE` to deal with historical time zones with seconds in the UTC offset.

  These are now correctly handled by the default type caster, so currently the function doesn’t do anything.

  New in version 2.0.9.

  Changed in version 2.2.2: function is no-op: see Time zones handling.

## Coroutine support

`psycopg2.extras.` `wait_select`(conn)

  Wait until a connection or cursor has data available.

  The function is an example of a wait callback to be registered with `set_wait_callback()`. This function uses `select()` to wait for data available.

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