# SQLAlchemy 0.6.0 Documentation

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Version: 0.6.0 Last Updated: 04/18/2010 19:16:18

# PostgreSQL

Support for the PostgreSQL database.

For information on connecting using specific drivers, see the documentation section regarding that driver.

## Sequences/SERIAL

PostgreSQL supports sequences, and SQLAlchemy uses these as the default means of creating new primary key values for integer-based primary key columns. When creating tables, SQLAlchemy will issue the `SERIAL` datatype for integer-based primary key columns, which generates a sequence corresponding to the column and associated with it based on a naming convention.

To specify a specific named sequence to be used for primary key generation, use the `Sequence()` construct:

    Table('sometable', metadata,
            Column('id', Integer, Sequence('some_id_seq'), primary_key=True)
        )

Currently, when SQLAlchemy issues a single insert statement, to fulfill the contract of having the “last insert identifier” available, the sequence is executed independently beforehand and the new value is retrieved, to be used in the subsequent insert. Note that when an `insert()` construct is executed using “executemany” semantics, the sequence is not pre-executed and normal PG SERIAL behavior is used.

PostgreSQL 8.2 supports an `INSERT...RETURNING` syntax which SQLAlchemy supports as well. A future release of SQLA will use this feature by default in lieu of sequence pre-execution in order to retrieve new primary key values, when available.

## INSERT/UPDATE...RETURNING

The dialect supports PG 8.2’s `INSERT..RETURNING`, `UPDATE..RETURNING` and `DELETE..RETURNING` syntaxes, but must be explicitly enabled on a per-statement basis:

    # INSERT..RETURNING
    result = table.insert().returning(table.c.col1, table.c.col2).\
        values(name='foo')
    print result.fetchall()

    # UPDATE..RETURNING
    result = table.update().returning(table.c.col1, table.c.col2).\
        where(table.c.name=='foo').values(name='bar')
    print result.fetchall()

    # DELETE..RETURNING
    result = table.delete().returning(table.c.col1, table.c.col2).\
        where(table.c.name=='foo')
    print result.fetchall()

## Indexes

PostgreSQL supports partial indexes. To create them pass a postgresql_where option to the Index constructor:

    Index('my_index', my_table.c.id, postgresql_where=tbl.c.value > 10)

## PostgresSQL Column Types

class `sqlalchemy.dialects.postgresql.base.``ARRAY`(item_type, mutable=True)

  Bases: `sqlalchemy.types.MutableType`, `sqlalchemy.types.Concatenable`, `sqlalchemy.types.TypeEngine`

  Postgresql ARRAY type.

  Represents values as Python lists.

  Note: be sure to read the notes for `MutableType` regarding ORM performance implications.

  `__init__`(item_type, mutable=True)

    Construct an ARRAY.

    E.g.:

        Column('myarray', ARRAY(Integer))

    Arguments are:

    Parameters:

    - item_type – The data type of items of this array. Note that dimensionality is irrelevant here, so multi-dimensional arrays like `INTEGER[][]`, are constructed as `ARRAY(Integer)`, not as `ARRAY(ARRAY(Integer))` or such. The type mapping figures out on the fly
    - mutable – Defaults to True: specify whether lists passed to this class should be considered mutable. If so, generic copy operations (typically used by the ORM) will shallow-copy values.

class `sqlalchemy.dialects.postgresql.base.``BIT`(*args, **kwargs)

  Bases: `sqlalchemy.types.TypeEngine`

  `__init__`(*args, **kwargs)

class `sqlalchemy.dialects.postgresql.base.``BYTEA`(length=None)

  Bases: `sqlalchemy.types.LargeBinary`

  `__init__`(length=None)

    Construct a LargeBinary type.

    Parameter:

    length – optional, a length for the column for use in DDL statements, for those BLOB types that accept a length (i.e. MySQL). It does not produce a small BINARY/VARBINARY type - use the BINARY/VARBINARY types specifically for those. May be safely omitted if no `CREATE TABLE` will be issued. Certain databases may require a length for use in DDL, and will raise an exception when the `CREATE TABLE` DDL is issued.

class `sqlalchemy.dialects.postgresql.base.``CIDR`(*args, **kwargs)

  Bases: `sqlalchemy.types.TypeEngine`

  `__init__`(*args, **kwargs)

class `sqlalchemy.dialects.postgresql.base.``DOUBLE_PRECISION`(precision=None, asdecimal=False, **kwargs)

  Bases: `sqlalchemy.types.Float`

  `__init__`(precision=None, asdecimal=False, **kwargs)

    Construct a Float.

    Parameters:

    - precision – the numeric precision for use in DDL `CREATE TABLE`.
    - asdecimal – the same flag as that of `Numeric`, but defaults to `False`. Note that setting this flag to `True` results in floating point conversion.

class `sqlalchemy.dialects.postgresql.base.``ENUM`(*enums, **kw)

  Bases: `sqlalchemy.types.Enum`

  `__init__`(*enums, **kw)

    Construct an enum.

    Keyword arguments which don’t apply to a specific backend are ignored by that backend.

    Parameters:

    - *enums – string or unicode enumeration labels. If unicode labels are present, the convert_unicode flag is auto-enabled.
    - convert_unicode – Enable unicode-aware bind parameter and result-set processing for this Enum’s data. This is set automatically based on the presence of unicode label strings.
    - metadata – Associate this type directly with a `MetaData` object. For types that exist on the target database as an independent schema construct (Postgresql), this type will be created and dropped within `create_all()` and `drop_all()` operations. If the type is not associated with any `MetaData` object, it will associate itself with each `Table` in which it is used, and will be created when any of those individual tables are created, after a check is performed for it’s existence. The type is only dropped when `drop_all()` is called for that `Table` object’s metadata, however.
    - name – The name of this type. This is required for Postgresql and any future supported database which requires an explicitly named type, or an explicitly named constraint in order to generate the type and/or a table that uses it.
    - native_enum – Use the database’s native ENUM type when available. Defaults to True. When False, uses VARCHAR + check constraint for all backends.
    - schema – Schemaname of this type. For types that exist on the target database as an independent schema construct (Postgresql), this parameter specifies the named schema in which the type is present.
    - quote – Force quoting to be on or off on the type’s name. If left as the default of None, the usual schema-level “case sensitive”/”reserved name” rules are used to determine if this type’s name should be quoted.

class `sqlalchemy.dialects.postgresql.base.``INET`(*args, **kwargs)

  Bases: `sqlalchemy.types.TypeEngine`

  `__init__`(*args, **kwargs)

class `sqlalchemy.dialects.postgresql.base.``INTERVAL`(precision=None)

  Bases: `sqlalchemy.types.TypeEngine`

  `__init__`(precision=None)

class `sqlalchemy.dialects.postgresql.base.``MACADDR`(*args, **kwargs)

  Bases: `sqlalchemy.types.TypeEngine`

  `__init__`(*args, **kwargs)

class `sqlalchemy.dialects.postgresql.base.``REAL`(precision=None, asdecimal=False, **kwargs)

  Bases: `sqlalchemy.types.Float`

  `__init__`(precision=None, asdecimal=False, **kwargs)

    Construct a Float.

    Parameters:

    - precision – the numeric precision for use in DDL `CREATE TABLE`.
    - asdecimal – the same flag as that of `Numeric`, but defaults to `False`. Note that setting this flag to `True` results in floating point conversion.

class `sqlalchemy.dialects.postgresql.base.``UUID`(*args, **kwargs)

  Bases: `sqlalchemy.types.TypeEngine`

  `__init__`(*args, **kwargs)

## psycopg2 Notes

Support for the PostgreSQL database via the psycopg2 driver.

### Driver

The psycopg2 driver is supported, available at http://pypi.python.org/pypi/psycopg2/ . The dialect has several behaviors which are specifically tailored towards compatibility with this module.

Note that psycopg1 is not supported.

### Connecting

URLs are of the form postgresql+psycopg2://user:password@host:port/dbname[?key=value&key=value...].

psycopg2-specific keyword arguments which are accepted by `create_engine()` are:

- server_side_cursors - Enable the usage of “server side cursors” for SQL statements which support this feature. What this essentially means from a psycopg2 point of view is that the cursor is created using a name, e.g. connection.cursor(‘some name’), which has the effect that result rows are not immediately pre-fetched and buffered after statement execution, but are instead left on the server and only retrieved as needed. SQLAlchemy’s `ResultProxy` uses special row-buffering behavior when this feature is enabled, such that groups of 100 rows at a time are fetched over the wire to reduce conversational overhead.
- use_native_unicode - Enable the usage of Psycopg2 “native unicode” mode per connection. True by default.
- isolation_level - Sets the transaction isolation level for each transaction within the engine. Valid isolation levels are READ_COMMITTED, READ_UNCOMMITTED, REPEATABLE_READ, and SERIALIZABLE.

### Transactions

The psycopg2 dialect fully supports SAVEPOINT and two-phase commit operations.

### NOTICE logging

The psycopg2 dialect will log Postgresql NOTICE messages via the `sqlalchemy.dialects.postgresql` logger:

    import logging
    logging.getLogger('sqlalchemy.dialects.postgresql').setLevel(logging.INFO)

### Per-Statement Execution Options

The following per-statement execution options are respected:

- stream_results - Enable or disable usage of server side cursors for the SELECT-statement. If None or not set, the server_side_cursors option of the connection is used. If auto-commit is enabled, the option is ignored.

## pg8000 Notes

Support for the PostgreSQL database via the pg8000 driver.

### Connecting

URLs are of the form postgresql+pg8000://user:password@host:port/dbname[?key=value&key=value...].

### Unicode

pg8000 requires that the postgresql client encoding be configured in the postgresql.conf file in order to use encodings other than ascii. Set this value to the same value as the “encoding” parameter on create_engine(), usually “utf-8”.

### Interval

Passing data from/to the Interval type is not supported as of yet.

## zxjdbc Notes

Support for the PostgreSQL database via the zxjdbc JDBC connector.

### JDBC Driver

The official Postgresql JDBC driver is at http://jdbc.postgresql.org/.