Support for the PostgreSQL database.
For information on connecting using specific drivers, see the documentation section regarding that driver.
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 and server side default corresponding to the column.
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)
)
When SQLAlchemy issues a single INSERT statement, to fulfill the contract of having the “last insert identifier” available, a RETURNING clause is added to the INSERT statement which specifies the primary key columns should be returned after the statement completes. The RETURNING functionality only takes place if Postgresql 8.2 or later is in use. As a fallback approach, the sequence, whether specified explicitly or implicitly via SERIAL, is executed independently beforehand, the returned value to be used in the subsequent insert. Note that when an insert() construct is executed using “executemany” semantics, the “last inserted identifier” functionality does not apply; no RETURNING clause is emitted nor is the sequence pre-executed in this case.
To force the usage of RETURNING by default off, specify the flag implicit_returning=False to create_engine().
create_engine() accepts an isolation_level parameter which results in the command SET SESSION CHARACTERISTICS AS TRANSACTION ISOLATION LEVEL <level> being invoked for every new connection. Valid values for this parameter are READ COMMITTED, READ UNCOMMITTED, REPEATABLE READ, and SERIALIZABLE:
engine = create_engine(
"postgresql+pg8000://scott:tiger@localhost/test",
isolation_level="READ UNCOMMITTED"
)
When using the psycopg2 dialect, a psycopg2-specific method of setting transaction isolation level is used, but the API of isolation_level remains the same - see Transaction Isolation Level.
Tables can be introspected from any accessible schema, including inter-schema foreign key relationships. However, care must be taken when specifying the “schema” argument for a given Table, when the given schema is also present in PostgreSQL’s search_path variable for the current connection.
If a FOREIGN KEY constraint reports that the remote table’s schema is within the current search_path, the “schema” attribute of the resulting Table will be set to None, unless the actual schema of the remote table matches that of the referencing table, and the “schema” argument was explicitly stated on the referencing table.
The best practice here is to not use the schema argument on Table for any schemas that are present in search_path. search_path defaults to “public”, but care should be taken to inspect the actual value using:
SHOW search_path;
Changed in version 0.7.3: Prior to this version, cross-schema foreign keys when the schemas were also in the search_path could make an incorrect assumption if the schemas were explicitly stated on each Table.
Background on PG’s search_path is at: http://www.postgresql.org/docs/9.0/static/ddl-schemas.html#DDL-SCHEMAS-PATH
The dialect supports PG 8.2’s INSERT..RETURNING, UPDATE..RETURNING and DELETE..RETURNING syntaxes. INSERT..RETURNING is used by default for single-row INSERT statements in order to fetch newly generated primary key identifiers. To specify an explicit RETURNING clause, use the _UpdateBase.returning() method 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()
Several extensions to the Index construct are available, specific to the PostgreSQL dialect.
Partial indexes add criterion to the index definition so that the index is applied to a subset of rows. These can be specified on Index using the postgresql_where keyword argument:
Index('my_index', my_table.c.id, postgresql_where=tbl.c.value > 10)
PostgreSQL allows the specification of an operator class for each column of an index (see http://www.postgresql.org/docs/8.3/interactive/indexes-opclass.html). The Index construct allows these to be specified via the postgresql_ops keyword argument:
Index('my_index', my_table.c.id, my_table.c.data,
postgresql_ops={
'data': 'text_pattern_ops',
'id': 'int4_ops'
})
New in version 0.7.2: postgresql_ops keyword argument to Index construct.
Note that the keys in the postgresql_ops dictionary are the “key” name of the Column, i.e. the name used to access it from the .c collection of Table, which can be configured to be different than the actual name of the column as expressed in the database.
PostgreSQL provides several index types: B-Tree, Hash, GiST, and GIN, as well as the ability for users to create their own (see http://www.postgresql.org/docs/8.3/static/indexes-types.html). These can be specified on Index using the postgresql_using keyword argument:
Index('my_index', my_table.c.data, postgresql_using='gin')
The value passed to the keyword argument will be simply passed through to the underlying CREATE INDEX command, so it must be a valid index type for your version of PostgreSQL.
As with all SQLAlchemy dialects, all UPPERCASE types that are known to be valid with Postgresql are importable from the top level dialect, whether they originate from sqlalchemy.types or from the local dialect:
from sqlalchemy.dialects.postgresql import \
ARRAY, BIGINT, BIT, BOOLEAN, BYTEA, CHAR, CIDR, DATE, \
DOUBLE_PRECISION, ENUM, FLOAT, INET, INTEGER, INTERVAL, \
MACADDR, NUMERIC, REAL, SMALLINT, TEXT, TIME, TIMESTAMP, \
UUID, VARCHAR
Types which are specific to PostgreSQL, or have PostgreSQL-specific construction arguments, are as follows:
Bases: sqlalchemy.types.MutableType, sqlalchemy.types.Concatenable, sqlalchemy.types.TypeEngine
Postgresql ARRAY type.
Represents values as Python lists.
The ARRAY type may not be supported on all DBAPIs. It is known to work on psycopg2 and not pg8000.
Construct an ARRAY.
E.g.:
Column('myarray', ARRAY(Integer))
Arguments are:
Parameters: |
|
---|
Bases: sqlalchemy.types.TypeEngine
Bases: sqlalchemy.types.LargeBinary
Construct a LargeBinary type.
Parameters: | 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. |
---|
Bases: sqlalchemy.types.TypeEngine
Support implementations that were passing arguments
Bases: sqlalchemy.types.Float
Construct a Float.
Parameters: |
|
---|
Bases: sqlalchemy.types.Enum
Postgresql ENUM type.
This is a subclass of types.Enum which includes support for PG’s CREATE TYPE.
ENUM is used automatically when using the types.Enum type on PG assuming the native_enum is left as True. However, the ENUM class can also be instantiated directly in order to access some additional Postgresql-specific options, namely finer control over whether or not CREATE TYPE should be emitted.
Note that both types.Enum as well as ENUM feature create/drop methods; the base types.Enum type ultimately delegates to the create() and drop() methods present here.
Construct an ENUM.
Arguments are the same as that of types.Enum, but also including the following parameters.
Parameters: | create_type – Defaults to True. Indicates that CREATE TYPE should be emitted, after optionally checking for the presence of the type, when the parent table is being created; and additionally that DROP TYPE is called when the table is dropped. When False, no check will be performed and no CREATE TYPE or DROP TYPE is emitted, unless create() or drop() are called directly. Setting to False is helpful when invoking a creation scheme to a SQL file without access to the actual database - the create() and drop() methods can be used to emit SQL to a target bind. New in version 0.7.4. |
---|
Emit CREATE TYPE for this ENUM.
If the underlying dialect does not support Postgresql CREATE TYPE, no action is taken.
Parameters: |
|
---|
Emit DROP TYPE for this ENUM.
If the underlying dialect does not support Postgresql DROP TYPE, no action is taken.
Parameters: |
|
---|
Bases: sqlalchemy.types.TypeEngine
Support implementations that were passing arguments
Bases: sqlalchemy.types.TypeEngine
Postgresql INTERVAL type.
The INTERVAL type may not be supported on all DBAPIs. It is known to work on psycopg2 and not pg8000 or zxjdbc.
Bases: sqlalchemy.types.TypeEngine
Support implementations that were passing arguments
Bases: sqlalchemy.types.Float
The SQL REAL type.
Construct a Float.
Parameters: |
|
---|
Bases: sqlalchemy.types.TypeEngine
Postgresql UUID type.
Represents the UUID column type, interpreting data either as natively returned by the DBAPI or as Python uuid objects.
The UUID type may not be supported on all DBAPIs. It is known to work on psycopg2 and not pg8000.
Construct a UUID type.
Parameters: | as_uuid=False – if True, values will be interpreted as Python uuid objects, converting to/from string via the DBAPI. |
---|
Support for the PostgreSQL database via the psycopg2 driver.
The psycopg2 driver is 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.
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:
psycopg2 supports connecting via Unix domain connections. When the host portion of the URL is omitted, SQLAlchemy passes None to psycopg2, which specifies Unix-domain communication rather than TCP/IP communication:
create_engine("postgresql+psycopg2://user:password@/dbname")
By default, the socket file used is to connect to a Unix-domain socket in /tmp, or whatever socket directory was specified when PostgreSQL was built. This value can be overridden by passing a pathname to psycopg2, using host as an additional keyword argument:
create_engine("postgresql+psycopg2://user:password@/dbname?host=/var/lib/postgresql")
See also:
The following DBAPI-specific options are respected when used with Connection.execution_options(), Executable.execution_options(), Query.execution_options(), in addition to those not specific to DBAPIs:
By default, the psycopg2 driver uses the psycopg2.extensions.UNICODE extension, such that the DBAPI receives and returns all strings as Python Unicode objects directly - SQLAlchemy passes these values through without change. Psycopg2 here will encode/decode string values based on the current “client encoding” setting; by default this is the value in the postgresql.conf file, which often defaults to SQL_ASCII. Typically, this can be changed to utf-8, as a more useful default:
#client_encoding = sql_ascii # actually, defaults to database
# encoding
client_encoding = utf8
A second way to affect the client encoding is to set it within Psycopg2 locally. SQLAlchemy will call psycopg2’s set_client_encoding() method (see: http://initd.org/psycopg/docs/connection.html#connection.set_client_encoding) on all new connections based on the value passed to create_engine() using the client_encoding parameter:
engine = create_engine("postgresql://user:pass@host/dbname", client_encoding='utf8')
This overrides the encoding specified in the Postgresql client configuration.
New in version 0.7.3: The psycopg2-specific client_encoding parameter to create_engine().
SQLAlchemy can also be instructed to skip the usage of the psycopg2 UNICODE extension and to instead utilize it’s own unicode encode/decode services, which are normally reserved only for those DBAPIs that don’t fully support unicode directly. Passing use_native_unicode=False to create_engine() will disable usage of psycopg2.extensions.UNICODE. SQLAlchemy will instead encode data itself into Python bytestrings on the way in and coerce from bytes on the way back, using the value of the create_engine() encoding parameter, which defaults to utf-8. SQLAlchemy’s own unicode encode/decode functionality is steadily becoming obsolete as more DBAPIs support unicode fully along with the approach of Python 3; in modern usage psycopg2 should be relied upon to handle unicode.
The psycopg2 dialect fully supports SAVEPOINT and two-phase commit operations.
The isolation_level parameter of create_engine() here makes use psycopg2’s set_isolation_level() connection method, rather than issuing a SET SESSION CHARACTERISTICS command. This because psycopg2 resets the isolation level on each new transaction, and needs to know at the API level what level should be used.
The psycopg2 dialect will log Postgresql NOTICE messages via the sqlalchemy.dialects.postgresql logger:
import logging
logging.getLogger('sqlalchemy.dialects.postgresql').setLevel(logging.INFO)
Support for the PostgreSQL database via py-postgresql.
URLs are of the form postgresql+pypostgresql://user:password@host:port/dbname[?key=value&key=value...].
Support for the PostgreSQL database via the pg8000 driver.
URLs are of the form postgresql+pg8000://user:password@host:port/dbname[?key=value&key=value...].
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”.
Passing data from/to the Interval type is not supported as of yet.
Support for the PostgreSQL database via the zxjdbc JDBC connector.
The official Postgresql JDBC driver is at http://jdbc.postgresql.org/.