# postgresql/base.py # Copyright (C) 2005-2022 the SQLAlchemy authors and contributors # # # This module is part of SQLAlchemy and is released under # the MIT License: https://www.opensource.org/licenses/mit-license.php r""" .. dialect:: postgresql :name: PostgreSQL :full_support: 9.6, 10, 11, 12, 13 :normal_support: 9.6+ :best_effort: 8+ .. _postgresql_sequences: Sequences/SERIAL/IDENTITY ------------------------- 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 :func:`~sqlalchemy.schema.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 :func:`~sqlalchemy.sql.expression.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 :func:`_sa.create_engine`. PostgreSQL 10 and above IDENTITY columns ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ PostgreSQL 10 and above have a new IDENTITY feature that supersedes the use of SERIAL. The :class:`_schema.Identity` construct in a :class:`_schema.Column` can be used to control its behavior:: from sqlalchemy import Table, Column, MetaData, Integer, Computed metadata = MetaData() data = Table( "data", metadata, Column( 'id', Integer, Identity(start=42, cycle=True), primary_key=True ), Column('data', String) ) The CREATE TABLE for the above :class:`_schema.Table` object would be: .. sourcecode:: sql CREATE TABLE data ( id INTEGER GENERATED BY DEFAULT AS IDENTITY (START WITH 42 CYCLE), data VARCHAR, PRIMARY KEY (id) ) .. versionchanged:: 1.4 Added :class:`_schema.Identity` construct in a :class:`_schema.Column` to specify the option of an autoincrementing column. .. note:: Previous versions of SQLAlchemy did not have built-in support for rendering of IDENTITY, and could use the following compilation hook to replace occurrences of SERIAL with IDENTITY:: from sqlalchemy.schema import CreateColumn from sqlalchemy.ext.compiler import compiles @compiles(CreateColumn, 'postgresql') def use_identity(element, compiler, **kw): text = compiler.visit_create_column(element, **kw) text = text.replace( "SERIAL", "INT GENERATED BY DEFAULT AS IDENTITY" ) return text Using the above, a table such as:: t = Table( 't', m, Column('id', Integer, primary_key=True), Column('data', String) ) Will generate on the backing database as:: CREATE TABLE t ( id INT GENERATED BY DEFAULT AS IDENTITY, data VARCHAR, PRIMARY KEY (id) ) .. _postgresql_ss_cursors: Server Side Cursors ------------------- Server-side cursor support is available for the psycopg2, asyncpg dialects and may also be available in others. Server side cursors are enabled on a per-statement basis by using the :paramref:`.Connection.execution_options.stream_results` connection execution option:: with engine.connect() as conn: result = conn.execution_options(stream_results=True).execute(text("select * from table")) Note that some kinds of SQL statements may not be supported with server side cursors; generally, only SQL statements that return rows should be used with this option. .. deprecated:: 1.4 The dialect-level server_side_cursors flag is deprecated and will be removed in a future release. Please use the :paramref:`_engine.Connection.stream_results` execution option for unbuffered cursor support. .. seealso:: :ref:`engine_stream_results` .. _postgresql_isolation_level: Transaction Isolation Level --------------------------- Most SQLAlchemy dialects support setting of transaction isolation level using the :paramref:`_sa.create_engine.execution_options` parameter at the :func:`_sa.create_engine` level, and at the :class:`_engine.Connection` level via the :paramref:`.Connection.execution_options.isolation_level` parameter. For PostgreSQL dialects, this feature works either by making use of the DBAPI-specific features, such as psycopg2's isolation level flags which will embed the isolation level setting inline with the ``"BEGIN"`` statement, or for DBAPIs with no direct support by emitting ``SET SESSION CHARACTERISTICS AS TRANSACTION ISOLATION LEVEL `` ahead of the ``"BEGIN"`` statement emitted by the DBAPI. For the special AUTOCOMMIT isolation level, DBAPI-specific techniques are used which is typically an ``.autocommit`` flag on the DBAPI connection object. To set isolation level using :func:`_sa.create_engine`:: engine = create_engine( "postgresql+pg8000://scott:tiger@localhost/test", execution_options={ "isolation_level": "REPEATABLE READ" } ) To set using per-connection execution options:: with engine.connect() as conn: conn = conn.execution_options( isolation_level="REPEATABLE READ" ) with conn.begin(): # ... work with transaction Valid values for ``isolation_level`` on most PostgreSQL dialects include: * ``READ COMMITTED`` * ``READ UNCOMMITTED`` * ``REPEATABLE READ`` * ``SERIALIZABLE`` * ``AUTOCOMMIT`` .. seealso:: :ref:`postgresql_readonly_deferrable` :ref:`dbapi_autocommit` :ref:`psycopg2_isolation_level` :ref:`pg8000_isolation_level` .. _postgresql_readonly_deferrable: Setting READ ONLY / DEFERRABLE ------------------------------ Most PostgreSQL dialects support setting the "READ ONLY" and "DEFERRABLE" characteristics of the transaction, which is in addition to the isolation level setting. These two attributes can be established either in conjunction with or independently of the isolation level by passing the ``postgresql_readonly`` and ``postgresql_deferrable`` flags with :meth:`_engine.Connection.execution_options`. The example below illustrates passing the ``"SERIALIZABLE"`` isolation level at the same time as setting "READ ONLY" and "DEFERRABLE":: with engine.connect() as conn: conn = conn.execution_options( isolation_level="SERIALIZABLE", postgresql_readonly=True, postgresql_deferrable=True ) with conn.begin(): # ... work with transaction Note that some DBAPIs such as asyncpg only support "readonly" with SERIALIZABLE isolation. .. versionadded:: 1.4 added support for the ``postgresql_readonly`` and ``postgresql_deferrable`` execution options. .. _postgresql_alternate_search_path: Setting Alternate Search Paths on Connect ------------------------------------------ The PostgreSQL ``search_path`` variable refers to the list of schema names that will be implicitly referred towards when a particular table or other object is referenced in a SQL statement. As detailed in the next section :ref:`postgresql_schema_reflection`, SQLAlchemy is generally organized around the concept of keeping this variable at its default value of ``public``, however, in order to have it set to any arbitrary name or names when connections are used automatically, the "SET SESSION search_path" command may be invoked for all connections in a pool using the following event handler, as discussed at :ref:`schema_set_default_connections`:: from sqlalchemy import event from sqlalchemy import create_engine engine = create_engine("postgresql+psycopg2://scott:tiger@host/dbname") @event.listens_for(engine, "connect", insert=True) def set_search_path(dbapi_connection, connection_record): existing_autocommit = dbapi_connection.autocommit dbapi_connection.autocommit = True cursor = dbapi_connection.cursor() cursor.execute("SET SESSION search_path='%s'" % schema_name) cursor.close() dbapi_connection.autocommit = existing_autocommit The reason the recipe is complicated by use of the ``.autocommit`` DBAPI attribute is so that when the ``SET SESSION search_path`` directive is invoked, it is invoked outside of the scope of any transaction and therefore will not be reverted when the DBAPI connection has a rollback. .. seealso:: :ref:`schema_set_default_connections` - in the :ref:`metadata_toplevel` documentation .. _postgresql_schema_reflection: Remote-Schema Table Introspection and PostgreSQL search_path ------------------------------------------------------------ .. admonition:: Section Best Practices Summarized keep the ``search_path`` variable set to its default of ``public``, without any other schema names. For other schema names, name these explicitly within :class:`_schema.Table` definitions. Alternatively, the ``postgresql_ignore_search_path`` option will cause all reflected :class:`_schema.Table` objects to have a :attr:`_schema.Table.schema` attribute set up. The PostgreSQL dialect can reflect tables from any schema, as outlined in :ref:`schema_table_reflection`. With regards to tables which these :class:`_schema.Table` objects refer to via foreign key constraint, a decision must be made as to how the ``.schema`` is represented in those remote tables, in the case where that remote schema name is also a member of the current `PostgreSQL search path `_. By default, the PostgreSQL dialect mimics the behavior encouraged by PostgreSQL's own ``pg_get_constraintdef()`` builtin procedure. This function returns a sample definition for a particular foreign key constraint, omitting the referenced schema name from that definition when the name is also in the PostgreSQL schema search path. The interaction below illustrates this behavior:: test=> CREATE TABLE test_schema.referred(id INTEGER PRIMARY KEY); CREATE TABLE test=> CREATE TABLE referring( test(> id INTEGER PRIMARY KEY, test(> referred_id INTEGER REFERENCES test_schema.referred(id)); CREATE TABLE test=> SET search_path TO public, test_schema; test=> SELECT pg_catalog.pg_get_constraintdef(r.oid, true) FROM test-> pg_catalog.pg_class c JOIN pg_catalog.pg_namespace n test-> ON n.oid = c.relnamespace test-> JOIN pg_catalog.pg_constraint r ON c.oid = r.conrelid test-> WHERE c.relname='referring' AND r.contype = 'f' test-> ; pg_get_constraintdef --------------------------------------------------- FOREIGN KEY (referred_id) REFERENCES referred(id) (1 row) Above, we created a table ``referred`` as a member of the remote schema ``test_schema``, however when we added ``test_schema`` to the PG ``search_path`` and then asked ``pg_get_constraintdef()`` for the ``FOREIGN KEY`` syntax, ``test_schema`` was not included in the output of the function. On the other hand, if we set the search path back to the typical default of ``public``:: test=> SET search_path TO public; SET The same query against ``pg_get_constraintdef()`` now returns the fully schema-qualified name for us:: test=> SELECT pg_catalog.pg_get_constraintdef(r.oid, true) FROM test-> pg_catalog.pg_class c JOIN pg_catalog.pg_namespace n test-> ON n.oid = c.relnamespace test-> JOIN pg_catalog.pg_constraint r ON c.oid = r.conrelid test-> WHERE c.relname='referring' AND r.contype = 'f'; pg_get_constraintdef --------------------------------------------------------------- FOREIGN KEY (referred_id) REFERENCES test_schema.referred(id) (1 row) SQLAlchemy will by default use the return value of ``pg_get_constraintdef()`` in order to determine the remote schema name. That is, if our ``search_path`` were set to include ``test_schema``, and we invoked a table reflection process as follows:: >>> from sqlalchemy import Table, MetaData, create_engine, text >>> engine = create_engine("postgresql://scott:tiger@localhost/test") >>> with engine.connect() as conn: ... conn.execute(text("SET search_path TO test_schema, public")) ... metadata_obj = MetaData() ... referring = Table('referring', metadata_obj, ... autoload_with=conn) ... The above process would deliver to the :attr:`_schema.MetaData.tables` collection ``referred`` table named **without** the schema:: >>> metadata_obj.tables['referred'].schema is None True To alter the behavior of reflection such that the referred schema is maintained regardless of the ``search_path`` setting, use the ``postgresql_ignore_search_path`` option, which can be specified as a dialect-specific argument to both :class:`_schema.Table` as well as :meth:`_schema.MetaData.reflect`:: >>> with engine.connect() as conn: ... conn.execute(text("SET search_path TO test_schema, public")) ... metadata_obj = MetaData() ... referring = Table('referring', metadata_obj, ... autoload_with=conn, ... postgresql_ignore_search_path=True) ... We will now have ``test_schema.referred`` stored as schema-qualified:: >>> metadata_obj.tables['test_schema.referred'].schema 'test_schema' .. sidebar:: Best Practices for PostgreSQL Schema reflection The description of PostgreSQL schema reflection behavior is complex, and is the product of many years of dealing with widely varied use cases and user preferences. But in fact, there's no need to understand any of it if you just stick to the simplest use pattern: leave the ``search_path`` set to its default of ``public`` only, never refer to the name ``public`` as an explicit schema name otherwise, and refer to all other schema names explicitly when building up a :class:`_schema.Table` object. The options described here are only for those users who can't, or prefer not to, stay within these guidelines. Note that **in all cases**, the "default" schema is always reflected as ``None``. The "default" schema on PostgreSQL is that which is returned by the PostgreSQL ``current_schema()`` function. On a typical PostgreSQL installation, this is the name ``public``. So a table that refers to another which is in the ``public`` (i.e. default) schema will always have the ``.schema`` attribute set to ``None``. .. seealso:: :ref:`reflection_schema_qualified_interaction` - discussion of the issue from a backend-agnostic perspective `The Schema Search Path `_ - on the PostgreSQL website. INSERT/UPDATE...RETURNING ------------------------- 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 :meth:`._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()) .. _postgresql_insert_on_conflict: INSERT...ON CONFLICT (Upsert) ------------------------------ Starting with version 9.5, PostgreSQL allows "upserts" (update or insert) of rows into a table via the ``ON CONFLICT`` clause of the ``INSERT`` statement. A candidate row will only be inserted if that row does not violate any unique constraints. In the case of a unique constraint violation, a secondary action can occur which can be either "DO UPDATE", indicating that the data in the target row should be updated, or "DO NOTHING", which indicates to silently skip this row. Conflicts are determined using existing unique constraints and indexes. These constraints may be identified either using their name as stated in DDL, or they may be inferred by stating the columns and conditions that comprise the indexes. SQLAlchemy provides ``ON CONFLICT`` support via the PostgreSQL-specific :func:`_postgresql.insert()` function, which provides the generative methods :meth:`_postgresql.Insert.on_conflict_do_update` and :meth:`~.postgresql.Insert.on_conflict_do_nothing`: .. sourcecode:: pycon+sql >>> from sqlalchemy.dialects.postgresql import insert >>> insert_stmt = insert(my_table).values( ... id='some_existing_id', ... data='inserted value') >>> do_nothing_stmt = insert_stmt.on_conflict_do_nothing( ... index_elements=['id'] ... ) >>> print(do_nothing_stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT (id) DO NOTHING {stop} >>> do_update_stmt = insert_stmt.on_conflict_do_update( ... constraint='pk_my_table', ... set_=dict(data='updated value') ... ) >>> print(do_update_stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT ON CONSTRAINT pk_my_table DO UPDATE SET data = %(param_1)s .. versionadded:: 1.1 .. seealso:: `INSERT .. ON CONFLICT `_ - in the PostgreSQL documentation. Specifying the Target ^^^^^^^^^^^^^^^^^^^^^ Both methods supply the "target" of the conflict using either the named constraint or by column inference: * The :paramref:`_postgresql.Insert.on_conflict_do_update.index_elements` argument specifies a sequence containing string column names, :class:`_schema.Column` objects, and/or SQL expression elements, which would identify a unique index: .. sourcecode:: pycon+sql >>> do_update_stmt = insert_stmt.on_conflict_do_update( ... index_elements=['id'], ... set_=dict(data='updated value') ... ) >>> print(do_update_stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT (id) DO UPDATE SET data = %(param_1)s {stop} >>> do_update_stmt = insert_stmt.on_conflict_do_update( ... index_elements=[my_table.c.id], ... set_=dict(data='updated value') ... ) >>> print(do_update_stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT (id) DO UPDATE SET data = %(param_1)s * When using :paramref:`_postgresql.Insert.on_conflict_do_update.index_elements` to infer an index, a partial index can be inferred by also specifying the use the :paramref:`_postgresql.Insert.on_conflict_do_update.index_where` parameter: .. sourcecode:: pycon+sql >>> stmt = insert(my_table).values(user_email='a@b.com', data='inserted data') >>> stmt = stmt.on_conflict_do_update( ... index_elements=[my_table.c.user_email], ... index_where=my_table.c.user_email.like('%@gmail.com'), ... set_=dict(data=stmt.excluded.data) ... ) >>> print(stmt) {opensql}INSERT INTO my_table (data, user_email) VALUES (%(data)s, %(user_email)s) ON CONFLICT (user_email) WHERE user_email LIKE %(user_email_1)s DO UPDATE SET data = excluded.data * The :paramref:`_postgresql.Insert.on_conflict_do_update.constraint` argument is used to specify an index directly rather than inferring it. This can be the name of a UNIQUE constraint, a PRIMARY KEY constraint, or an INDEX: .. sourcecode:: pycon+sql >>> do_update_stmt = insert_stmt.on_conflict_do_update( ... constraint='my_table_idx_1', ... set_=dict(data='updated value') ... ) >>> print(do_update_stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT ON CONSTRAINT my_table_idx_1 DO UPDATE SET data = %(param_1)s {stop} >>> do_update_stmt = insert_stmt.on_conflict_do_update( ... constraint='my_table_pk', ... set_=dict(data='updated value') ... ) >>> print(do_update_stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT ON CONSTRAINT my_table_pk DO UPDATE SET data = %(param_1)s {stop} * The :paramref:`_postgresql.Insert.on_conflict_do_update.constraint` argument may also refer to a SQLAlchemy construct representing a constraint, e.g. :class:`.UniqueConstraint`, :class:`.PrimaryKeyConstraint`, :class:`.Index`, or :class:`.ExcludeConstraint`. In this use, if the constraint has a name, it is used directly. Otherwise, if the constraint is unnamed, then inference will be used, where the expressions and optional WHERE clause of the constraint will be spelled out in the construct. This use is especially convenient to refer to the named or unnamed primary key of a :class:`_schema.Table` using the :attr:`_schema.Table.primary_key` attribute: .. sourcecode:: pycon+sql >>> do_update_stmt = insert_stmt.on_conflict_do_update( ... constraint=my_table.primary_key, ... set_=dict(data='updated value') ... ) >>> print(do_update_stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT (id) DO UPDATE SET data = %(param_1)s The SET Clause ^^^^^^^^^^^^^^^ ``ON CONFLICT...DO UPDATE`` is used to perform an update of the already existing row, using any combination of new values as well as values from the proposed insertion. These values are specified using the :paramref:`_postgresql.Insert.on_conflict_do_update.set_` parameter. This parameter accepts a dictionary which consists of direct values for UPDATE: .. sourcecode:: pycon+sql >>> stmt = insert(my_table).values(id='some_id', data='inserted value') >>> do_update_stmt = stmt.on_conflict_do_update( ... index_elements=['id'], ... set_=dict(data='updated value') ... ) >>> print(do_update_stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT (id) DO UPDATE SET data = %(param_1)s .. warning:: The :meth:`_expression.Insert.on_conflict_do_update` method does **not** take into account Python-side default UPDATE values or generation functions, e.g. those specified using :paramref:`_schema.Column.onupdate`. These values will not be exercised for an ON CONFLICT style of UPDATE, unless they are manually specified in the :paramref:`_postgresql.Insert.on_conflict_do_update.set_` dictionary. Updating using the Excluded INSERT Values ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ In order to refer to the proposed insertion row, the special alias :attr:`~.postgresql.Insert.excluded` is available as an attribute on the :class:`_postgresql.Insert` object; this object is a :class:`_expression.ColumnCollection` which alias contains all columns of the target table: .. sourcecode:: pycon+sql >>> stmt = insert(my_table).values( ... id='some_id', ... data='inserted value', ... author='jlh' ... ) >>> do_update_stmt = stmt.on_conflict_do_update( ... index_elements=['id'], ... set_=dict(data='updated value', author=stmt.excluded.author) ... ) >>> print(do_update_stmt) {opensql}INSERT INTO my_table (id, data, author) VALUES (%(id)s, %(data)s, %(author)s) ON CONFLICT (id) DO UPDATE SET data = %(param_1)s, author = excluded.author Additional WHERE Criteria ^^^^^^^^^^^^^^^^^^^^^^^^^ The :meth:`_expression.Insert.on_conflict_do_update` method also accepts a WHERE clause using the :paramref:`_postgresql.Insert.on_conflict_do_update.where` parameter, which will limit those rows which receive an UPDATE: .. sourcecode:: pycon+sql >>> stmt = insert(my_table).values( ... id='some_id', ... data='inserted value', ... author='jlh' ... ) >>> on_update_stmt = stmt.on_conflict_do_update( ... index_elements=['id'], ... set_=dict(data='updated value', author=stmt.excluded.author), ... where=(my_table.c.status == 2) ... ) >>> print(on_update_stmt) {opensql}INSERT INTO my_table (id, data, author) VALUES (%(id)s, %(data)s, %(author)s) ON CONFLICT (id) DO UPDATE SET data = %(param_1)s, author = excluded.author WHERE my_table.status = %(status_1)s Skipping Rows with DO NOTHING ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ``ON CONFLICT`` may be used to skip inserting a row entirely if any conflict with a unique or exclusion constraint occurs; below this is illustrated using the :meth:`~.postgresql.Insert.on_conflict_do_nothing` method: .. sourcecode:: pycon+sql >>> stmt = insert(my_table).values(id='some_id', data='inserted value') >>> stmt = stmt.on_conflict_do_nothing(index_elements=['id']) >>> print(stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT (id) DO NOTHING If ``DO NOTHING`` is used without specifying any columns or constraint, it has the effect of skipping the INSERT for any unique or exclusion constraint violation which occurs: .. sourcecode:: pycon+sql >>> stmt = insert(my_table).values(id='some_id', data='inserted value') >>> stmt = stmt.on_conflict_do_nothing() >>> print(stmt) {opensql}INSERT INTO my_table (id, data) VALUES (%(id)s, %(data)s) ON CONFLICT DO NOTHING .. _postgresql_match: Full Text Search ---------------- SQLAlchemy makes available the PostgreSQL ``@@`` operator via the :meth:`_expression.ColumnElement.match` method on any textual column expression. On the PostgreSQL dialect, an expression like the following:: select(sometable.c.text.match("search string")) will emit to the database:: SELECT text @@ to_tsquery('search string') FROM table Various other PostgreSQL text search functions such as ``to_tsquery()``, ``to_tsvector()``, and ``plainto_tsquery()`` are available by explicitly using the standard SQLAlchemy :data:`.func` construct. For example:: select(func.to_tsvector('fat cats ate rats').match('cat & rat')) Emits the equivalent of:: SELECT to_tsvector('fat cats ate rats') @@ to_tsquery('cat & rat') The :class:`_postgresql.TSVECTOR` type can provide for explicit CAST:: from sqlalchemy.dialects.postgresql import TSVECTOR from sqlalchemy import select, cast select(cast("some text", TSVECTOR)) produces a statement equivalent to:: SELECT CAST('some text' AS TSVECTOR) AS anon_1 .. tip:: It's important to remember that text searching in PostgreSQL is powerful but complicated, and SQLAlchemy users are advised to reference the PostgreSQL documentation regarding `Full Text Search `_. There are important differences between ``to_tsquery`` and ``plainto_tsquery``, the most significant of which is that ``to_tsquery`` expects specially formatted "querytext" that is written to PostgreSQL's own specification, while ``plainto_tsquery`` expects unformatted text that is transformed into ``to_tsquery`` compatible querytext. This means the input to ``.match()`` under PostgreSQL may be incompatible with the input to ``.match()`` under another database backend. SQLAlchemy users who support multiple backends are advised to carefully implement their usage of ``.match()`` to work around these constraints. Full Text Searches in PostgreSQL are influenced by a combination of: the PostgreSQL setting of ``default_text_search_config``, the ``regconfig`` used to build the GIN/GiST indexes, and the ``regconfig`` optionally passed in during a query. When performing a Full Text Search against a column that has a GIN or GiST index that is already pre-computed (which is common on full text searches) one may need to explicitly pass in a particular PostgreSQL ``regconfig`` value to ensure the query-planner utilizes the index and does not re-compute the column on demand. In order to provide for this explicit query planning, or to use different search strategies, the ``match`` method accepts a ``postgresql_regconfig`` keyword argument:: select(mytable.c.id).where( mytable.c.title.match('somestring', postgresql_regconfig='english') ) Emits the equivalent of:: SELECT mytable.id FROM mytable WHERE mytable.title @@ to_tsquery('english', 'somestring') One can also specifically pass in a `'regconfig'` value to the ``to_tsvector()`` command as the initial argument:: select(mytable.c.id).where( func.to_tsvector('english', mytable.c.title )\ .match('somestring', postgresql_regconfig='english') ) produces a statement equivalent to:: SELECT mytable.id FROM mytable WHERE to_tsvector('english', mytable.title) @@ to_tsquery('english', 'somestring') It is recommended that you use the ``EXPLAIN ANALYZE...`` tool from PostgreSQL to ensure that you are generating queries with SQLAlchemy that take full advantage of any indexes you may have created for full text search. FROM ONLY ... ------------- The dialect supports PostgreSQL's ONLY keyword for targeting only a particular table in an inheritance hierarchy. This can be used to produce the ``SELECT ... FROM ONLY``, ``UPDATE ONLY ...``, and ``DELETE FROM ONLY ...`` syntaxes. It uses SQLAlchemy's hints mechanism:: # SELECT ... FROM ONLY ... result = table.select().with_hint(table, 'ONLY', 'postgresql') print(result.fetchall()) # UPDATE ONLY ... table.update(values=dict(foo='bar')).with_hint('ONLY', dialect_name='postgresql') # DELETE FROM ONLY ... table.delete().with_hint('ONLY', dialect_name='postgresql') .. _postgresql_indexes: PostgreSQL-Specific Index Options --------------------------------- Several extensions to the :class:`.Index` construct are available, specific to the PostgreSQL dialect. Covering Indexes ^^^^^^^^^^^^^^^^ The ``postgresql_include`` option renders INCLUDE(colname) for the given string names:: Index("my_index", table.c.x, postgresql_include=['y']) would render the index as ``CREATE INDEX my_index ON table (x) INCLUDE (y)`` Note that this feature requires PostgreSQL 11 or later. .. versionadded:: 1.4 .. _postgresql_partial_indexes: Partial Indexes ^^^^^^^^^^^^^^^ Partial indexes add criterion to the index definition so that the index is applied to a subset of rows. These can be specified on :class:`.Index` using the ``postgresql_where`` keyword argument:: Index('my_index', my_table.c.id, postgresql_where=my_table.c.value > 10) .. _postgresql_operator_classes: Operator Classes ^^^^^^^^^^^^^^^^ PostgreSQL allows the specification of an *operator class* for each column of an index (see https://www.postgresql.org/docs/8.3/interactive/indexes-opclass.html). The :class:`.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' }) Note that the keys in the ``postgresql_ops`` dictionaries are the "key" name of the :class:`_schema.Column`, i.e. the name used to access it from the ``.c`` collection of :class:`_schema.Table`, which can be configured to be different than the actual name of the column as expressed in the database. If ``postgresql_ops`` is to be used against a complex SQL expression such as a function call, then to apply to the column it must be given a label that is identified in the dictionary by name, e.g.:: Index( 'my_index', my_table.c.id, func.lower(my_table.c.data).label('data_lower'), postgresql_ops={ 'data_lower': 'text_pattern_ops', 'id': 'int4_ops' }) Operator classes are also supported by the :class:`_postgresql.ExcludeConstraint` construct using the :paramref:`_postgresql.ExcludeConstraint.ops` parameter. See that parameter for details. .. versionadded:: 1.3.21 added support for operator classes with :class:`_postgresql.ExcludeConstraint`. Index Types ^^^^^^^^^^^ PostgreSQL provides several index types: B-Tree, Hash, GiST, and GIN, as well as the ability for users to create their own (see https://www.postgresql.org/docs/8.3/static/indexes-types.html). These can be specified on :class:`.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. .. _postgresql_index_storage: Index Storage Parameters ^^^^^^^^^^^^^^^^^^^^^^^^ PostgreSQL allows storage parameters to be set on indexes. The storage parameters available depend on the index method used by the index. Storage parameters can be specified on :class:`.Index` using the ``postgresql_with`` keyword argument:: Index('my_index', my_table.c.data, postgresql_with={"fillfactor": 50}) .. versionadded:: 1.0.6 PostgreSQL allows to define the tablespace in which to create the index. The tablespace can be specified on :class:`.Index` using the ``postgresql_tablespace`` keyword argument:: Index('my_index', my_table.c.data, postgresql_tablespace='my_tablespace') .. versionadded:: 1.1 Note that the same option is available on :class:`_schema.Table` as well. .. _postgresql_index_concurrently: Indexes with CONCURRENTLY ^^^^^^^^^^^^^^^^^^^^^^^^^ The PostgreSQL index option CONCURRENTLY is supported by passing the flag ``postgresql_concurrently`` to the :class:`.Index` construct:: tbl = Table('testtbl', m, Column('data', Integer)) idx1 = Index('test_idx1', tbl.c.data, postgresql_concurrently=True) The above index construct will render DDL for CREATE INDEX, assuming PostgreSQL 8.2 or higher is detected or for a connection-less dialect, as:: CREATE INDEX CONCURRENTLY test_idx1 ON testtbl (data) For DROP INDEX, assuming PostgreSQL 9.2 or higher is detected or for a connection-less dialect, it will emit:: DROP INDEX CONCURRENTLY test_idx1 .. versionadded:: 1.1 support for CONCURRENTLY on DROP INDEX. The CONCURRENTLY keyword is now only emitted if a high enough version of PostgreSQL is detected on the connection (or for a connection-less dialect). When using CONCURRENTLY, the PostgreSQL database requires that the statement be invoked outside of a transaction block. The Python DBAPI enforces that even for a single statement, a transaction is present, so to use this construct, the DBAPI's "autocommit" mode must be used:: metadata = MetaData() table = Table( "foo", metadata, Column("id", String)) index = Index( "foo_idx", table.c.id, postgresql_concurrently=True) with engine.connect() as conn: with conn.execution_options(isolation_level='AUTOCOMMIT'): table.create(conn) .. seealso:: :ref:`postgresql_isolation_level` .. _postgresql_index_reflection: PostgreSQL Index Reflection --------------------------- The PostgreSQL database creates a UNIQUE INDEX implicitly whenever the UNIQUE CONSTRAINT construct is used. When inspecting a table using :class:`_reflection.Inspector`, the :meth:`_reflection.Inspector.get_indexes` and the :meth:`_reflection.Inspector.get_unique_constraints` will report on these two constructs distinctly; in the case of the index, the key ``duplicates_constraint`` will be present in the index entry if it is detected as mirroring a constraint. When performing reflection using ``Table(..., autoload_with=engine)``, the UNIQUE INDEX is **not** returned in :attr:`_schema.Table.indexes` when it is detected as mirroring a :class:`.UniqueConstraint` in the :attr:`_schema.Table.constraints` collection . .. versionchanged:: 1.0.0 - :class:`_schema.Table` reflection now includes :class:`.UniqueConstraint` objects present in the :attr:`_schema.Table.constraints` collection; the PostgreSQL backend will no longer include a "mirrored" :class:`.Index` construct in :attr:`_schema.Table.indexes` if it is detected as corresponding to a unique constraint. Special Reflection Options -------------------------- The :class:`_reflection.Inspector` used for the PostgreSQL backend is an instance of :class:`.PGInspector`, which offers additional methods:: from sqlalchemy import create_engine, inspect engine = create_engine("postgresql+psycopg2://localhost/test") insp = inspect(engine) # will be a PGInspector print(insp.get_enums()) .. autoclass:: PGInspector :members: .. _postgresql_table_options: PostgreSQL Table Options ------------------------ Several options for CREATE TABLE are supported directly by the PostgreSQL dialect in conjunction with the :class:`_schema.Table` construct: * ``TABLESPACE``:: Table("some_table", metadata, ..., postgresql_tablespace='some_tablespace') The above option is also available on the :class:`.Index` construct. * ``ON COMMIT``:: Table("some_table", metadata, ..., postgresql_on_commit='PRESERVE ROWS') * ``WITH OIDS``:: Table("some_table", metadata, ..., postgresql_with_oids=True) * ``WITHOUT OIDS``:: Table("some_table", metadata, ..., postgresql_with_oids=False) * ``INHERITS``:: Table("some_table", metadata, ..., postgresql_inherits="some_supertable") Table("some_table", metadata, ..., postgresql_inherits=("t1", "t2", ...)) .. versionadded:: 1.0.0 * ``PARTITION BY``:: Table("some_table", metadata, ..., postgresql_partition_by='LIST (part_column)') .. versionadded:: 1.2.6 .. seealso:: `PostgreSQL CREATE TABLE options `_ .. _postgresql_table_valued_overview: Table values, Table and Column valued functions, Row and Tuple objects ----------------------------------------------------------------------- PostgreSQL makes great use of modern SQL forms such as table-valued functions, tables and rows as values. These constructs are commonly used as part of PostgreSQL's support for complex datatypes such as JSON, ARRAY, and other datatypes. SQLAlchemy's SQL expression language has native support for most table-valued and row-valued forms. .. _postgresql_table_valued: Table-Valued Functions ^^^^^^^^^^^^^^^^^^^^^^^ Many PostgreSQL built-in functions are intended to be used in the FROM clause of a SELECT statement, and are capable of returning table rows or sets of table rows. A large portion of PostgreSQL's JSON functions for example such as ``json_array_elements()``, ``json_object_keys()``, ``json_each_text()``, ``json_each()``, ``json_to_record()``, ``json_populate_recordset()`` use such forms. These classes of SQL function calling forms in SQLAlchemy are available using the :meth:`_functions.FunctionElement.table_valued` method in conjunction with :class:`_functions.Function` objects generated from the :data:`_sql.func` namespace. Examples from PostgreSQL's reference documentation follow below: * ``json_each()``:: >>> from sqlalchemy import select, func >>> stmt = select(func.json_each('{"a":"foo", "b":"bar"}').table_valued("key", "value")) >>> print(stmt) SELECT anon_1.key, anon_1.value FROM json_each(:json_each_1) AS anon_1 * ``json_populate_record()``:: >>> from sqlalchemy import select, func, literal_column >>> stmt = select( ... func.json_populate_record( ... literal_column("null::myrowtype"), ... '{"a":1,"b":2}' ... ).table_valued("a", "b", name="x") ... ) >>> print(stmt) SELECT x.a, x.b FROM json_populate_record(null::myrowtype, :json_populate_record_1) AS x * ``json_to_record()`` - this form uses a PostgreSQL specific form of derived columns in the alias, where we may make use of :func:`_sql.column` elements with types to produce them. The :meth:`_functions.FunctionElement.table_valued` method produces a :class:`_sql.TableValuedAlias` construct, and the method :meth:`_sql.TableValuedAlias.render_derived` method sets up the derived columns specification:: >>> from sqlalchemy import select, func, column, Integer, Text >>> stmt = select( ... func.json_to_record('{"a":1,"b":[1,2,3],"c":"bar"}').table_valued( ... column("a", Integer), column("b", Text), column("d", Text), ... ).render_derived(name="x", with_types=True) ... ) >>> print(stmt) SELECT x.a, x.b, x.d FROM json_to_record(:json_to_record_1) AS x(a INTEGER, b TEXT, d TEXT) * ``WITH ORDINALITY`` - part of the SQL standard, ``WITH ORDINALITY`` adds an ordinal counter to the output of a function and is accepted by a limited set of PostgreSQL functions including ``unnest()`` and ``generate_series()``. The :meth:`_functions.FunctionElement.table_valued` method accepts a keyword parameter ``with_ordinality`` for this purpose, which accepts the string name that will be applied to the "ordinality" column:: >>> from sqlalchemy import select, func >>> stmt = select( ... func.generate_series(4, 1, -1).table_valued("value", with_ordinality="ordinality") ... ) >>> print(stmt) SELECT anon_1.value, anon_1.ordinality FROM generate_series(:generate_series_1, :generate_series_2, :generate_series_3) WITH ORDINALITY AS anon_1 .. versionadded:: 1.4.0b2 .. seealso:: :ref:`tutorial_functions_table_valued` - in the :ref:`unified_tutorial` .. _postgresql_column_valued: Column Valued Functions ^^^^^^^^^^^^^^^^^^^^^^^ Similar to the table valued function, a column valued function is present in the FROM clause, but delivers itself to the columns clause as a single scalar value. PostgreSQL functions such as ``json_array_elements()``, ``unnest()`` and ``generate_series()`` may use this form. Column valued functions are available using the :meth:`_functions.FunctionElement.column_valued` method of :class:`_functions.FunctionElement`: * ``json_array_elements()``:: >>> from sqlalchemy import select, func >>> stmt = select(func.json_array_elements('["one", "two"]').column_valued("x")) >>> print(stmt) SELECT x FROM json_array_elements(:json_array_elements_1) AS x * ``unnest()`` - in order to generate a PostgreSQL ARRAY literal, the :func:`_postgresql.array` construct may be used:: >>> from sqlalchemy.dialects.postgresql import array >>> from sqlalchemy import select, func >>> stmt = select(func.unnest(array([1, 2])).column_valued()) >>> print(stmt) SELECT anon_1 FROM unnest(ARRAY[%(param_1)s, %(param_2)s]) AS anon_1 The function can of course be used against an existing table-bound column that's of type :class:`_types.ARRAY`:: >>> from sqlalchemy import table, column, ARRAY, Integer >>> from sqlalchemy import select, func >>> t = table("t", column('value', ARRAY(Integer))) >>> stmt = select(func.unnest(t.c.value).column_valued("unnested_value")) >>> print(stmt) SELECT unnested_value FROM unnest(t.value) AS unnested_value .. seealso:: :ref:`tutorial_functions_column_valued` - in the :ref:`unified_tutorial` Row Types ^^^^^^^^^ Built-in support for rendering a ``ROW`` may be approximated using ``func.ROW`` with the :attr:`_sa.func` namespace, or by using the :func:`_sql.tuple_` construct:: >>> from sqlalchemy import table, column, func, tuple_ >>> t = table("t", column("id"), column("fk")) >>> stmt = t.select().where( ... tuple_(t.c.id, t.c.fk) > (1,2) ... ).where( ... func.ROW(t.c.id, t.c.fk) < func.ROW(3, 7) ... ) >>> print(stmt) SELECT t.id, t.fk FROM t WHERE (t.id, t.fk) > (:param_1, :param_2) AND ROW(t.id, t.fk) < ROW(:ROW_1, :ROW_2) .. seealso:: `PostgreSQL Row Constructors `_ `PostgreSQL Row Constructor Comparison `_ Table Types passed to Functions ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ PostgreSQL supports passing a table as an argument to a function, which it refers towards as a "record" type. SQLAlchemy :class:`_sql.FromClause` objects such as :class:`_schema.Table` support this special form using the :meth:`_sql.FromClause.table_valued` method, which is comparable to the :meth:`_functions.FunctionElement.table_valued` method except that the collection of columns is already established by that of the :class:`_sql.FromClause` itself:: >>> from sqlalchemy import table, column, func, select >>> a = table( "a", column("id"), column("x"), column("y")) >>> stmt = select(func.row_to_json(a.table_valued())) >>> print(stmt) SELECT row_to_json(a) AS row_to_json_1 FROM a .. versionadded:: 1.4.0b2 ARRAY Types ----------- The PostgreSQL dialect supports arrays, both as multidimensional column types as well as array literals: * :class:`_postgresql.ARRAY` - ARRAY datatype * :class:`_postgresql.array` - array literal * :func:`_postgresql.array_agg` - ARRAY_AGG SQL function * :class:`_postgresql.aggregate_order_by` - helper for PG's ORDER BY aggregate function syntax. JSON Types ---------- The PostgreSQL dialect supports both JSON and JSONB datatypes, including psycopg2's native support and support for all of PostgreSQL's special operators: * :class:`_postgresql.JSON` * :class:`_postgresql.JSONB` HSTORE Type ----------- The PostgreSQL HSTORE type as well as hstore literals are supported: * :class:`_postgresql.HSTORE` - HSTORE datatype * :class:`_postgresql.hstore` - hstore literal ENUM Types ---------- PostgreSQL has an independently creatable TYPE structure which is used to implement an enumerated type. This approach introduces significant complexity on the SQLAlchemy side in terms of when this type should be CREATED and DROPPED. The type object is also an independently reflectable entity. The following sections should be consulted: * :class:`_postgresql.ENUM` - DDL and typing support for ENUM. * :meth:`.PGInspector.get_enums` - retrieve a listing of current ENUM types * :meth:`.postgresql.ENUM.create` , :meth:`.postgresql.ENUM.drop` - individual CREATE and DROP commands for ENUM. .. _postgresql_array_of_enum: Using ENUM with ARRAY ^^^^^^^^^^^^^^^^^^^^^ The combination of ENUM and ARRAY is not directly supported by backend DBAPIs at this time. Prior to SQLAlchemy 1.3.17, a special workaround was needed in order to allow this combination to work, described below. .. versionchanged:: 1.3.17 The combination of ENUM and ARRAY is now directly handled by SQLAlchemy's implementation without any workarounds needed. .. sourcecode:: python from sqlalchemy import TypeDecorator from sqlalchemy.dialects.postgresql import ARRAY class ArrayOfEnum(TypeDecorator): impl = ARRAY def bind_expression(self, bindvalue): return sa.cast(bindvalue, self) def result_processor(self, dialect, coltype): super_rp = super(ArrayOfEnum, self).result_processor( dialect, coltype) def handle_raw_string(value): inner = re.match(r"^{(.*)}$", value).group(1) return inner.split(",") if inner else [] def process(value): if value is None: return None return super_rp(handle_raw_string(value)) return process E.g.:: Table( 'mydata', metadata, Column('id', Integer, primary_key=True), Column('data', ArrayOfEnum(ENUM('a', 'b, 'c', name='myenum'))) ) This type is not included as a built-in type as it would be incompatible with a DBAPI that suddenly decides to support ARRAY of ENUM directly in a new version. .. _postgresql_array_of_json: Using JSON/JSONB with ARRAY ^^^^^^^^^^^^^^^^^^^^^^^^^^^ Similar to using ENUM, prior to SQLAlchemy 1.3.17, for an ARRAY of JSON/JSONB we need to render the appropriate CAST. Current psycopg2 drivers accommodate the result set correctly without any special steps. .. versionchanged:: 1.3.17 The combination of JSON/JSONB and ARRAY is now directly handled by SQLAlchemy's implementation without any workarounds needed. .. sourcecode:: python class CastingArray(ARRAY): def bind_expression(self, bindvalue): return sa.cast(bindvalue, self) E.g.:: Table( 'mydata', metadata, Column('id', Integer, primary_key=True), Column('data', CastingArray(JSONB)) ) """ # noqa E501 from collections import defaultdict import datetime as dt import re from uuid import UUID as _python_UUID from . import array as _array from . import hstore as _hstore from . import json as _json from . import ranges as _ranges from ... import exc from ... import schema from ... import sql from ... import util from ...engine import characteristics from ...engine import default from ...engine import reflection from ...sql import coercions from ...sql import compiler from ...sql import elements from ...sql import expression from ...sql import roles from ...sql import sqltypes from ...sql import util as sql_util from ...sql.ddl import DDLBase from ...types import BIGINT from ...types import BOOLEAN from ...types import CHAR from ...types import DATE from ...types import FLOAT from ...types import INTEGER from ...types import NUMERIC from ...types import REAL from ...types import SMALLINT from ...types import TEXT from ...types import VARCHAR IDX_USING = re.compile(r"^(?:btree|hash|gist|gin|[\w_]+)$", re.I) AUTOCOMMIT_REGEXP = re.compile( r"\s*(?:UPDATE|INSERT|CREATE|DELETE|DROP|ALTER|GRANT|REVOKE|" "IMPORT FOREIGN SCHEMA|REFRESH MATERIALIZED VIEW|TRUNCATE)", re.I | re.UNICODE, ) RESERVED_WORDS = set( [ "all", "analyse", "analyze", "and", "any", "array", "as", "asc", "asymmetric", "both", "case", "cast", "check", "collate", "column", "constraint", "create", "current_catalog", "current_date", "current_role", "current_time", "current_timestamp", "current_user", "default", "deferrable", "desc", "distinct", "do", "else", "end", "except", "false", "fetch", "for", "foreign", "from", "grant", "group", "having", "in", "initially", "intersect", "into", "leading", "limit", "localtime", "localtimestamp", "new", "not", "null", "of", "off", "offset", "old", "on", "only", "or", "order", "placing", "primary", "references", "returning", "select", "session_user", "some", "symmetric", "table", "then", "to", "trailing", "true", "union", "unique", "user", "using", "variadic", "when", "where", "window", "with", "authorization", "between", "binary", "cross", "current_schema", "freeze", "full", "ilike", "inner", "is", "isnull", "join", "left", "like", "natural", "notnull", "outer", "over", "overlaps", "right", "similar", "verbose", ] ) _DECIMAL_TYPES = (1231, 1700) _FLOAT_TYPES = (700, 701, 1021, 1022) _INT_TYPES = (20, 21, 23, 26, 1005, 1007, 1016) class BYTEA(sqltypes.LargeBinary): __visit_name__ = "BYTEA" class DOUBLE_PRECISION(sqltypes.Float): __visit_name__ = "DOUBLE_PRECISION" class INET(sqltypes.TypeEngine): __visit_name__ = "INET" PGInet = INET class CIDR(sqltypes.TypeEngine): __visit_name__ = "CIDR" PGCidr = CIDR class MACADDR(sqltypes.TypeEngine): __visit_name__ = "MACADDR" PGMacAddr = MACADDR class MONEY(sqltypes.TypeEngine): r"""Provide the PostgreSQL MONEY type. Depending on driver, result rows using this type may return a string value which includes currency symbols. For this reason, it may be preferable to provide conversion to a numerically-based currency datatype using :class:`_types.TypeDecorator`:: import re import decimal from sqlalchemy import TypeDecorator class NumericMoney(TypeDecorator): impl = MONEY def process_result_value(self, value: Any, dialect: Any) -> None: if value is not None: # adjust this for the currency and numeric m = re.match(r"\$([\d.]+)", value) if m: value = decimal.Decimal(m.group(1)) return value Alternatively, the conversion may be applied as a CAST using the :meth:`_types.TypeDecorator.column_expression` method as follows:: import decimal from sqlalchemy import cast from sqlalchemy import TypeDecorator class NumericMoney(TypeDecorator): impl = MONEY def column_expression(self, column: Any): return cast(column, Numeric()) .. versionadded:: 1.2 """ __visit_name__ = "MONEY" class OID(sqltypes.TypeEngine): """Provide the PostgreSQL OID type. .. versionadded:: 0.9.5 """ __visit_name__ = "OID" class REGCLASS(sqltypes.TypeEngine): """Provide the PostgreSQL REGCLASS type. .. versionadded:: 1.2.7 """ __visit_name__ = "REGCLASS" class TIMESTAMP(sqltypes.TIMESTAMP): def __init__(self, timezone=False, precision=None): super(TIMESTAMP, self).__init__(timezone=timezone) self.precision = precision class TIME(sqltypes.TIME): def __init__(self, timezone=False, precision=None): super(TIME, self).__init__(timezone=timezone) self.precision = precision class INTERVAL(sqltypes.NativeForEmulated, sqltypes._AbstractInterval): """PostgreSQL INTERVAL type.""" __visit_name__ = "INTERVAL" native = True def __init__(self, precision=None, fields=None): """Construct an INTERVAL. :param precision: optional integer precision value :param fields: string fields specifier. allows storage of fields to be limited, such as ``"YEAR"``, ``"MONTH"``, ``"DAY TO HOUR"``, etc. .. versionadded:: 1.2 """ self.precision = precision self.fields = fields @classmethod def adapt_emulated_to_native(cls, interval, **kw): return INTERVAL(precision=interval.second_precision) @property def _type_affinity(self): return sqltypes.Interval def as_generic(self, allow_nulltype=False): return sqltypes.Interval(native=True, second_precision=self.precision) @property def python_type(self): return dt.timedelta def coerce_compared_value(self, op, value): return self PGInterval = INTERVAL class BIT(sqltypes.TypeEngine): __visit_name__ = "BIT" def __init__(self, length=None, varying=False): if not varying: # BIT without VARYING defaults to length 1 self.length = length or 1 else: # but BIT VARYING can be unlimited-length, so no default self.length = length self.varying = varying PGBit = BIT class UUID(sqltypes.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 is currently known to work within the prominent DBAPI drivers supported by SQLAlchemy including psycopg2, pg8000 and asyncpg. Support for other DBAPI drivers may be incomplete or non-present. """ __visit_name__ = "UUID" def __init__(self, as_uuid=False): """Construct a UUID type. :param as_uuid=False: if True, values will be interpreted as Python uuid objects, converting to/from string via the DBAPI. """ self.as_uuid = as_uuid def coerce_compared_value(self, op, value): """See :meth:`.TypeEngine.coerce_compared_value` for a description.""" if isinstance(value, util.string_types): return self else: return super(UUID, self).coerce_compared_value(op, value) def bind_processor(self, dialect): if self.as_uuid: def process(value): if value is not None: value = util.text_type(value) return value return process else: return None def result_processor(self, dialect, coltype): if self.as_uuid: def process(value): if value is not None: value = _python_UUID(value) return value return process else: return None def literal_processor(self, dialect): if self.as_uuid: def process(value): if value is not None: value = "'%s'::UUID" % value return value return process else: def process(value): if value is not None: value = "'%s'" % value return value return process PGUuid = UUID class TSVECTOR(sqltypes.TypeEngine): """The :class:`_postgresql.TSVECTOR` type implements the PostgreSQL text search type TSVECTOR. It can be used to do full text queries on natural language documents. .. versionadded:: 0.9.0 .. seealso:: :ref:`postgresql_match` """ __visit_name__ = "TSVECTOR" class ENUM(sqltypes.NativeForEmulated, sqltypes.Enum): """PostgreSQL ENUM type. This is a subclass of :class:`_types.Enum` which includes support for PG's ``CREATE TYPE`` and ``DROP TYPE``. When the builtin type :class:`_types.Enum` is used and the :paramref:`.Enum.native_enum` flag is left at its default of True, the PostgreSQL backend will use a :class:`_postgresql.ENUM` type as the implementation, so the special create/drop rules will be used. The create/drop behavior of ENUM is necessarily intricate, due to the awkward relationship the ENUM type has in relationship to the parent table, in that it may be "owned" by just a single table, or may be shared among many tables. When using :class:`_types.Enum` or :class:`_postgresql.ENUM` in an "inline" fashion, the ``CREATE TYPE`` and ``DROP TYPE`` is emitted corresponding to when the :meth:`_schema.Table.create` and :meth:`_schema.Table.drop` methods are called:: table = Table('sometable', metadata, Column('some_enum', ENUM('a', 'b', 'c', name='myenum')) ) table.create(engine) # will emit CREATE ENUM and CREATE TABLE table.drop(engine) # will emit DROP TABLE and DROP ENUM To use a common enumerated type between multiple tables, the best practice is to declare the :class:`_types.Enum` or :class:`_postgresql.ENUM` independently, and associate it with the :class:`_schema.MetaData` object itself:: my_enum = ENUM('a', 'b', 'c', name='myenum', metadata=metadata) t1 = Table('sometable_one', metadata, Column('some_enum', myenum) ) t2 = Table('sometable_two', metadata, Column('some_enum', myenum) ) When this pattern is used, care must still be taken at the level of individual table creates. Emitting CREATE TABLE without also specifying ``checkfirst=True`` will still cause issues:: t1.create(engine) # will fail: no such type 'myenum' If we specify ``checkfirst=True``, the individual table-level create operation will check for the ``ENUM`` and create if not exists:: # will check if enum exists, and emit CREATE TYPE if not t1.create(engine, checkfirst=True) When using a metadata-level ENUM type, the type will always be created and dropped if either the metadata-wide create/drop is called:: metadata.create_all(engine) # will emit CREATE TYPE metadata.drop_all(engine) # will emit DROP TYPE The type can also be created and dropped directly:: my_enum.create(engine) my_enum.drop(engine) .. versionchanged:: 1.0.0 The PostgreSQL :class:`_postgresql.ENUM` type now behaves more strictly with regards to CREATE/DROP. A metadata-level ENUM type will only be created and dropped at the metadata level, not the table level, with the exception of ``table.create(checkfirst=True)``. The ``table.drop()`` call will now emit a DROP TYPE for a table-level enumerated type. """ native_enum = True def __init__(self, *enums, **kw): """Construct an :class:`_postgresql.ENUM`. Arguments are the same as that of :class:`_types.Enum`, but also including the following parameters. :param 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 :meth:`~.postgresql.ENUM.create` or :meth:`~.postgresql.ENUM.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 :meth:`~.postgresql.ENUM.create` and :meth:`~.postgresql.ENUM.drop` methods can be used to emit SQL to a target bind. """ native_enum = kw.pop("native_enum", None) if native_enum is False: util.warn( "the native_enum flag does not apply to the " "sqlalchemy.dialects.postgresql.ENUM datatype; this type " "always refers to ENUM. Use sqlalchemy.types.Enum for " "non-native enum." ) self.create_type = kw.pop("create_type", True) super(ENUM, self).__init__(*enums, **kw) @classmethod def adapt_emulated_to_native(cls, impl, **kw): """Produce a PostgreSQL native :class:`_postgresql.ENUM` from plain :class:`.Enum`. """ kw.setdefault("validate_strings", impl.validate_strings) kw.setdefault("name", impl.name) kw.setdefault("schema", impl.schema) kw.setdefault("inherit_schema", impl.inherit_schema) kw.setdefault("metadata", impl.metadata) kw.setdefault("_create_events", False) kw.setdefault("values_callable", impl.values_callable) kw.setdefault("omit_aliases", impl._omit_aliases) return cls(**kw) def create(self, bind=None, checkfirst=True): """Emit ``CREATE TYPE`` for this :class:`_postgresql.ENUM`. If the underlying dialect does not support PostgreSQL CREATE TYPE, no action is taken. :param bind: a connectable :class:`_engine.Engine`, :class:`_engine.Connection`, or similar object to emit SQL. :param checkfirst: if ``True``, a query against the PG catalog will be first performed to see if the type does not exist already before creating. """ if not bind.dialect.supports_native_enum: return bind._run_ddl_visitor(self.EnumGenerator, self, checkfirst=checkfirst) def drop(self, bind=None, checkfirst=True): """Emit ``DROP TYPE`` for this :class:`_postgresql.ENUM`. If the underlying dialect does not support PostgreSQL DROP TYPE, no action is taken. :param bind: a connectable :class:`_engine.Engine`, :class:`_engine.Connection`, or similar object to emit SQL. :param checkfirst: if ``True``, a query against the PG catalog will be first performed to see if the type actually exists before dropping. """ if not bind.dialect.supports_native_enum: return bind._run_ddl_visitor(self.EnumDropper, self, checkfirst=checkfirst) class EnumGenerator(DDLBase): def __init__(self, dialect, connection, checkfirst=False, **kwargs): super(ENUM.EnumGenerator, self).__init__(connection, **kwargs) self.checkfirst = checkfirst def _can_create_enum(self, enum): if not self.checkfirst: return True effective_schema = self.connection.schema_for_object(enum) return not self.connection.dialect.has_type( self.connection, enum.name, schema=effective_schema ) def visit_enum(self, enum): if not self._can_create_enum(enum): return self.connection.execute(CreateEnumType(enum)) class EnumDropper(DDLBase): def __init__(self, dialect, connection, checkfirst=False, **kwargs): super(ENUM.EnumDropper, self).__init__(connection, **kwargs) self.checkfirst = checkfirst def _can_drop_enum(self, enum): if not self.checkfirst: return True effective_schema = self.connection.schema_for_object(enum) return self.connection.dialect.has_type( self.connection, enum.name, schema=effective_schema ) def visit_enum(self, enum): if not self._can_drop_enum(enum): return self.connection.execute(DropEnumType(enum)) def _check_for_name_in_memos(self, checkfirst, kw): """Look in the 'ddl runner' for 'memos', then note our name in that collection. This to ensure a particular named enum is operated upon only once within any kind of create/drop sequence without relying upon "checkfirst". """ if not self.create_type: return True if "_ddl_runner" in kw: ddl_runner = kw["_ddl_runner"] if "_pg_enums" in ddl_runner.memo: pg_enums = ddl_runner.memo["_pg_enums"] else: pg_enums = ddl_runner.memo["_pg_enums"] = set() present = (self.schema, self.name) in pg_enums pg_enums.add((self.schema, self.name)) return present else: return False def _on_table_create(self, target, bind, checkfirst=False, **kw): if ( checkfirst or ( not self.metadata and not kw.get("_is_metadata_operation", False) ) ) and not self._check_for_name_in_memos(checkfirst, kw): self.create(bind=bind, checkfirst=checkfirst) def _on_table_drop(self, target, bind, checkfirst=False, **kw): if ( not self.metadata and not kw.get("_is_metadata_operation", False) and not self._check_for_name_in_memos(checkfirst, kw) ): self.drop(bind=bind, checkfirst=checkfirst) def _on_metadata_create(self, target, bind, checkfirst=False, **kw): if not self._check_for_name_in_memos(checkfirst, kw): self.create(bind=bind, checkfirst=checkfirst) def _on_metadata_drop(self, target, bind, checkfirst=False, **kw): if not self._check_for_name_in_memos(checkfirst, kw): self.drop(bind=bind, checkfirst=checkfirst) class _ColonCast(elements.Cast): __visit_name__ = "colon_cast" def __init__(self, expression, type_): self.type = type_ self.clause = expression self.typeclause = elements.TypeClause(type_) colspecs = { sqltypes.ARRAY: _array.ARRAY, sqltypes.Interval: INTERVAL, sqltypes.Enum: ENUM, sqltypes.JSON.JSONPathType: _json.JSONPathType, sqltypes.JSON: _json.JSON, } ischema_names = { "_array": _array.ARRAY, "hstore": _hstore.HSTORE, "json": _json.JSON, "jsonb": _json.JSONB, "int4range": _ranges.INT4RANGE, "int8range": _ranges.INT8RANGE, "numrange": _ranges.NUMRANGE, "daterange": _ranges.DATERANGE, "tsrange": _ranges.TSRANGE, "tstzrange": _ranges.TSTZRANGE, "integer": INTEGER, "bigint": BIGINT, "smallint": SMALLINT, "character varying": VARCHAR, "character": CHAR, '"char"': sqltypes.String, "name": sqltypes.String, "text": TEXT, "numeric": NUMERIC, "float": FLOAT, "real": REAL, "inet": INET, "cidr": CIDR, "uuid": UUID, "bit": BIT, "bit varying": BIT, "macaddr": MACADDR, "money": MONEY, "oid": OID, "regclass": REGCLASS, "double precision": DOUBLE_PRECISION, "timestamp": TIMESTAMP, "timestamp with time zone": TIMESTAMP, "timestamp without time zone": TIMESTAMP, "time with time zone": TIME, "time without time zone": TIME, "date": DATE, "time": TIME, "bytea": BYTEA, "boolean": BOOLEAN, "interval": INTERVAL, "tsvector": TSVECTOR, } class PGCompiler(compiler.SQLCompiler): def visit_colon_cast(self, element, **kw): return "%s::%s" % ( element.clause._compiler_dispatch(self, **kw), element.typeclause._compiler_dispatch(self, **kw), ) def visit_array(self, element, **kw): return "ARRAY[%s]" % self.visit_clauselist(element, **kw) def visit_slice(self, element, **kw): return "%s:%s" % ( self.process(element.start, **kw), self.process(element.stop, **kw), ) def visit_json_getitem_op_binary( self, binary, operator, _cast_applied=False, **kw ): if ( not _cast_applied and binary.type._type_affinity is not sqltypes.JSON ): kw["_cast_applied"] = True return self.process(sql.cast(binary, binary.type), **kw) kw["eager_grouping"] = True return self._generate_generic_binary( binary, " -> " if not _cast_applied else " ->> ", **kw ) def visit_json_path_getitem_op_binary( self, binary, operator, _cast_applied=False, **kw ): if ( not _cast_applied and binary.type._type_affinity is not sqltypes.JSON ): kw["_cast_applied"] = True return self.process(sql.cast(binary, binary.type), **kw) kw["eager_grouping"] = True return self._generate_generic_binary( binary, " #> " if not _cast_applied else " #>> ", **kw ) def visit_getitem_binary(self, binary, operator, **kw): return "%s[%s]" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) def visit_aggregate_order_by(self, element, **kw): return "%s ORDER BY %s" % ( self.process(element.target, **kw), self.process(element.order_by, **kw), ) def visit_match_op_binary(self, binary, operator, **kw): if "postgresql_regconfig" in binary.modifiers: regconfig = self.render_literal_value( binary.modifiers["postgresql_regconfig"], sqltypes.STRINGTYPE ) if regconfig: return "%s @@ to_tsquery(%s, %s)" % ( self.process(binary.left, **kw), regconfig, self.process(binary.right, **kw), ) return "%s @@ to_tsquery(%s)" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) def visit_ilike_op_binary(self, binary, operator, **kw): escape = binary.modifiers.get("escape", None) return "%s ILIKE %s" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) + ( " ESCAPE " + self.render_literal_value(escape, sqltypes.STRINGTYPE) if escape else "" ) def visit_not_ilike_op_binary(self, binary, operator, **kw): escape = binary.modifiers.get("escape", None) return "%s NOT ILIKE %s" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) + ( " ESCAPE " + self.render_literal_value(escape, sqltypes.STRINGTYPE) if escape else "" ) def _regexp_match(self, base_op, binary, operator, kw): flags = binary.modifiers["flags"] if flags is None: return self._generate_generic_binary( binary, " %s " % base_op, **kw ) if isinstance(flags, elements.BindParameter) and flags.value == "i": return self._generate_generic_binary( binary, " %s* " % base_op, **kw ) flags = self.process(flags, **kw) string = self.process(binary.left, **kw) pattern = self.process(binary.right, **kw) return "%s %s CONCAT('(?', %s, ')', %s)" % ( string, base_op, flags, pattern, ) def visit_regexp_match_op_binary(self, binary, operator, **kw): return self._regexp_match("~", binary, operator, kw) def visit_not_regexp_match_op_binary(self, binary, operator, **kw): return self._regexp_match("!~", binary, operator, kw) def visit_regexp_replace_op_binary(self, binary, operator, **kw): string = self.process(binary.left, **kw) pattern = self.process(binary.right, **kw) flags = binary.modifiers["flags"] if flags is not None: flags = self.process(flags, **kw) replacement = self.process(binary.modifiers["replacement"], **kw) if flags is None: return "REGEXP_REPLACE(%s, %s, %s)" % ( string, pattern, replacement, ) else: return "REGEXP_REPLACE(%s, %s, %s, %s)" % ( string, pattern, replacement, flags, ) def visit_empty_set_expr(self, element_types): # cast the empty set to the type we are comparing against. if # we are comparing against the null type, pick an arbitrary # datatype for the empty set return "SELECT %s WHERE 1!=1" % ( ", ".join( "CAST(NULL AS %s)" % self.dialect.type_compiler.process( INTEGER() if type_._isnull else type_ ) for type_ in element_types or [INTEGER()] ), ) def render_literal_value(self, value, type_): value = super(PGCompiler, self).render_literal_value(value, type_) if self.dialect._backslash_escapes: value = value.replace("\\", "\\\\") return value def visit_sequence(self, seq, **kw): return "nextval('%s')" % self.preparer.format_sequence(seq) def limit_clause(self, select, **kw): text = "" if select._limit_clause is not None: text += " \n LIMIT " + self.process(select._limit_clause, **kw) if select._offset_clause is not None: if select._limit_clause is None: text += "\n LIMIT ALL" text += " OFFSET " + self.process(select._offset_clause, **kw) return text def format_from_hint_text(self, sqltext, table, hint, iscrud): if hint.upper() != "ONLY": raise exc.CompileError("Unrecognized hint: %r" % hint) return "ONLY " + sqltext def get_select_precolumns(self, select, **kw): # Do not call super().get_select_precolumns because # it will warn/raise when distinct on is present if select._distinct or select._distinct_on: if select._distinct_on: return ( "DISTINCT ON (" + ", ".join( [ self.process(col, **kw) for col in select._distinct_on ] ) + ") " ) else: return "DISTINCT " else: return "" def for_update_clause(self, select, **kw): if select._for_update_arg.read: if select._for_update_arg.key_share: tmp = " FOR KEY SHARE" else: tmp = " FOR SHARE" elif select._for_update_arg.key_share: tmp = " FOR NO KEY UPDATE" else: tmp = " FOR UPDATE" if select._for_update_arg.of: tables = util.OrderedSet() for c in select._for_update_arg.of: tables.update(sql_util.surface_selectables_only(c)) tmp += " OF " + ", ".join( self.process(table, ashint=True, use_schema=False, **kw) for table in tables ) if select._for_update_arg.nowait: tmp += " NOWAIT" if select._for_update_arg.skip_locked: tmp += " SKIP LOCKED" return tmp def returning_clause(self, stmt, returning_cols): columns = [ self._label_returning_column(stmt, c) for c in expression._select_iterables(returning_cols) ] return "RETURNING " + ", ".join(columns) def visit_substring_func(self, func, **kw): s = self.process(func.clauses.clauses[0], **kw) start = self.process(func.clauses.clauses[1], **kw) if len(func.clauses.clauses) > 2: length = self.process(func.clauses.clauses[2], **kw) return "SUBSTRING(%s FROM %s FOR %s)" % (s, start, length) else: return "SUBSTRING(%s FROM %s)" % (s, start) def _on_conflict_target(self, clause, **kw): if clause.constraint_target is not None: # target may be a name of an Index, UniqueConstraint or # ExcludeConstraint. While there is a separate # "max_identifier_length" for indexes, PostgreSQL uses the same # length for all objects so we can use # truncate_and_render_constraint_name target_text = ( "ON CONSTRAINT %s" % self.preparer.truncate_and_render_constraint_name( clause.constraint_target ) ) elif clause.inferred_target_elements is not None: target_text = "(%s)" % ", ".join( ( self.preparer.quote(c) if isinstance(c, util.string_types) else self.process(c, include_table=False, use_schema=False) ) for c in clause.inferred_target_elements ) if clause.inferred_target_whereclause is not None: target_text += " WHERE %s" % self.process( clause.inferred_target_whereclause, include_table=False, use_schema=False, ) else: target_text = "" return target_text def visit_on_conflict_do_nothing(self, on_conflict, **kw): target_text = self._on_conflict_target(on_conflict, **kw) if target_text: return "ON CONFLICT %s DO NOTHING" % target_text else: return "ON CONFLICT DO NOTHING" def visit_on_conflict_do_update(self, on_conflict, **kw): clause = on_conflict target_text = self._on_conflict_target(on_conflict, **kw) action_set_ops = [] set_parameters = dict(clause.update_values_to_set) # create a list of column assignment clauses as tuples insert_statement = self.stack[-1]["selectable"] cols = insert_statement.table.c for c in cols: col_key = c.key if col_key in set_parameters: value = set_parameters.pop(col_key) elif c in set_parameters: value = set_parameters.pop(c) else: continue if coercions._is_literal(value): value = elements.BindParameter(None, value, type_=c.type) else: if ( isinstance(value, elements.BindParameter) and value.type._isnull ): value = value._clone() value.type = c.type value_text = self.process(value.self_group(), use_schema=False) key_text = self.preparer.quote(col_key) action_set_ops.append("%s = %s" % (key_text, value_text)) # check for names that don't match columns if set_parameters: util.warn( "Additional column names not matching " "any column keys in table '%s': %s" % ( self.current_executable.table.name, (", ".join("'%s'" % c for c in set_parameters)), ) ) for k, v in set_parameters.items(): key_text = ( self.preparer.quote(k) if isinstance(k, util.string_types) else self.process(k, use_schema=False) ) value_text = self.process( coercions.expect(roles.ExpressionElementRole, v), use_schema=False, ) action_set_ops.append("%s = %s" % (key_text, value_text)) action_text = ", ".join(action_set_ops) if clause.update_whereclause is not None: action_text += " WHERE %s" % self.process( clause.update_whereclause, include_table=True, use_schema=False ) return "ON CONFLICT %s DO UPDATE SET %s" % (target_text, action_text) def update_from_clause( self, update_stmt, from_table, extra_froms, from_hints, **kw ): kw["asfrom"] = True return "FROM " + ", ".join( t._compiler_dispatch(self, fromhints=from_hints, **kw) for t in extra_froms ) def delete_extra_from_clause( self, delete_stmt, from_table, extra_froms, from_hints, **kw ): """Render the DELETE .. USING clause specific to PostgreSQL.""" kw["asfrom"] = True return "USING " + ", ".join( t._compiler_dispatch(self, fromhints=from_hints, **kw) for t in extra_froms ) def fetch_clause(self, select, **kw): # pg requires parens for non literal clauses. It's also required for # bind parameters if a ::type casts is used by the driver (asyncpg), # so it's easiest to just always add it text = "" if select._offset_clause is not None: text += "\n OFFSET (%s) ROWS" % self.process( select._offset_clause, **kw ) if select._fetch_clause is not None: text += "\n FETCH FIRST (%s)%s ROWS %s" % ( self.process(select._fetch_clause, **kw), " PERCENT" if select._fetch_clause_options["percent"] else "", "WITH TIES" if select._fetch_clause_options["with_ties"] else "ONLY", ) return text class PGDDLCompiler(compiler.DDLCompiler): def get_column_specification(self, column, **kwargs): colspec = self.preparer.format_column(column) impl_type = column.type.dialect_impl(self.dialect) if isinstance(impl_type, sqltypes.TypeDecorator): impl_type = impl_type.impl has_identity = ( column.identity is not None and self.dialect.supports_identity_columns ) if ( column.primary_key and column is column.table._autoincrement_column and ( self.dialect.supports_smallserial or not isinstance(impl_type, sqltypes.SmallInteger) ) and not has_identity and ( column.default is None or ( isinstance(column.default, schema.Sequence) and column.default.optional ) ) ): if isinstance(impl_type, sqltypes.BigInteger): colspec += " BIGSERIAL" elif isinstance(impl_type, sqltypes.SmallInteger): colspec += " SMALLSERIAL" else: colspec += " SERIAL" else: colspec += " " + self.dialect.type_compiler.process( column.type, type_expression=column, identifier_preparer=self.preparer, ) default = self.get_column_default_string(column) if default is not None: colspec += " DEFAULT " + default if column.computed is not None: colspec += " " + self.process(column.computed) if has_identity: colspec += " " + self.process(column.identity) if not column.nullable and not has_identity: colspec += " NOT NULL" elif column.nullable and has_identity: colspec += " NULL" return colspec def visit_check_constraint(self, constraint): if constraint._type_bound: typ = list(constraint.columns)[0].type if ( isinstance(typ, sqltypes.ARRAY) and isinstance(typ.item_type, sqltypes.Enum) and not typ.item_type.native_enum ): raise exc.CompileError( "PostgreSQL dialect cannot produce the CHECK constraint " "for ARRAY of non-native ENUM; please specify " "create_constraint=False on this Enum datatype." ) return super(PGDDLCompiler, self).visit_check_constraint(constraint) def visit_drop_table_comment(self, drop): return "COMMENT ON TABLE %s IS NULL" % self.preparer.format_table( drop.element ) def visit_create_enum_type(self, create): type_ = create.element return "CREATE TYPE %s AS ENUM (%s)" % ( self.preparer.format_type(type_), ", ".join( self.sql_compiler.process(sql.literal(e), literal_binds=True) for e in type_.enums ), ) def visit_drop_enum_type(self, drop): type_ = drop.element return "DROP TYPE %s" % (self.preparer.format_type(type_)) def visit_create_index(self, create): preparer = self.preparer index = create.element self._verify_index_table(index) text = "CREATE " if index.unique: text += "UNIQUE " text += "INDEX " if self.dialect._supports_create_index_concurrently: concurrently = index.dialect_options["postgresql"]["concurrently"] if concurrently: text += "CONCURRENTLY " if create.if_not_exists: text += "IF NOT EXISTS " text += "%s ON %s " % ( self._prepared_index_name(index, include_schema=False), preparer.format_table(index.table), ) using = index.dialect_options["postgresql"]["using"] if using: text += ( "USING %s " % self.preparer.validate_sql_phrase(using, IDX_USING).lower() ) ops = index.dialect_options["postgresql"]["ops"] text += "(%s)" % ( ", ".join( [ self.sql_compiler.process( expr.self_group() if not isinstance(expr, expression.ColumnClause) else expr, include_table=False, literal_binds=True, ) + ( (" " + ops[expr.key]) if hasattr(expr, "key") and expr.key in ops else "" ) for expr in index.expressions ] ) ) includeclause = index.dialect_options["postgresql"]["include"] if includeclause: inclusions = [ index.table.c[col] if isinstance(col, util.string_types) else col for col in includeclause ] text += " INCLUDE (%s)" % ", ".join( [preparer.quote(c.name) for c in inclusions] ) withclause = index.dialect_options["postgresql"]["with"] if withclause: text += " WITH (%s)" % ( ", ".join( [ "%s = %s" % storage_parameter for storage_parameter in withclause.items() ] ) ) tablespace_name = index.dialect_options["postgresql"]["tablespace"] if tablespace_name: text += " TABLESPACE %s" % preparer.quote(tablespace_name) whereclause = index.dialect_options["postgresql"]["where"] if whereclause is not None: whereclause = coercions.expect( roles.DDLExpressionRole, whereclause ) where_compiled = self.sql_compiler.process( whereclause, include_table=False, literal_binds=True ) text += " WHERE " + where_compiled return text def visit_drop_index(self, drop): index = drop.element text = "\nDROP INDEX " if self.dialect._supports_drop_index_concurrently: concurrently = index.dialect_options["postgresql"]["concurrently"] if concurrently: text += "CONCURRENTLY " if drop.if_exists: text += "IF EXISTS " text += self._prepared_index_name(index, include_schema=True) return text def visit_exclude_constraint(self, constraint, **kw): text = "" if constraint.name is not None: text += "CONSTRAINT %s " % self.preparer.format_constraint( constraint ) elements = [] for expr, name, op in constraint._render_exprs: kw["include_table"] = False exclude_element = self.sql_compiler.process(expr, **kw) + ( (" " + constraint.ops[expr.key]) if hasattr(expr, "key") and expr.key in constraint.ops else "" ) elements.append("%s WITH %s" % (exclude_element, op)) text += "EXCLUDE USING %s (%s)" % ( self.preparer.validate_sql_phrase( constraint.using, IDX_USING ).lower(), ", ".join(elements), ) if constraint.where is not None: text += " WHERE (%s)" % self.sql_compiler.process( constraint.where, literal_binds=True ) text += self.define_constraint_deferrability(constraint) return text def post_create_table(self, table): table_opts = [] pg_opts = table.dialect_options["postgresql"] inherits = pg_opts.get("inherits") if inherits is not None: if not isinstance(inherits, (list, tuple)): inherits = (inherits,) table_opts.append( "\n INHERITS ( " + ", ".join(self.preparer.quote(name) for name in inherits) + " )" ) if pg_opts["partition_by"]: table_opts.append("\n PARTITION BY %s" % pg_opts["partition_by"]) if pg_opts["with_oids"] is True: table_opts.append("\n WITH OIDS") elif pg_opts["with_oids"] is False: table_opts.append("\n WITHOUT OIDS") if pg_opts["on_commit"]: on_commit_options = pg_opts["on_commit"].replace("_", " ").upper() table_opts.append("\n ON COMMIT %s" % on_commit_options) if pg_opts["tablespace"]: tablespace_name = pg_opts["tablespace"] table_opts.append( "\n TABLESPACE %s" % self.preparer.quote(tablespace_name) ) return "".join(table_opts) def visit_computed_column(self, generated): if generated.persisted is False: raise exc.CompileError( "PostrgreSQL computed columns do not support 'virtual' " "persistence; set the 'persisted' flag to None or True for " "PostgreSQL support." ) return "GENERATED ALWAYS AS (%s) STORED" % self.sql_compiler.process( generated.sqltext, include_table=False, literal_binds=True ) def visit_create_sequence(self, create, **kw): prefix = None if create.element.data_type is not None: prefix = " AS %s" % self.type_compiler.process( create.element.data_type ) return super(PGDDLCompiler, self).visit_create_sequence( create, prefix=prefix, **kw ) class PGTypeCompiler(compiler.GenericTypeCompiler): def visit_TSVECTOR(self, type_, **kw): return "TSVECTOR" def visit_INET(self, type_, **kw): return "INET" def visit_CIDR(self, type_, **kw): return "CIDR" def visit_MACADDR(self, type_, **kw): return "MACADDR" def visit_MONEY(self, type_, **kw): return "MONEY" def visit_OID(self, type_, **kw): return "OID" def visit_REGCLASS(self, type_, **kw): return "REGCLASS" def visit_FLOAT(self, type_, **kw): if not type_.precision: return "FLOAT" else: return "FLOAT(%(precision)s)" % {"precision": type_.precision} def visit_DOUBLE_PRECISION(self, type_, **kw): return "DOUBLE PRECISION" def visit_BIGINT(self, type_, **kw): return "BIGINT" def visit_HSTORE(self, type_, **kw): return "HSTORE" def visit_JSON(self, type_, **kw): return "JSON" def visit_JSONB(self, type_, **kw): return "JSONB" def visit_INT4RANGE(self, type_, **kw): return "INT4RANGE" def visit_INT8RANGE(self, type_, **kw): return "INT8RANGE" def visit_NUMRANGE(self, type_, **kw): return "NUMRANGE" def visit_DATERANGE(self, type_, **kw): return "DATERANGE" def visit_TSRANGE(self, type_, **kw): return "TSRANGE" def visit_TSTZRANGE(self, type_, **kw): return "TSTZRANGE" def visit_datetime(self, type_, **kw): return self.visit_TIMESTAMP(type_, **kw) def visit_enum(self, type_, **kw): if not type_.native_enum or not self.dialect.supports_native_enum: return super(PGTypeCompiler, self).visit_enum(type_, **kw) else: return self.visit_ENUM(type_, **kw) def visit_ENUM(self, type_, identifier_preparer=None, **kw): if identifier_preparer is None: identifier_preparer = self.dialect.identifier_preparer return identifier_preparer.format_type(type_) def visit_TIMESTAMP(self, type_, **kw): return "TIMESTAMP%s %s" % ( "(%d)" % type_.precision if getattr(type_, "precision", None) is not None else "", (type_.timezone and "WITH" or "WITHOUT") + " TIME ZONE", ) def visit_TIME(self, type_, **kw): return "TIME%s %s" % ( "(%d)" % type_.precision if getattr(type_, "precision", None) is not None else "", (type_.timezone and "WITH" or "WITHOUT") + " TIME ZONE", ) def visit_INTERVAL(self, type_, **kw): text = "INTERVAL" if type_.fields is not None: text += " " + type_.fields if type_.precision is not None: text += " (%d)" % type_.precision return text def visit_BIT(self, type_, **kw): if type_.varying: compiled = "BIT VARYING" if type_.length is not None: compiled += "(%d)" % type_.length else: compiled = "BIT(%d)" % type_.length return compiled def visit_UUID(self, type_, **kw): return "UUID" def visit_large_binary(self, type_, **kw): return self.visit_BYTEA(type_, **kw) def visit_BYTEA(self, type_, **kw): return "BYTEA" def visit_ARRAY(self, type_, **kw): inner = self.process(type_.item_type, **kw) return re.sub( r"((?: COLLATE.*)?)$", ( r"%s\1" % ( "[]" * (type_.dimensions if type_.dimensions is not None else 1) ) ), inner, count=1, ) class PGIdentifierPreparer(compiler.IdentifierPreparer): reserved_words = RESERVED_WORDS def _unquote_identifier(self, value): if value[0] == self.initial_quote: value = value[1:-1].replace( self.escape_to_quote, self.escape_quote ) return value def format_type(self, type_, use_schema=True): if not type_.name: raise exc.CompileError("PostgreSQL ENUM type requires a name.") name = self.quote(type_.name) effective_schema = self.schema_for_object(type_) if ( not self.omit_schema and use_schema and effective_schema is not None ): name = self.quote_schema(effective_schema) + "." + name return name class PGInspector(reflection.Inspector): def get_table_oid(self, table_name, schema=None): """Return the OID for the given table name.""" with self._operation_context() as conn: return self.dialect.get_table_oid( conn, table_name, schema, info_cache=self.info_cache ) def get_enums(self, schema=None): """Return a list of ENUM objects. Each member is a dictionary containing these fields: * name - name of the enum * schema - the schema name for the enum. * visible - boolean, whether or not this enum is visible in the default search path. * labels - a list of string labels that apply to the enum. :param schema: schema name. If None, the default schema (typically 'public') is used. May also be set to '*' to indicate load enums for all schemas. .. versionadded:: 1.0.0 """ schema = schema or self.default_schema_name with self._operation_context() as conn: return self.dialect._load_enums(conn, schema) def get_foreign_table_names(self, schema=None): """Return a list of FOREIGN TABLE names. Behavior is similar to that of :meth:`_reflection.Inspector.get_table_names`, except that the list is limited to those tables that report a ``relkind`` value of ``f``. .. versionadded:: 1.0.0 """ schema = schema or self.default_schema_name with self._operation_context() as conn: return self.dialect._get_foreign_table_names(conn, schema) def get_view_names(self, schema=None, include=("plain", "materialized")): """Return all view names in `schema`. :param schema: Optional, retrieve names from a non-default schema. For special quoting, use :class:`.quoted_name`. :param include: specify which types of views to return. Passed as a string value (for a single type) or a tuple (for any number of types). Defaults to ``('plain', 'materialized')``. .. versionadded:: 1.1 """ with self._operation_context() as conn: return self.dialect.get_view_names( conn, schema, info_cache=self.info_cache, include=include ) class CreateEnumType(schema._CreateDropBase): __visit_name__ = "create_enum_type" class DropEnumType(schema._CreateDropBase): __visit_name__ = "drop_enum_type" class PGExecutionContext(default.DefaultExecutionContext): def fire_sequence(self, seq, type_): return self._execute_scalar( ( "select nextval('%s')" % self.identifier_preparer.format_sequence(seq) ), type_, ) def get_insert_default(self, column): if column.primary_key and column is column.table._autoincrement_column: if column.server_default and column.server_default.has_argument: # pre-execute passive defaults on primary key columns return self._execute_scalar( "select %s" % column.server_default.arg, column.type ) elif column.default is None or ( column.default.is_sequence and column.default.optional ): # execute the sequence associated with a SERIAL primary # key column. for non-primary-key SERIAL, the ID just # generates server side. try: seq_name = column._postgresql_seq_name except AttributeError: tab = column.table.name col = column.name tab = tab[0 : 29 + max(0, (29 - len(col)))] col = col[0 : 29 + max(0, (29 - len(tab)))] name = "%s_%s_seq" % (tab, col) column._postgresql_seq_name = seq_name = name if column.table is not None: effective_schema = self.connection.schema_for_object( column.table ) else: effective_schema = None if effective_schema is not None: exc = 'select nextval(\'"%s"."%s"\')' % ( effective_schema, seq_name, ) else: exc = "select nextval('\"%s\"')" % (seq_name,) return self._execute_scalar(exc, column.type) return super(PGExecutionContext, self).get_insert_default(column) def should_autocommit_text(self, statement): return AUTOCOMMIT_REGEXP.match(statement) class PGReadOnlyConnectionCharacteristic( characteristics.ConnectionCharacteristic ): transactional = True def reset_characteristic(self, dialect, dbapi_conn): dialect.set_readonly(dbapi_conn, False) def set_characteristic(self, dialect, dbapi_conn, value): dialect.set_readonly(dbapi_conn, value) def get_characteristic(self, dialect, dbapi_conn): return dialect.get_readonly(dbapi_conn) class PGDeferrableConnectionCharacteristic( characteristics.ConnectionCharacteristic ): transactional = True def reset_characteristic(self, dialect, dbapi_conn): dialect.set_deferrable(dbapi_conn, False) def set_characteristic(self, dialect, dbapi_conn, value): dialect.set_deferrable(dbapi_conn, value) def get_characteristic(self, dialect, dbapi_conn): return dialect.get_deferrable(dbapi_conn) class PGDialect(default.DefaultDialect): name = "postgresql" supports_statement_cache = True supports_alter = True max_identifier_length = 63 supports_sane_rowcount = True supports_native_enum = True supports_native_boolean = True supports_smallserial = True supports_sequences = True sequences_optional = True preexecute_autoincrement_sequences = True postfetch_lastrowid = False supports_comments = True supports_default_values = True supports_default_metavalue = True supports_empty_insert = False supports_multivalues_insert = True supports_identity_columns = True default_paramstyle = "pyformat" ischema_names = ischema_names colspecs = colspecs statement_compiler = PGCompiler ddl_compiler = PGDDLCompiler type_compiler = PGTypeCompiler preparer = PGIdentifierPreparer execution_ctx_cls = PGExecutionContext inspector = PGInspector isolation_level = None implicit_returning = True full_returning = True connection_characteristics = ( default.DefaultDialect.connection_characteristics ) connection_characteristics = connection_characteristics.union( { "postgresql_readonly": PGReadOnlyConnectionCharacteristic(), "postgresql_deferrable": PGDeferrableConnectionCharacteristic(), } ) construct_arguments = [ ( schema.Index, { "using": False, "include": None, "where": None, "ops": {}, "concurrently": False, "with": {}, "tablespace": None, }, ), ( schema.Table, { "ignore_search_path": False, "tablespace": None, "partition_by": None, "with_oids": None, "on_commit": None, "inherits": None, }, ), ] reflection_options = ("postgresql_ignore_search_path",) _backslash_escapes = True _supports_create_index_concurrently = True _supports_drop_index_concurrently = True def __init__( self, isolation_level=None, json_serializer=None, json_deserializer=None, **kwargs ): default.DefaultDialect.__init__(self, **kwargs) # the isolation_level parameter to the PGDialect itself is legacy. # still works however the execution_options method is the one that # is documented. self.isolation_level = isolation_level self._json_deserializer = json_deserializer self._json_serializer = json_serializer def initialize(self, connection): super(PGDialect, self).initialize(connection) if self.server_version_info <= (8, 2): self.full_returning = self.implicit_returning = False self.supports_native_enum = self.server_version_info >= (8, 3) if not self.supports_native_enum: self.colspecs = self.colspecs.copy() # pop base Enum type self.colspecs.pop(sqltypes.Enum, None) # psycopg2, others may have placed ENUM here as well self.colspecs.pop(ENUM, None) # https://www.postgresql.org/docs/9.3/static/release-9-2.html#AEN116689 self.supports_smallserial = self.server_version_info >= (9, 2) if self.server_version_info < (8, 2): self._backslash_escapes = False else: # ensure this query is not emitted on server version < 8.2 # as it will fail std_string = connection.exec_driver_sql( "show standard_conforming_strings" ).scalar() self._backslash_escapes = std_string == "off" self._supports_create_index_concurrently = ( self.server_version_info >= (8, 2) ) self._supports_drop_index_concurrently = self.server_version_info >= ( 9, 2, ) self.supports_identity_columns = self.server_version_info >= (10,) def on_connect(self): if self.isolation_level is not None: def connect(conn): self.set_isolation_level(conn, self.isolation_level) return connect else: return None _isolation_lookup = set( [ "SERIALIZABLE", "READ UNCOMMITTED", "READ COMMITTED", "REPEATABLE READ", ] ) def set_isolation_level(self, connection, level): level = level.replace("_", " ") if level not in self._isolation_lookup: raise exc.ArgumentError( "Invalid value '%s' for isolation_level. " "Valid isolation levels for %s are %s" % (level, self.name, ", ".join(self._isolation_lookup)) ) cursor = connection.cursor() cursor.execute( "SET SESSION CHARACTERISTICS AS TRANSACTION " "ISOLATION LEVEL %s" % level ) cursor.execute("COMMIT") cursor.close() def get_isolation_level(self, connection): cursor = connection.cursor() cursor.execute("show transaction isolation level") val = cursor.fetchone()[0] cursor.close() return val.upper() def set_readonly(self, connection, value): raise NotImplementedError() def get_readonly(self, connection): raise NotImplementedError() def set_deferrable(self, connection, value): raise NotImplementedError() def get_deferrable(self, connection): raise NotImplementedError() def do_begin_twophase(self, connection, xid): self.do_begin(connection.connection) def do_prepare_twophase(self, connection, xid): connection.exec_driver_sql("PREPARE TRANSACTION '%s'" % xid) def do_rollback_twophase( self, connection, xid, is_prepared=True, recover=False ): if is_prepared: if recover: # FIXME: ugly hack to get out of transaction # context when committing recoverable transactions # Must find out a way how to make the dbapi not # open a transaction. connection.exec_driver_sql("ROLLBACK") connection.exec_driver_sql("ROLLBACK PREPARED '%s'" % xid) connection.exec_driver_sql("BEGIN") self.do_rollback(connection.connection) else: self.do_rollback(connection.connection) def do_commit_twophase( self, connection, xid, is_prepared=True, recover=False ): if is_prepared: if recover: connection.exec_driver_sql("ROLLBACK") connection.exec_driver_sql("COMMIT PREPARED '%s'" % xid) connection.exec_driver_sql("BEGIN") self.do_rollback(connection.connection) else: self.do_commit(connection.connection) def do_recover_twophase(self, connection): resultset = connection.execute( sql.text("SELECT gid FROM pg_prepared_xacts") ) return [row[0] for row in resultset] def _get_default_schema_name(self, connection): return connection.exec_driver_sql("select current_schema()").scalar() def has_schema(self, connection, schema): query = ( "select nspname from pg_namespace " "where lower(nspname)=:schema" ) cursor = connection.execute( sql.text(query).bindparams( sql.bindparam( "schema", util.text_type(schema.lower()), type_=sqltypes.Unicode, ) ) ) return bool(cursor.first()) def has_table(self, connection, table_name, schema=None): self._ensure_has_table_connection(connection) # seems like case gets folded in pg_class... if schema is None: cursor = connection.execute( sql.text( "select relname from pg_class c join pg_namespace n on " "n.oid=c.relnamespace where " "pg_catalog.pg_table_is_visible(c.oid) " "and relname=:name" ).bindparams( sql.bindparam( "name", util.text_type(table_name), type_=sqltypes.Unicode, ) ) ) else: cursor = connection.execute( sql.text( "select relname from pg_class c join pg_namespace n on " "n.oid=c.relnamespace where n.nspname=:schema and " "relname=:name" ).bindparams( sql.bindparam( "name", util.text_type(table_name), type_=sqltypes.Unicode, ), sql.bindparam( "schema", util.text_type(schema), type_=sqltypes.Unicode, ), ) ) return bool(cursor.first()) def has_sequence(self, connection, sequence_name, schema=None): if schema is None: schema = self.default_schema_name cursor = connection.execute( sql.text( "SELECT relname FROM pg_class c join pg_namespace n on " "n.oid=c.relnamespace where relkind='S' and " "n.nspname=:schema and relname=:name" ).bindparams( sql.bindparam( "name", util.text_type(sequence_name), type_=sqltypes.Unicode, ), sql.bindparam( "schema", util.text_type(schema), type_=sqltypes.Unicode, ), ) ) return bool(cursor.first()) def has_type(self, connection, type_name, schema=None): if schema is not None: query = """ SELECT EXISTS ( SELECT * FROM pg_catalog.pg_type t, pg_catalog.pg_namespace n WHERE t.typnamespace = n.oid AND t.typname = :typname AND n.nspname = :nspname ) """ query = sql.text(query) else: query = """ SELECT EXISTS ( SELECT * FROM pg_catalog.pg_type t WHERE t.typname = :typname AND pg_type_is_visible(t.oid) ) """ query = sql.text(query) query = query.bindparams( sql.bindparam( "typname", util.text_type(type_name), type_=sqltypes.Unicode ) ) if schema is not None: query = query.bindparams( sql.bindparam( "nspname", util.text_type(schema), type_=sqltypes.Unicode ) ) cursor = connection.execute(query) return bool(cursor.scalar()) def _get_server_version_info(self, connection): v = connection.exec_driver_sql("select pg_catalog.version()").scalar() m = re.match( r".*(?:PostgreSQL|EnterpriseDB) " r"(\d+)\.?(\d+)?(?:\.(\d+))?(?:\.\d+)?(?:devel|beta)?", v, ) if not m: raise AssertionError( "Could not determine version from string '%s'" % v ) return tuple([int(x) for x in m.group(1, 2, 3) if x is not None]) @reflection.cache def get_table_oid(self, connection, table_name, schema=None, **kw): """Fetch the oid for schema.table_name. Several reflection methods require the table oid. The idea for using this method is that it can be fetched one time and cached for subsequent calls. """ table_oid = None if schema is not None: schema_where_clause = "n.nspname = :schema" else: schema_where_clause = "pg_catalog.pg_table_is_visible(c.oid)" query = ( """ SELECT c.oid FROM pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_namespace n ON n.oid = c.relnamespace WHERE (%s) AND c.relname = :table_name AND c.relkind in ('r', 'v', 'm', 'f', 'p') """ % schema_where_clause ) # Since we're binding to unicode, table_name and schema_name must be # unicode. table_name = util.text_type(table_name) if schema is not None: schema = util.text_type(schema) s = sql.text(query).bindparams(table_name=sqltypes.Unicode) s = s.columns(oid=sqltypes.Integer) if schema: s = s.bindparams(sql.bindparam("schema", type_=sqltypes.Unicode)) c = connection.execute(s, dict(table_name=table_name, schema=schema)) table_oid = c.scalar() if table_oid is None: raise exc.NoSuchTableError(table_name) return table_oid @reflection.cache def get_schema_names(self, connection, **kw): result = connection.execute( sql.text( "SELECT nspname FROM pg_namespace " "WHERE nspname NOT LIKE 'pg_%' " "ORDER BY nspname" ).columns(nspname=sqltypes.Unicode) ) return [name for name, in result] @reflection.cache def get_table_names(self, connection, schema=None, **kw): result = connection.execute( sql.text( "SELECT c.relname FROM pg_class c " "JOIN pg_namespace n ON n.oid = c.relnamespace " "WHERE n.nspname = :schema AND c.relkind in ('r', 'p')" ).columns(relname=sqltypes.Unicode), dict( schema=schema if schema is not None else self.default_schema_name ), ) return [name for name, in result] @reflection.cache def _get_foreign_table_names(self, connection, schema=None, **kw): result = connection.execute( sql.text( "SELECT c.relname FROM pg_class c " "JOIN pg_namespace n ON n.oid = c.relnamespace " "WHERE n.nspname = :schema AND c.relkind = 'f'" ).columns(relname=sqltypes.Unicode), dict( schema=schema if schema is not None else self.default_schema_name ), ) return [name for name, in result] @reflection.cache def get_view_names( self, connection, schema=None, include=("plain", "materialized"), **kw ): include_kind = {"plain": "v", "materialized": "m"} try: kinds = [include_kind[i] for i in util.to_list(include)] except KeyError: raise ValueError( "include %r unknown, needs to be a sequence containing " "one or both of 'plain' and 'materialized'" % (include,) ) if not kinds: raise ValueError( "empty include, needs to be a sequence containing " "one or both of 'plain' and 'materialized'" ) result = connection.execute( sql.text( "SELECT c.relname FROM pg_class c " "JOIN pg_namespace n ON n.oid = c.relnamespace " "WHERE n.nspname = :schema AND c.relkind IN (%s)" % (", ".join("'%s'" % elem for elem in kinds)) ).columns(relname=sqltypes.Unicode), dict( schema=schema if schema is not None else self.default_schema_name ), ) return [name for name, in result] @reflection.cache def get_sequence_names(self, connection, schema=None, **kw): if not schema: schema = self.default_schema_name cursor = connection.execute( sql.text( "SELECT relname FROM pg_class c join pg_namespace n on " "n.oid=c.relnamespace where relkind='S' and " "n.nspname=:schema" ).bindparams( sql.bindparam( "schema", util.text_type(schema), type_=sqltypes.Unicode, ), ) ) return [row[0] for row in cursor] @reflection.cache def get_view_definition(self, connection, view_name, schema=None, **kw): view_def = connection.scalar( sql.text( "SELECT pg_get_viewdef(c.oid) view_def FROM pg_class c " "JOIN pg_namespace n ON n.oid = c.relnamespace " "WHERE n.nspname = :schema AND c.relname = :view_name " "AND c.relkind IN ('v', 'm')" ).columns(view_def=sqltypes.Unicode), dict( schema=schema if schema is not None else self.default_schema_name, view_name=view_name, ), ) return view_def @reflection.cache def get_columns(self, connection, table_name, schema=None, **kw): table_oid = self.get_table_oid( connection, table_name, schema, info_cache=kw.get("info_cache") ) generated = ( "a.attgenerated as generated" if self.server_version_info >= (12,) else "NULL as generated" ) if self.server_version_info >= (10,): # a.attidentity != '' is required or it will reflect also # serial columns as identity. identity = """\ (SELECT json_build_object( 'always', a.attidentity = 'a', 'start', s.seqstart, 'increment', s.seqincrement, 'minvalue', s.seqmin, 'maxvalue', s.seqmax, 'cache', s.seqcache, 'cycle', s.seqcycle) FROM pg_catalog.pg_sequence s JOIN pg_catalog.pg_class c on s.seqrelid = c."oid" WHERE c.relkind = 'S' AND a.attidentity != '' AND s.seqrelid = pg_catalog.pg_get_serial_sequence( a.attrelid::regclass::text, a.attname )::regclass::oid ) as identity_options\ """ else: identity = "NULL as identity_options" SQL_COLS = """ SELECT a.attname, pg_catalog.format_type(a.atttypid, a.atttypmod), ( SELECT pg_catalog.pg_get_expr(d.adbin, d.adrelid) FROM pg_catalog.pg_attrdef d WHERE d.adrelid = a.attrelid AND d.adnum = a.attnum AND a.atthasdef ) AS DEFAULT, a.attnotnull, a.attrelid as table_oid, pgd.description as comment, %s, %s FROM pg_catalog.pg_attribute a LEFT JOIN pg_catalog.pg_description pgd ON ( pgd.objoid = a.attrelid AND pgd.objsubid = a.attnum) WHERE a.attrelid = :table_oid AND a.attnum > 0 AND NOT a.attisdropped ORDER BY a.attnum """ % ( generated, identity, ) s = ( sql.text(SQL_COLS) .bindparams(sql.bindparam("table_oid", type_=sqltypes.Integer)) .columns(attname=sqltypes.Unicode, default=sqltypes.Unicode) ) c = connection.execute(s, dict(table_oid=table_oid)) rows = c.fetchall() # dictionary with (name, ) if default search path or (schema, name) # as keys domains = self._load_domains(connection) # dictionary with (name, ) if default search path or (schema, name) # as keys enums = dict( ((rec["name"],), rec) if rec["visible"] else ((rec["schema"], rec["name"]), rec) for rec in self._load_enums(connection, schema="*") ) # format columns columns = [] for ( name, format_type, default_, notnull, table_oid, comment, generated, identity, ) in rows: column_info = self._get_column_info( name, format_type, default_, notnull, domains, enums, schema, comment, generated, identity, ) columns.append(column_info) return columns def _get_column_info( self, name, format_type, default, notnull, domains, enums, schema, comment, generated, identity, ): def _handle_array_type(attype): return ( # strip '[]' from integer[], etc. re.sub(r"\[\]$", "", attype), attype.endswith("[]"), ) # strip (*) from character varying(5), timestamp(5) # with time zone, geometry(POLYGON), etc. attype = re.sub(r"\(.*\)", "", format_type) # strip '[]' from integer[], etc. and check if an array attype, is_array = _handle_array_type(attype) # strip quotes from case sensitive enum or domain names enum_or_domain_key = tuple(util.quoted_token_parser(attype)) nullable = not notnull charlen = re.search(r"\(([\d,]+)\)", format_type) if charlen: charlen = charlen.group(1) args = re.search(r"\((.*)\)", format_type) if args and args.group(1): args = tuple(re.split(r"\s*,\s*", args.group(1))) else: args = () kwargs = {} if attype == "numeric": if charlen: prec, scale = charlen.split(",") args = (int(prec), int(scale)) else: args = () elif attype == "double precision": args = (53,) elif attype == "integer": args = () elif attype in ("timestamp with time zone", "time with time zone"): kwargs["timezone"] = True if charlen: kwargs["precision"] = int(charlen) args = () elif attype in ( "timestamp without time zone", "time without time zone", "time", ): kwargs["timezone"] = False if charlen: kwargs["precision"] = int(charlen) args = () elif attype == "bit varying": kwargs["varying"] = True if charlen: args = (int(charlen),) else: args = () elif attype.startswith("interval"): field_match = re.match(r"interval (.+)", attype, re.I) if charlen: kwargs["precision"] = int(charlen) if field_match: kwargs["fields"] = field_match.group(1) attype = "interval" args = () elif charlen: args = (int(charlen),) while True: # looping here to suit nested domains if attype in self.ischema_names: coltype = self.ischema_names[attype] break elif enum_or_domain_key in enums: enum = enums[enum_or_domain_key] coltype = ENUM kwargs["name"] = enum["name"] if not enum["visible"]: kwargs["schema"] = enum["schema"] args = tuple(enum["labels"]) break elif enum_or_domain_key in domains: domain = domains[enum_or_domain_key] attype = domain["attype"] attype, is_array = _handle_array_type(attype) # strip quotes from case sensitive enum or domain names enum_or_domain_key = tuple(util.quoted_token_parser(attype)) # A table can't override a not null on the domain, # but can override nullable nullable = nullable and domain["nullable"] if domain["default"] and not default: # It can, however, override the default # value, but can't set it to null. default = domain["default"] continue else: coltype = None break if coltype: coltype = coltype(*args, **kwargs) if is_array: coltype = self.ischema_names["_array"](coltype) else: util.warn( "Did not recognize type '%s' of column '%s'" % (attype, name) ) coltype = sqltypes.NULLTYPE # If a zero byte or blank string depending on driver (is also absent # for older PG versions), then not a generated column. Otherwise, s = # stored. (Other values might be added in the future.) if generated not in (None, "", b"\x00"): computed = dict( sqltext=default, persisted=generated in ("s", b"s") ) default = None else: computed = None # adjust the default value autoincrement = False if default is not None: match = re.search(r"""(nextval\(')([^']+)('.*$)""", default) if match is not None: if issubclass(coltype._type_affinity, sqltypes.Integer): autoincrement = True # the default is related to a Sequence sch = schema if "." not in match.group(2) and sch is not None: # unconditionally quote the schema name. this could # later be enhanced to obey quoting rules / # "quote schema" default = ( match.group(1) + ('"%s"' % sch) + "." + match.group(2) + match.group(3) ) column_info = dict( name=name, type=coltype, nullable=nullable, default=default, autoincrement=autoincrement or identity is not None, comment=comment, ) if computed is not None: column_info["computed"] = computed if identity is not None: column_info["identity"] = identity return column_info @reflection.cache def get_pk_constraint(self, connection, table_name, schema=None, **kw): table_oid = self.get_table_oid( connection, table_name, schema, info_cache=kw.get("info_cache") ) if self.server_version_info < (8, 4): PK_SQL = """ SELECT a.attname FROM pg_class t join pg_index ix on t.oid = ix.indrelid join pg_attribute a on t.oid=a.attrelid AND %s WHERE t.oid = :table_oid and ix.indisprimary = 't' ORDER BY a.attnum """ % self._pg_index_any( "a.attnum", "ix.indkey" ) else: # unnest() and generate_subscripts() both introduced in # version 8.4 PK_SQL = """ SELECT a.attname FROM pg_attribute a JOIN ( SELECT unnest(ix.indkey) attnum, generate_subscripts(ix.indkey, 1) ord FROM pg_index ix WHERE ix.indrelid = :table_oid AND ix.indisprimary ) k ON a.attnum=k.attnum WHERE a.attrelid = :table_oid ORDER BY k.ord """ t = sql.text(PK_SQL).columns(attname=sqltypes.Unicode) c = connection.execute(t, dict(table_oid=table_oid)) cols = [r[0] for r in c.fetchall()] PK_CONS_SQL = """ SELECT conname FROM pg_catalog.pg_constraint r WHERE r.conrelid = :table_oid AND r.contype = 'p' ORDER BY 1 """ t = sql.text(PK_CONS_SQL).columns(conname=sqltypes.Unicode) c = connection.execute(t, dict(table_oid=table_oid)) name = c.scalar() return {"constrained_columns": cols, "name": name} @reflection.cache def get_foreign_keys( self, connection, table_name, schema=None, postgresql_ignore_search_path=False, **kw ): preparer = self.identifier_preparer table_oid = self.get_table_oid( connection, table_name, schema, info_cache=kw.get("info_cache") ) FK_SQL = """ SELECT r.conname, pg_catalog.pg_get_constraintdef(r.oid, true) as condef, n.nspname as conschema FROM pg_catalog.pg_constraint r, pg_namespace n, pg_class c WHERE r.conrelid = :table AND r.contype = 'f' AND c.oid = confrelid AND n.oid = c.relnamespace ORDER BY 1 """ # https://www.postgresql.org/docs/9.0/static/sql-createtable.html FK_REGEX = re.compile( r"FOREIGN KEY \((.*?)\) REFERENCES (?:(.*?)\.)?(.*?)\((.*?)\)" r"[\s]?(MATCH (FULL|PARTIAL|SIMPLE)+)?" r"[\s]?(ON UPDATE " r"(CASCADE|RESTRICT|NO ACTION|SET NULL|SET DEFAULT)+)?" r"[\s]?(ON DELETE " r"(CASCADE|RESTRICT|NO ACTION|SET NULL|SET DEFAULT)+)?" r"[\s]?(DEFERRABLE|NOT DEFERRABLE)?" r"[\s]?(INITIALLY (DEFERRED|IMMEDIATE)+)?" ) t = sql.text(FK_SQL).columns( conname=sqltypes.Unicode, condef=sqltypes.Unicode ) c = connection.execute(t, dict(table=table_oid)) fkeys = [] for conname, condef, conschema in c.fetchall(): m = re.search(FK_REGEX, condef).groups() ( constrained_columns, referred_schema, referred_table, referred_columns, _, match, _, onupdate, _, ondelete, deferrable, _, initially, ) = m if deferrable is not None: deferrable = True if deferrable == "DEFERRABLE" else False constrained_columns = [ preparer._unquote_identifier(x) for x in re.split(r"\s*,\s*", constrained_columns) ] if postgresql_ignore_search_path: # when ignoring search path, we use the actual schema # provided it isn't the "default" schema if conschema != self.default_schema_name: referred_schema = conschema else: referred_schema = schema elif referred_schema: # referred_schema is the schema that we regexp'ed from # pg_get_constraintdef(). If the schema is in the search # path, pg_get_constraintdef() will give us None. referred_schema = preparer._unquote_identifier(referred_schema) elif schema is not None and schema == conschema: # If the actual schema matches the schema of the table # we're reflecting, then we will use that. referred_schema = schema referred_table = preparer._unquote_identifier(referred_table) referred_columns = [ preparer._unquote_identifier(x) for x in re.split(r"\s*,\s", referred_columns) ] options = { k: v for k, v in [ ("onupdate", onupdate), ("ondelete", ondelete), ("initially", initially), ("deferrable", deferrable), ("match", match), ] if v is not None and v != "NO ACTION" } fkey_d = { "name": conname, "constrained_columns": constrained_columns, "referred_schema": referred_schema, "referred_table": referred_table, "referred_columns": referred_columns, "options": options, } fkeys.append(fkey_d) return fkeys def _pg_index_any(self, col, compare_to): if self.server_version_info < (8, 1): # https://www.postgresql.org/message-id/10279.1124395722@sss.pgh.pa.us # "In CVS tip you could replace this with "attnum = ANY (indkey)". # Unfortunately, most array support doesn't work on int2vector in # pre-8.1 releases, so I think you're kinda stuck with the above # for now. # regards, tom lane" return "(%s)" % " OR ".join( "%s[%d] = %s" % (compare_to, ind, col) for ind in range(0, 10) ) else: return "%s = ANY(%s)" % (col, compare_to) @reflection.cache def get_indexes(self, connection, table_name, schema, **kw): table_oid = self.get_table_oid( connection, table_name, schema, info_cache=kw.get("info_cache") ) # cast indkey as varchar since it's an int2vector, # returned as a list by some drivers such as pypostgresql if self.server_version_info < (8, 5): IDX_SQL = """ SELECT i.relname as relname, ix.indisunique, ix.indexprs, ix.indpred, a.attname, a.attnum, NULL, ix.indkey%s, %s, %s, am.amname, NULL as indnkeyatts FROM pg_class t join pg_index ix on t.oid = ix.indrelid join pg_class i on i.oid = ix.indexrelid left outer join pg_attribute a on t.oid = a.attrelid and %s left outer join pg_am am on i.relam = am.oid WHERE t.relkind IN ('r', 'v', 'f', 'm') and t.oid = :table_oid and ix.indisprimary = 'f' ORDER BY t.relname, i.relname """ % ( # version 8.3 here was based on observing the # cast does not work in PG 8.2.4, does work in 8.3.0. # nothing in PG changelogs regarding this. "::varchar" if self.server_version_info >= (8, 3) else "", "ix.indoption::varchar" if self.server_version_info >= (8, 3) else "NULL", "i.reloptions" if self.server_version_info >= (8, 2) else "NULL", self._pg_index_any("a.attnum", "ix.indkey"), ) else: IDX_SQL = """ SELECT i.relname as relname, ix.indisunique, ix.indexprs, a.attname, a.attnum, c.conrelid, ix.indkey::varchar, ix.indoption::varchar, i.reloptions, am.amname, pg_get_expr(ix.indpred, ix.indrelid), %s as indnkeyatts FROM pg_class t join pg_index ix on t.oid = ix.indrelid join pg_class i on i.oid = ix.indexrelid left outer join pg_attribute a on t.oid = a.attrelid and a.attnum = ANY(ix.indkey) left outer join pg_constraint c on (ix.indrelid = c.conrelid and ix.indexrelid = c.conindid and c.contype in ('p', 'u', 'x')) left outer join pg_am am on i.relam = am.oid WHERE t.relkind IN ('r', 'v', 'f', 'm', 'p') and t.oid = :table_oid and ix.indisprimary = 'f' ORDER BY t.relname, i.relname """ % ( "ix.indnkeyatts" if self.server_version_info >= (11, 0) else "NULL", ) t = sql.text(IDX_SQL).columns( relname=sqltypes.Unicode, attname=sqltypes.Unicode ) c = connection.execute(t, dict(table_oid=table_oid)) indexes = defaultdict(lambda: defaultdict(dict)) sv_idx_name = None for row in c.fetchall(): ( idx_name, unique, expr, col, col_num, conrelid, idx_key, idx_option, options, amname, filter_definition, indnkeyatts, ) = row if expr: if idx_name != sv_idx_name: util.warn( "Skipped unsupported reflection of " "expression-based index %s" % idx_name ) sv_idx_name = idx_name continue has_idx = idx_name in indexes index = indexes[idx_name] if col is not None: index["cols"][col_num] = col if not has_idx: idx_keys = idx_key.split() # "The number of key columns in the index, not counting any # included columns, which are merely stored and do not # participate in the index semantics" if indnkeyatts and idx_keys[indnkeyatts:]: # this is a "covering index" which has INCLUDE columns # as well as regular index columns inc_keys = idx_keys[indnkeyatts:] idx_keys = idx_keys[:indnkeyatts] else: inc_keys = [] index["key"] = [int(k.strip()) for k in idx_keys] index["inc"] = [int(k.strip()) for k in inc_keys] # (new in pg 8.3) # "pg_index.indoption" is list of ints, one per column/expr. # int acts as bitmask: 0x01=DESC, 0x02=NULLSFIRST sorting = {} for col_idx, col_flags in enumerate( (idx_option or "").split() ): col_flags = int(col_flags.strip()) col_sorting = () # try to set flags only if they differ from PG defaults... if col_flags & 0x01: col_sorting += ("desc",) if not (col_flags & 0x02): col_sorting += ("nulls_last",) else: if col_flags & 0x02: col_sorting += ("nulls_first",) if col_sorting: sorting[col_idx] = col_sorting if sorting: index["sorting"] = sorting index["unique"] = unique if conrelid is not None: index["duplicates_constraint"] = idx_name if options: index["options"] = dict( [option.split("=") for option in options] ) # it *might* be nice to include that this is 'btree' in the # reflection info. But we don't want an Index object # to have a ``postgresql_using`` in it that is just the # default, so for the moment leaving this out. if amname and amname != "btree": index["amname"] = amname if filter_definition: index["postgresql_where"] = filter_definition result = [] for name, idx in indexes.items(): entry = { "name": name, "unique": idx["unique"], "column_names": [idx["cols"][i] for i in idx["key"]], } if self.server_version_info >= (11, 0): # NOTE: this is legacy, this is part of dialect_options now # as of #7382 entry["include_columns"] = [idx["cols"][i] for i in idx["inc"]] if "duplicates_constraint" in idx: entry["duplicates_constraint"] = idx["duplicates_constraint"] if "sorting" in idx: entry["column_sorting"] = dict( (idx["cols"][idx["key"][i]], value) for i, value in idx["sorting"].items() ) if "include_columns" in entry: entry.setdefault("dialect_options", {})[ "postgresql_include" ] = entry["include_columns"] if "options" in idx: entry.setdefault("dialect_options", {})[ "postgresql_with" ] = idx["options"] if "amname" in idx: entry.setdefault("dialect_options", {})[ "postgresql_using" ] = idx["amname"] if "postgresql_where" in idx: entry.setdefault("dialect_options", {})[ "postgresql_where" ] = idx["postgresql_where"] result.append(entry) return result @reflection.cache def get_unique_constraints( self, connection, table_name, schema=None, **kw ): table_oid = self.get_table_oid( connection, table_name, schema, info_cache=kw.get("info_cache") ) UNIQUE_SQL = """ SELECT cons.conname as name, cons.conkey as key, a.attnum as col_num, a.attname as col_name FROM pg_catalog.pg_constraint cons join pg_attribute a on cons.conrelid = a.attrelid AND a.attnum = ANY(cons.conkey) WHERE cons.conrelid = :table_oid AND cons.contype = 'u' """ t = sql.text(UNIQUE_SQL).columns(col_name=sqltypes.Unicode) c = connection.execute(t, dict(table_oid=table_oid)) uniques = defaultdict(lambda: defaultdict(dict)) for row in c.fetchall(): uc = uniques[row.name] uc["key"] = row.key uc["cols"][row.col_num] = row.col_name return [ {"name": name, "column_names": [uc["cols"][i] for i in uc["key"]]} for name, uc in uniques.items() ] @reflection.cache def get_table_comment(self, connection, table_name, schema=None, **kw): table_oid = self.get_table_oid( connection, table_name, schema, info_cache=kw.get("info_cache") ) COMMENT_SQL = """ SELECT pgd.description as table_comment FROM pg_catalog.pg_description pgd WHERE pgd.objsubid = 0 AND pgd.objoid = :table_oid """ c = connection.execute( sql.text(COMMENT_SQL), dict(table_oid=table_oid) ) return {"text": c.scalar()} @reflection.cache def get_check_constraints(self, connection, table_name, schema=None, **kw): table_oid = self.get_table_oid( connection, table_name, schema, info_cache=kw.get("info_cache") ) CHECK_SQL = """ SELECT cons.conname as name, pg_get_constraintdef(cons.oid) as src FROM pg_catalog.pg_constraint cons WHERE cons.conrelid = :table_oid AND cons.contype = 'c' """ c = connection.execute(sql.text(CHECK_SQL), dict(table_oid=table_oid)) ret = [] for name, src in c: # samples: # "CHECK (((a > 1) AND (a < 5)))" # "CHECK (((a = 1) OR ((a > 2) AND (a < 5))))" # "CHECK (((a > 1) AND (a < 5))) NOT VALID" # "CHECK (some_boolean_function(a))" # "CHECK (((a\n < 1)\n OR\n (a\n >= 5))\n)" m = re.match( r"^CHECK *\((.+)\)( NOT VALID)?$", src, flags=re.DOTALL ) if not m: util.warn("Could not parse CHECK constraint text: %r" % src) sqltext = "" else: sqltext = re.compile( r"^[\s\n]*\((.+)\)[\s\n]*$", flags=re.DOTALL ).sub(r"\1", m.group(1)) entry = {"name": name, "sqltext": sqltext} if m and m.group(2): entry["dialect_options"] = {"not_valid": True} ret.append(entry) return ret def _load_enums(self, connection, schema=None): schema = schema or self.default_schema_name if not self.supports_native_enum: return {} # Load data types for enums: SQL_ENUMS = """ SELECT t.typname as "name", -- no enum defaults in 8.4 at least -- t.typdefault as "default", pg_catalog.pg_type_is_visible(t.oid) as "visible", n.nspname as "schema", e.enumlabel as "label" FROM pg_catalog.pg_type t LEFT JOIN pg_catalog.pg_namespace n ON n.oid = t.typnamespace LEFT JOIN pg_catalog.pg_enum e ON t.oid = e.enumtypid WHERE t.typtype = 'e' """ if schema != "*": SQL_ENUMS += "AND n.nspname = :schema " # e.oid gives us label order within an enum SQL_ENUMS += 'ORDER BY "schema", "name", e.oid' s = sql.text(SQL_ENUMS).columns( attname=sqltypes.Unicode, label=sqltypes.Unicode ) if schema != "*": s = s.bindparams(schema=schema) c = connection.execute(s) enums = [] enum_by_name = {} for enum in c.fetchall(): key = (enum.schema, enum.name) if key in enum_by_name: enum_by_name[key]["labels"].append(enum.label) else: enum_by_name[key] = enum_rec = { "name": enum.name, "schema": enum.schema, "visible": enum.visible, "labels": [], } if enum.label is not None: enum_rec["labels"].append(enum.label) enums.append(enum_rec) return enums def _load_domains(self, connection): # Load data types for domains: SQL_DOMAINS = """ SELECT t.typname as "name", pg_catalog.format_type(t.typbasetype, t.typtypmod) as "attype", not t.typnotnull as "nullable", t.typdefault as "default", pg_catalog.pg_type_is_visible(t.oid) as "visible", n.nspname as "schema" FROM pg_catalog.pg_type t LEFT JOIN pg_catalog.pg_namespace n ON n.oid = t.typnamespace WHERE t.typtype = 'd' """ s = sql.text(SQL_DOMAINS) c = connection.execution_options(future_result=True).execute(s) domains = {} for domain in c.mappings(): domain = domain # strip (30) from character varying(30) attype = re.search(r"([^\(]+)", domain["attype"]).group(1) # 'visible' just means whether or not the domain is in a # schema that's on the search path -- or not overridden by # a schema with higher precedence. If it's not visible, # it will be prefixed with the schema-name when it's used. if domain["visible"]: key = (domain["name"],) else: key = (domain["schema"], domain["name"]) domains[key] = { "attype": attype, "nullable": domain["nullable"], "default": domain["default"], } return domains