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bflw/venv/lib/python3.11/site-packages/sqlalchemy/dialects/postgresql/base.py

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# postgresql/base.py
# Copyright (C) 2005-2022 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# 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, 14
: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.isolation_level` 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 <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",
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
There are also more options for isolation level configurations, such as
"sub-engine" objects linked to a main :class:`_engine.Engine` which each apply
different isolation level settings. See the discussion at
:ref:`dbapi_autocommit` for background.
Valid values for ``isolation_level`` on most PostgreSQL dialects include:
* ``READ COMMITTED``
* ``READ UNCOMMITTED``
* ``REPEATABLE READ``
* ``SERIALIZABLE``
* ``AUTOCOMMIT``
.. seealso::
:ref:`dbapi_autocommit`
:ref:`postgresql_readonly_deferrable`
: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:`metadata_reflection_schemas`.
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
<https://www.postgresql.org/docs/current/static/ddl-schemas.html#DDL-SCHEMAS-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)
...
<sqlalchemy.engine.result.CursorResult object at 0x101612ed0>
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)
...
<sqlalchemy.engine.result.CursorResult object at 0x1016126d0>
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
<https://www.postgresql.org/docs/current/static/ddl-schemas.html#DDL-SCHEMAS-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
<https://www.postgresql.org/docs/current/static/sql-insert.html#SQL-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 <https://www.postgresql.org/docs/current/textsearch-controls.html>`_.
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.
.. seealso::
`Full Text Search <https://www.postgresql.org/docs/current/textsearch-controls.html>`_ - in the PostgreSQL documentation
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/current/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/current/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
<https://www.postgresql.org/docs/current/static/sql-createtable.html>`_ -
in the PostgreSQL documentation.
.. _postgresql_constraint_options:
PostgreSQL Constraint Options
-----------------------------
The following option(s) are supported by the PostgreSQL dialect in conjunction
with selected constraint constructs:
* ``NOT VALID``: This option applies towards CHECK and FOREIGN KEY constraints
when the constraint is being added to an existing table via ALTER TABLE,
and has the effect that existing rows are not scanned during the ALTER
operation against the constraint being added.
When using a SQL migration tool such as `Alembic <https://alembic.sqlalchemy.org>`_
that renders ALTER TABLE constructs, the ``postgresql_not_valid`` argument
may be specified as an additional keyword argument within the operation
that creates the constraint, as in the following Alembic example::
def update():
op.create_foreign_key(
"fk_user_address",
"address",
"user",
["user_id"],
["id"],
postgresql_not_valid=True
)
The keyword is ultimately accepted directly by the
:class:`_schema.CheckConstraint`, :class:`_schema.ForeignKeyConstraint`
and :class:`_schema.ForeignKey` constructs; when using a tool like
Alembic, dialect-specific keyword arguments are passed through to
these constructs from the migration operation directives::
CheckConstraint("some_field IS NOT NULL", postgresql_not_valid=True)
ForeignKeyConstraint(["some_id"], ["some_table.some_id"], postgresql_not_valid=True)
.. versionadded:: 1.4.32
.. seealso::
`PostgreSQL ALTER TABLE options
<https://www.postgresql.org/docs/current/static/sql-altertable.html>`_ -
in the PostgreSQL documentation.
.. _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").
... render_derived()
... )
>>> 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(value, ordinality)
.. 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
<https://www.postgresql.org/docs/current/sql-expressions.html#SQL-SYNTAX-ROW-CONSTRUCTORS>`_
`PostgreSQL Row Constructor Comparison
<https://www.postgresql.org/docs/current/functions-comparisons.html#ROW-WISE-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 dml
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):
"""Provide the PostgreSQL TIMESTAMP type."""
__visit_name__ = "TIMESTAMP"
def __init__(self, timezone=False, precision=None):
"""Construct a TIMESTAMP.
:param timezone: boolean value if timezone present, default False
:param precision: optional integer precision value
.. versionadded:: 1.4
"""
super(TIMESTAMP, self).__init__(timezone=timezone)
self.precision = precision
class TIME(sqltypes.TIME):
"""PostgreSQL TIME type."""
__visit_name__ = "TIME"
def __init__(self, timezone=False, precision=None):
"""Construct a TIME.
:param timezone: boolean value if timezone present, default False
:param precision: optional integer precision value
.. versionadded:: 1.4
"""
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
@property
def python_type(self):
return _python_UUID if self.as_uuid else str
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
@util.memoized_property
def _is_safe_for_fast_insert_values_helper(self):
# don't allow fast executemany if _post_values_clause is
# present and is not an OnConflictDoNothing. what this means
# concretely is that the
# "fast insert executemany helper" won't be used, in other
# words we won't convert "executemany()" of many parameter
# sets into a single INSERT with many elements in VALUES.
# We can't apply that optimization safely if for example the
# statement includes a clause like "ON CONFLICT DO UPDATE"
return self.insert_single_values_expr is not None and (
self.statement._post_values_clause is None
or isinstance(
self.statement._post_values_clause, dml.OnConflictDoNothing
)
)
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(c.name)
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 _define_constraint_validity(self, constraint):
not_valid = constraint.dialect_options["postgresql"]["not_valid"]
return " NOT VALID" if not_valid else ""
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."
)
text = super(PGDDLCompiler, self).visit_check_constraint(constraint)
text += self._define_constraint_validity(constraint)
return text
def visit_foreign_key_constraint(self, constraint):
text = super(PGDDLCompiler, self).visit_foreign_key_constraint(
constraint
)
text += self._define_constraint_validity(constraint)
return text
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,
},
),
(
schema.CheckConstraint,
{
"not_valid": False,
},
),
(
schema.ForeignKeyConstraint,
{
"not_valid": False,
},
),
]
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