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add start of sqlalchemy code examples
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‎content/pages/examples/sqlalchemy/sqlalchemy-dialects-postgresql-base-pgtypecompiler.markdown‎

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title: sqlalchemy.dialects.postgresql.base PGTypeCompiler code examples
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category: page
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slug: sqlalchemy-dialects-postgresql-base-pgtypecompiler-examples
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sortorder: 500031000
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toc: False
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sidebartitle: sqlalchemy.dialects.postgresql.base PGTypeCompiler
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meta: Python example code for the PGTypeCompiler class from the sqlalchemy.dialects.postgresql.base module of the SQLAlchemy project.
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PGTypeCompiler is a class within the sqlalchemy.dialects.postgresql.base module of the SQLAlchemy project.
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## Example 1 from sqlalchemy-utils
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[sqlalchemy-utils](https://github.com/kvesteri/sqlalchemy-utils)
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([project documentation](https://sqlalchemy-utils.readthedocs.io/en/latest/)
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and
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[PyPI package information](https://pypi.org/project/SQLAlchemy-Utils/))
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is a code library with various helper functions and new data types
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that make it easier to use [SQLAlchemy](/sqlachemy.html) when building
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projects that involve more specific storage requirements such as
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[currency](https://sqlalchemy-utils.readthedocs.io/en/latest/data_types.html#module-sqlalchemy_utils.types.currency).
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The wide array of
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[data types](https://sqlalchemy-utils.readthedocs.io/en/latest/data_types.html)
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includes [ranged values](https://sqlalchemy-utils.readthedocs.io/en/latest/range_data_types.html)
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and [aggregated attributes](https://sqlalchemy-utils.readthedocs.io/en/latest/aggregates.html).
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[**sqlalchemy-utils / sqlalchemy_utils / types / ltree.py**](https://github.com/kvesteri/sqlalchemy-utils/blob/master/sqlalchemy_utils/types/ltree.py)
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```python
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# ltree.py
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from __future__ import absolute_import
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from sqlalchemy import types
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from sqlalchemy.dialects.postgresql import ARRAY
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~~from sqlalchemy.dialects.postgresql.base import ischema_names, PGTypeCompiler
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from sqlalchemy.sql import expression
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from ..primitives import Ltree
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from .scalar_coercible import ScalarCoercible
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class LtreeType(types.Concatenable, types.UserDefinedType, ScalarCoercible):
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"""Postgresql LtreeType type.
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The LtreeType datatype can be used for representing labels of data stored
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in hierarchial tree-like structure. For more detailed information please
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refer to http://www.postgresql.org/docs/current/static/ltree.html
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::
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from sqlalchemy_utils import LtreeType, Ltree
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class DocumentSection(Base):
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__tablename__ = 'document_section'
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id = sa.Column(sa.Integer, autoincrement=True, primary_key=True)
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path = sa.Column(LtreeType)
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## ... source file abbreviated to get to PGTypeCompiler examples ...
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__visit_name__ = 'LTXTQUERY'
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ischema_names['ltree'] = LtreeType
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ischema_names['lquery'] = LQUERY
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ischema_names['ltxtquery'] = LTXTQUERY
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def visit_LTREE(self, type_, **kw):
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return 'LTREE'
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def visit_LQUERY(self, type_, **kw):
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return 'LQUERY'
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def visit_LTXTQUERY(self, type_, **kw):
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return 'LTXTQUERY'
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~~PGTypeCompiler.visit_LTREE = visit_LTREE
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~~PGTypeCompiler.visit_LQUERY = visit_LQUERY
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~~PGTypeCompiler.visit_LTXTQUERY = visit_LTXTQUERY
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## ... source file continues with no further PGTypeCompiler examples...
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```
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‎content/pages/examples/sqlalchemy/sqlalchemy-dialects-postgresql-psycopg2-pgdialect-psycopg2.markdown‎

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title: sqlalchemy.dialects.postgresql.psycopg2 PGDialect_psycopg2 code examples
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category: page
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slug: sqlalchemy-dialects-postgresql-psycopg2-pgdialect-psycopg2-examples
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sortorder: 500031000
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toc: False
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sidebartitle: sqlalchemy.dialects.postgresql.psycopg2 PGDialect_psycopg2
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meta: Python example code for the PGDialect_psycopg2 class from the sqlalchemy.dialects.postgresql.psycopg2 module of the SQLAlchemy project.
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PGDialect_psycopg2 is a class within the sqlalchemy.dialects.postgresql.psycopg2 module of the SQLAlchemy project.
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## Example 1 from sqlalchemy-utils
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[sqlalchemy-utils](https://github.com/kvesteri/sqlalchemy-utils)
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([project documentation](https://sqlalchemy-utils.readthedocs.io/en/latest/)
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and
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[PyPI package information](https://pypi.org/project/SQLAlchemy-Utils/))
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is a code library with various helper functions and new data types
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that make it easier to use [SQLAlchemy](/sqlachemy.html) when building
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projects that involve more specific storage requirements such as
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[currency](https://sqlalchemy-utils.readthedocs.io/en/latest/data_types.html#module-sqlalchemy_utils.types.currency).
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The wide array of
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[data types](https://sqlalchemy-utils.readthedocs.io/en/latest/data_types.html)
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includes [ranged values](https://sqlalchemy-utils.readthedocs.io/en/latest/range_data_types.html)
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and [aggregated attributes](https://sqlalchemy-utils.readthedocs.io/en/latest/aggregates.html).
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[**sqlalchemy-utils / sqlalchemy_utils / types / pg_composite.py**](https://github.com/kvesteri/sqlalchemy-utils/blob/master/sqlalchemy_utils/types/pg_composite.py)
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```python
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# pg_composite.py
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"""
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CompositeType provides means to interact with
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`PostgreSQL composite types`_. Currently this type features:
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* Easy attribute access to composite type fields
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* Supports SQLAlchemy TypeDecorator types
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* Ability to include composite types as part of PostgreSQL arrays
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* Type creation and dropping
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Installation
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^^^^^^^^^^^^
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CompositeType automatically attaches `before_create` and `after_drop` DDL
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listeners. These listeners create and drop the composite type in the
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database. This means it works out of the box in your test environment where
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you create the tables on each test run.
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When you already have your database set up you should call
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:func:`register_composites` after you've set up all models.
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::
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register_composites(conn)
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Usage
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^^^^^
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::
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## ... source file abbreviated to get to PGDialect_psycopg2 examples ...
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sa.Column('amount', sa.Integer)
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]
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)
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)
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)
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.. _PostgreSQL composite types:
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http://www.postgresql.org/docs/current/static/rowtypes.html
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Related links:
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http://schinckel.net/2014/09/24/using-postgres-composite-types-in-django/
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"""
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from collections import namedtuple
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import six
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import sqlalchemy as sa
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from sqlalchemy.dialects.postgresql import ARRAY
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~~from sqlalchemy.dialects.postgresql.psycopg2 import PGDialect_psycopg2
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from sqlalchemy.ext.compiler import compiles
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from sqlalchemy.schema import _CreateDropBase
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from sqlalchemy.sql.expression import FunctionElement
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from sqlalchemy.types import (
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SchemaType,
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to_instance,
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TypeDecorator,
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UserDefinedType
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)
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from .. import ImproperlyConfigured
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psycopg2 = None
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CompositeCaster = None
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adapt = None
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AsIs = None
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register_adapter = None
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try:
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import psycopg2
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from psycopg2.extras import CompositeCaster
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from psycopg2.extensions import adapt, AsIs, register_adapter
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except ImportError:
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pass
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## ... source file abbreviated to get to PGDialect_psycopg2 examples ...
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bind.dialect.has_type(bind, self.name, schema=self.schema)
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):
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bind.execute(DropCompositeType(self))
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def register_psycopg2_composite(dbapi_connection, composite):
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psycopg2.extras.register_composite(
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composite.name,
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dbapi_connection,
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globally=True,
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factory=composite.caster
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)
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def adapt_composite(value):
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adapted = [
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adapt(
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getattr(value, column.name)
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if not isinstance(column.type, TypeDecorator)
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else column.type.process_bind_param(
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getattr(value, column.name),
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~~ PGDialect_psycopg2()
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)
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)
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for column in
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composite.columns
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]
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for value in adapted:
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if hasattr(value, 'prepare'):
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value.prepare(dbapi_connection)
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values = [
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value.getquoted().decode(dbapi_connection.encoding)
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if six.PY3
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else value.getquoted()
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for value in adapted
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]
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return AsIs("(%s)::%s" % (', '.join(values), composite.name))
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register_adapter(composite.type_cls, adapt_composite)
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def before_create(target, connection, **kw):
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for name, composite in registered_composites.items():
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composite.create(connection, checkfirst=True)
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register_psycopg2_composite(
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connection.connection.connection,
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## ... source file continues with no further PGDialect_psycopg2 examples...
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```
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‎content/pages/examples/sqlalchemy/sqlalchemy-engine-default-defaultdialect.markdown‎

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title: sqlalchemy.engine.default DefaultDialect code examples
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category: page
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slug: sqlalchemy-engine-default-defaultdialect-examples
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sortorder: 500031000
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toc: False
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sidebartitle: sqlalchemy.engine.default DefaultDialect
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meta: Python example code for the DefaultDialect class from the sqlalchemy.engine.default module of the SQLAlchemy project.
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DefaultDialect is a class within the sqlalchemy.engine.default module of the SQLAlchemy project.
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## Example 1 from alembic
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[Alembic](https://github.com/sqlalchemy/alembic)
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([project documentation](https://alembic.sqlalchemy.org/) and
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[PyPI page](https://pypi.org/project/alembic/))
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is a data migrations tool used with [SQLAlchemy](/sqlalchemy.html) to make
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database schema changes. The Alembic project is open sourced under the
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[MIT license](https://github.com/sqlalchemy/alembic/blob/master/LICENSE).
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[**alembic / alembic / autogenerate / api.py**](https://github.com/sqlalchemy/alembic/blob/master/alembic/autogenerate/api.py)
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```python
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# api.py
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"""Provide the 'autogenerate' feature which can produce migration operations
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automatically."""
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import contextlib
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from sqlalchemy import inspect
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from . import compare
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from . import render
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from .. import util
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from ..operations import ops
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def compare_metadata(context, metadata):
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"""Compare a database schema to that given in a
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:class:`-sqlalchemy.schema.MetaData` instance.
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The database connection is presented in the context
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of a :class:`.MigrationContext` object, which
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provides database connectivity as well as optional
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comparison functions to use for datatypes and
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server defaults - see the "autogenerate" arguments
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at :meth:`.EnvironmentContext.configure`
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for details on these.
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The return format is a list of "diff" directives,
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each representing individual differences::
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from alembic.migration import MigrationContext
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from alembic.autogenerate import compare_metadata
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## ... source file abbreviated to get to DefaultDialect examples ...
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imports=(),
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render_item=None,
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migration_context=None,
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):
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"""Render Python code given an :class:`.UpgradeOps` or
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:class:`.DowngradeOps` object.
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This is a convenience function that can be used to test the
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autogenerate output of a user-defined :class:`.MigrationScript` structure.
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"""
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opts = {
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"sqlalchemy_module_prefix": sqlalchemy_module_prefix,
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"alembic_module_prefix": alembic_module_prefix,
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"render_item": render_item,
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"render_as_batch": render_as_batch,
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}
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if migration_context is None:
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from ..runtime.migration import MigrationContext
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~~ from sqlalchemy.engine.default import DefaultDialect
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migration_context = MigrationContext.configure(
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~~ dialect=DefaultDialect()
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)
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autogen_context = AutogenContext(migration_context, opts=opts)
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autogen_context.imports = set(imports)
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return render._indent(
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render._render_cmd_body(up_or_down_op, autogen_context)
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)
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def _render_migration_diffs(context, template_args):
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"""legacy, used by test_autogen_composition at the moment"""
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autogen_context = AutogenContext(context)
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upgrade_ops = ops.UpgradeOps([])
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compare._produce_net_changes(autogen_context, upgrade_ops)
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migration_script = ops.MigrationScript(
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rev_id=None,
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upgrade_ops=upgrade_ops,
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downgrade_ops=upgrade_ops.reverse(),
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)
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render._render_python_into_templatevars(
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## ... source file continues with no further DefaultDialect examples...
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```
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