The SQLAlchemy SQL Toolkit and Object Relational Mapper is a comprehensive set of tools for working with databases and Python. It has several distinct areas of functionality which can be used individually or combined together. Its major components are illustrated in below, with component dependencies organized into layers:
Above, the two most significant front-facing portions of SQLAlchemy are the Object Relational Mapper and the SQL Expression Language. SQL Expressions can be used independently of the ORM. When using the ORM, the SQL Expression language remains part of the public facing API as it is used within object-relational configurations and queries.
The documentation is separated into three sections: SQLAlchemy ORM, SQLAlchemy Core, and Dialects.
In SQLAlchemy ORM, the Object Relational Mapper is introduced and fully described. New users should begin with the Object Relational Tutorial. If you want to work with higher-level SQL which is constructed automatically for you, as well as management of Python objects, proceed to this tutorial.
In SQLAlchemy Core, the breadth of SQLAlchemy’s SQL and database integration and description services are documented, the core of which is the SQL Expression language. The SQL Expression Language is a toolkit all its own, independent of the ORM package, which can be used to construct manipulable SQL expressions which can be programmatically constructed, modified, and executed, returning cursor-like result sets. In contrast to the ORM’s domain-centric mode of usage, the expression language provides a schema-centric usage paradigm. New users should begin here with SQL Expression Language Tutorial. SQLAlchemy engine, connection, and pooling services are also described in SQLAlchemy Core.
In Dialects, reference documentation for all provided database and DBAPI backends is provided.
Working code examples, mostly regarding the ORM, are included in the SQLAlchemy distribution. A description of all the included example applications is at ORM Examples.
There is also a wide variety of examples involving both core SQLAlchemy constructs as well as the ORM on the wiki. See Theatrum Chemicum.
SQLAlchemy has been tested against the following platforms:
Changed in version 0.9: Python 2.6 is now the minimum Python version supported.
Platforms that don’t currently have support include Jython, IronPython. Jython has been supported in the past and may be supported in future releases as well, depending on the state of Jython itself.
SQLAlchemy supports installation using standard Python “distutils” or “setuptools” methodologies. An overview of potential setups is as follows:
setup.py
script. The C extensions as well as Python 3 builds are supported.setup.py
or easy_install
, and the C
extensions are supported.setuptools
or distribute
, replacing the usage
of easy_install
. It is often preferred for its simpler mode of usage.When pip
is available, the distribution can be
downloaded from Pypi and installed in one step:
pip install SQLAlchemy
This command will download the latest released version of SQLAlchemy from the Python Cheese Shop and install it to your system.
In order to install the latest prerelease version, such as 1.0.0b1
,
pip requires that the --pre
flag be used:
pip install --pre SQLAlchemy
Where above, if the most recent version is a prerelease, it will be installed instead of the latest released version.
Otherwise, you can install from the distribution using the setup.py
script:
python setup.py install
SQLAlchemy includes C extensions which provide an extra speed boost for dealing with result sets. The extensions are supported on both the 2.xx and 3.xx series of cPython.
Changed in version 0.9.0: The C extensions now compile on Python 3 as well as Python 2.
setup.py
will automatically build the extensions if an appropriate platform is
detected. If the build of the C extensions fails, due to missing compiler or
other issue, the setup process will output a warning message, and re-run the
build without the C extensions, upon completion reporting final status.
To run the build/install without even attempting to compile the C extensions,
the DISABLE_SQLALCHEMY_CEXT
environment variable may be specified. The
use case for this is either for special testing circumstances, or in the rare
case of compatibility/build issues not overcome by the usual “rebuild”
mechanism:
# *** only in SQLAlchemy 0.9.4 / 0.8.6 or greater ***
export DISABLE_SQLALCHEMY_CEXT=1; python setup.py install
New in version 0.9.4,0.8.6: Support for disabling the build of
C extensions using the DISABLE_SQLALCHEMY_CEXT
environment variable
has been added. This allows control of C extension building whether or not
setuptools is available, and additionally works around the fact that
setuptools will possibly be removing support for command-line switches
such as --without-extensions
in a future release.
For versions of SQLAlchemy prior to 0.9.4 or 0.8.6, the
--without-cextensions
option may be used to disable the attempt to build
C extensions, provided setupools is in use, and provided the Feature
construct is supported by the installed version of setuptools:
python setup.py --without-cextensions install
Or with pip:
pip install --global-option='--without-cextensions' SQLAlchemy
SQLAlchemy runs directly on Python 2 or Python 3, and can be installed in either environment without any adjustments or code conversion.
Changed in version 0.9.0: Python 3 is now supported in place with no 2to3 step required.
SQLAlchemy is designed to operate with a DBAPI implementation built for a particular database, and includes support for the most popular databases. The individual database sections in Dialects enumerate the available DBAPIs for each database, including external links.
This documentation covers SQLAlchemy version 1.0. If you’re working on a system that already has SQLAlchemy installed, check the version from your Python prompt like this:
>>> import sqlalchemy
>>> sqlalchemy.__version__
1.0.0
Notes on what’s changed from 0.9 to 1.0 is available here at What’s New in SQLAlchemy 1.0?.