157 lines
5.7 KiB
Text
157 lines
5.7 KiB
Text
Metadata-Version: 2.0
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Name: SQLAlchemy
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Version: 1.0.11
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Summary: Database Abstraction Library
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Home-page: http://www.sqlalchemy.org
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Author: Mike Bayer
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Author-email: mike_mp@zzzcomputing.com
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License: MIT License
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Platform: UNKNOWN
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Classifier: Development Status :: 5 - Production/Stable
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Classifier: Intended Audience :: Developers
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Classifier: License :: OSI Approved :: MIT License
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Classifier: Programming Language :: Python
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: Implementation :: CPython
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Classifier: Programming Language :: Python :: Implementation :: Jython
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Classifier: Programming Language :: Python :: Implementation :: PyPy
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Classifier: Topic :: Database :: Front-Ends
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Classifier: Operating System :: OS Independent
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SQLAlchemy
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==========
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The Python SQL Toolkit and Object Relational Mapper
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Introduction
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-------------
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SQLAlchemy is the Python SQL toolkit and Object Relational Mapper
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that gives application developers the full power and
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flexibility of SQL. SQLAlchemy provides a full suite
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of well known enterprise-level persistence patterns,
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designed for efficient and high-performing database
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access, adapted into a simple and Pythonic domain
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language.
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Major SQLAlchemy features include:
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* An industrial strength ORM, built
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from the core on the identity map, unit of work,
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and data mapper patterns. These patterns
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allow transparent persistence of objects
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using a declarative configuration system.
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Domain models
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can be constructed and manipulated naturally,
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and changes are synchronized with the
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current transaction automatically.
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* A relationally-oriented query system, exposing
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the full range of SQL's capabilities
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explicitly, including joins, subqueries,
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correlation, and most everything else,
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in terms of the object model.
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Writing queries with the ORM uses the same
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techniques of relational composition you use
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when writing SQL. While you can drop into
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literal SQL at any time, it's virtually never
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needed.
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* A comprehensive and flexible system
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of eager loading for related collections and objects.
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Collections are cached within a session,
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and can be loaded on individual access, all
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at once using joins, or by query per collection
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across the full result set.
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* A Core SQL construction system and DBAPI
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interaction layer. The SQLAlchemy Core is
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separate from the ORM and is a full database
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abstraction layer in its own right, and includes
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an extensible Python-based SQL expression
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language, schema metadata, connection pooling,
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type coercion, and custom types.
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* All primary and foreign key constraints are
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assumed to be composite and natural. Surrogate
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integer primary keys are of course still the
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norm, but SQLAlchemy never assumes or hardcodes
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to this model.
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* Database introspection and generation. Database
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schemas can be "reflected" in one step into
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Python structures representing database metadata;
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those same structures can then generate
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CREATE statements right back out - all within
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the Core, independent of the ORM.
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SQLAlchemy's philosophy:
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* SQL databases behave less and less like object
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collections the more size and performance start to
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matter; object collections behave less and less like
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tables and rows the more abstraction starts to matter.
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SQLAlchemy aims to accommodate both of these
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principles.
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* An ORM doesn't need to hide the "R". A relational
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database provides rich, set-based functionality
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that should be fully exposed. SQLAlchemy's
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ORM provides an open-ended set of patterns
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that allow a developer to construct a custom
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mediation layer between a domain model and
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a relational schema, turning the so-called
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"object relational impedance" issue into
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a distant memory.
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* The developer, in all cases, makes all decisions
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regarding the design, structure, and naming conventions
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of both the object model as well as the relational
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schema. SQLAlchemy only provides the means
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to automate the execution of these decisions.
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* With SQLAlchemy, there's no such thing as
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"the ORM generated a bad query" - you
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retain full control over the structure of
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queries, including how joins are organized,
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how subqueries and correlation is used, what
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columns are requested. Everything SQLAlchemy
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does is ultimately the result of a developer-
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initiated decision.
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* Don't use an ORM if the problem doesn't need one.
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SQLAlchemy consists of a Core and separate ORM
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component. The Core offers a full SQL expression
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language that allows Pythonic construction
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of SQL constructs that render directly to SQL
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strings for a target database, returning
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result sets that are essentially enhanced DBAPI
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cursors.
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* Transactions should be the norm. With SQLAlchemy's
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ORM, nothing goes to permanent storage until
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commit() is called. SQLAlchemy encourages applications
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to create a consistent means of delineating
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the start and end of a series of operations.
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* Never render a literal value in a SQL statement.
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Bound parameters are used to the greatest degree
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possible, allowing query optimizers to cache
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query plans effectively and making SQL injection
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attacks a non-issue.
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Documentation
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-------------
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Latest documentation is at:
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http://www.sqlalchemy.org/docs/
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Installation / Requirements
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---------------------------
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Full documentation for installation is at
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`Installation <http://www.sqlalchemy.org/docs/intro.html#installation>`_.
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Getting Help / Development / Bug reporting
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------------------------------------------
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Please refer to the `SQLAlchemy Community Guide <http://www.sqlalchemy.org/support.html>`_.
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License
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-------
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SQLAlchemy is distributed under the `MIT license
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<http://www.opensource.org/licenses/mit-license.php>`_.
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