SQLAlchemy 0.4 Documentation
- Overview
- Tutorials
- Reference Documentation
- Installing SQLAlchemy
- 0.3 to 0.4 Migration
-
- ORM Package is now sqlalchemy.orm
- BoundMetaData is now MetaData
- "Magic" Global MetaData removed
- Some existing select() methods become generative
- collection_class behavior is changed
- All "engine", "bind_to", "connectable" Keyword Arguments Changed to "bind"
- All "type" Keyword Arguments Changed to "type_"
- Mapper Extensions must return EXT_CONTINUE to continue execution to the next mapper
Overview
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 API components, all public-facing, are illustrated below:
+-----------------------------------------------------------+
| Object Relational Mapper (ORM) |
| [tutorial] [docs] |
+-----------------------------------------------------------+
+---------+ +------------------------------------+ +--------+
| | | SQL Expression Language | | |
| | | [tutorial] [docs] | | |
| | +------------------------------------+ | |
| +-----------------------+ +--------------+ |
| Dialect/Execution | | Schema Management |
| [docs] | | [docs] |
+---------------------------------+ +-----------------------+
+----------------------+ +----------------------------------+
| Connection Pooling | | Types |
| [docs] | | [docs] |
+----------------------+ +----------------------------------+
Above, the two most significant front-facing portions of SQLAlchemy are the Object Relational Mapper and the SQL Expression Language. These are two separate toolkits, one building off the other. SQL Expressions can be used independently of the ORM. When using the ORM, the SQL Expression language is used to establish object-relational configurations as well as in querying.
back to section topTutorials
- Object Relational Tutorial - This describes the richest feature of SQLAlchemy, its object relational mapper. 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.
- SQL Expression Tutorial - The core of SQLAlchemy is its 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. It's a lot more lightweight than the ORM and is appropriate for higher scaling SQL operations. It's also heavily present within the ORM's public facing API, so advanced ORM users will want to master this language as well.
Reference Documentation
- Datamapping - A comprehensive walkthrough of major ORM patterns and techniques.
- Session - A detailed description of SQLAlchemy's Session object
- Engines - Describes SQLAlchemy's database-connection facilities, including connection documentation and working with connections and transactions.
- Connection Pools - Further detail about SQLAlchemy's connection pool library.
-
Metadata - All about schema management using
MetaDataandTableobjects; reading database schemas into your application, creating and dropping tables, constraints, defaults, sequences, indexes. - Types - Datatypes included with SQLAlchemy, their functions, as well as how to create your own types.
- Plugins - Included addons for SQLAlchemy
Installing SQLAlchemy
Installing SQLAlchemy from scratch is most easily achieved with setuptools. (setuptools installation). Just run this from the command-line:
# easy_install SQLAlchemy
This command will download the latest version of SQLAlchemy from the Python Cheese Shop and install it to your system.
Otherwise, you can install from the distribution using the setup.py script:
# python setup.py install
Installing a Database API
SQLAlchemy is designed to operate with a DB-API implementation built for a particular database, and includes support for the most popular databases:
- Postgres: psycopg2
- SQLite: pysqlite, sqlite3 (included with Python 2.5 or greater)
- MySQL: MySQLdb
- Oracle: cx_Oracle
- MS-SQL: pyodbc (recommended), adodbapi or pymssql
- Firebird: kinterbasdb
- Informix: informixdb
Checking the Installed SQLAlchemy Version
This documentation covers SQLAlchemy version 0.4. 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__ 0.4.0
0.3 to 0.4 Migration
From version 0.3 to version 0.4 of SQLAlchemy, some conventions have changed. Most of these conventions are available in the most recent releases of the 0.3 series starting with version 0.3.9, so that you can make a 0.3 application compatible with 0.4 in most cases.
This section will detail only those things that have changed in a backwards-incompatible manner. For a full overview of everything that's new and changed, see WhatsNewIn04.
ORM Package is now sqlalchemy.orm
All symbols related to the SQLAlchemy Object Relational Mapper, i.e. names like mapper(), relation(), backref(), create_session() synonym(), eagerload(), etc. are now only in the sqlalchemy.orm package, and not in sqlalchemy. So if you were previously importing everything on an asterisk:
from sqlalchemy import *
You should now import separately from orm:
from sqlalchemy import * from sqlalchemy.orm import *
Or more commonly, just pull in the names you'll need:
from sqlalchemy import create_engine, MetaData, Table, Column, types from sqlalchemy.orm import mapper, relation, backref, create_session
BoundMetaData is now MetaData
The BoundMetaData name is removed. Now, you just use MetaData. Additionally, the engine parameter/attribute is now called bind, and connect() is deprecated:
# plain metadata meta = MetaData() # metadata bound to an engine meta = MetaData(engine) # bind metadata to an engine later meta.bind = engine
Additionally, DynamicMetaData is now known as ThreadLocalMetaData.
"Magic" Global MetaData removed
There was an old way to specify Table objects using an implicit, global MetaData object. To do this you'd omit the second positional argument, and specify Table('tablename', Column(...)). This no longer exists in 0.4 and the second MetaData positional argument is required, i.e. Table('tablename', meta, Column(...)).
Some existing select() methods become generative
The methods correlate(), order_by(), and group_by() on the select() construct now return a new select object, and do not change the original one. Additionally, the generative methods where(), column(), distinct(), and several others have been added:
s = table.select().order_by(table.c.id).where(table.c.x==7) result = engine.execute(s)
collection_class behavior is changed
If you've been using the collection_class option on mapper(), the requirements for instrumented collections have changed. For an overview, see Alternate Collection Implementations.
All "engine", "bind_to", "connectable" Keyword Arguments Changed to "bind"
This is for create/drop statements, sessions, SQL constructs, metadatas:
myengine = create_engine('sqlite://') meta = MetaData(myengine) meta2 = MetaData() meta2.bind = myengine session = create_session(bind=myengine) statement = select([table], bind=myengine) meta.create_all(bind=myengine)
All "type" Keyword Arguments Changed to "type_"
This mostly applies to SQL constructs where you pass a type in:
s = select([mytable], mytable.c.x=bindparam(y, type_=DateTime)) func.now(type_=DateTime)
Mapper Extensions must return EXT_CONTINUE to continue execution to the next mapper
If you extend the mapper, the methods in your mapper extension must return EXT_CONTINUE to continue executing additional mappers.
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