SQLAlchemy
Original author(s) | Michael Bayer[1] |
---|---|
Initial release | February 14, 2006[2] |
Stable release | 1.0.11 / 23 December 2015 |
Development status | Active |
Written in | Python |
Operating system | Cross-platform |
Type | Object-relational mapping |
License | MIT License[3] |
Website |
www |
SQLAlchemy is an open source SQL toolkit and object-relational mapper (ORM) for the Python programming language released under the MIT License.[3]
SQLAlchemy provides "a full suite of well known enterprise-level persistence patterns, designed for efficient and high-performing database access, adapted into a simple and Pythonic domain language". SQLAlchemy's philosophy is that SQL databases behave less and less like object collections the more size and performance start to matter, while object collections behave less and less like tables and rows the more abstraction starts to matter. For this reason it has adopted the data mapper pattern (like Hibernate for Java) rather than the active record pattern used by a number of other object-relational mappers.[4] However, optional plugins allow users to develop using declarative syntax.[5]
SQLAlchemy was first released in February 2006[6][2] and has quickly become one of the most widely used object-relational mapping tools in the Python community, alongside Django's ORM.
Example
The following example represents an n-to-1 relationship between movies and their directors. It is shown how user-defined Python classes create corresponding database tables, how instances with relationships are created from either side of the relationship, and finally how the data can be queried—illustrating automatically-generated SQL queries for both lazy and eager loading.
Schema definition
Creating two Python classes and according database tables in the DBMS:
from sqlalchemy import *
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import relation, sessionmaker
Base = declarative_base()
class Movie(Base):
__tablename__ = 'movies'
id = Column(Integer, primary_key=True)
title = Column(String(255), nullable=False)
year = Column(Integer)
directed_by = Column(Integer, ForeignKey('directors.id'))
director = relation("Director", backref='movies', lazy=False)
def __init__(self, title=None, year=None):
self.title = title
self.year = year
def __repr__(self):
return "Movie(%r, %r, %r)" % (self.title, self.year, self.director)
class Director(Base):
__tablename__ = 'directors'
id = Column(Integer, primary_key=True)
name = Column(String(50), nullable=False, unique=True)
def __init__(self, name=None):
self.name = name
def __repr__(self):
return "Director(%r)" % (self.name)
engine = create_engine('dbms://user:pwd@host/dbname')
Base.metadata.create_all(engine)
Data insertion
One can insert a director-movie relationship via either entity:
Session = sessionmaker(bind=engine)
session = Session()
m1 = Movie("Robocop", 1987)
m1.director = Director("Paul Verhoeven")
d2 = Director("George Lucas")
d2.movies = [Movie("Star Wars", 1977), Movie("THX 1138", 1971)]
try:
session.add(m1)
session.add(d2)
session.commit()
except:
session.rollback()
Querying
alldata = session.query(Movie).all()
for somedata in alldata:
print somedata
SQLAlchemy issues the following query to the DBMS (omitting aliases):
SELECT movies.id, movies.title, movies.year, movies.directed_by, directors.id, directors.name
FROM movies LEFT OUTER JOIN directors ON directors.id = movies.directed_by
The output:
Movie('Robocop', 1987L, Director('Paul Verhoeven'))
Movie('Star Wars', 1977L, Director('George Lucas'))
Movie('THX 1138', 1971L, Director('George Lucas'))
Setting lazy=True
(default) instead, SQLAlchemy would first issue a query to get the list of movies and only when needed (lazy) for each director a query to get the name of the according director:
SELECT movies.id, movies.title, movies.year, movies.directed_by
FROM movies
SELECT directors.id, directors.name
FROM directors
WHERE directors.id = %s
See also
- SQLObject
- Storm
- Peewee ORM
- Pylons
- TurboGears
- Mako (template engine) (by same author)
- Cubes (OLAP server)
References
- ↑ Mike Bayer is the creator of SQLAlchemy and Mako Templates for Python.
- 1 2 "Download - SQLAlchemy". SQLAlchemy. Retrieved 21 February 2015.
- 1 2 "zzzeek / sqlalchemy / source / LICENSE". BitBucket. Retrieved 21 February 2015.
- ↑ in The architecture of open source applications
- ↑ declarative
- ↑ http://decisionstats.com/2015/12/29/interview-mike-bayer-sqlalchemy-pydata-python/
- Notes
- Gift, Noah (12 Aug 2008). "Using SQLAlchemy". Developerworks. IBM. Retrieved 8 Feb 2011.
- Rick Copeland, Essential SQLAlchemy, O'Reilly, 2008, ISBN 0-596-51614-2