Misplaced Pages

SQLAlchemy

Article snapshot taken from Wikipedia with creative commons attribution-sharealike license. Give it a read and then ask your questions in the chat. We can research this topic together.
SQL toolkit and object-relational mapper
Abbreviated SQLAlchemy Logo
Original author(s)Michael Bayer
Initial releaseFebruary 14, 2006; 18 years ago (2006-02-14)
Stable release2.0.36 Edit this on Wikidata / 15 October 2024; 2 months ago (15 October 2024)
Repository
Written inPython
Operating systemCross-platform
TypeObject-relational mapping
LicenseMIT License
Websitewww.sqlalchemy.org Edit this on Wikidata
Mike Bayer talking about SQLAlchemy at PyCon 2012

SQLAlchemy is an open-source Python library that provides an SQL toolkit (called "SQLAlchemy Core") and an Object Relational Mapper (ORM) for database interactions. It allows developers to work with databases using Python objects, enabling efficient and flexible database access.

Description

SQLAlchemy offers tools for database schema generation, querying, and object-relational mapping. Key features include:

  • A comprehensive embedded domain-specific language for SQL in Python called "SQLAlchemy Core" that provides means to construct and execute SQL queries.
  • A powerful ORM that allows the mapping of Python classes to database tables.
  • Support for database schema migrations.
  • Compatibility with multiple database backends.
  • Tools for database connection pooling and transaction management.

History

SQLAlchemy was first released in February 2006. It has evolved to include a wide range of features for database interaction and has gained popularity among Python developers. Notable versions include:

  • Version 0.1 (2006): Initial release.
  • Version 1.0 (2015): Major enhancements in ORM and SQL expression language.
  • Version 1.4 (2021): Introduction of a new ORM API.

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 corresponding 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 f"Movie({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 f"Director({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 = 
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 corresponding 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

References

  1. Mike Bayer is the creator of SQLAlchemy and Mako Templates for Python.
  2. "Download - SQLAlchemy". SQLAlchemy. Retrieved 21 February 2015.
  3. "Release 2.0.36". 15 October 2024. Retrieved 27 October 2024.
  4. "zzzeek / sqlalchemy / source / LICENSE". BitBucket. Retrieved 21 February 2015.
  5. "0.1 Changelog — SQLAlchemy 2.0 Documentation". docs.sqlalchemy.org. Retrieved 2024-07-04.
  6. "1.0 Changelog — SQLAlchemy 2.0 Documentation". docs.sqlalchemy.org. Retrieved 2024-07-04.
  7. "1.4 Changelog — SQLAlchemy 2.0 Documentation". docs.sqlalchemy.org. Retrieved 2024-07-04.
Notes
Categories: