Sqlalchemy Online Tutorials

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.

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):^[5] Initial release.
• Version 1.0 (2015):^[6] Major enhancements in ORM and SQL expression language.
• Version 1.4 (2021):^[7] Introduction of a new ORM API.

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.

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)

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()