| SQLAlchemy | |
| Author: | Michael Bayer[1] |
| Released: | [2] |
| Programming Language: | Python |
| Operating System: | Cross-platform |
| Genre: | Object-relational mapping |
| License: | MIT License[3] |
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.
SQLAlchemy offers tools for database schema generation, querying, and object-relational mapping. Key features include:
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:
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:
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"
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"
engine = create_engine("dbms://user:pwd@host/dbname")Base.metadata.create_all(engine)
One can insert a director-movie relationship via either entity:
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.commitexcept: session.rollback
SQLAlchemy issues the following query to the DBMS (omitting aliases):
The output:
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 directors.id, directors.nameFROM directorsWHERE directors.id = %s