Of course! sqlacodegen is an incredibly useful command-line tool that automatically generates Python model code for SQLAlchemy from an existing database. It saves you a massive amount of time when you need to reverse-engineer a database schema.

Here’s a complete guide covering what it is, why you'd use it, how to install and run it, and how to interpret the output.

What is sqlacodegen?

sqlacodegen is a tool that introspects a database (by connecting to it) and reads its schema (tables, columns, data types, relationships, indexes, etc.). It then generates Python code that defines these tables as SQLAlchemy ORM (Object-Relational Mapping) models.

In short, it turns a database schema into a Python file you can use in your application.

Why Use It?

1. Rapid Prototyping: Get a basic ORM model for an existing database in seconds, allowing you to start building your application immediately.
2. Legacy Database Integration: When you're handed a database with no existing Python code, sqlacodegen provides a solid starting point for your models.
3. Documentation: The generated code serves as a clear, machine-readable representation of your database structure.
4. Learning: It's a great way to see how complex database schemas (like those with foreign keys and many-to-many relationships) are represented in SQLAlchemy.

Step 1: Installation

First, you need to install sqlacodegen. It's available on PyPI.

pip install sqlacodegen

You will also need a database driver for the specific database you're connecting to. For example:

• PostgreSQL: pip install psycopg2-binary
• MySQL: pip install PyMySQL or pip install mysql-connector-python
• SQLite: pip install pysqlite3 (or use the built-in sqlite3)
• SQL Server: pip install pymssql

Step 2: Basic Usage

The command structure is simple:

sqlacodegen <database_uri> > models.py

Let's break this down:

• sqlacodegen: The command you run.
• <database_uri>: The connection string to your database. This is the most important part.
• >: A shell redirect operator. It takes the output from the command and writes it into a file.
• models.py: The name of the output file where the generated code will be saved.

Database URI Examples

The format of the database URI depends on the database you're using.

Step 3: A Complete Example with SQLite

Let's walk through a full example.

Create a Sample SQLite Database

First, let's create a simple database with a couple of tables and some relationships.

# setup_db.py
import sqlite3
# Connect to the database (it will be created if it doesn't exist)
conn = sqlite3.connect('my_database.db')
cursor = conn.cursor()
# Create a 'users' table
cursor.execute('''
CREATE TABLE users (
    id INTEGER PRIMARY KEY,
    username TEXT NOT NULL UNIQUE,
    email TEXT NOT NULL,
    full_name TEXT
)
''')
# Create a 'posts' table
cursor.execute('''
CREATE TABLE posts (
    id INTEGER PRIMARY KEY,TEXT NOT NULL,
    content TEXT,
    user_id INTEGER,
    FOREIGN KEY (user_id) REFERENCES users (id)
)
''')
# Create a 'tags' table
cursor.execute('''
CREATE TABLE tags (
    id INTEGER PRIMARY KEY,
    name TEXT NOT NULL UNIQUE
)
''')
# Create a 'post_tags' junction table for a many-to-many relationship
cursor.execute('''
CREATE TABLE post_tags (
    post_id INTEGER,
    tag_id INTEGER,
    PRIMARY KEY (post_id, tag_id),
    FOREIGN KEY (post_id) REFERENCES posts (id),
    FOREIGN KEY (tag_id) REFERENCES tags (id)
)
''')
# Commit the changes and close the connection
conn.commit()
conn.close()
print("Database 'my_database.db' created successfully.")

Run this script to generate my_database.db.

Run sqlacodegen

Now, run the generator on the database you just created.

sqlacodegen sqlite:///my_database.db > models.py

Inspect the Generated models.py

The tool will create a models.py file. Here is what it will look like, with explanations for each part.

# models.py
from sqlalchemy import Column, ForeignKey, Integer, String, Table
from sqlalchemy.orm import relationship
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
metadata = Base.metadata
# This is the "junction table" for the many-to-many relationship.
# It's automatically detected and created as a Table object.
t_post_tags = Table(
    'post_tags', metadata,
    Column('post_id', Integer, ForeignKey('posts.id')),
    Column('tag_id', Integer, ForeignKey('tags.id'))
)
class User(Base):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    username = Column(String, nullable=False, unique=True)
    email = Column(String, nullable=False)
    full_name = Column(String)
    # This defines the one-to-many relationship: one User can have many Posts.
    # The `back_populates` ensures the relationship is two-way.
    posts = relationship("Post", back_populates="user")
class Post(Base):
    __tablename__ = 'posts'
    id = Column(Integer, primary_key=True)= Column(String, nullable=False)
    content = Column(String)
    user_id = Column(Integer, ForeignKey('users.id'))
    # This is the "many" side of the one-to-many relationship.
    # It links back to the User.
    user = relationship("User", back_populates="posts")
    # This defines the many-to-many relationship: a Post can have many Tags.
    # The `secondary` argument points to our junction table.
    tags = relationship("Tag", secondary=t_post_tags, back_populates="posts")
class Tag(Base):
    __tablename__ = 'tags'
    id = Column(Integer, primary_key=True)
    name = Column(String, nullable=False, unique=True)
    # This is the other side of the many-to-many relationship.
    # It links back to the Post.
    posts = relationship("Post", secondary=t_post_tags, back_populates="tags")

Key Takeaways from the Output:

• Base = declarative_base(): This is the standard base class for your SQLAlchemy ORM models.
• __tablename__ = 'users': Each class corresponds to a database table.
• Column(...): Each attribute in the class is a column, with its type (Integer, String) and constraints (primary_key=True, nullable=False, unique=True).
• ForeignKey(...): This correctly identifies foreign key relationships.
• relationship(...): This is the magic of SQLAlchemy ORM. It defines how tables relate to each other.
  • One-to-Many (User -> Post): The User has a posts relationship, and the Post has a user relationship. back_populates links them together.
  • Many-to-Many (Post <-> Tag): The tool correctly identifies the junction table (post_tags) and uses the secondary argument in the relationship() to define the link. Both Post and Tag have a relationship back to each other.

Advanced Options and Flags

sqlacodegen offers several useful flags to customize the output.

You can see all options by running sqlacodegen --help.

Here are some of the most common ones:

Example: Generating for Specific Tables

If your database is huge and you only need a few tables, this is a huge time-saver.

# Only generate the User and Post models
sqlacodegen --tables users,posts sqlite:///my_database.db > user_post_models.py

This will produce a much smaller file containing only the User and Post classes and their relationship.