0Pricing
FastAPI Backend Development Bootcamp · Leçon

Fondamentaux de l’ORM SQLAlchemy

Commencez à utiliser le mappeur objet-relationnel (ORM) de SQLAlchemy pour définir des modèles de base de données et interagir avec votre base de données.

Fondamentaux de l’ORM SQLAlchemy est une leçon FastAPI Backend Development Bootcamp gratuite sur CoddyKit. Ceci est la leçon 1 sur 4. Tu peux lire la leçon complète ci-dessous gratuitement — puis la pratiquer en direct dans le navigateur avec un éditeur de code intégré et un tuteur IA 24/7. Elle fait partie du parcours d'apprentissage FastAPI Backend Development Bootcamp, et ta progression se synchronise sur le web et l'application CoddyKit. Le cours FastAPI Backend Development Bootcamp comprend 4 leçons au total.

Certaines parties de cette leçon n'ont pas encore été traduites et s'affichent en anglais.

Bridging Code and Databases

Welcome to SQLAlchemy ORM! You'll learn how to connect your Python code to a database in a powerful, object-oriented way.

An Object Relational Mapper (ORM) is a tool that helps you interact with a database using objects from your programming language, instead of writing raw SQL.

  • It maps database tables to Python classes.
  • It maps database rows to Python objects.
  • It maps database columns to Python attributes.

This makes database operations feel more like working with regular Python objects.

Meet SQLAlchemy: Your ORM Tool

SQLAlchemy is a comprehensive and powerful ORM for Python. It provides a full suite of well-known persistence patterns for efficient and high-performing database access.

We'll focus on its ORM capabilities, which allow you to define your database structure (schema) using Python classes and interact with data using instances of those classes.

It supports many databases, including SQLite, PostgreSQL, MySQL, and more!

The Foundation: Declarative Base

To start defining our database models, we need a special base class. SQLAlchemy's Declarative Base provides this foundation.

It's essentially a factory that generates a base class which your ORM models will inherit from. This base class connects your Python classes to the underlying database tables.

Here's how you get it:

from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

Defining Your First Model

Once you have your Base, you can define your database tables as Python classes. Each class will represent a table, and its attributes will represent the columns.

Let's create a simple User model. It will have an id and a name.

from sqlalchemy import Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class User(Base):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    name = Column(String(50))

Model Attributes: Columns

In our User model, id and name are defined using Column objects. The Column function lets you specify details about each database column:

  • Data Type: Integer for whole numbers, String for text. SQLAlchemy has many more!
  • Primary Key: primary_key=True marks a column as the unique identifier for each row.
  • Length: String(50) sets a maximum length for text fields.
  • Nullable: By default, columns are nullable. You can set nullable=False to require a value.

The __tablename__ attribute is crucial; it tells SQLAlchemy the actual name of the table in your database.

Setting Up the Database Engine

Before we can create tables or interact with the database, SQLAlchemy needs to know where it is! This is where the Engine comes in.

An Engine is the starting point for any SQLAlchemy application. It connects your application to a specific database using a connection string.

For simplicity, we'll use an in-memory SQLite database, which is great for testing as it disappears when the program ends:

from sqlalchemy import create_engine

# Connect to an in-memory SQLite database
engine = create_engine('sqlite:///:memory:')

# For a file-based SQLite database:
# engine = create_engine('sqlite:///./test.db')

Creating Database Tables

With our Base, defined models, and engine, we can now create the actual database tables!

The Base.metadata.create_all(engine) method inspects all classes that inherit from Base and creates the corresponding tables in the database connected by the engine.

If the tables already exist, SQLAlchemy won't try to recreate them, preventing errors.

Full Example: Define & Create

Let's put it all together! Run this code to see how to define a model and create its table in an in-memory SQLite database.

Notice how we import everything needed, define Base, create our User model, set up the engine, and finally, create the tables.

from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base

# 1. Define the Base for ORM models
Base = declarative_base()

# 2. Define a Model (e.g., User table)
class User(Base):
    __tablename__ = 'users' # The actual table name in the database
    id = Column(Integer, primary_key=True) # Unique ID, automatically managed
    name = Column(String(50), nullable=False) # User's name, max 50 chars, required

    # A helpful representation for printing User objects
    def __repr__(self):
        return f"<User(id={self.id}, name='{self.name}')>"

# 3. Create a database engine
# Using an in-memory SQLite database for simplicity
engine = create_engine('sqlite:///:memory:')

# 4. Create all tables defined in Base
Base.metadata.create_all(engine)

print("Database tables created successfully!")
print("The 'users' table is now ready for data.")

Your Database Interaction Hub: The Session

Defining models and creating tables are just the first steps. To actually interact with the data (add, query, update, delete), you need a Session.

A Session is like a temporary workspace for your database operations. It holds all the objects you've loaded or created and keeps track of changes.

You create a Session using sessionmaker and bind it to your engine:

from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine

# (Assume 'engine' is already created as shown before)
engine = create_engine('sqlite:///:memory:')

# Create a Session factory
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# To get a session:
# db = SessionLocal()
# try:
#     # Perform operations with db
#     pass
# finally:
#     db.close()

Quick Check: Model Setup

You've learned how to set up the basics of SQLAlchemy ORM. Let's test your understanding of the core components.

Recap: SQLAlchemy ORM Basics

Great job! You've taken your first steps into the world of SQLAlchemy ORM.

Here's what we covered:

  • What is an ORM: Maps Python objects to database tables.
  • SQLAlchemy: A powerful Python ORM.
  • Declarative Base: The foundation (Base = declarative_base()) for your models.
  • Defining Models: Creating Python classes (like User) that inherit from Base.
  • Columns: Using Column with data types (Integer, String) and attributes (primary_key).
  • Engine: Connecting to your database (create_engine).
  • Table Creation: Bringing models to life in the database (Base.metadata.create_all(engine)).
  • Session: Your workspace for database interactions (sessionmaker).

Next, we'll learn how to add, query, update, and delete data using these concepts!

Questions Fréquemment Posées

La leçon « Fondamentaux de l’ORM SQLAlchemy » est-elle gratuite ?

Oui — le texte complet de « Fondamentaux de l’ORM SQLAlchemy » est gratuit à lire ici sur le web. Pour la pratiquer de manière interactive (un éditeur de code intégré et un tuteur IA 24/7) et déverrouiller le reste du cours FastAPI Backend Development Bootcamp, passe à CoddyKit PRO. Le cours FastAPI Backend Development Bootcamp comprend 4 leçons au total.

Qu'est-ce que j'apprendrai dans « Fondamentaux de l’ORM SQLAlchemy » ?

Commencez à utiliser le mappeur objet-relationnel (ORM) de SQLAlchemy pour définir des modèles de base de données et interagir avec votre base de données. Tu pratiques FastAPI Backend Development Bootcamp avec du code pratique que tu exécutes directement dans le navigateur, et un tuteur IA 24/7 répond à tes questions au fur et à mesure que tu avances dans la leçon.

Dois-je avoir de l'expérience pour commencer FastAPI Backend Development Bootcamp ?

Aucune expérience préalable n'est requise. FastAPI Backend Development Bootcamp sur CoddyKit est structuré pour les débutants jusqu'aux apprenants avancés, donc tu peux commencer ici ou depuis le début et avancer à ton rythme. Ceci est la leçon 1 sur 4.

Combien de temps prend la leçon « Fondamentaux de l’ORM SQLAlchemy » ?

La plupart des leçons CoddyKit prennent environ 5–10 minutes. Chacune est courte et interactive, tu progresses régulièrement et tu repiques exactement où tu t'es arrêté sur le web et l'app.

Peux-tu écrire et exécuter du code dans cette leçon FastAPI Backend Development Bootcamp ?

Oui. Chaque leçon FastAPI Backend Development Bootcamp inclut un éditeur de code intégré, tu écris et exécutes du vrai code directement dans ton navigateur et tu reçois des retours IA instantanés — aucune configuration locale requise.

Toutes les leçons de ce cours

  1. Fondamentaux de l’ORM SQLAlchemy
  2. Connecter FastAPI à PostgreSQL
  3. Opérations CRUD avec SQLAlchemy
  4. Migrations de base de données avec Alembic
← Retour à FastAPI Backend Development Bootcamp