Python ORM – Object-Relational Mapping - Learn PYTHON-BACKEND | Revochamp

Name: Python ORM – Object-Relational Mapping
Availability: InStock
Author: Revochamp

What is an ORM?

Object-Relational Mapping (ORM) is a technique that lets you query and manipulate data from a database using an object-oriented paradigm. Instead of writing raw SQL strings, you define your database tables as Python classes. For a Technical Lead, using an ORM means faster development, cleaner code, and built-in protection against SQL injection.

The Concept: Class to Table

An ORM maps a Class to a database Table, an Instance of that class to a Row, and Attributes to Columns.

SQLAlchemy (The Toolkit)

SQLAlchemy is the most flexible and widely used ORM in the Python ecosystem. It provides two main components: the Core (SQL expression language) and the ORM (High-level mapping).

PythonRead-only

from sqlalchemy import Column, Integer, String, create_engine
from sqlalchemy.orm import declarative_base, sessionmaker

Base = declarative_base()

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

# Database setup
engine = create_engine('sqlite:///:memory:')
Base.metadata.create_all(engine)

# Interaction
Session = sessionmaker(bind=engine)
session = Session()
new_user = User(name="Kishore")
session.add(new_user)
session.commit()

from sqlalchemy import Column, Integer, String, create_engine
from sqlalchemy.orm import declarative_base, sessionmaker

Base = declarative_base()

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

# Database setup
engine = create_engine('sqlite:///:memory:')
Base.metadata.create_all(engine)

# Interaction
Session = sessionmaker(bind=engine)
session = Session()
new_user = User(name="Kishore")
session.add(new_user)
session.commit()

Django ORM (The Integrated Choice)

If you are using the Django framework, the ORM is built-in and tightly integrated with the rest of the ecosystem. It is famous for its simple syntax and powerful migration system.

PythonRead-only

# Django Model Example
class Project(models.Model):
    title = models.CharField(max_length=100)

# Querying
projs = Project.objects.filter(title__contains='Flutter')

# Django Model Example
class Project(models.Model):
    title = models.CharField(max_length=100)

# Querying
projs = Project.objects.filter(title__contains='Flutter')

Comparison of Python ORMs

ORM	Philosophy	Best For
SQLAlchemy	Explicit & Flexible	Enterprise, Complex Flask/FastAPI apps
Django ORM	Opinionated & Fast	Full-stack Django applications
Peewee	Small & Simple	Micro-services, small CLI tools
Tortoise ORM	Async-first	High-performance AsyncIO apps

Why Use an ORM?

Maintainability: Code is written in Python, making it easier to read and debug for developers.
Database Agnostic: Switch from SQLite (local) to PostgreSQL (production) with minimal code changes.
Security: ORMs automatically use parameterized queries, preventing SQL Injection.
Migrations: Most ORMs provide tools to track and apply database schema changes over time.

Test Your Knowledge

of 3

What does 'Mapping' refer to in ORM?

GPS coordinates of the server

The relationship between Python Classes and Database Tables

A list of all functions in a module

The process of connecting to a VPN

of 3

Which Python ORM is known for being 'async-first' and inspired by Django?

SQLAlchemy

Peewee

Tortoise ORM

SQLite3

of 3

What is the benefit of a database-agnostic ORM?

It makes the database faster

It allows the app to work with different database engines (e.g., MySQL or Postgres) with little to no code change

It eliminates the need for a database administrator

It encrypts all data automatically

Frequently Asked Questions

Is an ORM slower than raw SQL?

Yes, there is a small performance overhead because the ORM has to translate Python objects into SQL. However, for 95% of applications, this is negligible compared to the development speed gained.

What is the 'N+1 Problem'?

A common ORM pitfall where the app makes one query to fetch parent records and then N separate queries to fetch children. This can be solved using 'Eager Loading' or 'Selected Related' techniques.

Can I still write raw SQL with an ORM?

Absolutely. All major Python ORMs provide an 'escape hatch' to execute raw SQL for highly complex queries that are difficult to express in Python syntax.

from sqlalchemy import Column, Integer, String, create_engine from sqlalchemy.orm import declarative_base, sessionmaker Base = declarative_base() class User(Base): __tablename__ = 'users' id = Column(Integer, primary_key=True) name = Column(String) # Database setup engine = create_engine('sqlite:///:memory:') Base.metadata.create_all(engine) # Interaction Session = sessionmaker(bind=engine) session = Session() new_user = User(name="Kishore") session.add(new_user) session.commit()

ORM

Philosophy

Best For

SQLAlchemy

Explicit & Flexible

Enterprise, Complex Flask/FastAPI apps

Django ORM

Opinionated & Fast

Full-stack Django applications

Peewee

Small & Simple

Micro-services, small CLI tools

Tortoise ORM

Async-first

High-performance AsyncIO apps

Test Your Knowledge

of 3

What does 'Mapping' refer to in ORM?

GPS coordinates of the server

The relationship between Python Classes and Database Tables

A list of all functions in a module

The process of connecting to a VPN

of 3

Which Python ORM is known for being 'async-first' and inspired by Django?

SQLAlchemy

Peewee

Tortoise ORM

SQLite3

of 3

What is the benefit of a database-agnostic ORM?

It makes the database faster

It allows the app to work with different database engines (e.g., MySQL or Postgres) with little to no code change

It eliminates the need for a database administrator

It encrypts all data automatically

Frequently Asked Questions

Is an ORM slower than raw SQL?

Yes, there is a small performance overhead because the ORM has to translate Python objects into SQL. However, for 95% of applications, this is negligible compared to the development speed gained.

What is the 'N+1 Problem'?

A common ORM pitfall where the app makes one query to fetch parent records and then N separate queries to fetch children. This can be solved using 'Eager Loading' or 'Selected Related' techniques.

Can I still write raw SQL with an ORM?

Absolutely. All major Python ORMs provide an 'escape hatch' to execute raw SQL for highly complex queries that are difficult to express in Python syntax.

Python ORM – Object-Relational Mapping

Python ORM – Object-Relational Mapping

What is an ORM?

The Concept: Class to Table

SQLAlchemy (The Toolkit)

Django ORM (The Integrated Choice)

Comparison of Python ORMs

Why Use an ORM?

Test Your Knowledge

Frequently Asked Questions

Need help?

Python ORM – Object-Relational Mapping

Python ORM – Object-Relational Mapping

What is an ORM?

The Concept: Class to Table

SQLAlchemy (The Toolkit)

Django ORM (The Integrated Choice)

Comparison of Python ORMs

Why Use an ORM?

Test Your Knowledge

Frequently Asked Questions

Need help?