Python PonyORM ORM In a Nutshell

Why Use PonyORM?

• Super easy queries – Querying with PonyORM looks like native Python code.
• Entity definitions are clean – No need for crazy configurations.
• Automatic relationship handling – Foreign keys? Pony’s got you.
• Visualization tools – You can see your database schema in a visual format.
• Supports multiple databases – SQLite, MySQL, PostgreSQL, and more!
• Pythonic syntax – No raw SQL needed (unless you want to get fancy).

Installation

Before we do anything, let’s install PonyORM:

1

pip install pony

That’s it! No complex setup, no headaches.

Defining Your Models

PonyORM uses a class-based approach to define database models. Here’s an example:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16

from pony.orm import Database, Required, Set

db = Database()

class User(db.Entity):
    username = Required(str, unique=True)
    age = Required(int)
    posts = Set("Post")

class Post(db.Entity):
    title = Required(str)
    content = Required(str)
    author = Required(User)

db.bind(provider='sqlite', filename=':memory:', create_db=True)
db.generate_mapping(create_tables=True)

In just a few lines, we have a User and Post model, complete with a one-to-many relationship.

Adding Data

Now, let’s add some users and posts:

1
2
3
4
5
6
7
8

from pony.orm import db_session

with db_session():
    user1 = User(username="john_doe", age=25)
    user2 = User(username="jane_doe", age=28)
    
    Post(title="Hello World", content="This is my first post!", author=user1)
    Post(title="Another Post", content="PonyORM is awesome!", author=user2)

Boom! We just added two users and two posts.

Querying Data (The Fun Part)

This is where PonyORM really shines. Querying is super Pythonic:

1
2
3
4

with db_session():
    young_users = User.select(lambda u: u.age < 30)
    for user in young_users:
        print(user.username)

See that? No .filter(), no .all(). Just pure Python magic.

Need something fancier?

1
2
3

with db_session():
    post_count = count(p for p in Post if p.author.age < 30)
    print(f"Users under 30 have written {post_count} posts.")

Yeah, that’s right—Python generators in ORM queries.

Updating and Deleting Data

Updating is easy:

1
2
3

with db_session():
    user = User.get(username="john_doe")
    user.age = 26

Deleting? Also simple:

1
2
3

with db_session():
    user = User.get(username="jane_doe")
    user.delete()

Comparison: PonyORM vs. SQLAlchemy vs. Django ORM

If you just want a fast, easy, and clean ORM, PonyORM is a great choice. If you need something super customizable, SQLAlchemy might be better. If you’re using Django, well… stick with Django’s ORM.

When Should You Use PonyORM?

• If you want an ORM that feels like native Python.
• If you’re working on small to medium projects and want an easy setup.
• If you love clean, readable code.
• If you want an ORM that doesn’t make you cry.

However, if you need raw SQL control or enterprise-level features, SQLAlchemy might be a better fit.

Key Ideas

References

• PonyORM Official Documentation
• PonyORM GitHub Repository
• Python ORMs Comparison