avatarFarhan Tanvir

Summary

The article introduces seven top Python ORM libraries that enhance Python development by simplifying database interactions.

Abstract

The article "7 Best Python ORM Libraries You Should Know" provides an overview of Python's Object-Relational Mapping (ORM) libraries, which are essential tools for developers working with databases. It emphasizes the importance of ORMs in bridging the gap between object-oriented programming and relational databases. The libraries featured include Peewee, known for its simplicity and support for multiple databases; SQLAlchemy, a robust and enterprise-level tool; Tortoise, an async ORM for non-blocking database operations; Pypika, a query builder for crafting complex SQL queries; Databases, which offers async support for various databases; Ormar, a modern async ORM tailored for FastAPI and Pydantic; and Pony, which allows writing queries in pure Python using generator expressions. The article highlights the unique features and GitHub popularity of each library, aiming to guide developers in selecting the right tool for their projects.

Opinions

  • The author suggests that the choice of ORM library can significantly impact the quality and performance of a Python project.
  • Peewee is praised for its simplicity and rich feature set, making it a versatile choice for developers.
  • SQLAlchemy is highlighted as a pillar in the Python community, known for its comprehensive database access capabilities.
  • Tortoise ORM is seen as a valuable tool for projects that require asynchronous database interactions.
  • Pypika is recognized as a helpful library for developers who need to construct complex SQL queries in a Pythonic way.
  • The Databases library is recommended for its modern async and await support, providing both performance and simplicity.
  • Ormar is noted as an excellent choice for FastAPI enthusiasts, emphasizing its strong correlation between models and database structure through type hints.
  • Pony ORM is considered unique for its ability to translate Python generator expressions into SQL queries, offering an intuitive interface for database modeling and querying.
  • The author encourages readers to explore these libraries further and invites them to share other favorite Python libraries in the comments, fostering a sense of community and ongoing learning.

7 Best Python ORM Libraries You Should Know

Power up your Python development

Photo by Árpád Czapp on Unsplash

The world is one big data problem — Andrew McAfee

Navigating the intricate dance between objects in programming and the relational tables of databases is like translating poetry from one language to another. The essence needs to remain, even as the form changes. In this dance, Object-Relational Mapping (ORM) libraries are the master choreographers, ensuring that every step and every transition is flawless.

We all know the power of Python: it’s the jack of all trades in the coding world, powering everything from data science projects to web applications and automation scripts. But just as a master craftsman knows the value of his tools, the best Python developers appreciate top-notch libraries that can turn a good project into a masterpiece.

Ready to upgrade your Python game? Take a look at these 7 awesome libraries that can be a game changer for your projects. Prepare to be inspired!

1. Peewee

If simplicity with an expressive query syntax is what you seek, this is your go-to ORM. This small, yet powerful library, provides a simple and intuitive way to define data models and query databases. It supports MySQL, PostgreSQL, and SQLite, making it a versatile choice. Its simplistic approach doesn’t compromise on features, offering a rich set of functionalities, including database migrations and a robust querying system. It has more than 10k stars on GitHub.

2. Sqlalchemy

When it comes to robust database access, this library stands as a pillar in the Python community. This library provides a full suite of well-known enterprise-level persistence patterns and is designed for efficient and high-performing database access. Its expressive SQL construct allows you to work with databases seamlessly, ensuring your data models adhere to your requirements while benefiting from the full spectrum of database capabilities. It has more than 7.5k stars on GitHub.

3. Tortoise

For the async enthusiasts, this library is a breath of fresh air. It’s a modern asynchronous ORM inspired by Django ORM that brings the joy of non-blocking IO to your database interactions. It shines in projects where async operations are a must, providing a solid foundation for handling database tasks asynchronously without breaking a sweat. It has more than 3.5k stars on GitHub.

4. Pypika

When the goal is crafting intricate SQL queries, this library offers a helping hand. While not a traditional ORM, it’s a Pythonic SQL query builder that allows you to construct SQL queries in a clean and Pythonic way. It’s a library for those who need to work closely with SQL, providing a neat abstraction that simplifies complex query generation. It has more than 2k stars on GitHub.

5. Databases

When you need async and await support for a variety of databases, this library is a solid choice. It provides async interaction with databases in SQLAlchemy core style. Its support for multiple databases and its async nature make it a modern and versatile choice for developers seeking performance and simplicity in database interactions. It has more than 3.5k stars on GitHub.

6. Ormar

FastAPI enthusiasts will find a friend in this library. This modern, async mini ORM is designed to work with FastAPI and Pydantic. By leveraging type hints, it ensures a strong correlation between your models and the database structure. Its asynchronous nature makes it a great fit for modern web applications, where performance and responsiveness are key. It has more than 1.5k stars on GitHub.

7. Pony

When you wish to express database queries in pure Python, this library steps into the limelight. Its unique ability to write queries using Python generators is a game-changer. Pony ORM translates generator expressions into SQL queries, providing a seamless bridge between Python and databases. The intuitive interface, coupled with its entity-relationship diagram editor, makes database modeling and querying an enjoyable task. It has more than 3k stars on GitHub.

Where are some other awesome resources?

There are always new things to learn. If you want to learn more about awesome resources please check out the below link.

That’s all for today. I believe these libraries will help you a lot in your development journey.

If you know of any other beautiful Python libraries, please share them in the comments. Until we meet again…Cheers!

Want to Connect? If you want to, you can connect with me on Twitter.

In Plain English

Thank you for being a part of our community! Before you go:

Python
Python Programming
Software Engineering
Software Development
Programming
Recommended from ReadMedium
avatarBryson Meiling
What is Pydantic and how can it help your next python project?

For anyone that has been either living under a programming rock you may not have heard of Pydantic…

5 min read
avatarLeandro 🤖 👾 🚀
Building State-Aware Applications with Finite State Machines and FastAPI

Building Dynamic Workflows with Ease

4 min read
avatarAungkon Malakar
Better ORM then Sqlalchemy Python ? Tortoise ORM 101

What is Tortoise ORM?

2 min read
avatarHarendra
11 Open-Source SaaS Killer — Selfhost With Docker

Selfhost Supabase, Grafana, Uptime Kuma, NocoDB, Dokku, Appwrite, N8N, Redash, Jitsi, Plausible and Nextcloud with docker

6 min read
avatarChris Karvouniaris
Python’s SQLAlchemy: 3 powerful features you need to know

Python SQLAlchemy basics and 3 powerful features

11 min read
avatarCoding Pit
Building a Dynamic Table App with FastHTML and HTMX

A Step-by-Step Guide to Creating a CRUD Web Application in a Single View.

7 min read