Best Python ORM 2023

Alice 99 Published: 12/14/2024

Best Python ORM 2023

I'd be happy to help!

Python is a popular programming language known for its simplicity and ease of use. When it comes to database interactions, you need a powerful ORM (Object-Relational Mapping) tool that can simplify the process. Here are some top ORMs in Python, each with their unique strengths:

SQLAlchemy: This is one of the most widely used and respected ORMs in Python. It supports many databases, including SQLite, MySQL, PostgreSQL, Oracle, Microsoft SQL Server, etc. SQLAlchemy provides a flexible way to interact with your database using Python's syntax.

Pros:

Supports multiple databases Highly customizable Excellent documentation

Cons:

Steep learning curve for beginners Can be overkill if you only need simple database interactions Django ORM: If you're building web applications in Django, you'll likely use the built-in ORM. This powerful tool provides an easy-to-use interface to interact with your database.

Pros:

Specifically designed for Django Easy to learn and integrate Includes automatic transaction handling and connection pooling

Cons:

Limited support for non-Django projects May be less flexible than SQLAlchemy due to being tied to the Django framework Pandas: This library is primarily used for data analysis, but it also includes an ORM that can interact with databases.

Pros:

Excellent for data manipulation and analysis Supports multiple database types (e.g., MySQL, PostgreSQL, SQLite) Easy to use for simple tasks

Cons:

Primarily designed for data manipulation, not heavy-duty ORMs Not as flexible as SQLAlchemy or Django's ORM Tortoise: This is a Python ORM that supports databases like SQLite, MySQL, and PostgreSQL.

Pros:

Lightweight and easy to learn Supports basic CRUD (Create, Read, Update, Delete) operations Can work with multiple databases simultaneously

Cons:

Limited support for more complex database interactions Not as well-known or widely used as other ORMs Peewee: This is a lightweight ORM that supports SQLite and MySQL.

Pros:

Easy to learn and use Supports basic CRUD operations Fast and efficient

Cons:

Limited support for more complex database interactions Not as customizable as SQLAlchemy

In conclusion, the best Python ORM depends on your specific needs and preferences. If you're building a Django web application, the Django ORM is likely a good choice. For general-purpose use, SQLAlchemy is an excellent option.

As for 2023, I can say that these ORMs are all still widely used and respected in the Python community. However, there may be other options available as well, such as Pydantic, which combines database operations with data validation.

I hope this helps you make an informed decision!

Best python orm reddit

The eternal debate!

When it comes to choosing the best Python ORM (Object-Relational Mapping) on Reddit, there are a few contenders that stand out from the pack. Now, I'm not here to claim that one is definitively better than the others, but rather to provide an overview of the most popular ones.

1. SQLAlchemy

The granddaddy of them all, SQLAlchemy has been around since 2006 and is widely considered a best-of-breed ORM. It's a comprehensive toolset for working with databases in Python, supporting a wide range of databases (e.g., MySQL, PostgreSQL, Oracle) and offering features like unit-of-work, session management, and connection pooling.

Redditors rave about its ease of use, flexibility, and robustness. If you're new to ORMs or looking for a reliable solution with extensive support, SQLAlchemy is an excellent choice.

2. Django ORM (ORM part of Django)

As part of the popular Django web framework, the Django ORM is specifically designed for use within Django projects. While it might not be as flexible as SQLAlchemy, it's an integral part of the Django ecosystem and provides seamless integration with the rest of the framework.

Fans of Django love its simplicity, ease of use, and tight coupling to the rest of the framework, making it an ideal choice for large-scale web applications where Django is already being used.

3. PonyORM

PonyORM is a relatively new player on the scene (released in 2016), but it's gained significant traction among developers due to its simplicity, speed, and ease of use. It supports multiple databases (e.g., MySQL, PostgreSQL, SQLite) and offers features like connection pooling and automatic schema creation.

Reddit enthusiasts praise PonyORM for its lightweight nature, flexibility, and ease of integration with other Python libraries and frameworks.

4. Tenjin

Tenjin is another popular ORM in the Python world, known for its simplicity, speed, and ease of use. It's particularly well-suited for small to medium-sized projects where a lightweight solution is desired.

Tenjin enthusiasts appreciate its minimalistic approach, flexibility, and support for various databases (e.g., MySQL, PostgreSQL, SQLite).

5. TypeORM

TypeORM is a relatively new ORM in the Python landscape (released in 2020), but it's quickly gained popularity due to its unique type-safe approach, which ensures strong typing and helps prevent errors at compile-time.

Redditors love TypeORM for its innovative design, speed, and ease of use, making it an excellent choice for large-scale projects where type safety is crucial.

In conclusion, when it comes to choosing the best Python ORM on Reddit, each has its strengths and weaknesses. If you're looking for a comprehensive, flexible solution with extensive support, SQLAlchemy might be your top choice. For those already invested in the Django ecosystem, the Django ORM could be the way to go. For smaller projects or those seeking a lightweight solution, PonyORM, Tenjin, or TypeORM might be more suitable.

Remember, ultimately, the best ORM for you will depend on your specific needs and preferences. Take some time to explore each option, read up on their respective strengths and weaknesses, and choose the one that best fits your project's requirements.