Asynchronous ORM through the eyes of a Python developer

First impressions

Recently I was faced with the task of choosing an ORM for a new Python project, and my attention was drawn to TortoiseORM. Frankly, I was surprised at how much this ORM simplifies working with databases in asynchronous applications.

As a developer, I'm used to tools like SQLAlchemy and Peewee. However, integrating async into these ORMs often requires additional configuration and can be quite confusing. TortoiseORM was initially designed with asynchrony in mind, which immediately makes life easier.

Familiar syntax

One of the biggest advantages is the syntax, which is reminiscent of Django ORM. If you've worked with Django, you'll have no problem getting started with TortoiseORM. The definition of models looks intuitive:

from tortoise.models import Model
from tortoise import fields

class User(Model):
    id = fields.IntField(pk=True)
    username = fields.CharField(max_length=50)
    email = fields.CharField(max_length=100)

Executing queries is also not difficult:

user = await User.filter(username="test_user").first()

Why TortoiseORM is impressive

Native async

Support async/await built in by default. This means you can efficiently handle a large number of simultaneous requests without any additional configuration.

Simplicity and convenience

Unlike some other ORMs, there is no need to dive into complex documentation or learn new concepts. Everything is simple and clear at first glance.

Performance

In my tests, TortoiseORM showed high performance when working with large amounts of data. Asynchronous operations are performed quickly and without delay, which is critical for highly loaded applications.

Comparison with other ORMs

• Peewee: An excellent ORM for synchronous applications, but the lack of native asynchrony can be a hindrance in modern projects.

• SQLAlchemy: A powerful tool with a lot of features, but the complexity of setting up asynchrony and the cumbersome syntax can be daunting.

• PonyORM: Convenient declarative syntax, but in some cases inferior to TortoiseORM in performance and ease of use.

Pros of TortoiseORM

• Asynchrony out of the box: No need for additional libraries or complex settings.

• Familiar syntax: Fast learning due to similarity to Django ORM.

• High performance: Optimized for working with a large number of simultaneous requests.

• Wide database support: Works with PostgreSQL, MySQL, SQLite and others.

• Active development: The community actively supports and develops the project.

Conclusion

This is my first article, and although I don't have much experience in writing, I wanted to share my findings with others. Having discovered TortoiseORMI was pleasantly surprised by its capabilities and convenience. For Python developers looking for an efficient and easy-to-use asynchronous ORM, this solution could be a godsend. I recommend trying TortoiseORM in your projects – perhaps it will surprise you as much as it did me.