Atoma VS pydantic

Compare Atoma vs pydantic and see what are their differences.

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Atoma pydantic
0 166
103 18,226
- 4.2%
0.0 9.8
over 1 year ago about 19 hours ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Atoma

Posts with mentions or reviews of Atoma. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Atoma yet.
Tracking mentions began in Dec 2020.

pydantic

Posts with mentions or reviews of pydantic. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-15.

What are some alternatives?

When comparing Atoma and pydantic you can also consider the following projects:

Cerberus - Lightweight, extensible data validation library for Python

nexe - 🎉 create a single executable out of your node.js apps

msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML

SQLAlchemy - The Database Toolkit for Python

sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.

mypy - Optional static typing for Python

pyparsing - Python library for creating PEG parsers [Moved to: https://github.com/pyparsing/pyparsing]

phonenumbers - Python port of Google's libphonenumber

dacite - Simple creation of data classes from dictionaries.

Lark - Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.

beanie - Asynchronous Python ODM for MongoDB

beartype - Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.