Investigating Pydantic v2's Bold Performance Claims

1. pytest-benchmark

   1 3 1,350 7.7 Python

   pytest fixture for benchmarking code

   

   To test this, we will setup some benchmarks using pytest-benchmark, some sample data with a simple schema, and compare results between Python's dataclass, Pydantic v1, and v2.

2. InfluxDB

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   InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

   

3. pydantic-core

   2 18 1,618 9.4 Python

   Core validation logic for pydantic written in rust

   

   I encourage you to checkout the official benchmarks for more realistic and detailed examples, and, as always, YMMV.

4. rust

   3 2,845 104,543 10.0 Rust

   Empowering everyone to build reliable and efficient software.

   

   For those unfamiliar, Pydantic is currently implemented in Python and this rewrite shifts most of the code to Rust, a systems programming language touted as "blazingly fast" and safe.

5. powertools-lambda-python

   4 32 3,084 9.9 Python

   A developer toolkit to implement Serverless best practices and increase developer velocity.

   

   It's worth noting that these improvements will also impact other libraries and frameworks that rely on Pydantic, such as FastAPI and AWS Lambda Powertools, which could deliver some transitive performance improvements to various projects that don't directly depend on Pydantic themselves.

6. fastapi

   5 549 86,522 9.8 Python

   FastAPI framework, high performance, easy to learn, fast to code, ready for production

   

   If you work with backend APIs in Python, you've probably used or heard of Pydantic, perhaps from FastAPI. The library advertises itself as "data validation and settings management using Python type annotations" and it makes (de)serialization of data a breeze.1

7. SaaSHub

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