© 2025-2026 PySpect
Loading...
| Package | Comment | Downloads/day | Recent releases ⓘ | GitHub Stars |
|---|---|---|---|---|
| pydantic | The most widely used data validation library, using Python type hints to define and validate data models. | 19.9M | 26 | · |
| marshmallow | A library for object serialization, deserialization, and validation via declarative schemas. | 3.4M | 11 | · |
| msgspec | High-performance serialization and validation library using Python type annotations, with JSON and MessagePack support. | 758K | 3 | · |
| cattrs | Structuring and unstructuring of attrs and dataclass objects, with composable validation hooks. | 1.8M | 4 | · |
| jsonschema | Reference implementation of the JSON Schema specification for validating JSON documents. | 10.8M | 4 | · |
| cerberus | Lightweight and extensible schema validation for Python dictionaries. | 191K | 1 | · |
| voluptuous | Schema validation library focused on validating data coming into Python from external sources. | 171K | 1 | · |
| pandera | Statistical data validation for pandas, Polars, and other DataFrame libraries, with type annotations support. | 273K | 15 | · |
| great-expectations | Data quality framework for defining, documenting, and validating expectations on large datasets in pipelines. | 823K | 44 | · |
| typeguard | Runtime type checking for Python functions and variables, enforcing type annotations at execution time. | 1.6M | 5 | · |
| beartype | Fast runtime type checker using O(1) constant-time type checks with no overhead at scale. | 1.1M | 10 | · |