{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering"}],"enrichment":{"capability":"Pandera provides a flexible API for validating dataframe-like objects using declarative schemas with type checking and custom validation rules.","skillfed_tags":["data-validation","schema-enforcement","quality-assurance"],"use_cases":["Validate incoming data before processing in a pipeline to catch upstream errors early","Define and enforce data contracts between pipeline stages with executable schema definitions","Test data quality in unit tests by asserting that fixtures conform to expected schemas","Document expected column types and constraints as executable code in data transformation functions","Catch type mismatches and constraint violations across multiple dataframe libraries with one API"],"what_it_does":"Pandera is a data validation framework that lets you define schemas for dataframe-like objects and validate them at runtime. It supports multiple dataframe libraries and offers two ways to define schemas: an object-based API using DataFrameSchema and a class-based API using DataFrameModel with type annotations. You specify column types, constraints (like minimum/maximum values), and custom validation functions, then call validate() to check whether your data conforms.\n\nThe package is designed for data scientists, engineers, and analysts who want to make data pipelines more readable and catch data quality issues early. It integrates with pydantic for type validation and uses typeguard for runtime type checking. The framework has been in active development since 2018 and is maintained as an open-source project, with support for modern Python versions (3.10 through 3.14).","worth_installing":"Yes. Pandera is actively maintained, has no known vulnerabilities, installs with low friction, and offers a mature, permissive MIT license. It solves a real problem\u2014catching data quality issues early in pipelines\u2014and supports multiple dataframe libraries. The only prerequisite is Python 3.10 or later."},"id":"pandera","links":{"html":"https://skillfed.io/packages/pandera","md":"https://skillfed.io/packages/pandera.md","pypi":"https://pypi.org/project/pandera/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-29","license_spdx":null,"license_treatment":"permissive","name":"pandera","python_support":"supports_current","summary":"A light-weight and flexible data validation and testing tool for statistical data objects."},"popularity":{"monthly_downloads":9225733,"position":1553,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.32.1"}