API

The command-line interface (installation, usage, generated help, and Python entry points) is documented on the dedicated CLI page.

DataFrames

Core	The core objects for defining pandera schemas
GeoPandas	GeoDataFrameSchema and GeoDataFrameModel entry point
Data Types	Data types for type checking and coercion.
DataFrame Models	Alternative class-based API for defining types for tabular/array-like data.
Decorators	Decorators for integrating pandera schemas with python functions.
Schema Inference	Bootstrap schemas from real data
IO Utilities	Utility functions for reading/writing schemas
Data Synthesis Strategies	Module of functions for generating data from schemas.
Narwhals Backend	Opt-in Narwhals-powered backend unifying the Polars, Ibis, and PySpark SQL validation paths.
Extensions	Utility functions for extending pandera functionality
Errors	Pandera-specific exceptions

Multi-dimensional arrays

Xarray

Schemas for labelled N-dimensional xarray arrays, datasets, and datatrees

Configuration

PanderaConfig	Global configuration (validation enabled, depth, caching)
ValidationDepth	Whether to apply checks at schema-level, data-level, or both
ValidationScope	Indicates whether a check operates at schema or data level
config_context()	Context manager to temporarily override config settings
get_config_context()	Get the current configuration context
get_config_global()	Get the global configuration
set_config()	Set global configuration options (also available as set_config())
reset_config_context()	Reset context configuration to the global default