How-To Guides

Goal-oriented guides for specific tasks. Each one solves a particular problem and assumes you already know the basics from the Getting Started tutorial.

Choosing your API

• How to Choose an API Style – Pick between the ArrowModel base class, ArrowModelConverter, and convenience functions.

Conversion features

• How to Use Validated Mode – Enable full Pydantic validation during conversion and understand the performance trade-off.

• How to Work with Aliases – Map Arrow column names to Pydantic field names using aliases, validation_alias, and populate_by_name.

• How to Convert Nested Models – Convert Arrow Struct columns into nested Pydantic models, including optional and deeply nested types.

• How to Iterate over Large Datasets – Process large Tables lazily without materialising every model instance in memory.

Integrations

• How to Integrate with FastAPI – Serve Arrow query results as typed JSON responses through FastAPI endpoints.

• How to Use with Poldantic – Fit arrowmodel into a poldantic workflow with Polars DataFrames.

• How to Use with Pandera – Convert pandera-validated Arrow data into Pydantic model instances.