dataframely

What problem does it solve?

This guide helps engineers apply dataframely to enforce schema-driven validation in Polars workflows, reducing data quality issues and streamlining typing and testing.

Core Features & Use Cases

• Define schemas with dy.Schema and collections with dy.Collection to model dataframe structures.
• Validate and filter data frames at runtime using dy.Schema.validate and dy.Schema.filter to enforce constraints.
• Leverage type hints and testing conventions to improve readability and reliability in Polars-based pipelines.

Quick Start

Read this guide to implement dataframely schemas and validations in your Polars workflows.