datacompose 0.2.5.2

Copy-pasteable data transformation primitives for PySpark. Inspired by shadcn-svelte.

Datacompose

A powerful data transformation framework for building reusable, composable data cleaning pipelines in PySpark.

Installation

pip install datacompose

What is Datacompose?

Datacompose provides production-ready PySpark data transformation primitives that become part of YOUR codebase. Inspired by shadcn's approach to components, we believe in giving you full ownership and control over your code.

Key Features

• No Runtime Dependencies: Standalone PySpark code that runs without Datacompose
• Composable Primitives: Build complex transformations from simple, reusable functions
• Smart Partial Application: Pre-configure transformations with parameters for reuse
• Optimized Operations: Efficient Spark transformations with minimal overhead
• Comprehensive Libraries: Pre-built primitives for emails, addresses, and phone numbers

Available Transformers

• Emails: Validation, extraction, standardization, typo correction
• Addresses: Street parsing, state/zip validation, PO Box detection
• Phone Numbers: NANP/international validation, formatting, toll-free detection

Documentation

For detailed documentation, examples, and API reference, visit datacompose.io.

Philosophy

This is NOT a traditional library - it gives you production-ready data transformation primitives that you can modify to fit your exact needs. You own the code, with no external dependencies to manage or worry about breaking changes.

License

MIT License - see LICENSE file for details