Documentation
Learn FrameX step-by-step with practical tutorials, architecture notes, and a complete API reference.
Introduction
- Overview
What FrameX is, where it fits, and who it is for.
- Getting Started
Install FrameX and run your first end-to-end dataframe pipeline.
- Installation
Python requirements, optional dependencies, and local development setup.
Guides
- Features
Core FrameX capabilities across DataFrame, NDArray, runtime, and interoperability.
- Use Cases
Practical scenarios where FrameX fits today.
- Configuration Guide
How to tune backend, workers, kernel, array acceleration, and cluster settings.
- Performance Test
How to run, interpret, and compare FrameX benchmark results.
- SQLite Guide
Read and write FrameX DataFrames to SQLite tables using table and query workflows.
Tutorials
- Tutorial: ETL Pipeline
Build a practical Parquet ETL flow with filtering, enrichment, and grouped outputs.
- Tutorial: NumPy NDArray Interop
Use FrameX NDArray with NumPy ufuncs and reductions.
Reference
- Architecture
Storage, execution, memory, and scheduling model.
- API Reference
Public FrameX API surface by module.
- FrameX Benchmarking