boompython

BoomPython is an open-source software project that provides a high-performance computing toolkit for Python. It aims to deliver near-native execution speeds for numeric and data-intensive workloads while preserving the usability of Python. The project bundles a JIT-compiled execution engine, a collection of optimized kernels, and Python bindings that resemble familiar libraries such as NumPy and pandas, enabling developers to migrate performance-critical code with minimal changes.

Key features include a just-in-time compiler that translates hot Python code paths into optimized machine code, vectorized operations over arrays, automatic parallel execution on multi-core CPUs, and optional offload to accelerators through backends such as CUDA or OpenCL. The API is designed to be familiar to data scientists, with data structures analogous to arrays and data frames, alongside explicit APIs for kernel authors to write custom accelerated routines.

BoomPython is built with a modular architecture: a core runtime in C++ provides execution and memory management; a JIT layer targets multiple architectures; and Python bindings connect the runtime to Python code. The project emphasizes interoperability, allowing existing Python ecosystems to interoperate with BoomPython arrays and kernels without rewriting large portions of code.

Development is community-driven, with publicly visible repositories, issue trackers, and contribution guidelines. BoomPython is released under a permissive open-source license and follows standard community practices for documentation, testing, and continuous integration.