awkward

Awkward Array is a Python library designed for manipulating nested, variable-sized data structures—such as arbitrary-length lists, records, mixed types, and missing data—using familiar NumPy-like idioms. ### Key Features: - **Irregular Data Support**: Enables efficient processing of JSON-like, heterogeneous, and jagged arrays that standard NumPy arrays cannot handle natively. - **NumPy-like API**: Provides an intuitive, declarative syntax for slicing, filtering, and transforming complex nested structures, reducing boilerplate Python code. - **High Performance**: Despite being dynamically typed, operations are compiled and optimized, offering dramatic speedups (often 10x to 100x faster) and reduced memory overhead compared to pure Python loops. It integrates seamlessly with Numba for just-in-time compilation. - **Easy Installation**: Available on PyPI and conda-forge as a pure Python package with optional compiled C++ dependencies (`awkward-cpp`) for maximum platform performance. ### Performance: In benchmarks involving large-scale, nested datasets, Awkward Array completes operations in seconds using a fraction of the memory required by equivalent native Python implementations, making it ideal for high-energy physics, scientific computing, and large-scale machine learning pipelines.