PyFastUtil is a high-performance utility library for Python, inspired by the popular FastUtil library in Java. However, PyFastUtil is not a Python binding of any existing library, but a complete re-implementation from scratch, designed to bring the same efficiency and functionality to Python.

Note: PyFastUtil is still in its early development phase. The codebase is under active development and is not yet ready for production use. We are working hard to make it feature-complete and thoroughly tested before releasing it on PyPI.

• Implements all corresponding Python data structure interfaces, while providing significant performance improvements through targeted optimizations. Users can choose the most suitable data structure for their specific needs.
• Fully implemented in C/C++, leveraging hardware-specific optimizations such as SIMD to maximize the performance of data structures.
• Offers efficient Python bindings for certain C APIs, allowing advanced users to perform low-level, "unsafe" operations when needed.

Note: For some very fast O(1) operations (such as pop and extend), PyFastUtil may perform slightly worse than Python's native implementation due to the non-negligible overhead of CPython's C extension calls. We are working on optimizing this.

CPU: AMD Ryzen 7 5700G (AVX2)

Windows 11 23H2, Python 3.12, MSVC 19.41.34120

---Python list & IntArrayList Benchmark---
Batch size: 10000
Repeat: 3

Python list sort time: 1.31 ms
PyFastUtil IntArrayList sort time: 0.03 ms
PyFastUtil speed of Python list (sort): 4139.240 %

Python list append time: 0.44 ms
PyFastUtil IntArrayList append time: 0.43 ms
PyFastUtil speed of Python list (append): 102.314 %

Python list insert time: 71.75 ms
PyFastUtil IntArrayList insert time: 10.68 ms
PyFastUtil speed of Python list (insert): 671.948 %

Python list pop time: 0.34 ms
PyFastUtil IntArrayList pop time: 0.40 ms
PyFastUtil speed of Python list (pop): 85.341 %

Python list remove time: 5.13 ms
PyFastUtil IntArrayList remove time: 2.55 ms
PyFastUtil speed of Python list (remove): 201.138 %

Python list contains time: 536.74 ms
PyFastUtil IntArrayList contains time: 15.29 ms
PyFastUtil speed of Python list (contains): 3511.205 %

Python list index time: 414.75 ms
PyFastUtil IntArrayList index time: 3.85 ms
PyFastUtil speed of Python list (index): 10764.189 %

Python list extend time: 0.09 ms
PyFastUtil IntArrayList extend time: 0.20 ms
PyFastUtil speed of Python list (extend): 44.228 %


Avg speed of PyFastUtil compared to Python list: 2439.950 %

---Python list & ObjectArrayList Benchmark---
Batch size: 10000
Repeat: 3

Python list sort time: 125.56 ms
PyFastUtil ObjectArrayList sort time: 116.61 ms
PyFastUtil speed of Python list (sort): 107.668 %

Python list append time: 0.30 ms
PyFastUtil ObjectArrayList append time: 0.35 ms
PyFastUtil speed of Python list (append): 86.724 %

Python list insert time: 81.55 ms
PyFastUtil ObjectArrayList insert time: 23.95 ms
PyFastUtil speed of Python list (insert): 340.471 %

Python list pop time: 0.44 ms
PyFastUtil ObjectArrayList pop time: 0.32 ms
PyFastUtil speed of Python list (pop): 139.226 %

Python list remove time: 5.25 ms
PyFastUtil ObjectArrayList remove time: 5.14 ms
PyFastUtil speed of Python list (remove): 102.170 %

Python list contains time: 1140.28 ms
PyFastUtil ObjectArrayList contains time: 16.37 ms
PyFastUtil speed of Python list (contains): 6966.576 %

Python list index time: 866.88 ms
PyFastUtil ObjectArrayList index time: 6.77 ms
PyFastUtil speed of Python list (index): 12803.132 %

Python list extend time: 0.12 ms
PyFastUtil ObjectArrayList extend time: 0.15 ms
PyFastUtil speed of Python list (extend): 80.975 %


Avg speed of PyFastUtil compared to Python list: 2578.368 %

Currently, PyFastUtil is not officially available on PyPI. However, you can install it from Test PyPI or build it from the source code.

You can install the latest pre-release version of PyFastUtil from Test PyPI:

pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple pyfastutil

Note: Test PyPI is a separate package repository used for testing purposes. Packages hosted there may not be as stable as those on the official PyPI.

If you'd prefer to build the project from the source code, follow these steps:

1. Clone the repository:

   git clone https://github.com/yourusername/PyFastUtil.git
   cd PyFastUtil

2. Build the project:

   • On Windows:

     build.cmd

   • On Linux/macOS:

     ./build.sh

Note: Future releases will be available on the official PyPI repository once the project is feature-complete and well-tested.

This project is licensed under the Apache License 2.0. See the LICENSE file for more details.

• Implement core data structures (e.g., fast lists, maps, sets).
• Numpy support.
• Provide SIMD and inline assembly bindings for Python.
• Thorough testing and benchmarking.
• PyPI release.

Contributions are welcome! Feel free to submit issues or pull requests. Please note that the project is in an early stage, and we appreciate any feedback or suggestions.

This project includes code from the following amazing open-source projects:

• CPython: The official Python interpreter, licensed under the Python Software Foundation License.
• cpp-TimSort: A C++ implementation of the TimSort algorithm, licensed under the MIT License.
• ankerl::unordered_dense: A fast and memory-efficient hash map implementation for modern C++, licensed under the MIT License.
• C++ Standard Library (STL): The C++ Standard Library, which provides essential data structures, algorithms, and utilities, licensed under the ISO C++ Standard.

Special thanks to the contributors of these open-source projects!

The "mascot" image is provided by the artist kokola and is used with permission. You can find the original image on X.