#Cython

CyToolz is a Cython implementation that accelerates utility functions for iterables, functions, and dictionaries based on the toolz package. Seamless integration with libraries such as itertools and functools allows for improved processing speeds, crucial for handling large datasets. It provides a C API and utilizes iterator protocols to maintain efficiency with low memory consumption. Compatible with Python 3.8+, CyToolz remains lightweight with minimal dependencies. Contributions are encouraged, promoting a collaborative environment for those interested in functional programming.

Explore Python's utility library, Toolz, which enhances iterators, functions, and dictionaries with modules like itertoolz, functoolz, and dicttoolz. It supports Python 3.8+ and requires no external dependencies. For better performance, consider using CyToolz, its Cython-based counterpart. Engage with the supportive community or discover similar libraries such as Underscore.js for JavaScript or Enumerable for Ruby.

cymem offers a reliable solution for Cython developers, automating memory management by linking memory allocations to Python object lifecycles. Its key feature, cymem.Pool, autonomously frees memory, minimizing errors in intricate data structures. Installation requires Cython and can be completed using pip. This project simplifies manual memory deallocation, preventing typical memory leaks found in C extensions, and is particularly beneficial for handling complex nested structs or when custom memory allocators are needed.