fastpyx 0.5.4

A fast memory optimization extension for Python

FastPyX 🚀

FastPyX is a high-performance C extension for Python, designed to optimize memory usage and significantly improve execution speed.

Why FastPyX?

🔥 Faster than Python's built-in list for fappend operations
📉 Uses up to 56% less memory than Python lists
⚡ Ideal for high-performance applications requiring optimized data structures

Features

• 🚀 Written in C for extreme performance
• 📌 Optimized FastList implementation (efficient fappend method)
• 🔹 Supports multiple data types seamlessly
• 🔧 Efficient memory allocation to reduce fragmentation
• 🔄 Convert to Python list (to_list) for compatibility
• 📊 Fast random access (fget) and optimized length retrieval (len())

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Installation

To install FastPyX:

pip install fastpyx  

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Usage

import fastpyx  

fl = fastpyx.FastList()

# Append values  
for i in range(10):  
    fl.fappend(i)

# Print all elements  
fl.fprint()

# Access an element  
index = 5  
value = fl.fget(index)  
print(f"Index {index}: {value}")

# Convert to Python list  
py_list = fl.to_list()  
print("Converted list:", py_list)

# Get length  
print("Length:", len(fl))

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Benchmark Results

Operation	FastList	Python List	Speedup	Memory Usage (10M items)
fappend	0.56s	0.67s	🔥 17% Faster	30.5MB (FastList) vs. 69MB (Python List)
fget	0.0067s	0.0062s	Slightly slower (needs optimization)	-
to_list	0.8999s	0.124s	Needs improvement	-

✅ FastList is both faster and more memory-efficient than Python's built-in list!

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📜 License

MIT License. Feel free to contribute and improve FastPyX!

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🔗 Future Roadmap

✅ Optimize to_list performance
✅ Add slicing support
✅ Implement iterator support for better compatibility
✅ Advanced memory management optimizations for Django and other frameworks
✅ Additional performance improvements for lists, dictionaries, and sets
✅ More Pythonic API and integration with NumPy/Pandas