Data Structures Implementation and Performance Analysis

This repository implements various data structures in Python, C++, and Zig, including Trees, Lists, Linked Lists, Union-Find, and Hash Tables. It analyzes the complexity of these data structures and compares their performance across different implementations.

Features

• Implementations of fundamental data structures:

  • Trees (AVL, BST, HEAP)
  • Lists
  • Linked Lists (Single, Double, Tail)
  • Union-Find
  • Hash Tables

• Complexity analysis of each data structure.

• Performance comparisons between different implementations.

• Integration of C++ and Zig code into Python using Pybind11.

• Compilation of code with CMake.

• Analysis conducted using Jupyter Notebooks.

Repository Structure

• Src/: Source code for data structure implementations.
• structures/: Compile code to run in the notebooks.
• Exercise/: Exercises solved using the implemented data structures.
• analisysHash.ipynb: Jupyter Notebook analyzing hash table implementations.
• analisysList.ipynb, analisysList2.ipynb, analisysList3.ipynb: Jupyter Notebooks analyzing the rest of the structures.

Notes

• The project utilizes Pybind11 to integrate C++ and Zig code into Python, allowing for seamless performance comparisons.
• All analyses are conducted within Jupyter Notebooks, providing an interactive environment for exploration.
• The implementations are executed through the CPython interpreter.

License

This project is licensed under the MIT License.