DSA implementation in multiple programming languages
This repository contains implementations of various algorithms in three different programming languages: Rust, Python, and TypeScript. The goal of this project is to provide clear and concise implementations of fundamental algorithms, allowing developers to study and compare the differences in syntax, performance, and language-specific features across these three languages.
Algorithms are essential building blocks of computer science and software engineering. They provide efficient solutions to various computational problems and are used extensively in fields like data structures, machine learning, cryptography, and more. By implementing algorithms in multiple languages, this repository aims to:
- Help developers understand the core concepts of algorithms in different programming paradigms.
- Provide practical examples of algorithm implementations in popular languages like Rust, Python, and TypeScript.
- Facilitate learning and comparison between languages, enabling developers to choose the most suitable language for their specific use cases.
The repository contains implementations of a wide range of algorithms, including but not limited to:
- Sorting algorithms (e.g., bubble sort, quicksort, merge sort)
- Searching algorithms (e.g., binary search, depth-first search, breadth-first search)
- Graph algorithms (e.g., Dijkstra's algorithm, Prim's algorithm, Kruskal's algorithm)
- Dynamic programming algorithms (e.g., Fibonacci sequence, longest common subsequence)
The implementations are organized into separate directories for each language, allowing developers to explore and compare implementations across different languages easily.
- Rust: Contains implementations of algorithms written in Rust programming language.
- Python: Contains implementations of algorithms written in Python programming language.
- TypeScript: Contains implementations of algorithms written in TypeScript programming language.
Each directory follows a similar structure, with separate files for each algorithm implementation, along with accompanying documentation and test cases.
Developers can clone this repository and explore the implementations in their preferred language. Each algorithm is documented with comments to explain the logic and approach used. Additionally, test cases are provided to validate the correctness of each implementation.
To use the algorithms:
- Clone the repository to your local machine.
- Navigate to the directory of the desired language (e.g.,
rust,python,typescript). - Explore the individual algorithm implementations.
- Run test cases to verify the correctness of the implementations.
Contributions to this repository are welcome! If you have additional algorithms to add or improvements to existing implementations, feel free to submit a pull request. Please follow the guidelines provided in the repository for contributing code.