Pythonic Structures

A repository dedicated to exploring and implementing efficient, "Pythonic" data structures and algorithms, with a focus on performance benchmarking and modern development practices.

🚀 Getting Started

This project uses uv for dependency management and Task for automation.

Prerequisites

• uv (Extremely fast Python package installer and resolver)
• Task (A task runner / simpler alternative to Make)

Installation

1. Clone the repository:

   git clone https://github.com/NavneetSinghArora/pythonic-structures.git
   cd pythonic-structures

2. Setup the environment:

   uv sync

3. Install pre-commit hooks:

   uv run pre-commit install

🛠 Usage

We use Taskfile to manage common development tasks. You can run task --list to see all available commands.

Development Tasks

Command	Description
task tests	Run all tests (including benchmarks)
task tests-only	Run unit tests only
task benchmarks	Run performance benchmarks
task format	Format and fix linting issues with Ruff
task lint	Check for linting issues

Manual Execution

If you prefer using uv directly:

• Run tests: uv run pytest
• Format code: uv run ruff format .

📂 Project Structure

• sorting/: Implementations of various sorting algorithms.
• utils/: Utility functions and decorators (e.g., performance timers).
• tests/: Unit tests for ensuring correctness.
• benchmarks/: Performance tests and result tracking.

📊 Benchmark Results

System Information

• CPU: Apple M4
• Architecture: arm64
• Python: 3.14.2
• OS: Darwin 25.2.0

Sorting Algorithms

Algorithm	Mean	Min	Max	Std Dev	Ops/s	Rounds
Native Sort	260.90 ns	228.05 ns	3.66 µs	32.68 ns	3.83M ops/s	195,123
Bubble Sort	15.89 µs	15.04 µs	682.25 µs	7.17 µs	62.93K ops/s	9,026
Insertion Sort	52.67 µs	49.33 µs	503.79 µs	6.88 µs	18.99K ops/s	13,023