An educational tool that visualizes six classic sorting algorithms with step‑by‑step animation and real‑time metrics.
- Six algorithms: Bubble Sort, Insertion Sort, Merge Sort, Quick Sort, Heap Sort, Counting Sort.
- Step‑by‑step animation with highlighted comparisons and swaps.
- Real‑time HUD: comparisons, swaps, auxiliary memory used, and elapsed time (pauses excluded).
- Two operating modes:
- Interactive: guided console prompts to choose algorithm, array, and speed.
- Batch: command‑line arguments (e.g.
--algorithm bubble --size 50 --interval 50).
- Playback controls: pause/resume (
Space) and frame‑by‑frame step (→). - Export:
- Save animation as GIF or MP4.
- Save trace states as CSV or JSON (all frames or key frames only).
- Algorithm comparison (upcoming) – side‑by‑side synchronized animation.
- User settings persistence between interactive sessions.
- Cross‑platform: Windows, macOS, Linux.
- Clone the repository:
git clone https://github.com/yourusername/sorting-visualizer.git cd sorting-visualizer - Create and activate a virtual environment:
python -m venv venv source venv/bin/activate # Linux/macOS venv\Scripts\activate # Windows
- Install dependencies:
pip install -e ".[dev]" - Launch interactive mode:
python -m src.ui.console_ui --interactive or(!) python -m src.ui.console_ui --algorithm bubble --size 20 --interval 100 - Export an animation:
python -m src.ui.console_ui --algorithm quick --size 30 --export-gif quick_sort.gif
by 1) Algorithm name; 2) Average complexity; 3) Extra memory; 4) Notes.
Bubble Sort; O(n²); O(1); Simple comparison‑based.
Insertion Sort; O(n²;) O(1); Efficient on partially sorted data.
Merge Sort; O(n log n); O(n); Iterative bottom‑up implementation.
Quick Sort; O(n log n); O(log n)*; 3‑way partition, median‑of‑three pivot.
Heap Sort; O(n log n); O(1); In‑place heap construction.
Counting Sort; O(n + k); O(n + k); Non‑negative integers only.
Python 3.10+, matplotlib (animation and drawing), numpy, Pillow (GIF export), pytest (testing), black, ruff, mypy (code style and type checking)
This project is designed to help students and developers understand sorting algorithms through direct visualisation. Every swap, comparison, and memory allocation is visible in real time. The source code itself serves as an example of generator‑based algorithm design, type annotations, and SOLID architecture.
This project is licensed under the MIT License. See LICENSE for details.