leetcode-compensation

<p align="center"> <img src="./assets/leetcomp_banner.png"> _{https://kuutsav.github.io/leetcode-compensation} </p> <p align="center"> <a href="https://github.com/kuutsav/leetcode-compensation/actions/workflows/data-refresh.yaml"><img src="https://github.com/kuutsav/leetcode-compensation/actions/workflows/data-refresh.yaml/badge.svg" alt="automatic-data-update"/ ></a> <a href="https://github.com/kuutsav/leetcode-compensation/actions/workflows/pages/pages-build-deployment"><img src="https://github.com/kuutsav/leetcode-compensation/actions/workflows/pages/pages-build-deployment/badge.svg" alt="pages-build-deployment" /></a> <a href="http://mypy-lang.org/"><img src="http://www.mypy-lang.org/static/mypy_badge.svg" alt="Checked with mypy" /></a> </p>

LeetCode Compensation is a tool that helps you find Software Engineer Salary in India by:

• Fetching compensation data from Leetcode forums.
• Updating Bi-weekly through GitHub action PRs.
• Using LLMs for parsing and sanitizing structured data from posts, followed by aggregation.

[!WARNING] A 2-day data refresh delay allows the votes to accumulate, after that posts with negative votes are dropped.

Getting Started

Install uv from Standalone Installers or from PyPI:

To create a virtual environment:

uv venv  # Create a virtual environment at .venv.

To activate the virtual environment:

# On macOS and Linux.
source .venv/bin/activate

# On Windows.
.venv\Scripts\activate

To install a package into the virtual environment:

uv pip install -r requirements.txt  # Install from a requirements.txt file.

Updating data

[!NOTE] You'll need llm inference setup (config.toml: llms) using local: ollama, vllm, or api: openrouter

$ export PYTHONPATH=.
$ python leetcomp/refresh.py && python leetcomp/parse.py

Roadmap

• Sort by Compensation and Yoe
• Add pagination
• Filters for Yoe, Compensation
• Search for Companies and Locations

Contributions

PRs are welcome but please go through CONTRIBUTING.md before raising a PR.