{"repo":"jjaju/statlift","free":true,"listed":false,"github":"https://github.com/jjaju/statlift","clone":"git clone https://github.com/jjaju/statlift.git","description":"Free Analytics for Strong Data.","language":"Python","stars":19,"topics":["analytics","fitness","fitness-tracker","gym","python","sports","sports-analytics","streamlit","strong","strong-app"],"license":"MIT","category":"analytics","readme_excerpt":"statlift Free Analytics for Strong Data. :rocket: :mechanical arm: About: StatLift is a web app that enables users of the Strong App to keep track of their training progress. StatLift was built with Streamlit and is hosted on the Streamlit Community Cloud. Find it here: https://statlift.streamlit.app/ I'm neither a Streamlit expert nor physically able to produce the most impressive dataset for stress testing StatLift, so feel free to leave feedback or suggestions for improvement by opening a new issue. :bulb: How to use: 1. Export your workout data from the Strong App: Profile - Settings - Export Strong Data 2. Visit https://statlift.streamlit.app/ 3. Upload your exported csv file and celebrate your training progress :computer: Alternatively run StatLift locally: 1. Clone this repository: git clone https://github.com/jjaju/statlift.git 2. Navigate to cloned folder: cd statlift 3. Start statlift using streamlit: - Option A: uv uv run --frozen streamlit run statlift.py - Option B: pip pip install -r requirements.txt streamlit run statlift.py","default_branch":null,"files":null,"tree":[],"storefront":"/r/jjaju","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/jjaju/statlift/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}