https://github.com/luizassimoes/fitness-report

Create a personalized Fitness Wrapped report using your Apple Health data with this Streamlit application. Generate comprehensive, detailed summaries of your annual fitness activities, providing valuable insights into your year-long progress and achievements.
https://github.com/luizassimoes/fitness-report

data-analysis data-visualization python streamlit

Last synced: 4 days ago
JSON representation

Create a personalized Fitness Wrapped report using your Apple Health data with this Streamlit application. Generate comprehensive, detailed summaries of your annual fitness activities, providing valuable insights into your year-long progress and achievements.

• Host: GitHub
• URL: https://github.com/luizassimoes/fitness-report
• Owner: luizassimoes
• Created: 2024-12-10T12:16:40.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2025-01-03T14:56:31.000Z (about 2 months ago)
• Last Synced: 2025-01-03T15:40:31.603Z (about 2 months ago)
• Topics: data-analysis, data-visualization, python, streamlit
• Language: Python
• Homepage:
• Size: 444 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Fitness Report for Apple Watch

Get your year stats here! See how much you pushed yourself this year with a detailed report containing time, mileage, calories, and heart rate information!

Go to [fitness-report.streamlit.app](https://fitness-report.streamlit.app/)!

### Motivation:

Every December, I get excited about Spotify Wrapped — it is like a recap of my year, and it makes me relive the fun moments. That gets me thinking: Why don’t other apps do something similar?

As someone who starts and stops their watch religiously for every workout, I wanted to see a Wrapped for my fitness journey, but Apple Health did not have it. Then, in true “shower thoughts” fashion, inspiration struck: “I can build that!”

### Details

All you need to do is extract the health data from your account and submit it to the app, then we do the work! You can see more detailed instructions on the app's page or through [this LinkedIn post](https://www.linkedin.com/posts/luizassimoes_datavisualization-dataanalysis-python-activity-7282161729596252162-S5ah?utm_source=share&utm_medium=member_desktop).

### Contact info

If you have any questions or if your submission did not work, please send me an [e-mail](mailto:[email protected]).

### How to use it locally

1. Clone this repository with ```git clone https://github.com/luizassimoes/fitness-report.git```

2. Create an environment and install the code's dependencies by running ```pip install -r requirements.txt```

3. Run your app with ```streamlit run app.py```

And there you go! Hope you have as much fun as I did :)