# 🏃‍♂️ Jogging Dashboard

Interactive Python Dash app to visualize, analyze, and explore your jogging or running sessions recorded as GPX/FIT files.

<p align="left">
    <img src="DashboardApp_WebVersion.png" alt="Description" width="800">
</p>

SVG-Export:
<p align="left">
    <img src="2025-09-15_HH_Run_10.90Km_overlay.png" alt="Description" width="600">
</p>
This SVG can then be overlaid on another image (Strava‑inspired).

---

## Features

- **Select file** choose a data file to analyse your run
- **export SVG** creates a transparent SVG image of your Course and the Info Banner statistics (Strava‑inspired)
- **Info Banner** with total distance, duration, and average pace
- **Interactive Map View** with route trace and start/stop markers
- **Elevation Profile** with relative height and gradient fill
- **Speed Over Time** plot with smoothing and average line
- **Heart Rate Over Time** plot with smoothing and average line (if .fit file)
- **Deviation from Mean Speed** to see pacing consistency
- **Pace Bar Chart** showing per-kilometer pace breakdown

---

## Project Structure

```
jogging_dashboard_browser_app.py    # Main Dash application (Web-Version)
jogging_dashboard_gui_app.py        # Main Dash application (loading Web-Version in a Gui)
gpx_files/                          # Folder for storing GPX files
fit_files/                          # Folder for storing FIT files
requirements.txt                    # Required Python packages
README.md                           # Project description file
```

---

## Getting Started

### 1. Clone the repository

```bash
git clone https://github.com/yourusername/jogging-dashboard.git
cd jogging-dashboard
```

### 2. Install dependencies

It is recommend using a virtual environment:

```bash
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
```

**Content of the requirements.txt file**:

[Dash & Web Components]
- dash
- dash-bootstrap-components
- plotly
- pandas
- numpy
- scipy
- gpxpy
- fitparse

[GUI Version (PyQt6)]
- PyQt6
- PyQt6-WebEngine

[Additional Dependencies (usually automatically installed)]
- requests


### 3. Run the app

```bash
python jogging_dashboard_browser_app.py
```

Then open your browser and go to:
[http://127.0.0.1:8051](http://127.0.0.1:8051)

Or as Gui-Version

```bash
python jogging_dashboard_gui_app.py
```

---

## Uploading Your GPX File

1. Export your activity (e.g., from Strava, Garmin, etc.) as a `.gpx` or `.fit` file
2. Place the file into the `gpx_files/` or `fit_files/` directory
3. Select it via the dropdown in the dashboard

---

## Tech Stack

- **Dash** (by Plotly) for building the UI and graphs
- **Pandas** for data wrangling
- **Plotly Graph Objects & Express** for advanced visuals
- **Scipy** for smoothing the data lines
- **GPXPy** for parsing `.gpx` files
- **Numpy** for vectorized math and smoothing
- **FitParse** for  parsing `.fit` files

---

## Example GPX File

You can test the dashboard by either placing any valid `.gpx` file in the `gpx_files/` or any valid `.fit` file in the `fit_files/` directory.
Make sure it contains track points with elevation and time data.

---

## To Do / Ideas

- [X] Plotting heart rate data - **if** FIT file choosen.
- [ ] Export as PDF report
- [ ] Multi-run comparison

---

## License

This project is open source under the [MIT License](LICENSE).

---

## Feedback / Contributions

Feel free to open issues or pull requests!
If you enjoy this project, a ⭐️ star is always appreciated.