https://github.com/annenkovdmitrii/nyc-app
My Streamlit App has some everyday data that is useful for New Yorkers.
https://github.com/annenkovdmitrii/nyc-app
docker python streamlit
Last synced: 2 months ago
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My Streamlit App has some everyday data that is useful for New Yorkers.
- Host: GitHub
- URL: https://github.com/annenkovdmitrii/nyc-app
- Owner: annenkovdmitrii
- Created: 2025-03-08T18:24:06.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-10T00:26:49.000Z (over 1 year ago)
- Last Synced: 2025-07-26T11:48:05.224Z (11 months ago)
- Topics: docker, python, streamlit
- Language: Python
- Homepage:
- Size: 109 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# NYC Local Dashboard
A streamlined Raspberry Pi-friendly dashboard for New York City weather and subway information. This application provides real-time updates on weather conditions and upcoming subway train arrivals for your favorite stations.
## Features
- **Current Weather**: Display current conditions, temperature, wind, humidity, and UV index for NYC
- **Weather Forecast**: Show upcoming 3-hour forecast
- **Subway Arrivals**: Monitor train arrivals at three configurable stations
- **Auto-Refresh**: Keep data updated with built-in auto-refresh functionality
- **Station Search**: Find any subway station in the MTA system
- **Detailed Weather**: Access comprehensive weather information including air quality
- **Customizable**: Configure your default stations and preferences
## Installation
### Prerequisites
- Python 3.9+
- Raspberry Pi (recommended) or any computer that can run Python
- Internet connection
### Setup
1. Clone the repository:
```bash
git clone https://github.com/dmitriiannenkov/nyc-dashboard.git
cd nyc-dashboard
```
2. Create a virtual environment:
```bash
python -m venv nyc-app
source nyc-app/bin/activate # On Windows: nyc-app\Scripts\activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Create a `.env` file with your API key:
```
WEATHER_API_KEY=your_weatherapi_com_key
```
### Running the Dashboard
```bash
cd app
streamlit run main.py
```
The dashboard will open in your web browser at http://localhost:8501
## Project Structure
```
nyc-app/
├── app/ # Application code
│ ├── assets/ # Static assets
│ │ ├── styles.css # Custom styling
│ │ └── nyc_icon.png # App icon
│ ├── main.py # Main Streamlit UI and page logic
│ ├── nyc_weather.py # NYCWeather class for weather data
│ ├── mta_client.py # MTAClient class for subway data
│ └── utils.py # Utility functions
├── data/ # Data cache directories
│ ├── mta_cache/ # MTA data cache
│ └── weather_cache/ # Weather data cache
├── tests/ # Test files
├── docker-compose.yml # Docker configuration
├── Dockerfile # Docker build file
└── requirements.txt # Python dependencies
```
## Docker Deployment
You can also run the application using Docker:
```bash
docker-compose up
```
This will build and start the container with the application running on port 8501.
## API Usage
This application uses:
1. **WeatherAPI.com**: For real-time weather data and forecasts. You'll need to [sign up](https://www.weatherapi.com/signup.aspx) for a free API key.
2. **MTA GTFS Realtime Feed**: For subway arrival information. This is publicly available and doesn't require an API key.
## Performance Considerations
The application is optimized for Raspberry Pi usage:
- Efficient caching system to reduce API calls
- Lazy loading of components to minimize startup time
- Performance monitoring with timing decorators
- Single auto-refresh mechanism to reduce resource usage
## Customization
### Adding Default Stations
1. Navigate to the "Subway Lookup" page
2. Search for a station
3. Use the "Add to Defaults" feature to set it as one of your default stations
### Changing Refresh Rate
The auto-refresh is set to 60 seconds by default. This can be modified in the `setup_auto_refresh` function in `main.py`.
## Testing
Run the tests with:
```bash
cd tests
python -m unittest test_mta_client.py
```
## License
[MIT License](LICENSE)
## Acknowledgments
- Built with [Streamlit](https://streamlit.io/)
- Subway data from [MTA GTFS-Realtime Feed](https://api.mta.info/)
- Weather data from [WeatherAPI.com](https://www.weatherapi.com/)