🔭 AstroScope: NASA Asteroid Dashboard

AstroScope is an interactive dashboard that visualizes near-Earth asteroid data from NASA's NeoWs API. It provides insights into asteroid sizes, velocities, miss distances, and potential hazards.

📋 Features

• Data Fetching: Automatically fetches asteroid data from NASA's NeoWs API
• Data Analysis: Calculates risk scores, identifies anomalies, and generates time series data
• Interactive Dashboard: Visualizes asteroid data with interactive charts and tables
• Filtering: Filter data by date range and risk threshold
• Risk Heatmap Calendar: GitHub-style calendar heatmap of daily average risk scores
• Daily Closest Miss Table: Ranks the top 10 dates by the closest asteroid approach, with details per day
• Responsive Design: Works on desktop and mobile devices

🚀 Getting Started

Prerequisites

• Python 3.7 or higher
• NASA API key (get one at https://api.nasa.gov)

Getting a NASA API Key

1. Go to https://api.nasa.gov.
2. In the "Generate API Key" form, fill in the required fields:
   • First Name (required)
   • Last Name (required)
   • Email (required)
   • How will you use the APIs? (optional)
3. Submit the form and check your email to receive your API key.
4. Add the key to your .env file:

   NASA_API_KEY="YOUR_KEY_HERE"
   

Installation

1. Clone the repository:

   git clone https://github.com/ArjunCodess/astroscope.git
   cd astroscope

2. Install dependencies:

   pip install -r requirements.txt

3. Duplicate the .env.example file to create a .env file in the project root directory and update the NASA_API_KEY with your own key:

   NASA_API_KEY=""
   

Configuration

The application can be configured using environment variables in the .env file:

• NASA_API_KEY: Your NASA API key (required)
• DATA_FETCH_DAYS: Number of days to fetch asteroid data for (default: 30)
• DATA_DIR: Directory to store data files (default: "data")
• API_CHUNK_SIZE: Maximum number of days per API request (default: 7, NASA API limit)
• RISK_THRESHOLD: Threshold for classifying asteroids as high risk (default: 0.6)

📊 Running the Application

Start the Streamlit dashboard with a single command:

python -m streamlit run app.py

The dashboard will be available at http://localhost:8501.

The application will automatically:

1. Check if data files exist
2. If not, fetch asteroid data from NASA's NeoWs API
3. Process the raw data into a clean format
4. Analyze the data to calculate risk scores and generate time series data
5. Display the interactive dashboard
   • Includes a "Daily Closest Miss" table showing the closest approach per day and ranking the top 10 dates by proximity

Note: You can still run the data pipeline steps separately if needed:

• python -m lib.data_fetcher - Fetch data only
• python -m lib.data_processing - Process data only
• python -m lib.analysis - Analyze data only

📁 Project Structure

• app.py: Main Streamlit application
• lib/: Library modules
  • data_fetcher.py: Fetches data from NASA's NeoWs API
  • data_processing.py: Processes raw data into clean format
  • analysis.py: Analyzes data and calculates risk scores
  • visualizer.py: Creates visualizations for the dashboard
• data/: Data directory (created automatically)
• docs/: Documentation
  • PRD.md: Product Requirements Document

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.