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Climate Data Visualization Project

This project is a FastAPI-based web application that fetches and visualizes climate data from the Copernicus Climate Data Store (CDS). It provides an API endpoint to retrieve temperature data for a specific year and month, and processes this data to provide useful statistics.

Screenshot

Features

  • Data Retrieval:

    • Fetch monthly average temperature data from the Copernicus Climate Data Store (CDS) API
    • Cache results for 24 hours
    • Support for specifying year and month for data retrieval

  • Data Processing:

    • Process and analyze temperature data to provide comprehensive statistics
    • Calculate average, median, minimum, and maximum temperatures
    • Compute standard deviation for temperature variation
    • Determine 25th and 75th percentile temperatures
    • Provide latitude and longitude ranges for the data

  • API Endpoints:

    • RESTful API endpoint to retrieve processed climate data
    • Swagger UI documentation for easy API exploration and testing

  • Error Handling and Logging:

    • Robust error handling for data retrieval and processing
    • Detailed logging for troubleshooting and monitoring

  • Frontend:

    • Simple and clean HTML interface for data visualization
    • Integration of Apache ECharts for creating dynamic and responsive charts

  • Backend:

    • FastAPI framework for high-performance, easy-to-use API development
    • Efficient serving of static files for frontend assets

Prerequisites

Before you begin, ensure you have met the following requirements:

Installation

  1. Clone the repository:

    git clone https://github.com/esoltys/climate-data-viz.git
cd climate-data-viz

  2. Create a virtual environment and activate it:

    python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

  3. Install the required packages:

    pip install -r requirements.txt

  4. Set up your CDS API key:

    • Create a file named .cdsapirc in your home directory
    • Add the following content to the file, replacing YOUR-API-KEY with your actual CDS API key: 
      url: https://cds-beta.climate.copernicus.eu/api
key: YOUR-API-KEY

  5. Accept the "Terms of Use" at the bottom of the Download tab for the dataset:

Usage

  1. Start the FastAPI server:

    uvicorn app.main:app --reload

  2. View the Data Visualization:

    • Open your web browser and navigate to http://127.0.0.1:8000/static/index.html

  3. Access the API:

    • Open your web browser and navigate to http://127.0.0.1:8000/docs to view the Swagger UI documentation for the API.
    • Use the /api/temperature endpoint to retrieve temperature data for a specific year and month: 
      GET http://127.0.0.1:8000/api/temperature?year=2023&month=7

  4. API Response Format: When using the /api/temperature endpoint, you'll receive a JSON response with the following structure:

    {
  "year": 2023,
  "month": 7,
  "average_temperature": 8.64,
  "median_temperature": 9.12,
  "min_temperature": -64.73,
  "max_temperature": 41.73,
  "std_deviation": 22.18,
  "unit": "Celsius",
  "data_points": 73728,
  "latitude_range": [-90.0, 90.0],
  "longitude_range": [0.0, 359.75],
  "25th_percentile": -8.31,
  "75th_percentile": 24.89
}

Note: The current implementation uses fixed data for July 2023. To visualize data for different months or years, you'll need to modify the main function in static/js/visualization.js.

Running Tests and Type Checking

To run the tests, use the following command:

pytest

To check type annotations:

pyright

Architecture

graph TB
    User((User))
    
    subgraph "Climate Data Visualization System"
        FrontendApp["Frontend Application<br/>(HTML, JavaScript)"]
        
        subgraph "Backend Services"
            APIServer["API Server<br/>(FastAPI)"]
            DataProcessingService["Data Processing Service<br/>(Python)"]
            CacheService["Cache Service<br/>(Python)"]
        end
        
        subgraph "Data Storage"
            FileCache[("File Cache<br/>(JSON)")]
        end
    end
    
    subgraph "External Services"
        CDSApi["Copernicus Climate Data Store API<br/>(CDS API)"]
    end
    
    User --> FrontendApp
    FrontendApp --> APIServer
    APIServer --> DataProcessingService
    APIServer --> CacheService
    CacheService --> FileCache
    DataProcessingService --> CDSApi
    
    classDef frontend fill:#1168bd,stroke:#0b4884,color:#ffffff
    classDef backend fill:#2694ab,stroke:#1a6d7d,color:#ffffff
    classDef database fill:#2b78e4,stroke:#1a4d91,color:#ffffff
    classDef external fill:#999999,stroke:#666666,color:#ffffff
    
    class FrontendApp frontend
    class APIServer,DataProcessingService,CacheService backend
    class FileCache database
    class CDSApi external
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License

This project is open source and available under the MIT License.

Acknowledgments

This project would not have been possible without the following open-source libraries and services:

These tools and libraries have greatly contributed to the development and success of this project.