🌦️ RainCheck

RainCheck is a Python-based automation tool designed to monitor real-time weather data and provide proactive notifications for rain alerts. By integrating with external Weather APIs, the system helps users stay prepared for changing weather conditions.

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🚀 Key Features

• Real-time Monitoring: Fetches live weather updates from external providers.
• Automated Logic: Evaluates weather conditions and triggers notifications based on predefined rain thresholds.
• API Integration: Robust handling of JSON data from RESTful Weather APIs.
• Secure Configuration: Supports environment variables for sensitive API credentials.

🛠 Tech Stack

• Language: Python 3.x
• Libraries: requests (for API calls), json (for data parsing), python-dotenv (for security).
• Concepts: API Integration, Data Processing, Automation.

📋 Prerequisites

• Python 3.8+
• A valid API Key from a weather provider (e.g., OpenWeatherMap or WeatherAPI).

⚙️ Configuration

To keep your API keys secure and follow industry best practices for a Senior Software Engineer:

1. Create a .env file in the project root:

   touch .env
   

2. Add your API credentials to the .env file:

   WEATHER_API_KEY=your_api_key_here
   CITY_NAME=your_city_Name
   

3. Note: Ensure your .gitignore includes .env to avoid leaking credentials to GitHub.

💻 Setup & Usage

1. Clone the repository:

   git clone [https://github.com/natalie-adiv/rain-check.git](https://github.com/natalie-adiv/rain-check.git)
   cd rain-check   
   

2. Install dependencies:

   pip install requests python-dotenv
   

3. Run the application:

   python main.py
   

🧠 Notification Logic

The core logic of RainCheck follows a simple yet effective flow:

1. Fetch: Request current and forecast data for the specified location.
2. Parse: Extract precipitation probability and weather condition codes.
3. Analyze: If rain is detected within the next 12 hours (probability > 50%), a notification is prepared.
4. Trigger: Send the alert via the configured notification channel (e.g., Terminal, Email, or Desktop Notification).

🎓 Academic Connection & Future Work

As part of my Master of Science in Machine Learning & Big Data, I plan to expand RainCheck with:

• Predictive Models: Using historical weather patterns to forecast localized rain events with higher accuracy.
• Data Pipelines: Implementing advanced data collection for long-term weather trend analysis.