☁️ https://www.youtube.com/watch?v=A95XBJFOqjw

Weather Dashboard Demo

Project Overview

The Weather Dashboard demonstrates:

• API Integration: Real-time weather data retrieval using the OpenWeather API.

• Cloud Storage: Secure storage of weather data in AWS S3 buckets.

• Environment Management: Configurable with environment variables for sensitive information like API keys and bucket names.

• DevOps Principles: Simplified deployment and cloud integration.

Key Features

• Real-Time Weather Data: Fetches up-to-date weather information for multiple cities.

• Detailed Insights: Displays temperature (°F), humidity levels, and current weather conditions.

• Cloud Storage Integration: Automatically saves weather data to AWS S3 buckets for secure storage.

• Bucket Name Randomization: Attaches a unique tag to the base bucket name.

• Multi-City Monitoring: Tracks weather conditions for various cities simultaneously.

Technical Architecture

• Language: Python 3.x

• Cloud Provider: AWS (S3)

• External API: OpenWeather API

Core Dependencies

• boto3: AWS SDK for Python.

• python-dotenv: For managing environment variables.

• requests: Simplified HTTP requests for API integration.

Project Structure

• weather-dashboard/

•   ├── src/

•   │   ├── __init__.py

•   │   └── weather_dashboard.py

•   ├── tests/

•   ├── data/

•   ├── .env

•   ├── .gitignore

•   ├── requirements.txt

Setup Instructions

Step 1: Clone the Repository

bash

code

• git clone <repository-url>

• cd weather-dashboard

Alternatively, manually recreate the structure listed above for learning purposes.

Step 2: Create a Virtual Environment (Optional)

bash

code

• python3 -m venv env

• source env/bin/activate  # Activate the environment

Note: This step may not be needed if using GitHub tools/terminal.

Step 3: Install Dependencies

bash

code

• pip install -r requirements.txt

Step 4: Configure Environment Variables

Create a .env file in the root directory with the following content:

plaintext

code

• OPENWEATHER_API_KEY=your_openweather_api_key

• AWS_BUCKET_NAME_BASE=your_s3_bucket_name

• AWS_ACCESS_KEY_ID=your_aws_access_key_id

• AWS_SECRET_ACCESS_KEY=your_aws_secret_access_key

Tip: Use the AWS Toolkit extension for easier connectivity. Keep sensitive data secure after completing the project.

Step 5: Configure AWS Credentials (Optional)

Set up AWS CLI credentials:

bash

code

• aws configure

Provide:

• Access Key ID

• Secret Access Key

• Default Region (e.g., us-east-1)

Step 6: Run the Application

Execute the script to fetch and save weather data:

bash

code

• python src/weather_dashboard.py

Common Issues

1. Bucket Name Issues: Ensure the bucket name in .env is valid and unique.

2. AWS Credentials Error: Verify that AWS CLI is properly configured with sufficient permissions.

3. OpenWeather API Key Error: Ensure the API key is active and correctly entered in .env.

4. Missing Dependencies: Install required libraries using pip install -r requirements.txt.

5. Permission Errors: Make the script executable:
   bash
   code
   chmod +x src/weather_dashboard.py

6. S3 Access Issues: Ensure the AWS user/role has S3 permissions.

7. CloudFormation Access Error: Use the following inline policy to resolve:
   json
   code
   {

•     "Version": "2012-10-17",

•     "Statement": [

•         {

•             "Effect": "Allow",

•             "Action": "cloudformation:ListStacks",

•             "Resource": "*"

•         }

•     ]

• }

Learning Goals

This project is part of a 30-day DevOps challenge aimed at mastering:

• Python Scripting: Efficiently handle and process data.

• Cloud Integration: Work with AWS services like S3.

• API Consumption: Fetch and manage data from external APIs.

• Error Handling and Debugging: Identify and resolve issues efficiently.