Day 1: Setting up the AWS Weather Dashboard Application

Background

This project is a part of the 30 Days All Star Devops Challenge that aims to increase proficiency in Devops through a series of hands-on projects and documentation.

Project Description

This project makes use of Python and AWS Services (S3) to retrieve weather data from OpenWeatherAPI and stores the results in a json format in an S3 Bucket.

Tools Used:

• Python: Language used to set up the Weather Dashboard
• AWS S3 ( Simple Storage Service): AWS Storage Solution
• OpenWeather API Key
• Boto3 : AWS SDK used by python to interact with the S3 Bucket
• requests: Python library used to send requests and fetch data

Environment Setup

Before implementing the weather dashboard, here are a few things needed to set up your environment.

1. AWS Account and AWS CLI: You need an AWS Account where your bucket will be created and the AWS CLI to set up credentials to interact with AWS

2. Python: Make sure Python 3.x is installed on your system as well as pip, It will be needed to install libraries

3. OpenWeather API Key: Get the OpenWeather API Key by signing up to this page OpenWeather

Architecture Diagram

Project Workflow

This project uses a python script that fetches weather data from openweather via its API Key and then sends/stores it to a S3 bucket in JSON Format

Here are some excerpts of the code:

class WeatherDashboard:
def __init__(self):
    self.api_key = os.getenv('OPENWEATHER_API_KEY') # Get the OpenWeather API key from environment variables
    self.bucket_name = os.getenv('AWS_BUCKET_NAME') # Get the AWS S3 bucket name from environment variables
    self.s3_client = boto3.client('s3') # Create an S3 client for interacting with AWS S3

This sets up the API key, bucket name, and S3 client when you create an instance of the WeatherDashboard class.

def fetch_weather(self, city):
    base_url = "http://api.openweathermap.org/data/2.5/weather"  # The API endpoint for weather data
    params = {
        "q": city,                        # The city name to fetch weather for
        "appid": self.api_key,            # The API key for authentication
        "units": "imperial"               # Use imperial units (Fahrenheit)
    }

    try:
        response = requests.get(base_url, params=params)  # Make a GET request to the API
        response.raise_for_status()                       # Raise an error if the response indicates failure
        return response.json()                            # Return the weather data as JSON
    except requests.exceptions.RequestException as e:
        print(f"Error fetching weather data: {e}")  # Print error if the request fails
        return None

This section gets weather information like temperature and conditions for a given city

def save_to_s3(self, weather_data, city):
    if not weather_data:  # If no data is passed, return False (skip saving)
        return False

    timestamp = datetime.now().strftime('%Y%m%d-%H%M%S')  # Create a timestamp (e.g., 20250107-153045)
    file_name = f"weather-data/{city}-{timestamp}.json"    # Define the file path and name

    try:
        weather_data['timestamp'] = timestamp  # Add a timestamp to the weather data
        self.s3_client.put_object(             # Save the data to S3
            Bucket=self.bucket_name,           # The S3 bucket name
            Key=file_name,                     # The file path in the bucket
            Body=json.dumps(weather_data),     # Convert data to JSON format for saving
            ContentType='application/json'     # Specify the file type as JSON
        )
        print(f"Successfully saved data for {city} to S3")  # Confirm success
        return True
    except Exception as e:
        print(f"Error saving to S3: {e}")  # Print error if saving fails
        return False

This section saves it in s3 bucket

To run the project on your machine, follow these steps:

1. Clone the repository from here: Github Repo

2. Follow the instructions in the README here: README.md

When the project has been run, you should get the following output

Conclusion

This project successfully demonstrates how to build a simple yet functional weather dashboard application by integrating Python, OpenWeatherAPI, and AWS S3. Through this project, we explored retrieving real-time weather data using APIs, processing it in Python, and securely storing the results in an S3 bucket in JSON format. It highlights practical use cases of Python libraries like boto3 and requests, emphasizing the importance of cloud storage solutions in managing and persisting data. This project is an excellent starting point for developers looking to enhance their skills in API integration, cloud computing, and DevOps practices.