Why Use Python and OpenWeather API Together?

Python is an excellent language thanks to its readability, extensive libraries and strong community. Combined with the OpenWeather API — a popular, developer-friendly service providing weather data globally — it’s perfect for building real-time applications. The combination allows you to practice working with APIs, handling JSON, and displaying useful information in a clean interface.

Prerequisites

• Python 3 installed (https://www.python.org/)
• An API key from OpenWeatherMap
• Basic Python knowledge (variables, functions, dictionaries)
• Optional: a simple GUI toolkit like Tkinter or CLI-only

Step 1: Install Required Libraries

Open a terminal and install the requests library for API calls:

pip install requests

This library will help you make HTTP requests to the OpenWeather API.

Step 2: Set Up Your Python Script

Create a new file named weather_dashboard.py and add the following starter code:

import requests

API_KEY = "YOUR_API_KEY"
BASE_URL = "https://api.openweathermap.org/data/2.5/weather"

city = input("Enter city name: ")
params = {
    'q': city,
    'appid': API_KEY,
    'units': 'metric'
}

response = requests.get(BASE_URL, params=params)
data = response.json()

Replace YOUR_API_KEY with the actual API key from OpenWeather.

Step 3: Parse and Display the Data

Below the existing code, add logic to extract and print relevant data:

if response.status_code == 200:
    main = data['main']
    weather = data['weather'][0]
    print(f"\nWeather in {city}:")
    print(f"Temperature: {main['temp']} °C")
    print(f"Humidity: {main['humidity']}%")
    print(f"Condition: {weather['description'].capitalize()}")
else:
    print("Error: Could not retrieve data")

This displays a simple but functional weather report in the console.

Step 4: Improve the Interface

For a basic GUI, you can add Tkinter. Add this to the top of your script:

import tkinter as tk
from tkinter import messagebox

Then create a window and display results using widgets. (This step is optional and can be customized later for a more advanced dashboard.)

Step 5: Final Touches

• Format the output using string formatting
• Handle errors like invalid city names or API key issues
• Style the GUI with labels and buttons if using Tkinter

Conclusion

You’ve just built a simple yet powerful weather dashboard using Python and the OpenWeather API. Whether you stop at the command-line version or build a GUI, this project is great practice for API calls, error handling, and data formatting. You now have a working app that you can expand with forecasts, map views, or historical weather data!