INTRODUCTION:
Hello, esteemed community members! I’m thrilled to share my captivating program that unlocks the incredible potential of data extraction and web data—two vital skills that can elevate your journey in the field of data science.

TOOLS:
Here are the powerful tools that drive this program:

1. Python Programming Language
2. PyCharm
3. OpenWeatherMap API
4. JSON

PYTHON LIBRARIES:

1. urllib
2. json
3. datetime

PROGRAM PHILOSOPHY AND LOGIC:
This program was designed with a passion for learning and discovery. By leveraging the OpenWeatherMap API, a cutting-edge open-source platform for weather forecasting, we can tap into a wealth of data.

1. I began by importing the urllib, json, and datetime libraries, laying the foundation for our data adventure.
2. I generated an API key from the platform, granting us access to invaluable resources and data.
3. With this key in hand, I expertly navigated to the base URL, setting the parameters necessary to connect and retrieve essential data.
4. Once the first phase was complete, I harnessed the API key to extract raw JSON data for any city, opening doors to new insights.
5. I committed to thoroughly analyzing the data, uncovering its parameters and logic, and transforming raw information into valuable knowledge.
6. This analysis led me to the second phase, where I engaged in parsing the data to present it in a clear and impactful way.
7. We can present this data in two powerful formats: one captures the essence of the current day, while the other utilizes the datetime library, allowing us to explore selected time frames and reveal the rich narratives behind the weather events we wish to study.

Join me on this journey of exploration and empowerment through data!

Below is my GitHub link. Feel free to look at my project.
https://github.com/h2005mirza/weather-forecasting

Below is the Python code I developed:

import urllib.request, urllib.error, urllib.parse
import json
from datetime import datetime

api_key = "fa07f03ac7822f26f40d5bb67daf3d3c"
weather_url = "http://api.openweathermap.org/data/2.5/forecast?"

city = input("Enter the name of the city: ")
start_date = input("Enter the start date (YYYY-MM-DD): ")
end_date = input("Enter the end date (YYYY-MM-DD): ")

parsed_url = f"{weather_url}q={city}&appid={api_key}&units=metric"

try:
    response = urllib.request.urlopen(parsed_url)
    weather_data = json.load(response)
    print(f"Weather forecast of {city} from {start_date} to {end_date}")
    for forecast in weather_data['list']:
        forecast_date = forecast['dt_txt']
        forecast_datetime = datetime.strptime(forecast_date, '%Y-%m-%d %H:%M:%S')
        start_datetime = datetime.strptime(start_date, '%Y-%m-%d')
        end_datetime = datetime.strptime(end_date, '%Y-%m-%d')

        if start_datetime <= forecast_datetime <= end_datetime:
            temp = forecast['main']['temp']
            description = forecast['weather'][0]['description']
            print(f"Date: {forecast_date} | Temperature: {temp}°C | Description: {description}")

except urllib.error.URLError as e:
    print(f"An HTTP error occurred: {e.reason}")
except Exception as e:
    print(f"An error: {e}")