weather.py

import requests
from datetime import datetime, timezone
import pandas as pd
import numpy as np
import sys
from tqdm import tqdm
from xml.etree.ElementTree import Element, SubElement, tostring, ElementTree

# Define your OpenWeatherMap API key
API_KEY = "" # Get your API key from https://home.openweathermap.org/users/sign_up

# Check if API key is provided
if not API_KEY:
    print("API key is not found. Please provide a valid API key.")
    sys.exit(1)

# Initialize a list to store city data
cities_data = []

# Read city names from CSV file
city_df = pd.read_csv('in_cities.csv') # CSV file containing city names

# Function to fetch city data
def fetch_city_data(city_name):
    URL = f"http://api.openweathermap.org/data/2.5/weather?q={city_name}&appid={API_KEY}&units=metric"
    response = requests.get(URL)
    if response.status_code == 200:
        data = response.json()
        return {
            "name": data['name'],
            "lat": data['coord']['lat'],
            "lon": data['coord']['lon']
        }
    else:
        print(f"Failed to fetch data for {city_name}")
        return None

# Iterate over each city in the DataFrame and fetch data
print("Fetching city data...")
for city in tqdm(city_df['City'], desc="City Data", bar_format="{l_bar}{bar:10}{r_bar}{bar:-10b}", ncols=100):
    city_info = fetch_city_data(city)
    if city_info:
        cities_data.append(city_info)

# Print the collected city data
print(cities_data)

# Function to fetch forecast data for a city
def fetch_forecast_data(city):
    URL = f"http://api.openweathermap.org/data/2.5/forecast?lat={city['lat']}&lon={city['lon']}&appid={API_KEY}&units=metric"
    response = requests.get(URL)
    if response.status_code == 200:
        data = response.json()
        forecasts = []
        for forecast_data in data['list']:
            forecast = {
                'city': city['name'],
                'timestamp': forecast_data['dt'],
                'date_time': datetime.fromtimestamp(forecast_data['dt'], timezone.utc).strftime('%d-%m-%Y %H:%M:%S'),
                'weather_main': forecast_data['weather'][0]['main'],
                'weather_description': forecast_data['weather'][0]['description'],
                'temperature_celsius': forecast_data['main']['temp'],
                'feels_like_celsius': forecast_data['main']['feels_like'],
                'temp_min_celsius': forecast_data['main']['temp_min'],
                'temp_max_celsius': forecast_data['main']['temp_max'],
                'pressure': forecast_data['main']['pressure'],
                'humidity': forecast_data['main']['humidity'],
                'wind_speed': forecast_data['wind']['speed'],
                'wind_deg': forecast_data['wind']['deg'],
                'clouds': forecast_data['clouds']['all'],
                'lat': city['lat'],
                'lon': city['lon']
            }
            forecasts.append(forecast)
        return forecasts
    else:
        print(f"Failed to fetch data for {city['name']}")
        return []

# Collect forecasts for all cities
all_forecasts = []
print("Fetching forecast data...")
for city in tqdm(cities_data, desc="Forecast Data", bar_format="{l_bar}{bar:10}{r_bar}{bar:-10b}", ncols=100):
    city_forecasts = fetch_forecast_data(city)
    all_forecasts.extend(city_forecasts)

# Convert data to DataFrame
df = pd.DataFrame(all_forecasts)

# Display the first 10 rows of the DataFrame
print(df.head(10))

# Ask the user for the preferred output format
output_format = input("Enter the preferred output format (csv/json/xml/html): ").strip().lower()

# Save the DataFrame based on the user's choice
if output_format == "csv":
    df.to_csv('weather_data.csv', index=False)
    print('The DataFrame has been successfully saved to a CSV file')
elif output_format == "json":
    df.to_json('weather_data.json', orient='records', lines=True)
    print('The DataFrame has been successfully saved to a JSON file')
elif output_format == "xml":
    # Define a function to convert DataFrame to XML using etree
    def df_to_xml(df, filename=None):
        root = Element('root')
        for _, row in df.iterrows():
            item = SubElement(root, 'item')
            for field in df.columns:
                field_element = SubElement(item, field)
                field_element.text = str(row[field])
        tree = ElementTree(root)
        if filename:
            tree.write(filename)
        return tree

    df_to_xml(df, 'weather_data.xml')
    print('The DataFrame has been successfully saved to an XML file')
elif output_format == "html":
    df.to_html('weather_data.html', index=False)
    print('The DataFrame has been successfully saved to an HTML file')
else:
    print("Invalid format. Please choose either 'csv', 'json', 'xml', or 'html'.")
    sys.exit(1)