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| import requests | |
| from collections import defaultdict | |
| from datetime import datetime, timedelta | |
| import json | |
| import pandas as pd | |
| import threading | |
| import time | |
| import os | |
| import signal | |
| api_key = "c6dfc4d92a8f972d237ef696ec87b37a" | |
| def shutdown(): | |
| # Wait a bit before shutdown to allow the response to be returned | |
| def stop(): | |
| time.sleep(1) | |
| os.kill(os.getpid(), signal.SIGTERM) # Send SIGTERM to the current process to stop Gradio | |
| os._exit(0) | |
| threading.Thread(target=stop).start() | |
| return "Shutting down and closing the Gradio window..." | |
| def get_weather_info(city): | |
| """Fetches current weather information for a city using OpenWeatherMap API.""" | |
| url_current = f"http://api.openweathermap.org/data/2.5/weather?q={city}&appid={api_key}&units=metric" | |
| response_current = requests.get(url_current) | |
| if response_current.status_code != 200: | |
| return "Error: Could not fetch weather data." | |
| data_current = response_current.json() | |
| weather_description = data_current['weather'][0]['description'] | |
| temperature_current = data_current['main']['temp'] | |
| temperature_feels_like = data_current['main']['feels_like'] | |
| temperature_min = data_current['main']['temp_min'] | |
| temperature_max = data_current['main']['temp_max'] | |
| pressure_sea_level = data_current['main'].get('sea_level', data_current['main']['pressure']) | |
| pressure_ground_level = data_current['main'].get('grnd_level', data_current['main']['pressure']) | |
| humidity = data_current['main']['humidity'] | |
| visibility = data_current['visibility'] | |
| wind_speed = data_current['wind']['speed'] | |
| wind_deg = data_current['wind']['deg'] | |
| clouds = data_current['clouds']['all'] | |
| rain = data_current.get('rain', {}).get('1h', 0) | |
| dt = datetime.utcfromtimestamp(data_current['dt']).strftime('%Y-%m-%d %H:%M:%S') | |
| timezone = data_current['timezone'] | |
| city_name = data_current['name'] | |
| response_code = data_current['cod'] | |
| formatted_info = ( | |
| f"Weather: {weather_description}, " | |
| f"Temperature: current {temperature_current}°C, feels like {temperature_feels_like}°C, min {temperature_min}°C, max {temperature_max}°C, " | |
| f"Pressure: sea level {pressure_sea_level} hPa, ground level {pressure_ground_level} hPa, " | |
| f"Humidity: {humidity}%, " | |
| f"Visibility: {visibility} meters, " | |
| f"Wind: speed {wind_speed} m/s, deg {wind_deg}, " | |
| f"Clouds: {clouds}%, " | |
| f"Rain: {rain} mm, " | |
| f"Date/Time: {dt}, " | |
| f"Timezone: {timezone} seconds, " | |
| f"City Name: {city_name}, " | |
| f"Response Code: {response_code}" | |
| ) | |
| return formatted_info | |
| def get_forecast(city): | |
| """Fetches 2-day weather forecast for a city using OpenWeatherMap API and restructures the data into a table format.""" | |
| url_forecast = f"http://api.openweathermap.org/data/2.5/forecast?q={city}&appid={api_key}&units=metric" | |
| response_forecast = requests.get(url_forecast) | |
| if response_forecast.status_code != 200: | |
| return "Error: Could not fetch forecast data." | |
| forecast_json = response_forecast.json() | |
| current_date = datetime.now().date() | |
| forecast_dates = [current_date + timedelta(days=i) for i in range(1, 3)] | |
| important_hours = ['09:00:00', '15:00:00', '21:00:00'] | |
| data = [] | |
| for entry in forecast_json['list']: | |
| date, time = entry['dt_txt'].split() | |
| date_obj = datetime.strptime(date, '%Y-%m-%d').date() | |
| if date_obj in forecast_dates and time in important_hours: | |
| data.append({ | |
| 'Date': date, | |
| 'Time': time, | |
| 'Temperature': entry['main']['temp'], | |
| 'Feels Like': entry['main']['feels_like'], | |
| 'Temp Min': entry['main']['temp_min'], | |
| 'Temp Max': entry['main']['temp_max'], | |
| 'Pressure': entry['main']['pressure'], | |
| 'Humidity': entry['main']['humidity'], | |
| 'Weather': entry['weather'][0]['description'], | |
| 'Icon': entry['weather'][0]['icon'], | |
| 'Wind Speed': entry['wind']['speed'], | |
| 'Wind Deg': entry['wind']['deg'], | |
| 'Visibility': entry['visibility'], | |
| 'Pop': entry['pop'], | |
| 'Rain': entry['rain']['3h'] if 'rain' in entry else 0, | |
| 'Clouds': entry['clouds']['all'] | |
| }) | |
| df = pd.DataFrame(data) | |
| df.set_index(['Date', 'Time'], inplace=True) | |
| return df | |
| def restructure_forecast_00(forecast_json): | |
| """Restructures the forecast JSON data into a single-line sentence format.""" | |
| current_date = datetime.now().date() | |
| forecast_dates = [current_date + timedelta(days=i) for i in range(1, 3)] | |
| important_hours = ['09:00:00', '12:00:00', '15:00:00', '18:00:00', '21:00:00'] | |
| structured_data = defaultdict(dict) | |
| for entry in forecast_json['list']: | |
| date, time = entry['dt_txt'].split() | |
| date_obj = datetime.strptime(date, '%Y-%m-%d').date() | |
| if date_obj in forecast_dates and time in important_hours: | |
| structured_data[date][time] = { | |
| 'temperature': entry['main']['temp'], | |
| 'feels like': entry['main']['feels_like'], | |
| 'temp min': entry['main']['temp_min'], | |
| 'temp max': entry['main']['temp_max'], | |
| 'pressure': entry['main']['pressure'], | |
| 'humidity': entry['main']['humidity'], | |
| 'weather': entry['weather'][0]['description'], | |
| 'icon': entry['weather'][0]['icon'], | |
| 'wind speed': entry['wind']['speed'], | |
| 'wind deg': entry['wind']['deg'], | |
| 'visibility': entry['visibility'], | |
| 'pop': entry['pop'], | |
| 'rain': entry['rain']['3h'] if 'rain' in entry else 0, | |
| 'clouds': entry['clouds']['all'] | |
| } | |
| return format_forecast(structured_data, forecast_dates) | |
| def format_forecast_00(structured_data, forecast_dates): | |
| """Formats the structured forecast data into a single-line sentence format.""" | |
| formatted_forecast = [] | |
| for date in forecast_dates: | |
| date_str = str(date) | |
| for time, data in structured_data[date_str].items(): | |
| formatted_forecast.append( | |
| f"{date_str} : {time} ( " + | |
| ", ".join(f"{key} - {value}" for key, value in data.items()) + | |
| " )" | |
| ) | |
| return "\n".join(formatted_forecast) | |
| def restructure_forecast2(forecast_json): | |
| """Restructures the forecast JSON data into a nested dictionary by date and time, including the next three days.""" | |
| current_date = datetime.now().date() | |
| forecast_dates = [current_date + timedelta(days=i) for i in range(1, 3)] | |
| structured_data = defaultdict(dict) | |
| for entry in forecast_json['list']: | |
| date, time = entry['dt_txt'].split() | |
| date_obj = datetime.strptime(date, '%Y-%m-%d').date() | |
| if date_obj in forecast_dates: | |
| structured_data[date][time] = { | |
| 'temperature': entry['main']['temp'], | |
| 'feels_like': entry['main']['feels_like'], | |
| 'temp_min': entry['main']['temp_min'], | |
| 'temp_max': entry['main']['temp_max'], | |
| 'pressure': entry['main']['pressure'], | |
| 'humidity': entry['main']['humidity'], | |
| 'weather': entry['weather'][0]['description'], | |
| 'icon': entry['weather'][0]['icon'], | |
| 'wind_speed': entry['wind']['speed'], | |
| 'wind_deg': entry['wind']['deg'], | |
| 'visibility': entry['visibility'], | |
| 'pop': entry['pop'], | |
| 'rain': entry['rain']['3h'] if 'rain' in entry else 0, | |
| 'clouds': entry['clouds']['all'] | |
| } | |
| return {str(date): structured_data[str(date)] for date in forecast_dates} | |
| def restructure_forecast_0(forecast_json): | |
| """Restructures the forecast JSON data into a nested dictionary by date and specific times.""" | |
| current_date = datetime.now().date() | |
| forecast_dates = [current_date + timedelta(days=i) for i in range(1, 3)] | |
| important_hours = ['09:00:00', '12:00:00', '15:00:00', '18:00:00', '21:00:00'] | |
| structured_data = defaultdict(dict) | |
| for entry in forecast_json['list']: | |
| date, time = entry['dt_txt'].split() | |
| date_obj = datetime.strptime(date, '%Y-%m-%d').date() | |
| if date_obj in forecast_dates and time in important_hours: | |
| structured_data[date][time] = { | |
| 'temperature': entry['main']['temp'], | |
| 'feels_like': entry['main']['feels_like'], | |
| 'temp_min': entry['main']['temp_min'], | |
| 'temp_max': entry['main']['temp_max'], | |
| 'pressure': entry['main']['pressure'], | |
| 'humidity': entry['main']['humidity'], | |
| 'weather': entry['weather'][0]['description'], | |
| 'icon': entry['weather'][0]['icon'], | |
| 'wind_speed': entry['wind']['speed'], | |
| 'wind_deg': entry['wind']['deg'], | |
| 'visibility': entry['visibility'], | |
| 'pop': entry['pop'], | |
| 'rain': entry['rain']['3h'] if 'rain' in entry else 0, | |
| 'clouds': entry['clouds']['all'] | |
| } | |
| return {str(date): structured_data[str(date)] for date in forecast_dates} | |
| def restructure_forecast3(forecast_json): | |
| """Restructures the forecast JSON data into a nested dictionary by date and time, including the next three days.""" | |
| current_date = datetime.now().date() | |
| forecast_dates = [current_date + timedelta(days=i) for i in range(1, 4)] | |
| structured_data = defaultdict(dict) | |
| for entry in forecast_json['list']: | |
| date, time = entry['dt_txt'].split() | |
| date_obj = datetime.strptime(date, '%Y-%m-%d').date() | |
| if date_obj in forecast_dates: | |
| structured_data[date][time] = { | |
| 'temperature': entry['main']['temp'], | |
| 'feels_like': entry['main']['feels_like'], | |
| 'temp_min': entry['main']['temp_min'], | |
| 'temp_max': entry['main']['temp_max'], | |
| 'pressure': entry['main']['pressure'], | |
| 'humidity': entry['main']['humidity'], | |
| 'weather': entry['weather'][0]['description'], | |
| 'icon': entry['weather'][0]['icon'], | |
| 'wind_speed': entry['wind']['speed'], | |
| 'wind_deg': entry['wind']['deg'], | |
| 'visibility': entry['visibility'], | |
| 'pop': entry['pop'], | |
| 'rain': entry['rain']['3h'] if 'rain' in entry else 0, | |
| 'clouds': entry['clouds']['all'] | |
| } | |
| return {str(date): structured_data[str(date)] for date in forecast_dates} | |
| def get_weather_info_0(city): | |
| """Fetches current weather information for a city using OpenWeatherMap API.""" | |
| url_current = f"http://api.openweathermap.org/data/2.5/weather?q={city}&appid={api_key}&units=metric" | |
| response_current = requests.get(url_current) | |
| if response_current.status_code != 200: | |
| return "Error: Could not fetch weather data." | |
| data_current = response_current.json() | |
| response = { | |
| 'coordinates': data_current['coord'], | |
| 'weather': data_current['weather'][0], | |
| 'temperature': { | |
| 'current': data_current['main']['temp'], | |
| 'feels_like': data_current['main']['feels_like'], | |
| 'min': data_current['main']['temp_min'], | |
| 'max': data_current['main']['temp_max'] | |
| }, | |
| 'pressure': { | |
| 'sea_level': data_current['main'].get('sea_level', data_current['main']['pressure']), | |
| 'ground_level': data_current['main'].get('grnd_level', data_current['main']['pressure']) | |
| }, | |
| 'humidity': data_current['main']['humidity'], | |
| 'visibility': data_current['visibility'], | |
| 'wind': data_current['wind'], | |
| 'clouds': data_current['clouds'], | |
| 'rain': data_current.get('rain', {}), | |
| 'dt': data_current['dt'], | |
| 'sys': data_current['sys'], | |
| 'timezone': data_current['timezone'], | |
| 'id': data_current['id'], | |
| 'name': data_current['name'], | |
| 'cod': data_current['cod'] | |
| } | |
| return json.dumps(response, indent=2) | |