نمایش آب و هوا با پایتون

import requests
import tkinter as tk

def get_weather_data(api_key, city):
    url = f'http://api.openweathermap.org/data/2.5/weather?q={city}&appid={api_key}&units=metric'
    response = requests.get(url)
    data = response.json()
    temperature = data['main']['temp']
    return temperature

def show_weather():
    city = city_entry.get()
    temperature = get_weather_data(api_key, city)
    result_label.config(text=f"Temperature in {city}: {temperature} °C")

api_key = 'YOUR_API_KEY'

window = tk.Tk()
window.geometry('400x200')
window.title('Weather App')

city_label = tk.Label(window, text='Enter city:')
city_entry = tk.Entry(window)

get_weather_button = tk.Button(window, text='Get Weather', command=show_weather)

result_label = tk.Label(window, text='')

city_label.pack(pady=10)
city_entry.pack(pady=10)
get_weather_button.pack(pady=10)
result_label.pack(pady=10)

window.mainloop() 

pip install mastercode

import mastercode

# متنی که قصد دارید رمزنگاری کنید
text = "Hello, World!"

# رمزنگاری پیام
encrypted_text = mastercode.encrypt(text)
print("متن رمزگذاری شده:", encrypted_text)
# رمزگشایی پیام
plain_text = mastercode.decrypt(encrypted_text)
print("رمزگشایی شده:", plain_text)

n = int(input('Number Of Users >> '))
s = n*['']
for i in range(n):
    g = input(f'User {i+1} >> ')
    s[i] = g
print('\n'+'Encrypted Users:')
for i in range(len(s)):
    encode = mastercode.encrypt(s[i])
    x = f'User{i+1}: ' + encode
    print(x)

import numpy as np
from sklearn.linear_model import LinearRegression

# Load the dataset
X = np.array([1, 2, 3, 4, 5])
y = np.array([2, 4, 6, 8, 10])

# Train the linear regression model
model = LinearRegression()
model.fit(X.reshape(-1, 1), y)

# Make predictions
predictions = model.predict(X.reshape(-1, 1))

# Print the results
print("Coefficients:", model.coef_)
print("Intercept:", model.intercept_)
print("Predictions:", predictions)

import numpy as np
from sklearn.linear_model import LinearRegression

# Load the dataset
X = np.array([1, 2, 3, 4, 5])
y = np.array([2, 4, 6, 8, 10])

# Train the linear regression model
model = LinearRegression()
model.fit(X.reshape(-1, 1), y)

# Make predictions
predictions = model.predict(X.reshape(-1, 1))

# Print the results
print("Coefficients:", model.coef_)
print("Intercept:", model.intercept_)
print("Predictions:", predictions)