import os
# 獲取當(dāng)前目錄
print(os.getcwd())
# 遍歷目錄
for file in os.listdir():
    if file.endswith(".py"):
        print(file)

from datetime import datetime
now = datetime.now()
print(f"當(dāng)前時間: {now.strftime('%Y-%m-%d %H:%M:%S')}")

import json
data = {"name": "Alice", "age": 30}
json_str = json.dumps(data)  # 轉(zhuǎn)為JSON字符串
restored_data = json.loads(json_str)  # 解析JSON

import pandas as pd
df = pd.DataFrame({
    '產(chǎn)品': ['A', 'B', 'C'],
    '銷量': [120, 85, 150]
})
# 計算平均銷量
mean_sales = df['銷量'].mean()
print(f"平均銷量: {mean_sales}")

import requests
response = requests.get("https://api.example.com/data")
if response.status_code == 200:
    print(response.json())  # 輸出API返回的JSON數(shù)據(jù)

import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [10, 15, 7, 20]
plt.plot(x, y, marker='o')
plt.xlabel('X軸')
plt.ylabel('Y軸')
plt.savefig('plot.png')  # 保存圖表

python -m venv myenv  # 創(chuàng)建虛擬環(huán)境
source myenv/bin/activate  # 激活（Linux/Mac）

pip freeze > requirements.txt  # 生成依賴清單
pip install -r requirements.txt  # 安裝所有依賴

# requirements.txt
numpy==1.21.0
pandas>=1.3.0

import requests
import pandas as pd
# 1. 獲取數(shù)據(jù)
url = "https://api.weather.com/v3/forecast"
params = {"location": "beijing", "apikey": "YOUR_KEY"}
data = requests.get(url, params=params).json()
# 2. 轉(zhuǎn)為DataFrame
df = pd.DataFrame(data['daily'])
print(df[['date', 'maxTemp', 'minTemp']].head())
# 3. 計算平均溫差
df['temp_diff'] = df['maxTemp'] - df['minTemp']
print(f"平均溫差: {df['temp_diff'].mean():.1f}℃")