常用第三方模块

# 安装包
pip install requests

# 安装指定版本
pip install requests==2.28.0

# 安装requirements.txt中的所有包
pip install -r requirements.txt

# 升级包到最新版本
pip install --upgrade requests

# 卸载包
pip uninstall requests

# 查看已安装的包
pip list

# 导出已安装的包到requirements.txt
pip freeze > requirements.txt 

# 安装virtualenv
pip install virtualenv

# 创建虚拟环境
virtualenv myenv

# 激活虚拟环境 (Linux/Mac)
source myenv/bin/activate

# 激活虚拟环境 (Windows)
myenv\Scripts\activate

# 在虚拟环境中安装包
pip install django

# 退出虚拟环境
deactivate 

# 安装: pip install requests
import requests

# ===== GET请求 =====
response = requests.get("https://api.github.com")
print(response.status_code)  # 200
print(response.json())        # 解析JSON响应

# 带参数的GET请求
params = {"q": "python", "page": 1, "per_page": 10}
response = requests.get("https://api.github.com/search/repositories",
                        params=params)
print(response.url)  # 自动编码为URL参数

# ===== POST请求 =====
# 表单数据
response = requests.post("https://httpbin.org/post",
                         data={"username": "admin", "password": "123456"})

# JSON数据 (推荐)
response = requests.post("https://httpbin.org/post",
                         json={"title": "Python教程", "content": "详细内容..."})

# ===== 请求头和Cookie =====
headers = {"User-Agent": "Mozilla/5.0", "Authorization": "Bearer xxx"}
cookies = {"session_id": "abc123"}
response = requests.get("https://api.example.com/user",
                       headers=headers, cookies=cookies)

# ===== 上传文件 =====
with open("report.xls", "rb") as f:
    files = {"file": f}
    response = requests.post("https://httpbin.org/post", files=files)

# ===== 超时设置 =====
response = requests.get("https://api.example.com", timeout=5)

# ===== 响应内容 =====
print(response.text)      # 文本内容
print(response.content)   # 二进制内容
print(response.json())    # JSON解析
print(response.headers)   # 响应头
print(response.cookies)   # Cookie
print(response.status_code) # 状态码 

# 安装: pip install psutil
import psutil

# ===== CPU信息 =====
print(f"CPU数量: {psutil.cpu_count()}")           # 逻辑CPU数量
print(f"物理CPU: {psutil.cpu_count(logical=False)}")  # 物理核心数
print(f"CPU使用率: {psutil.cpu_percent(interval=1)}%")  # 每秒刷新
print(f"CPU使用率(每个核心): {psutil.cpu_percent(interval=1, percpu=True)}")

# ===== 内存信息 =====
mem = psutil.virtual_memory()
print(f"内存总量: {mem.total / (1024**3):.2f} GB")
print(f"内存使用: {mem.used / (1024**3):.2f} GB")
print(f"内存使用率: {mem.percent}%")
print(f"可用内存: {mem.available / (1024**3):.2f} GB")

# ===== 磁盘信息 =====
print("磁盘分区:")
for partition in psutil.disk_partitions():
    print(f"  {partition.device} -> {partition.mountpoint} ({partition.fstype})")

disk = psutil.disk_usage("/")
print(f"磁盘总量: {disk.total / (1024**3):.2f} GB")
print(f"磁盘使用: {disk.used / (1024**3):.2f} GB")
print(f"磁盘使用率: {disk.percent}%")

# ===== 网络信息 =====
net = psutil.net_io_counters()
print(f"发送字节: {net.bytes_sent / (1024**2):.2f} MB")
print(f"接收字节: {net.bytes_recv / (1024**2):.2f} MB")

# ===== 进程管理 =====
print("当前进程信息:")
p = psutil.Process()
print(f"  进程名: {p.name()}")
print(f"  PID: {p.pid}")
print(f"  内存使用: {p.memory_info().rss / (1024**2):.2f} MB")
print(f"  CPU使用率: {p.cpu_percent():.1f}%")
print(f"  线程数: {p.num_threads()}")

# 遍历所有进程
for proc in psutil.process_iter(['pid', 'name'])[:5]:
    print(f"PID: {proc.info['pid']}, Name: {proc.info['name']}") 

# 安装: pip install Pillow
from PIL import Image, ImageFilter, ImageDraw, ImageFont

# ===== 基本操作 =====
img = Image.open("photo.jpg")
print(img.size, img.format, img.mode)  # (width, height), 'JPEG', 'RGB'

# 调整大小
img_resized = img.resize((800, 600))
img_resized.save("photo_resized.jpg")

# 缩略图 (保持比例)
img.thumbnail((200, 200))

# 旋转和翻转
img_rotated = img.rotate(45)           # 顺时针旋转45度
img_flipped = img.transpose(Image.FLIP_LEFT_RIGHT)  # 左右翻转

# 裁剪 (left, top, right, bottom)
img_cropped = img.crop((100, 100, 400, 300))

# ===== 图像模式转换 =====
img_gray = img.convert("L")              # 转为灰度图
img_rgba = img.convert("RGBA")           # 转为RGBA模式

# ===== 滤镜效果 =====
img_blur = img.filter(ImageFilter.BLUR)          # 模糊
img_sharp = img.filter(ImageFilter.SHARPEN)      # 锐化
img_edge = img.filter(ImageFilter.FIND_EDGES)    # 边缘检测
img_contour = img.filter(ImageFilter.CONTOUR)    # 轮廓

# ===== 绘图和文字 =====
img = Image.open("photo.jpg")
draw = ImageDraw.Draw(img)

# 画矩形
draw.rectangle([50, 50, 150, 100], outline="red", width=2)

# 画圆形
draw.ellipse([200, 50, 300, 150], fill="blue", outline="black")

# 画文字
font = ImageFont.truetype("arial.ttf", 36)
draw.text((300, 100), "Hello!", fill="white", font=font)

# 画线条
draw.line([0, 0, 100, 100], fill="green", width=3)

img.save("photo_annotated.jpg")

# ===== 创建新图像 =====
# 创建纯色图像
new_img = Image.new("RGB", (400, 300), color="white")

# 创建渐变图像
for x in range(400):
    for y in range(300):
        r = int(x / 400 * 255)
        g = int(y / 300 * 255)
        b = 128
        new_img.putpixel((x, y), (r, g, b))

# ===== 图像合成 =====
img1 = Image.open("image1.png")
img2 = Image.open("image2.png")
mask = Image.open("mask.png").convert("L")
img1.paste(img2, (50, 50), mask)  # 使用mask控制透明度 

# 安装: pip install chardet
import chardet

# 检测字节串编码
data = "你好世界".encode("utf-8")
result = chardet.detect(data)
print(result)
# {'encoding': 'utf-8', 'confidence': 0.99, 'language': ''}

# 检测文件编码
with open("document.txt", "rb") as f:
    raw_data = f.read()
    encoding = chardet.detect(raw_data)
    print(f"检测到编码: {encoding['encoding']}")
    print(f"置信度: {encoding['confidence'] * 100}%")
    content = raw_data.decode(encoding['encoding'])

# 自动读取任意编码文件
def read_file_auto_encoding(filepath):
    with open(filepath, "rb") as f:
        raw = f.read()
        detected = chardet.detect(raw)
        return raw.decode(detected['encoding'])

content = read_file_auto_encoding("unknown_encoding.txt")
print(content)