python中httpx库的详细使用及案例-EW帮帮网

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httpx 是一个现代化的 Python HTTP 客户端库，支持同步和异步请求，功能强大且易于使用。它比 requests 更高效，支持 HTTP/2 和异步操作。以下是 httpx 的详细使用方法：

1. 安装 httpx

首先，确保已经安装了 httpx。可以通过以下命令安装：pip install httpx

如果需要支持 HTTP/2，可以安装额外依赖：pip install httpx[http2]

2. 同步请求

发送 GET 请求

import httpx

# 发送 GET 请求
response = httpx.get('https://httpbin.org/get')
print(response.status_code)  # 状态码
print(response.text)         # 响应内容

发送 POST 请求

# 发送 POST 请求
data = {'key': 'value'}
response = httpx.post('https://httpbin.org/post', json=data)
print(response.json())  # 解析 JSON 响应

设置请求头

headers = {'User-Agent': 'my-app/1.0.0'}
response = httpx.get('https://httpbin.org/headers', headers=headers)
print(response.json())

设置查询参数

params = {'key1': 'value1', 'key2': 'value2'}
response = httpx.get('https://httpbin.org/get', params=params)
print(response.json())

处理超时

try:
    response = httpx.get('https://httpbin.org/delay/5', timeout=2.0)
except httpx.TimeoutException:
    print("请求超时")

3. 异步请求

httpx 支持异步操作，适合高性能场景。

发送异步 GET 请求

import httpx
import asyncio

async def fetch(url):
    async with httpx.AsyncClient() as client:
        response = await client.get(url)
        print(response.text)

asyncio.run(fetch('https://httpbin.org/get'))

发送异步 POST 请求

async def post_data(url, data):
    async with httpx.AsyncClient() as client:
        response = await client.post(url, json=data)
        print(response.json())

asyncio.run(post_data('https://httpbin.org/post', {'key': 'value'}))

并发请求

async def fetch_multiple(urls):
    async with httpx.AsyncClient() as client:
        tasks = [client.get(url) for url in urls]
        responses = await asyncio.gather(*tasks)
        for response in responses:
            print(response.text)

urls = ['https://httpbin.org/get', 'https://httpbin.org/ip']
asyncio.run(fetch_multiple(urls))

4. 高级功能

使用 HTTP/2

# 启用 HTTP/2
client = httpx.Client(http2=True)
response = client.get('https://httpbin.org/get')
print(response.http_version)  # 输出协议版本

文件上传

files = {'file': open('example.txt', 'rb')}
response = httpx.post('https://httpbin.org/post', files=files)
print(response.json())

流式请求

# 流式上传
def generate_data():
    yield b"part1"
    yield b"part2"

response = httpx.post('https://httpbin.org/post', data=generate_data())
print(response.json())

流式响应

# 流式下载
with httpx.stream('GET', 'https://httpbin.org/stream/10') as response:
    for chunk in response.iter_bytes():
        print(chunk)

5. 错误处理

httpx 提供了多种异常类，方便处理错误。

处理网络错误

try:
    response = httpx.get('https://nonexistent-domain.com')
except httpx.NetworkError:
    print("网络错误")

处理 HTTP 错误状态码

response = httpx.get('https://httpbin.org/status/404')
if response.status_code == 404:
    print("页面未找到")

6. 配置客户端

可以通过 httpx.Client 或 httpx.AsyncClient 配置全局设置。

设置超时

client = httpx.Client(timeout=10.0)
response = client.get('https://httpbin.org/get')
print(response.text)

设置代理

proxies = {
    "http://": "http://proxy.example.com:8080",
    "https://": "http://proxy.example.com:8080",
}
client = httpx.Client(proxies=proxies)
response = client.get('https://httpbin.org/get')
print(response.text)

设置基础 URL

client = httpx.Client(base_url='https://httpbin.org')
response = client.get('/get')
print(response.text)

7. 结合 Beautiful Soup 使用

httpx 可以与 Beautiful Soup 结合使用，抓取并解析网页。

import httpx
from bs4 import BeautifulSoup

# 抓取网页
response = httpx.get('https://example.com')
html = response.text

# 解析网页
soup = BeautifulSoup(html, 'lxml')
title = soup.find('title').text
print("网页标题:", title)

8. 示例：抓取并解析网页

以下是一个完整的示例，展示如何使用 httpx 抓取并解析网页数据：

import httpx
from bs4 import BeautifulSoup

# 抓取网页
url = 'https://example.com'
response = httpx.get(url)
html = response.text

# 解析网页
soup = BeautifulSoup(html, 'lxml')

# 提取标题
title = soup.find('title').text
print("网页标题:", title)

# 提取所有链接
links = soup.find_all('a', href=True)
for link in links:
    href = link['href']
    text = link.text
    print(f"链接文本: {text}, 链接地址: {href}")

9. 注意事项

性能：httpx 的异步模式适合高并发场景。

兼容性：httpx 的 API 与 requests 高度兼容，迁移成本低。

HTTP/2：如果需要使用 HTTP/2，确保安装了 httpx[http2]。

通过以上方法，可以使用 httpx 高效地发送 HTTP 请求，并结合其他工具（如 Beautiful Soup）实现数据抓取和解析。

python中httpx库的详细使用及案例