Python 网络请求利器：requests 包详解与实战
诸神缄默不语-个人技能博文与视频目次一、前言
在举行网络编程或爬虫开辟时，我们经常须要向网页或服务器发送 HTTP 请求，获取数据。这时，requests 包无疑是最受接待、最简便易用的 Python 库之一。
相比原生的 urllib 模块，requests 提供了更人性化的 API，更容易上手，险些成为了网络请求的“标准库”。
本文将介绍 requests 的基本用法、进阶操纵以及常见问题处置惩罚，配合实际代码演示，带你快速把握这个神器！
https://httpbin.org/是一个简单的用来模拟各种HTTP服务请求的网站，以下很多代码示例都会用这个网站的链接来实现。
因为这个网站部署在海外，以是大概会出现网络访问的问题，可以通过部署到当地来解决。部署到当地可以参考官方教程，大概这篇博文：五、接口测试 — Httpbin介绍（请求调试工具） - 知乎
二、安装方式
pip install requests
三、基本使用
关于get请求和post请求的区别请参考我撰写的另一篇博文：Web应用中的GET与POST请求详解
1. 发起 GET 请求
import requests
response = requests.get('https://httpbin.org/get')
print(response.status_code) # 状态码
print(response.text) # 响应内容（字符串）
print(response.json()) # 如果是 JSON，解析成字典
2. 发起 POST 请求
payload = {'username': 'test', 'password': '123456'}
response = requests.post('https://httpbin.org/post', data=payload)
print(response.json())
四、requests请求调用常用参数
1. URL
就是第一个参数，网站的链接地点
2. 数据data
请求携带的数据。
如果值是字符串或字节流，默认不设置Content-Type会设置。
如果值是字典、元组构成的列表或列表对象，会默认Content-Type会设置为application/x-www-form-urlencoded，也就是HTML表单形式的键值对数据。（对Content-Type的详细介绍请见下一节headers参数）
import requests
import json
payload = {"key1": "value1", "key2": "value2"}
# String payload in json format
r = requests.post("https://httpbin.org/post", data="a random sentence")
print(r.json())
print(r.json()["headers"].get("Content-Type","None"))
# String payload in json format
r = requests.post("https://httpbin.org/post", data=json.dumps(payload))
print(r.json())
print(r.json()["headers"].get("Content-Type","None"))
# String payload in json content type
r = requests.post(
"https://httpbin.org/post",
data=json.dumps(payload),
headers={"Content-Type": "application/json"},
)
print(r.json())
print(r.json()["headers"].get("Content-Type","None"))
# Dictionary payload
r = requests.post("https://httpbin.org/post", data=payload)
print(r.json())
print(r.json()["headers"].get("Content-Type","None"))
# List of tuples payload
payload_tuples = [("key1", "value1"), ("key2", "value2")]
r = requests.post("https://httpbin.org/post", data=payload_tuples)
print(r.json())
print(r.json()["headers"].get("Content-Type","None"))
# Bytes payload
payload_bytes = "key1=value1&key2=value2".encode("utf-8")
r = requests.post("https://httpbin.org/post", data=payload_bytes)
print(r.json())
print(r.json()["headers"].get("Content-Type","None"))
3. 请求头 headers
一样平常会携带请求的Content-Type、体系信息（如使用的设备、编码方式等）、认证信息、时间戳等
headers = {'User-Agent': 'MyUserAgent/1.0'}
response = requests.get('https://httpbin.org/headers', headers=headers)
print(response.json())
Content-Type的常见范例：
https://i-blog.csdnimg.cn/direct/be1eecfecef14610aa581632bb83005d.png
（图源1）
4. 参数 params
这个在get请求中的效果就类似于直接在URL后面加?k=v
params = {'q': 'python'}
response = requests.get('https://httpbin.org/get', params=params)
print(response.url)# 实际请求的完整 URL
输出：https://httpbin.org/get?q=python
5. 超时时间 timeout
response = requests.get('https://httpbin.org/delay/3', timeout=2)
如果超过2秒没相应，会抛出 requests.exceptions.Timeout 异常。
6. 文件上传 file：上传纯文本文件流
files = {'file': open('test.txt', 'rb')}
response = requests.post('https://httpbin.org/post', files=files)
print(response.text)
↑ 须要注意的是虽然file参数确实可以直接这么传文件流……但我没咋见过真这么干的。
一样平常纯文本不用file传，一样平常都直接塞data里面带过去。
非纯文本文件流（二进制字节流），我一样平常看比较多的传输方式是把字节流转换为base64编码塞到data里带。用base64编码的代码可参考我写的另一篇博文：深入理解 Python 的 base64 模块
（不过说实话直接用file参数传文件流好像实际上背后也颠末了base64编码-解码的过程，但是大家都这么干肯定有大家的原理）
7. json
用json参数传JSON对象（在Python 3中表现为字典对象）就相当于用data参数传JSON对象、然后表现设置Content-Type为application/json
payload = {'id': 1, 'name': 'chatgpt'}
response = requests.post('https://httpbin.org/post', json=payload)
print(response.json())
上面这个请求和下面这个请求是一样的：
response = requests.post(
"https://httpbin.org/post",
data=json.dumps(payload),
headers={"Content-Type": "application/json"},
)
print(response.json())
作为对比可以看看别的两种请求参数格式的效果（可以注意到第一种写法返回的data和json值好歹还是一样的，第二种写法的话对象就放到form里了，因为是以表单对象形式来解析的）：
response = requests.post(
"https://httpbin.org/post",
data=json.dumps(payload)
)
print(response.json())
response = requests.post(
"https://httpbin.org/post",
data=payload
)
print(response.json())
五. 相应的属性和函数
1. 属性：headers、cookies、编码格式
r = requests.get('https://httpbin.org/get')
print(r.headers)
print(r.cookies)
print(r.encoding)
2. 异常处置惩罚：raise_for_status()
如果status_code不是200就报错
六、Session 会话对象（保持登录态）
requests.Session() 可以模拟保持会话，得当须要登录认证的网站。
s = requests.Session()
s.post('https://httpbin.org/cookies/set', data={'cookie': 'value'})
response = s.get('https://httpbin.org/cookies')
print(response.text)
七、进阶用法
1. 上传压缩文件
[*]gzip实现import requests
import gzip
import json
data = json.dumps({'key': 'value'}).encode('utf-8')
compressed_data = gzip.compress(data)
headers = {'Content-Encoding': 'gzip'}
response = requests.post('https://httpbin.dev/api', data=compressed_data, headers=headers)
response.raise_for_status()
print("Gzip Compressed Request Status:", response.status_code)
[*]brotli实现import requests
import brotli
data = json.dumps({'key': 'value'}).encode('utf-8')
compressed_data = brotli.compress(data)
headers = {'Content-Encoding': 'br'}
response = requests.post('https://httpbin.dev/api', data=compressed_data, headers=headers)
response.raise_for_status()
print("Brotli Compressed Request Status:", response.status_code)
2. 并发
[*]httpx实现（泉源于Concurrency vs Parallelism）import asyncio
import httpx
import time
# Asynchronous function to fetch the content of a URL
async def fetch(url):
async with httpx.AsyncClient(timeout=10.0) as client:
response = await client.get(url)
return response.text
# Concurrently fetch multiple URLs using asyncio.gather
async def concurrent_fetch(urls):
tasks =
return await asyncio.gather(*tasks)
# Synchronous version to demonstrate performance difference
def sync_fetch(urls):
results = []
for url in urls:
response = httpx.get(url)
results.append(response.text)
return results
def run_concurrent():
urls = ["http://httpbin.org/delay/2"] * 100# Use the same delay for simplicity
start_time = time.time()
# Running fetch requests concurrently
asyncio.run(concurrent_fetch(urls))
duration = time.time() - start_time
print(f"Concurrent fetch completed in {duration:.2f} seconds")
def run_sync():
urls = ["http://httpbin.org/delay/2"] * 100# Use the same delay for simplicity
start_time = time.time()
# Running fetch requests synchronously
sync_fetch(urls)
duration = time.time() - start_time
print(f"Synchronous fetch completed in {duration:.2f} seconds")
if __name__ == "__main__":
print("Running concurrent version:")
# Concurrent fetch completed in 2.05 seconds
run_concurrent()
print("Running synchronous version:")
# Synchronous fetch completed in 200.15 seconds
run_sync()
[*]threading实现import threading
import requests
def post_data(data):
requests.post('https://httpbin.dev/api', json=data)
# Sample data list
data_list = [{'name': 'User1'}, {'name': 'User2'}]
threads = []
for data in data_list:
thread = threading.Thread(target=post_data, args=(data,))
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
关于并发的相关知识也可以参考我写的另一篇博文：Python中的并发与并行
七、常见异常
1. requests.exceptions.JSONDecodeError
如果response带的报文不是JSON，还调用response.json()函数，会报requests.exceptions.JSONDecodeError错误，完整的报错信息类似如许：
Traceback (most recent call last):
File "myenv_path\Lib\site-packages\requests\models.py", line 974, in json
return complexjson.loads(self.text, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\json\__init__.py", line 346, in
loads
return _default_decoder.decode(s)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\json\decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\json\decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "tryrequests1.py", line 6, in <module>
print(response.json()) # 如果是 JSON，解析成字典
^^^^^^^^^^^^^^^
File "myenv_path\Lib\site-packages\requests\models.py", line 978, in json
raise RequestsJSONDecodeError(e.msg, e.doc, e.pos)
requests.exceptions.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
2. requests.exceptions.Timeout
期待请求返回结果的时长超过了timeout参数设置的时长。
3. requests.exceptions.ProxyError: HTTPSConnectionPool
访问URL失败。
偶尔候网络服务不稳定是临时的，直接重试频频就行。重试的计谋可以参考我撰写的另一篇博文：Python3：在访问不可靠服务时的重试计谋（持续更新ing…）
一个典型的由于临时的网络不稳定而产生的访问失败报错输出全文：
Traceback (most recent call last):
File "myenv_path\Lib\site-packages\urllib3\connectionpool.py", line 789, in urlopen
response = self._make_request(
^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\site-packages\urllib3\connectionpool.py", line 536, in _make_request
response = conn.getresponse()
^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\site-packages\urllib3\connection.py", line 507, in getresponse
httplib_response = super().getresponse()
^^^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\http\client.py", line 1374, in getresponse
response.begin()
File "myenv_path\Lib\http\client.py", line 318, in begin
version, status, reason = self._read_status()
^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\http\client.py", line 287, in _read_status
raise RemoteDisconnected("Remote end closed connection without"
http.client.RemoteDisconnected: Remote end closed connection without response
The above exception was the direct cause of the following exception:
urllib3.exceptions.ProxyError: ('Unable to connect to proxy', RemoteDisconnected('Remote end closed connection without response'))
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "myenv_path\Lib\site-packages\requests\adapters.py", line 667, in send
resp = conn.urlopen(
^^^^^^^^^^^^^
File "myenv_path\Lib\site-packages\urllib3\connectionpool.py", line 843, in urlopen
retries = retries.increment(
^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\site-packages\urllib3\util\retry.py", line 519, in increment
raise MaxRetryError(_pool, url, reason) from reason# type: ignore
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='httpbin.org', port=443): Max retries exceeded with url: /cookies (Caused by ProxyError('Unable to connect to proxy', RemoteDisconnected('Remote end
closed connection without response')))
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "tryrequests1.py", line 5, in <module>
response = s.get('https://httpbin.org/cookies')
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\site-packages\requests\sessions.py", line 602, in get
return self.request("GET", url, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\site-packages\requests\sessions.py", line 589, in request
resp = self.send(prep, **send_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\site-packages\requests\sessions.py", line 703, in send
r = adapter.send(request, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "myenv_path\Lib\site-packages\requests\adapters.py", line 694, in send
raise ProxyError(e, request=request)
requests.exceptions.ProxyError: HTTPSConnectionPool(host='httpbin.org', port=443): Max retries exceeded
with url: /cookies (Caused by ProxyError('Unable to connect to proxy', RemoteDisconnected('Remote end closed connection without response')))
八、实战案例：爬取豆瓣电影 Top250（示例）
import requests
from bs4 import BeautifulSoup
headers = {'User-Agent': 'Mozilla/5.0'}
for start in range(0, 250, 25):
url = f'https://movie.douban.com/top250?start={start}'
r = requests.get(url, headers=headers)
soup = BeautifulSoup(r.text, 'html.parser')
titles = soup.find_all('span', class_='title')
for title in titles:
print(title.text)
本文撰写过程中参考的其他网络资料
[*]What is the difference between the ‘json’ and ‘data’ parameters in Requests? | WebScraping.AI
[*]python requests.post() 请求中 json 和 data 的区别 - 小嘉欣 - 博客园
[*]Python requests.post()方法中data和json参数的使用_requests.post中data和json是否可以同时设置-CSDN博客
https://i-blog.csdnimg.cn/direct/a8db606d157b4a648deda5a3b93501c5.jpeg
[*]Python requests POST ↩︎
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