Example of implementation of Requests library in Python

1. Introduction to the Requests library

Requests are in the Python ecosystemThe most widely used HTTP client library, with "human friendly" as the core design concept, simplifying the complexity of HTTP protocol interaction. Its core values include:

Minimalist API:pass()、post()Equal functions implement complex network operations, with a larger amount of code than nativeurllibReduced by more than 70%.
Full agreement support: Overwrite mainstream HTTP methods such as GET, POST, PUT, DELETE, and adapt to RESTful API, WebSocket and other scenarios.
Efficient and stable: Built-in connection pool multiplexing, automatic retry, timeout control and other mechanisms, supporting 1000+ times high concurrent requests per second.
Eco-compatibility: Seamless dockingBeautifulSoup(Web page analysis),Pandas(Data processing),Flask(Service Testing) and other tool chains.

2. Installation and environment configuration

# Basic installation (Python 3.7+ environment)pip install requests  

# Domestic mirroring accelerated installationpip install -i /simple requests

Verify installation：

import requests  
print(requests.__version__)  # Output example：2.31.0

3. Core functions and common functions

1. HTTP basic request method

function	Function description	Sample code
()	Send a GET request (data acquisition scenario)	response = ("")
()	Send a POST request (form submission/API call)	("/post", data={"key": "value"})
()	Send PUT request (resource update)	("/data/1", json={"name": "Kimi"})
()	Send a DELETE request (resource deletion)	("/data/1")
()	Create session objects (make the cookies and TCP connections multiplexed to improve performance)	with () as s: ("")

2. Request parameters and customization

Query parameter passing：

params = {"q": "Python", "page": 2}  
response = ("", params=params)

Generate URL:?q=Python&page=2

Request header customization：

headers = {"User-Agent": "Mozilla/5.0", "Authorization": "Bearer YOUR_TOKEN"}  
("", headers=headers)

Simulate browser behavior or authentication

JSON Data Submission：
```
("/login", json={"username": "admin", "password": "secret"})  
```
Automatic settingContent-Type: application/json

3. Response processing and analysis

Properties/Methods	Function description	Sample code
response.status_code	Get the HTTP status code (such as 200 means successful, 404 resource not found)	if response.status_code == 200: print("Success")
****	Get the response content (automatically decode text, such as HTML/XML)	print([:500]) # Intercept the first 500 characters
()	Parsing the JSON response to a Python dictionary or list	data = (); print(data["temperature"])
****	Get response header information (such as server type, cache policy)	print(["Content-Type"])
response.raise_for_status()	Automatically throw an exception (triggered when the status code is not 200)	try: response.raise_for_status() except : ...

4. Advanced features

File upload and download：

# Upload filefiles = {"file": open("", "rb")}  
("/upload", files=files)[4,6](@ref)  

# Streaming large fileswith ("/large_video.mp4", stream=True) as r:  
    with open("video.mp4", "wb") as f:  
        for chunk in r.iter_content(chunk_size=8192):  
            (chunk)

Timeout and retry strategy：

from  import HTTPAdapter  
from  import Retry  

retry = Retry(total=3, backoff_factor=1, status_forcelist=[500, 502, 503])  
adapter = HTTPAdapter(max_retries=retry)  
session = ()  
("https://", adapter)  
("", timeout=5)  # time out5Second，Try again3Second-rate[4,6](@ref)

4. Application scenarios and practical cases

Data collection and crawling：
- Crawl the news title:() + BeautifulSoupParse HTML
- Dynamic content loading: CooperateSeleniumProcessing JavaScript rendering pages
API Integrated Development：
- Call the weather interface:("?city=Beijing")
- Docking ChatGPT: Send a JSON request and process streaming responses
Automated testing：
- Verification REST API functionality: Assert response status code and data format
- Stress test: Multi-threaded concurrent sending requests (need to be combined）
Enterprise-level applications：
- Financial statement batch download: session hold + timing tasks
- Cross-system data synchronization: OAuth authentication + POST/PUT method

5. Precautions and optimization techniques

Safety Specifications：
- Sensitive data (such as API Key) avoids hard coding and uses environment variable management
- Enable HTTPS and verify the certificate:verify=True(default)
Performance Tuning：
- ReuseSessionObject reduction TCP handshake overhead
- Set reasonable timeout:timeout=10Prevent blocking of the main thread

Exception handling：

try:  
    response = (url, timeout=5)  
    response.raise_for_status()  
except :  
    print("Request timeout")  
except :  
    print("Network connection failed")

This is the end of this article about the implementation example of the Requests library in Python. For more related content of the Python Requests library, please search for my previous articles or continue browsing the related articles below. I hope everyone will support me in the future!