Tips & How tos

5 Best Tricks for Scraping With Python Requests Library 

Scraping data has become a crucial part of any business. Every company seeks a reliable way to scrape useful online data, from monitoring competitor prices to market analysis. 

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Python users rely on the Requests library to send requests, customize them, inspect the data, and configure their requests. 

If you’re a relatively new Python user, you must know your way around the Python Requests library to use it to the maximum. Apart from outlining the general features, we’ll share some tips to scrape data efficiently with the Requests library. 

What Is The Requests Library and How Does It Work? 

The python Requests library is used to make HTTP requests in Python. Although numerous libraries enable HTTP requests, not all simplify it like the Requests library. 

Its elegant and straightforward API overcomes the complications of making HTTP requests and makes data consumption easier. 

Using this library, you can retrieve, update, delete, and post the data for a specific URL. 

Besides, it also handles sessions and cookies and makes web scraping hassle-free. Further, the authentication module support of the library makes your tasks more secure and convenient. Click here for a more in-depth technical tutorial or read on to grasp the basics. 

Steps Needed To Make an HTTP Request 

You must complete some prerequisites to make an HTTP request using Requests in Python. Here are some steps to keep in mind. 

Install Python 

To begin with, you must install Python on your operating system. Various Python versions are available on the official website; you can install one per your liking. We recommend downloading the latest version to utilize newer features.

Understand the HTTP Requests

HTTP requests indicate the working of the web. When you search a web page, your browser sends various requests to the server. The server then responds with the needed data by displaying the page, and your browser renders it for you to see. 

Request methods are part of the data sent by the client in a request. Popular request methods include GET, POST, and PUT. 

Download Python Requests 

Lastly, you have to install Python requests. Initiate the following command to download it: 

$ pip install requests

Once the library downloads, you’re all set to explore it. 

Top 5 Tips to Start Using Python Requests Library for Web Scraping

Because the Python Requests library is meant to simplify your task, it shouldn’t be the other way around. Here are a few tips that’ll ensure an easier process. 

Make Your First Request 

Create a file script.py to make your first request. Then, add the following code: 

import requests

res = requests.get()

print(res)

You can add the desired URL in the brackets. Although you used .get() here, the library allows you to use .put() and >post(), too. 

You can run them by using the same script.py file. 

The output generated would be the response that you need to understand. 

Understand the Status Codes 

Understanding codes is crucial to ensure a successful request. Standard status codes include 404, 200, and 500. However, HTTP codes can be anything from 1XX to 5XX. Here’s what they mean. 

  • 5XX – the server made an error
  • 4XX – An error on your behalf (Client error)
  • 3XX – Redirect 
  • 2XX – Success
  • 1XX – Information 

When you make your request, you’re typically looking for status codes in the 200s. The Request detects 5XX and 4XX as errors, and when those status codes return, the request appears False. 

You can always check if the request response was successful or not. Response OK signifies a successful response, while Response Failed tells otherwise. 

The latter only shows up when 500 or 400 error code returns. 

Learn About Headers and Response Text

Headers are what you receive from the response. You can always check the headers dictionary to check them. 

Generate the command print(res.headers), and the output will display on the screen. 

Headers are forwarded with the request and sent back in response. They help the user and server understand the data being forwarded and received. 

Lastly, the response text that appears as res.text generates the final output. It will display the HTML. Once you download and open the file, you’ll be able to see the retrieved data. 

Know the Rules 

While understanding the operation of Requests library works is essential, you must also know the rules when scraping a website. 

Each website has a robots.txt on its domain. It states what the scrapers and bots can do on a particular website. 

The User-agent field displays the bot name and rules the bot must comply with. Make sure you scrape the web ethically and respect the site’s privacy. 

Consider Using Proxies 

Proxies help speed up web scraping by masking your IP address. Because sites do not like receiving multiple requests from the same user, you may get blocked. 

Proxies, however, eliminate the trouble by changing your IP with each request. This allows for efficient scraping using the Requests library. 

Conclusion

Python Requests library offers a simple way to make requests, receive responses, and translate the text. The sophisticated API of the library makes it well-liked among Python developers. 

You can simplify your web scraping tasks and other related projects using it.