Data scraping Python is one of the most fundamental factors in the development of machine learning algorithms recently. With the excellent libraries that the Python programming language provides to the developers and the unmatched code development speed, Python data scraping is developed as a separate application in many businesses, not just machine learning. For example, e-commerce applications scrape price information to follow the pricing policies of their competitors.
These processes, which took time to perform in the past, are now performed with a proxy web scraper API with only a single API call. This is actually an incredible process that has evolved from hours or even days to mere seconds. Python data scraping API applications are used in almost every domain in terms of speed and usability today. In this article, we will tell you why a developer should choose the proxy web scraping API in a web scraping process. Next, we’ll list the most popular web scraping APIs today and integrate a web scraping API into the Python programming language.
Why Should Developers Use a Proxy Web Scraping API for a Web Scraping Project?
It is highly advantageous for developers to use a web scraping API with a proxy pool for a web scraping project. Some of the benefits this API provides to developers are as follows:
- Bypassing IP Blocking Measures: Websites can use IP blocking measures to block excessive traffic or repetitive data acquisition attempts. A web scraping API using a proxy changes the IP address of developers regularly, allowing them to bypass these blocks and keep developers accessing the website.
- Bypass Geographical Restrictions: Some websites may restrict access from certain regions or geographically limit the content on the website. A web scraping API using a proxy allows developers to bypass these restrictions quite easily using proxy servers in different geographic locations.
- Data Privacy and Anonymity: Using a web scraper API with proxy hides the real IP address of the developers. Thus, it provides developers with anonymity in their data scraping. This makes it difficult for the website to track your data withdrawals and ensures confidentiality.
Learn more about the benefits of using proxies for Python web scraping.
Best Web Scraping API List
If developers and businesses plan to extract data from the internet with a web scraping API, they should do so with a good web scraping API. Many web scraping APIs today do not offer their users services such as proxy service, JavaScript rendering, flexible pricing, and integration with multiple programming languages.
Below you can find the most popular web scraping APIs that many developers and businesses use:
- Zenscrape API
- Zenserp API
- ScraperAPI
- ScrapingBee API
- Apify
- Scrape.do API
- Scrape-it.cloud API
- Abstract Web Scraping API
How to Develop Python Web Scraping Application With the Zenscrape API?
In this section, we will develop a Python web scraping application with the Zenscrape API in just a few steps. This will actually be a Python web scraping tutorial. With this application, we will get the HTML code of the website ‘https://example.org/‘ from the Zenscrape API. After scraping data, we can store this HTML code in a CSV file and perform analysis on this data in the future.
Before we start developing the application, we will sign up for one of the flexible-priced subscription plans that Zenscrape offers and we will get an API key.
After obtaining the API key, let’s create a Python file and name it ‘python-web-scraper-with-zenscrape-api.py’. Now, we can copy and paste the following codes into the file we have created.
import requests
headers = {
"apikey": "YOUR-API-KEY"}
params = (
("url","https://example.org/"),
("premium","true"),
("country","de"),
("render","true"),
);
response = requests.get('https://app.zenscrape.com/api/v1/get', headers=headers, params=params);
print(response.text)With this code, we will collect data from the target website. Before starting the application, let’s paste the API key we obtained after registration in the ‘YOUR-API-KEY’ field and run the application with the following command
python python-web-scraper-with-zenscrape-api.pyAfter running the application, the HTML document we obtained from the target website is as follows:
Conclusion
All in all, opting for a web scraping API that uses a proxy for web scraping gives developers many advantages. Security, automated processes, and anonymity are just a few of them. By using the proxy web scraping API with Python, developers can stay ahead of their competitors and improve their marketing strategies in terms of rapid code development and code analysis.
FAQs
Q: What are the Advantages of Data Scraping Python?
A: Data scraping is the process of automatically collecting data from websites. There are many advantages for developers to be able to perform this operation with Python code. Some of the advantages of Python web scraper for developers are as follows:
- Convenience and Rapid Development
- Rich Python Web Scraping Libraries
- Multiple Sources for Web Scraping Python Tutorial
- Multi-Platform Support
- Community Support
Q: What are the Challenges of Extracting Data From a Web Page?
A: Developers can extract data from multiple web pages today. However, there may be some difficulties faced by developers in these processes. The first is the HTML complexity on the target websites that the developers will scrape, then the captcha and anti-bot measures on the target website. Finally, IP blocking.
Q: What are Some Popular Web Scraping APIs?
There are many web scraping APIs in the market today. Not all of these APIs allow users to create automated processes and are not secure. Some of the most reliable and best web scraping APIs in the market are as follows:
- Zenscrape API
- Zenserp API
- ScraperAPI
- ScrapingBee API
- Apify
Q: What are the Benefits of a Web Scraping API Having a Proxy Pool?
A: A web scraping API can scrape data from almost every web page. It’s not enough for a web scraping API to just have a good software architecture to make it happen. Thanks to the proxy pool, web scraping APIs obtain data from target websites in a confidential, fast, and efficient manner. Thanks to the proxy, the developers protect their anonymity and obtain data without being noticed by the target website.
