Python is a high-level programming language that is used for web development, mobile application development, and also for scraping the web.
Python is considered as the finest programming language for web scraping because it can handle all the crawling processes smoothly. When you combine the capabilities of Python with the security of a web proxy, then you can perform all your scraping activities smoothly without the fear of IP banning.
In this article, you will understand how proxies are used for web scraping with Python. But, first, let’s understand the basics.
Web scraping is the method of extracting data from websites. Generally, web scraping is done either by using a HyperText Transfer Protocol (HTTP) request or with the help of a web browser.
Web scraping works by first crawling the URLs and then downloading the page data one by one. All the extracted data is stored in a spreadsheet. You save tons of time when you automate the process of copying and pasting data. You can easily extract data from thousands of URLs based on your requirement to stay ahead of your competitors.
An example of a web scraping would be to download a list of all pet parents in California. You can scrape a web directory that lists the name and email ids of people in California who own a pet. You can use web scraping software to do this task for you. The software will crawl all the required URLs and then extract the required data. The extracted data will be kept in a spreadsheet.
Now that you have understood the basics of web scraping and proxies. Let’s learn how you can perform web scraping using a proxy with the Python programming language.
To scrape a website, you need to understand the HTML structure of the page you are trying to extract information from. You can inspect the HTML elements of a website by right-clicking on the page and selecting “Inspect Element.” This will open the developer tools in your browser and show you the HTML code behind the page.
Now that you have set up your environment and understand the HTML structure of a website, you can write the code to scrape the data you are interested in.
The first step is to send an HTTP request to the website we want to scrape. We can use the Requests library to do this as follows:
Next, you will need to parse the HTML response so that we can extract the data you are interested in. Use the BeautifulSoup library for this, as follows:
Finally, you can extract the data from the HTML response by using the find() method from the BeautifulSoup object and specifying the element you are interested in. For example, if you want to extract data from ana
Web scraping is a powerful tool for data collection, but it can also be subject to geographical restrictions. To overcome this, you can use a VPN API, such as our GeoSurf VPN API, to change your location and bypass geographical restrictions.
The following code shows how to use GeoSurf VPN API in Python to change the location for web scraping. First, set the URL of the website you want to scrape and the proxy server provided by GeoSurf VPN API. Then, set the proxy authentication credentials and create the proxy dictionary/ Next, send the request to the website using the requests library, passing it into the proxy dictionary as the proxy parameter. Finally, you will parse the HTML response using the BeautifulSoup library and extract the data you need.
# Set the URL and the proxy
URL = “http://example.com”
proxy = “us-30m.geosurf.io:8000”
# Set the proxy authentication credentials
proxy_auth = “1234+US+1234-4321:12345678”
# Create the proxy dictionary
proxy_dict = {
http”: f”http://{proxy_auth}@{proxy}”,
“https”: f”https://{proxy_auth}@{proxy}”,
}
# Send the request
response = requests.URL(url, proxies=proxy_dict)
# Parse the HTML response
soup = BeautifulSoup(response.text, “html.parser”)
# Extract the data
data = soup.find(“div”, {“class”: “data”}).text
# Print the data
print(data)
Using a VPN API like GeoSurf VPN API have several benefits for web scraping:
Dynamic websites, which rely on JavaScript and other technologies to load content, can be challenging to scrape. To handle these types of websites, you can use tools such as Selenium, which allows you to automate the browsing process and interact with dynamic content.
CAPTCHAs, or Completely Automated Public Turing tests to tell Computers and Humans Apart, are security measures used by websites to prevent automated scraping. To deal with CAPTCHAs, you can use tools such as Anti-Captcha, which provides a service to solve CAPTCHAs automatically.
Websites can ban IP addresses that make excessive requests, which can prevent you from scraping the website. To avoid IP bans, you can use a VPN API like GeoSurf VPN API to change your IP address, or you can use tools such as rotating proxies, which allow you to switch between multiple proxies.
Web scraping is a necessity for several businesses, especially eCommerce websites. Real-time data needs to be captured from a variety of sources to make better business decisions at the right time. Python offers different frameworks and libraries that make web scraping easy. You can extract data fast and efficiently. Moreover, it is crucial to use a proxy to hide your machine’s IP address to avoid blacklisting. Python along with a secure proxy should be the base for successful web scraping.
