The Ultimate Guide To Make Money With Web Scraping Using Python And Residential Proxies

Opportunities for making money online abound, each with varying difficulty and likelihood of success. Some methods require a substantial investment in time and startup funds, for making money online. Others require a little know-how and a computer. You’ll learn how to make money with web scraping using Python in this article.

One of the ways of how to make money with web scraping using Python is by web scraping public websites for data. This can be done in several ways including using open-source software, buying a hosted web scraping product, or programming your own with Python and using proxies, which you can resell for profit (explained later in this article).

 

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What Is Web Scraping With Python?

What Is Web Scraping With Python?

A wide range of businesses can use information publicly available on websites for various reasons. Data can be collected, analyzed, saved, and used for research and development purposes.

The data collected could be used to:

  • Set prices of products based on competitors’ prices
  • Find keywords that other companies are using
  • Calculate a competitor’s average shipping costs
  • Analyze public sentiments on social media
  • Identify market trends and patterns
  • Monitor competitor activity
  • Research product reviews or client testimonials
  • Gather contact information for lead generation
  • Analyze financial data such as stock price fluctuations
  • Monitor property listings or average real estate prices

These are just a few examples of what could be done with the data and are are big element of how to make money with web scraping using Python. The specific use of data and the type of sites analyzed would change depending on the type of business. The problem is businesses need to collect large amounts of data from a large number of sites.

Scraping dynamic web pages with Python is one method for collecting large amounts of data from many web pages. Python was designed to make object-oriented programs readable. It also allows programmers to write programs in fewer lines of code. The language also makes heavy use of an extensive list of libraries and frameworks with already-written code to make programming easier and quicker.

Programs can be run with Python that automatically opens URLs and saves the data from the web pages. This saves a tremendous amount of time and effort because, without automated software, you’d have to open each page you want data from and save the data manually.

To scrape the web, you would choose one of several methods: purchasing a hosted web scraper program, using an open-source web scraper, or programming a web scraper yourself using a programming language such as Python and one of several web scraping libraries.

To stay within the law and to collect data ethically means collecting data that is available to the public on public HTML pages. That means avoiding attempting to collect private data or data behind password-protected accounts. Be sure to only use web scraping ethically and for legal purposes.

How To Do Web Scraping With Python?

How To Do Web Scraping With Python?

Before learning about how to make money with web scraping using Python, you’re going to need to know some of the technical details about how the web scraping process is done. To make your scraper from scratch — as opposed to buying a web scraper — you’ll need a small amount of programming aptitude but it’s not too difficult. Python is known as a very beginner-friendly programming language, and there are in-depth tutorials online if you get stuck.

This is the Python web scraping process:

  1. Choose the type of data you want to scrape, such as the prices of the products of your competitors.
  2. Download and install the latest version of Python.
  3. Open your integrated development environment (IDE) such as Visual Code Studio.
  4. Import web scraping libraries such as Scrapy.
  5. Select a browser to open the web pages you want to scrape, such as Chrome—the browser could be “headless,” with no user interface for faster browsing.
  6. Define objects including a page source object and results object.
  7. Run the page source object through the web scraper class.
  8. Extract the data you want from the HTML pages.
  9. Export the data into a .csv file to analyze and read with a spreadsheet program.

If you don’t want to go through the coding and technical steps, you can always either hire a freelance programmer to do it for you on places such as Upwork. Further, you could buy an off-the-shelf web scraper that is ready to start scraping. This web scraper could be downloaded to your desktop or used in a browser. The other option is to use a hosted web scraper that you can use in the cloud.

Best Python Module For Web Scraping

Though you can purchase a web scraper, this article assumes you are using Python to do your web scraping. For that, you could either code every line of code needed for crawling the web and scraping data, or you could use a library. A library is a collection of code that is already written. Programming languages such as Python make extensive use of frameworks and libraries. That is one reason why Python is so easy to use and learn—libraries take a lot of the work out of programming.

Scrapy is one of the most popular web scraping libraries. However, there are numerous other web scraping libraries as well, such as BeautifulSoup, Requests, and Selenium. One of the reasons Scrapy is the best is that it is fully free and open-source, meaning the code is made readily available for you to use right away, without a paywall.

Scrapy is a collaborative and open-source framework for scraping web pages. With Scrapy, you can build and run web spiders and deploy them on the cloud. It works by making requests to URLs that are defined in the program. Then, it loops through the elements of data you want from a page using a CSS selector. It can make requests asynchronous. That is, it can make lots of requests simultaneously, making Scrapy a very fast web scraper.

How To Use Proxy With Requests Python Library

How To Use Proxy With Requests Python Library

If you’re going to be web scraping from a single IP address, websites can detect that you’re scraping and may block your IP address. The workaround is to use a proxy to scrape websites with many rotating IP addresses.

This is a way to mask your IP address. So, the website doesn’t block you. This lets you scrape numerous websites for large amounts of data. Proxies provide you with a layer of security and anonymity that you can’t afford to skip when web scraping. With proxies, the chance of websites blocking you when scraping large amounts of data at once is much less.

Python Requests is a popular library that lets developers send automated HTTP requests to collect data from the HTML or XML of websites such as page contents, cookies, headers, and other data. Using a proxy means hiding your IP behind a proxy server while using the Python Requests library. This will help make your scraping much more secure and anonymous and lets you bypass censorship and filters as well.

To use a proxy with Python Requests, you would:

  1. Have a proxy server with an HTTP address that you can put in the code.
  2. Make sure to have the latest version of Python installed.
  3. Import the requests package.
  4. Put the address and port number of your proxy server in the code.
  5. Put your username and password in the code if the proxy server requires it.

The above list is one basic and simplified example of using libraries in your web scraper code to work with proxies. You would need some code for the program, which isn’t too difficult to find examples of. In the code, you would make sure to replace the address and port number. So, you use your proxy server.

If you don’t have a proxy server already at this point, there are proxies readily available to you. For example, Rayobyte offers residential proxies to help you hide your IP when web scraping. Rayobyte, one of the largest American proxy providers, has over 300,000 data center IP addresses and offers status, shared, or rotating IP addresses.

You’ve learned the technical details of web scraping. Now, you’re going to want to know how to make money with web scraping using Python.

How to Make Money With Web Scraping Using Python

How to Make Money With Web Scraping Using Python

After learning how to use Python to do web scraping, some of the questions you may have is “How can I make money with Python?” or more specifically “How to make money with web scraping using Python?” If you’re entrepreneurial, you may have thought about how you can profit from scraping the web and using proxies to hide your IP address while doing so.

Using Python and proxies to make money online may be one of the easier ways how to make money with web scraping using Python once you learn a little bit of coding and have your programs set up. Much of the code in the programs you may write has already been written and can be freely used.

Taking advantage of proxies is also easy to do, even for most non-programmers. You just have to write the proxy information into your code. So, your program cycles through the proxies to hide your IP address. Once you have a proxy, you can input the username and password, if required, and provide the address and port number of the proxy. So, the program hides your IP address.

Reselling proxies

But how to make money with web scraping using Python and proxies? One way to make money is by reselling proxies. You can do this by becoming a vetted reseller and acquiring proxies directly from a provider such as Rayobyte in the form of data center IPs, residential proxies, or ISP IPs that can be purchased in bulk. By reselling these proxies and offering your clients high-quality IPs, you can get repeat orders and continue growing your business.

To resell proxies on your website, you could use an API from Rayobyte. This will act as your delivery system and can integrate directly into your software, giving you full control and allowing you to easily manage your proxies.

Next, you’ll want to find customers. Your client could either be a regular internet user who wants to shield their IP, or they may be a business doing web scraping that wants to hide its IP from anti-bot software. Market your proxies to either of these types of customers on your website with articles and testimonials to get their trust. Then, integrate Raybyte’s easy-to-use API to sell your proxies for profit. This is a major way how to make money with web scraping using Python.

Selling data

Another way how to make money with web scraping using Python is by scraping the web, structuring the data you’ve found, and offering that data for sale. Some companies may want the kind of data you’ve scraped and don’t have the time or resources to write programs and figure out how to scrape the web. That’s where you can offer value to them.

Trading and retail arbitrage

One more way how to make money with web scraping using Python is trading. An income can be earned online by buying one thing for a low price and selling it for a higher price. Using web scraping, you can find when prices drop to a price you want. So, you can purchase an item. If average prices increase, you can sell the item at a high price.

The above ideas are just a few ways how to make money with web scraping using Python. Other ways are up to your ideas, your research, and your imagination.

 

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Final Thoughts on Making Money Online With Python

Final Thoughts on Making Money Online With Python

Web scraping with Python and reselling proxies can be a fun and lucrative way to earn an income online. If you’re still wondering how to make money with web scraping using Python? The answer is by using Python libraries, having a little coding knowledge, and using residential proxies, you can get started with web scraping hundreds of public websites for valuable data collection. You can sell the data you’ve scraped, use it for your profitable purposes, or resell proxies you’ve acquired for additional income.

Hopefully, you’ve learned how to make money with web scraping using Python in this article. Get in touch with us here at Rayobyte for the best proxy residential product on the market today.

The information contained within this article, including information posted by official staff, guest-submitted material, message board postings, or other third-party material is presented solely for the purposes of education and furtherance of the knowledge of the reader. All trademarks used in this publication are hereby acknowledged as the property of their respective owners.

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