Web scraping allows you to automatically extract data from websites. When done legally and ethically, it can be a useful tool for gathering public data from across the web. Python is one of the most popular programming languages for web scraping due to its large collection of scraping libraries and simple syntax.
In this article, I'll walk through some of the basics of how you can leverage Python web scraping to make money, along with key tips, legal considerations, and example code.
Gathering & Analyzing Data to Sell
One of the most common web scraping business models is gathering public data from across the web, analyzing it, and re-packaging it into products or services you can sell. For example:
Here's some sample code for scraping a site:
import requests
from bs4 import BeautifulSoup
url = 'http://example.com'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
print(soup.get_text())
The key is finding helpful public data other businesses would pay for access to. Make sure to follow terms of service and check your jurisdiction's laws.
Creating Content Sites
Another option is using web scraping to auto-generate content for sites you can monetize with ads. For example, aggregating news articles or product listings into a site in a niche industry. Again, be mindful of copyright and attribution requirements.
Overall the most important things when making money via web scraping are finding legal and ethical sources of data others find valuable, and understanding restrictions in your jurisdiction. Start slowly, check terms of service, and consult a lawyer if unsure.