Web scraping is a technique for extracting data from websites, creating databases, gathering market research data, analyzing market trends, monitoring competitor activity and consumer behavior, and finding trends in online conversations.
Knowing how these technologies work will help to create effective web scrapers and provide insights into how websites are built and find the data that can be collected from them.
Different Types of Web Scraping
There are three types of web scraping, each with different techniques.
It is used to extract data from websites that don't change very often, such as news websites or blogs. The data is usually in the form of HTML and can be easily extracted using web scraping tools like Beautiful Soup.
Some websites provide Application Programming Interfaces (APIs) that allow developers to access website data programmatically. In this case, instead of scraping the HTML of the website, you can access the data directly through the API. This type of scraping can be faster and more reliable than web scraping, but it will be restricted to the information exposed by the API, which may differ from what can be viewed in the web interface. Also, some APIs are protected with API Keys or Authorization checks, so you need to understand how the API security works and mimic the behavior.
A few websites follow the robots.txt specification, a standard used to communicate to web robots about which pages or sections of a website should not be crawled or scraped.
Another important best practice is to avoid overloading the website. When we scrape too many pages too quickly, we can overload the website, causing it to crash or lose service. It is important to set a reasonable rate limit for your scraping and to respect the website server resources.
Using a randomized user-agent header is another good best practice. Some websites can detect web scraping by checking the user-agent of the request. Talking about headers, it is important to manage the request and response headers. Some websites also check the header's call sequence or if a specific header is included in the requests.
Scraping a website is challenging, there are several topics to worry about. The most common challenges are:
Inconsistent Data Format
Some websites do not render the pages with a consistent data format, causing errors in the web robot . There are a few techniques to handle this issue, like different parsers for specific parts of the page or regular expressions.
Website Structure Changes
Probably the most popular web scraping challenge. Any small change in the website structure can break the scraping robot. This is something we have no control over, and we need to create scraping robots to handle failures trying to find or parse a specific section of a website. This error handling should identify the missing section and try to collect information to identify the problem.
Web Scraping: Ethical Considerations and Legal Issues
It is also important to be aware of the laws and regulations that apply in your country and the country where the website you are scraping is located. Some countries or regions have specific regulations, such as the "General Data Protection Regulation" (GDPR) in the European Union and the "Computer Fraud and Abuse Act" (CFAA) in the United States, which must be considered when processing personal or sensitive data.
This article was written by Paulo Roberto Sigrist Junior, Systems Architect and Innovation Expert at Encora. Thanks to Andre Scandaroli and João Caleffi for their reviews and insights.
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