Web scraping, also known as web data extraction, is the process of collecting and gathering data from websites. With the increasing amount of data available on the internet, web scraping has become essential, especially when it comes to businesses and organizations gathering and analyzing data to make informed decisions. Over the last three years, we have worked with many companies providing them with external data. Gaining a lot of experience, we would like to share some web scraping best practices we have gathered.
One of the most important web scraping best practices is to respect the website's terms of service. Many websites have specific policies in place that prohibit or limit the use of web scraping. Before beginning any web scraping project, it is essential to read and understand the website's terms of service and ensure that the data being collected is within the boundaries of those terms.
Another lesson is to be mindful of the website's performance. Web scraping can put a significant strain on a website's servers, mainly if the scraping is done on a large scale or at a high frequency. To avoid this, it is best to implement a crawl delay, a waiting period between requests to the website. This will give the website's servers time to recover and prevent them from being overloaded.
It's also important to invest in the right scraping tools and technologies. Using the right tools and technologies can help you to extract data more efficiently and effectively. It can also help you to avoid common scraping pitfalls, such as getting blocked by a website's security measures. There are many tools on the market that will provide you with web scraping best practices from day one without writing a line of code. A great example might be Apify, Simplescraper, and of course Forloop.
Another best practice is to use a proxy server. A proxy server is an intermediary server that acts as a relay between the web scraping software and the website. Using a proxy server allows the web scraping software to make requests to the website without revealing the true IP address of the computer or network that is running the software. This can help to prevent being blocked by the website and protect your IP address from being blacklisted.
Next, one of the most important web scraping best practices is to store and handle data responsibly. This means that businesses and researchers must be transparent about their data collection practices and obtain consent from users when necessary. Additionally, scraped data should be kept secure, and any personal information should be properly anonymized to protect users' privacy.
Another key web scraping best practices for web scraping is to keep track of changes. Websites are constantly updating, and a scraped dataset that was accurate at one point in time may become outdated. To avoid this, businesses and researchers should periodically check for changes to the website and update their scraped data accordingly.
Caching is another important best practice for web scraping. Caching involves storing a copy of the scraped data on the business or researcher's own servers, so that the website does not have to be scraped every time the data is needed. This not only speeds up the scraping process, but it also reduces the load on the website, which can help to prevent the website from blocking the scraper's IP address.
Finally, businesses and researchers must use a proper User-Agent when scraping websites. A User-Agent is a string of text that identifies the scraper to the website, and it is important to use a User-Agent that accurately describes the scraper. This will help to prevent the website from blocking the scraper's IP address and make it easier to track any issues that may arise.
Finally, it's important to be aware of and comply with any legal and ethical considerations. This includes adhering to data protection regulations such as the General Data Protection Regulation (GDPR) in the European Union, and being mindful of sensitive information such as personal data.
In conclusion, web scraping best practices can be a powerful tool for businesses and organizations to gather and analyze data in a proper way. It is essential to follow those steps to ensure that the data being collected is accurate, legal, and ethical.
