If you‘re looking to get started with web scraping in 2023, following best practices is crucial for success. Without proper precautions, your scraper can easily get blocked, deliver corrupted data, or land you in legal trouble.
This comprehensive guide explores 10 key web scraping best practices you need to integrate into your workflows this year. Adopt these techniques and you‘ll be able to scrape more efficiently, avoid bans, and access higher quality data.
In this article, you‘ll learn:
- Why respecting robots.txt and ToS should be your top priority
- How proxies and rotating IPs can hide your scraper‘s tracks
- When to use headless browsers for faster scraping
- The right way to leverage site APIs where available
- How to build scrapers quickly with Python libraries
- Techniques for mimicking natural human behavior
- The importance of monitoring your scrapers for errors
- Ethical principles to scrape responsibly
Let‘s dig in!
Follow Robots.txt and Terms of Service
The first rule of ethical web scraping: always respect a website‘s robots.txt file and terms of service (ToS).
Found at www.example.com/robots.txt, the robots.txt file outlines which pages the site owner does not want indexed and crawled. Violating these guidelines can quickly get your scraper blocked.
According to a 2019 survey by Moz, over 115 million websites have implemented a robots.txt file. So it‘s critical to check this file before scraping a site.
Paying attention to a website‘s terms of service is equally important. Many sites expressly prohibit scraping for commercial purposes without permission. Others ban it outright.
Ignoring a site‘s ToS can open your business up to lawsuits. For example, in 2019, LinkedIn sued scrapers who violated their ToS, winning a case against 100 nameless "John Doe" defendants.
So before scraping any site, carefully review their terms to ensure you have permission. This helps avoid legal issues and blocks down the road.
Mask Your Identity with Proxies
Websites can easily spot scrapers originating from a single, static IP address. Once detected, they may block your IP completely.
To prevent this, you‘ll need to mask your scraper‘s true IP address via proxy services.
Proxies route your traffic through intermediary proxy servers before reaching the target site. This hides your scraper‘s real IP, preventing blocks.
Rotating proxies go a step further by automatically switching your IP on each new request. This makes it virtually impossible for sites to identify your scraper by IP.
Residential rotating proxies are ideal, since they are based on IPs belonging to home networks. This makes your scraper traffic appear more human.
Services like Bright Data offer reliable pools of millions of residential IPs perfect for masking your scraper.
Leverage Headless Browsers
For web scraping, this comprehensive rendering is unnecessary and slows down crawling.
Headless browsers provide an alternative – they fetch and parse web pages without actually rendering the UI.
For example, Headless Chrome and Firefox grab all the underlying HTML from a page, but don‘t load images, style sheets, etc.
This makes headless browsers extremely efficient for scraping content from text-heavy sites.
According to Browserling, Headless Chrome can run approximately 3x faster than full Chrome with the UI and extensions.
So consider using a headless browser if you need to scrape complex, interactive sites with less overhead.
Popular options include:
- Headless Chrome – Based on the Chrome browser.
- Headless Firefox – Based on the Firefox browser.
- Puppeteer – Headless Chrome browser API by Google.
Check for Data APIs Before Scraping
Before scraping any site, first check to see if they provide an API for accessing their data directly.
APIs give structured access to a website‘s backend data and content. Scraping via API is more sustainable than from the frontend UI.
For example, sites like Reddit, Twitter and YouTube offer APIs for retrieving posts, tweets and videos programmatically.
Accessing data through a site‘s API reduces your risk of getting blocked down the road due to site changes. The API acts as an official conduit for the data.
Scraping should be more of a last resort when you have no other option to obtain the data needed for your project.
Build Scrapers Quickly with Python Libraries
While you can build web scrapers completely from scratch, doing so requires significant programming experience.
Fortunately, Python offers some excellent libraries that abstract away much of the complexity:
- Scrapy – Leading web scraping framework designed for large crawls. Easy to scale up.
- Requests – Simplifies making HTTP requests to crawl pages.
- Beautiful Soup – Parses HTML/XML so data can be extracted.
For example, here is sample Scrapy code to crawl a page and extract links:
name = ‘example‘
urls = [‘http://example.com‘]
for url in urls:
yield scrapy.Request(url=url, callback=self.parse)
def parse(self, response):
page = response.url
links = response.css(‘a::attr(href)‘).getall()
Integrating libraries like these will significantly accelerate your scraping project.
Mimic Natural Human Behavior
Sites can easily detect bots scraping too quickly, uniformly, and not interacting. To appear more human:
- Add random delays between 2-7 seconds between page requests. Avoid a strict cadence.
- Rotate user agents with each request to mimic different devices and browsers accessing the site.
- Use services like Puppeteer to scroll pages and click links like a real user would.
- Access sites through residential proxies since they naturally vary requests.
- Consider integrating a headless browser like Puppeteer to render pages as a real browser would.
Blending in this way makes it much harder for sites to distinguish your traffic from a legitimate human visitor.
Monitor Your Scrapers for Errors
Once you‘ve built a scraper, your work isn‘t done. You‘ll need to closely monitor its performance over time.
Errors and changes to a site can often break parts of a scraper, leading to incomplete or corrupt data.
Use tools like Scrapyd to monitor scraper uptime and catch errors quickly. Manually verify random samples of scraped content.
If errors are identified, fix them immediately before the scraper accumulates too much bad data. Frequent monitoring helps avoid this.
You can also use this monitoring to optimize scraper performance over time as sites change. Continual refinement keeps quality high.
Scraping Ethically and Responsibly
In additional to the technical practices above, ethical principles should guide your web scraping activities:
- Avoid scraping private, personal data like emails or financial information without permission.
- Use scraped data responsibly for lawful purposes, not harassment or discrimination.
- Spread out scraping over longer periods to avoid overloading sites.
- Obtain a site‘s consent for commercial usage if terms are unclear.
- Disclose source data to maintain transparency around scraping.
- Limit scraped data retention and securely delete it when no longer needed.
Adhering to strong ethics will help legitimize the practice of responsible web scraping.
Key Takeaways to Remember
To recap, here are 10 of the most important web scraping best practices:
- Follow a website‘s robots.txt guidelines and terms of service.
- Use rotating proxies to mask your scraper‘s true IP address.
- Leverage headless browsers to scrape complex sites faster.
- Check for APIs before resorting to frontend scraping.
- Build scrapers efficiently with Python libraries like Scrapy.
- Mimic natural human behaviors like scrolling and clicking.
- Continuously monitor your scrapers for errors and issues.
- Avoid scraping private user data without permission.
- Use scraped data responsibly for lawful purposes only.
- Spread out scraping activity over time to avoid overloading sites.
Keeping these tips in mind will help ensure your scraper stays undetected, gathers useful data, and operates legally and ethically.
Ready to put these scraping best practices into action? Check out our guide to selecting the best web scraping tools and services to get started on the right foot.