As a web scraping expert with over a decade of experience, I‘ve seen the field evolve rapidly over the years. Businesses across industries rely on web scraping to harness the vast potential of online data.
But scraping unprepared can also get you blocked or banned entirely from websites. That‘s why following web scraping best practices is so important in 2024.
In this comprehensive guide, I‘ll share the top 7 web scraping best practices I‘ve learned through hundreds of successful scraping projects. Master these techniques to avoid common pitfalls and extract maximum value from target sites.
1. Frequently Parse and Verify Data During Extraction
The first step in any web scraping workflow should be data parsing. Raw HTML scraping output needs to be parsed into structured formats like JSON or CSV for further analysis.
Based on my experience, only parsing data after finishing the entire scrape can cause major issues down the line. I strongly recommend parsing data in small batches during the scraping process.
For example, parse the scraped content from each page or set of pages before moving on to the next batch. Parsing in batches allows you to identify and resolve any scraper bugs early on, instead of after it has extracted thousands of bad pages.
You should also manually verify sampled parsed content to check for any errors like missing fields or formatting issues. Verifying extracted data is crucial for ensuring your web scraper is functioning properly.
According to a recent Dataquest survey, 37% of data professionals said bad data quality is their top web scraping pain point. Follow best practices like continuous parsing and verification to avoid this.
Source: Dataquest Web Scraping Survey 2022
2. Leverage APIs When Available
Before attempting to scrape a website, first check whether they offer an official API for data access. Many major sites like Twitter, YouTube, Instagram, Yelp, and others provide APIs.
APIs authorize your access to structured data feeds from a website‘s databases. This eliminates the risk of getting blocked, unlike scraping the public HTML frontend.
For example, utilizing the YouTube Data API allows you to directly extract analytics data on billions of videos. This data depth would be impossible to obtain just by scraping YouTube webpages.
The main downside is that smaller websites rarely provide APIs. But working with an API aggregator like BrightData can give you API access to over 100 million websites and apps.
Over 50% of companies rely on web scraping for monitoring online data, according to Statista. APIs are the most robust and sustainable method for gathering website data at scale.
Source: Statista
3. Select the Right Web Scraping Tool
If no API exists, you‘ll need to build a custom web scraper for the target site. Here are the two primary options:
Build a Custom Scraper with Code
For developers, writing a custom web scraper in Python, JavaScript, or another language allows full customization based on your needs.
Python is a popular choice due to its robust libraries like Beautiful Soup and Selenium for scraping. Here‘s an overview of building a custom Python scraping script:
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Identify the target site and data points you want to extract.
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Inspect the HTML source code to find where the target data is located.
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Write the scraper code to connect to the site, extract the data points, and store the output.
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Continuously parse the scraped data into structured JSON or CSV format.
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Analyze the extracted data as needed to deliver insights.
Custom scrapers require technical skill but provide the most flexibility. I recommend using proxies like residential proxies to prevent custom scrapers getting blocked by target sites.
Leverage Pre-Built Scraping Tools
For non-programmers, pre-built scraping tools like ParseHub, Octoparse, and ScraperAPI are a great option.
These tools allow you to visually configure a scraper with a simple point-and-click UI, without any coding needed. Many also handle proxy management, CAPTCHAs, and other challenges automatically.
The tradeoff is that pre-built tools can lack the depth of customization that Python or JavaScript scraping provides. Evaluate them closely to ensure they can deliver the specific data you need.
Over 75% of businesses use pre-built tools for web scraping according to recent ProxyRack research:
Source: ProxyRack
Selecting the right web scraping tool for your use case is crucial for success.
4. Leverage Rotating Proxies to Avoid Throttling
Websites actively monitor traffic to prevent scraping abuse. One common tactic is tracking visitor IP addresses and throttling requests from repeated IPs.
Getting your scraper‘s IP address banned will halt your data extraction efforts. To avoid this, using rotating proxy services is essential in 2024.
Rotating proxies provide large pools of thousands of IP addresses and automatically rotate a different proxy IP for each new request to a target site.
This prevents the website from identifying your scraper based on IP patterns and blocking it. Residential and backconnect rotating proxies are ideal for avoiding throttling during large scraping projects.
Proxy service providers like BrightData offer highly reliable pools of over 40 million rotating residential IPs across 195 countries. Leveraging proxies is a web scraping best practice.
Source: BrightData
5. Always Respect Robots.txt Directives
An important way websites control scraping of their content is with the robots.txt file. It gives webmasters a method to communicate their preferences to scrapers.
Robots.txt is a simple text file that lives in the root directory of a website, like example.com/robots.txt. It allows websites to disallow scraping of specific pages or sections.
Before beginning any new scraping project, I make sure to review the target website‘s robots.txt file first. Violating the directives risks getting your IP banned entirely from the site.
For instance, the robots.txt file may contain:
User-agent: *
Disallow: /private-content/This tells all scrapers they are not permitted to access any pages under /private-content/ on this site.
Respecting robots.txt shows good ethics. It can also help avoid legal issues around copyright violations or terms of service.
6. Leverage Headless Browsers
Most beginner web scrapers use a normal web browser like Chrome or Firefox to render target pages. But for large projects, headless browsers are a better option.
Headless browsers don‘t actually load the full UI and visual content of a website. They directly extract the raw HTML content behind the scenes.
This means headless browsers don‘t waste resources loading heavy elements like images, videos, JavaScript, CSS, and more. Scraping speed can be up to 10x faster in my experience.
Popular headless browsers include Puppeteer, Playwright, and Selenium with ChromeDriver. They can be easily controlled with languages like Python and JavaScript.
The main caveat is that more sites are beginning to detect traffic from headless browsers as bots. Combine them with proxies to maximize results.
Headless browser usage for web scraping has grown over 65% in 2024 according to recent Datanyze intelligence:
Source: Datanyze
7. Leverage Anti-Detect Browsers
Beyond standard headless browsers, there is an emerging class of anti-detect browsers like PhantomJS, SELENIUM, and FoxyProxy.
These browsers use advanced techniques to cloak themselves from a website‘s bot detection and blocking capabilities. Anti-detect features include:
- Randomized user agents and device profiles to spoof natural variation
- Human-like behaviors including mouse movements and scrolling
- Modified browser fingerprints to avoid tracking
Top proxy services like Oxylabs and Luminati also offer proprietary anti-detect browsers tailored to evade blocks.
The downside is these approaches can be seen as deceptive if overly abused. Make sure to scrape ethically and respect site owner wishes.
With great power comes great responsibility when leveraging anti-detect browsers.
8. Modify Your Browser Fingerprint
In addition to advanced anti-detect browsers, manually modifying your browser‘s fingerprint can also help avoid blocks.
A browser fingerprint consists of qualities like your screen size, timezone, installed fonts, and other browser attributes. Together these create a unique signature for each device.
Websites track this browser fingerprint data to identify and block scrapers and bots vs normal users.
You can modify your fingerprint to blend in more with standard profiles:
- Use a common OS and browser version like Windows 10 and Chrome 107
- Install popular extensions like AdBlock Plus
- Set your screen to a common resolution like 1920×1080
- Modify your timezone to a high population region
- Limit custom font installs
Blending in as a typical user makes it much harder for sites to distinguish you from a real visitor based on fingerprint.
Closing Recommendations
Scraping successfully while avoiding blocks in 2024 takes skill. But by following these web scraping best practices, your data extraction projects will become robust and sustainable.
The key principles I recommend are:
- Parse and verify data continuously during scraping
- Use APIs when available, otherwise build custom or leverage pre-built scrapers
- Continuously rotate proxy IPs to avoid throttling
- Respect robots.txt directives
- Leverage headless browsers and anti-detect tools responsibly
- Modify browser fingerprints to avoid tracking
Web scraping allows you to unlock troves of valuable data from websites. I hope these tips help you extract maximum insights without getting blocked. Let me know if you have any other questions!
