The Good Tech Companies - Web Scraping Optimization: Tips for Faster, Smarter Scrapers

Episode Date: November 15, 2024

This story was originally published on HackerNoon at: https://hackernoon.com/web-scraping-optimization-tips-for-faster-smarter-scrapers. Let's dive into advanced web scraping tips for optimization. Take your scraper to the next level! Check more stories related to life-hacking at: https://hackernoon.com/c/life-hacking. You can also check exclusive content about #tips-and-tricks, #ai, #web-scraping, #python, #javascript, #tips, #web-development, #good-company, and more. This story was written by: @brightdata. Learn more about this writer by checking @brightdata's about page, and for more stories, please visit hackernoon.com. Optimizing web scrapers involves implementing advanced techniques for more efficient data extraction. Key tips include implementing error handling to manage connection issues and page failures, utilizing retries with exponential backoff to avoid overloading servers, and writing flexible CSS or XPath selectors to prevent breakage with page structure changes. For faster scraping, use fast HTML parsers like lxml and leverage HTTP/2 to reduce latency by sending multiple requests over a single connection. These techniques help scale scrapers effectively, enhancing both speed and resilience for large-scale operations.

This audio is presented by Hacker Noon, where anyone can learn anything about any technology. Web Scraping Optimization. Tips for Faster, Smarter Scrapers, by Bright Data. Red exclamation mark disclaimer. This is part 3 of our 6-piece series on Advanced Web Scraping. New to the series? Start from the beginning by reading part 1. In part 2 of our Advanced Web Scraping series, you learned how to scrape data from spas, PWAs, and AI-powered sites. By now, you should have all the knowledge needed to build a scraper that works against most modern websites. What's next? Time to optimize your scraper with some pro scraping tips and tricks, web scraping made simple, or is it? Building a web scraper? It's all about scripting. Man technologist and

let's be honest, if you've ever written code, you know scripting isn't feathered most of the time. A few lines here, a there, and boom, you're scraping data like a pro. Sounds simple, right? Open mouth smile but here's the problem. The simplicity of writing a small scraper can lull you into a false sense of security. Why bother with proper comments, error handling, logs, or even neat indentation when it's just a dozen lines of code anyone can read? We get it, why overengineer something that doesn't need it? Overengineering is the enemy of progress. But what happens when you need to scale your scrapers to multiple pages or even entire

sites? Thinking face that's when your quick and dirty, spaghetti-coated scraper falls apart. Spaghetti here's why you need some advanced web scraping tips. Optimizing web scraping, top 7 tips and tricks. You must have already heard the usual web scraping tips, prioritize pages with critical data first, randomize your requests, and so on. Great advice, but let's be honest, those tricks are old news. Newspaper when you're dealing with more advanced scenarios, those basics might not cut it. If you really want to level up your scraping game, you'll need to explore Soma

next level techniques. Ready? Buckle up, it's time to take your web scraping skills to the next level. Biceps warning warning. Don't worry if some of the tips feel familiar, keep going. There are a plenty of interesting insights as you dive deeper. Diving mask implement error handling one of the most common mistakes in web scraping is forgetting that the internet isn't some magical, infallible technology. When you send a request to a site, a whole range of things can, and will, at some point, go wrong. Crossmark let's look at some common scenarios. Your Wi-Fi or connection might hiccup momentarily. The server hosting the website may be unavailable. The page you're looking for may no longer exist.

The target site might be experiencing a temporary slowdown, leading to a timeout error. Now, mix in data parsing, pre-processing, and exporting to a database, and you've got a perfect recipe for chaos. Collision so, what's the solution? Error handling. Shield error handling is your best friend in web scraping. Your script will likely process dozens, or thousands, of pages, and one single error shouldn't bring your whole operation crashing down. Remember that the block is your friend. Use it to wrap your requests and processing logic. Also, keep in mind that most HTTP libraries don't raise exceptions for bad HTTP responses, like or. Astonished face if you're not familiar with http://www.youtube.com.watch.v="wja5ctifj7u and embeddable="true". For instance, in Python's requests library you need to manually check the response status code as follows, or, equivalently, use the raise underscore for underscore status method.

Failure recovery with request retries your advanced web scraping script should not only be able to handle errors but also recover from them. Since most errors related to web scraping are tied to macking web requests, you can significantly improve your scraper's effectiveness by implementing retrievable requests. The concept is simple. If a request fails, you try it again, one, two, three, or more times, until it's successful. Anti-clockwise arrows but here's the catch. Since one of the most common reasons for a failed request is the target server being temporarily down or slow, you don't want to overwhelm it by sending the same request repeatedly in a short period of time.

If a request fails now, it's likely to fail again immediately. That's where exponential backoff comes into play. Instead of retrying instantly, this technique gradually increases the time between retries, improving your chances of success by giving the target server time to recover. Hourglass While you can manually implement simple retry strategies with custom code, many HTTP clients come with built-in utilities or libraries to handle retries automatically. For example, Axios offers the Axios retry library, which you can use like this. Similarly, Python's package comes with a retry class that integrates seamlessly with most Python HTTP clients. Write generic selectors when inspecting elements in the dev tools.

You might be tempted to right-click and select the copy selector option. But be warned, the result might look something like this. That's definitely not ideal for web scraping. The problem? Overly specific selectors like these can break easily when the page structure changes. The more detailed your selector, the more fragile it becomes. To make your web scraping more resilient, you must keep your selectors flexible. Instead of relying on style-related classes, which change all the time, focus in attributes that are less likely to change, like, or. Most of those attributes are meant for testing and accessibility, so they tend to remain consistent over time. Lightbulb and while CSS selectors are easier to read and understand, XPath offers more power. But don't worry, you can often achieve the same results with simple CSS selectors,

saving you from needing complex XPath code. Relieved face for more information on that, take a look at our guide on XPath vs CSS selectors. Prefer fast HTML parsers? Parsing HTML pages takes time and resources, particularly if you're dealing with a large, nested DOM. If your scraper is only parsing a few pages, it's not such a big deal. Now, what happens when your scraping operation scales up and you have to retrieve data from millions of pages? That small overhead can quickly drain server resources and add hours to your total scraping time. Hourglass to get a deeper understanding, refer to these resources.

Python HTML Parser Performance Comparison Benchmark of JavaScript Libraries for Parsing HTML HTML Parsers Benchmark Looking for a full comparison? Read our article on the best HTML parsers. The good news? Switching from one parser to another isn't that difficult. For example, in BeautifulSoup, it's just a simple parameter change. And what about HTML parsers built into browsers like Chrome? Thinking face find out more in the video below. ps colon slash slash www youtube com watch v equals ll rig force one underscore ya and embeddable

equals true harness http 2 for faster req uest s http 2 is an updated version of http that allows multiple requests over a single connection this reduces latency and can improve the overall performance of your scraping task. To check if a site supports HTTP 2, simply open DevTools in your browser, go to the Network tab, and look for the Protocol column. If it says, the site is using HTTP 2. Unfortunately, not all HTTP clients and scraping libraries support HTTP 2. However, tools like HTTPx for Python offer full support for HTTP 2. Task parallelization web scraping is mostly an I-O bound task. You send requests to the server, wait for the response, process the data, and repeat.

During the wait time, your scraper is basically idle, which is inefficient. The solution? Parallelism or concurrency. By sending multiple requests at once, you can minimize those dead times and optimize network usage. Revolving light but be careful. Revolving light bombarding a server with too many simultaneous requests can lead to rate limiting or getting your IP banned, two popular anti-scraping measures. Grimace Pro Tip. You can also parallelize parsing tasks, especially if you're using multiple CPUs, which will speed up the data extraction process. High-voltage Embrace AI-based adaptive ALGORITHMSAI-based adaptive algorithms learn from patterns in data and HTML page structures, adjusting their behavior in real

time to stay on top of changes. Open mouth face that's a game changer for web scraping. Exploding head when websites update their layout or deploy anti-bot measures. These algorithms can quickly adapt, ensuring your scraper keeps running smoothly. Brain in short, they make scrapers smarter, helping you extract data efficiently, even when the site throws unexpected curveballs. Baseball with adaptive algorithms, Brain in short, they make scrapers smarter, helping you extract data efficiently, even when the site throws unexpected curveballs. Baseball with adaptive algorithms, it's like having a scraper that evolves over time, learn more in chapter 4 of this video by Forrest Knight. https colon slash slash www. youtube.com. watch. v equals vxk6YPRVG underscore O and embeddable equals true the best tool for web scraping optimization. Sure, all the tips and tricks we've mentioned so far

can make your scraper faster, more reliable, robust, and effective. But let's be real, they also bring a lot of complexity. Cold sweat smile the good news is that most of these lessons apply to the great majority of scraping projects. So, instead of coding everything from scratch, you could use separate built functions to tackle specific tasks. That's exactly what bright data scraping functions offer. With 73 plus ready-made JavaScript functions, users have built over 38k scrapers operating across 195 plus countries. that's a ton of scraping power upward trend speed up your development with a runtime environment designed to scrape unlock and scale web data collection effortlessly https colon slash slash www youtube com watch

v equals vo4 underscore 6 gdkvu and embeddable equals true final thoughts. Now you know how to level up your scraper with insights from experienced scraping developers. Remember that this is only part 3, so we're just halfway through our 6-part journey into advanced web scraping. Keep that seatbelt fastened because we're about to dive into even more cutting-edge tech, clever solutions, and insider tips. Next stop, harnessing the power of eye-driven proxy management. Globe thank you for listening to this Hackernoon story, read by Artificial Intelligence. Visit hackernoon.com to read, write, learn and publish.