Speed up Web Scraping with Python – A Quick & Easy Tutorial

by Alexander Scott

To be successful in today’s competitive business world, you need to find and have access to a lot of information quickly. To do this efficiently, you’ll have to process huge amounts of page content fast so that you don’t waste your time. But what could stop you from quickly gathering all this data? And how can you speed up the process?

Do you want to learn how to quickly collect public data? In this article, we will show you some great ways and provide code examples that you can use in your data scraping project.

Sluggish Network Speeds Can Cause Major Delays in Web Scraping Projects

Whenever you are doing a project where you have to get info from the internet, there can be delays. It takes time to send a request to the web server and likewise when the web server sends its response back. This process causes delays.

When you visit web pages, the time it takes for a page to load quickly isn’t noticeable. But if you’re running code that needs to fetch information from lots of different pages, like ten thousand pages, then those load times can really add up so that it takes a long time – almost three hours!

Network speed is just one part of the puzzle when it comes to slowing things down. Your web scraping code does more than just send and receive requests – it also manipulates the data. That’s when you might run into problems like too slow Input/Output or maybe your Computer Processor not being able to keep up with processing everything quickly enough.

Unlocking the I/O Bottleneck for Faster Computation Performance!

I/O bottleneck is an issue that has to do with how quickly your computer gets stuff done. That could mean reading data, writing data, copying files and downloading files. Programs that rely on the input-output system can take longer than others and this delay time is called I/O bound delays.

Understanding the Difference Between CPU and I/O for Increased Performance

The other situation is when a program depends on the speed of the CPU. CPU happens to be the brains of your computer or device – it stands for Central Processing Unit. The faster your CPU, the quicker your program runs.

An example of a task that requires many calculations is called a CPU-bound application. This type of program uses multiple processors in the CPU to increase computing power and make things run faster.

It’s important to understand the difference between I/O and CPU because it helps us figure out which approach can help us get better performance from our program.

Speed Up Your Scraping with Multiprocessing, Multithreading, and Asyncio!

There are three different ways to make scraping faster: Multiprocessing, Multithreading, and Asyncio. Before trying those approaches, let’s first try an unoptimized code just to see the difference between them all. You can also find a tutorial about this on our YouTube channel if you’re interested.

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