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Web scraping of a dynamic website using Python with HTTP Client

· 13 min read
Max
Community Member of Crawlee and web scraping expert

Dynamic websites that use JavaScript for content rendering and backend interaction often create challenges for web scraping. The traditional approach to solving this problem is browser emulation, but it's not very efficient in terms of resource consumption.

note

One of our community members wrote this blog as a contribution to Crawlee Blog. If you want to contribute blogs like these to Crawlee Blog, please reach out to us on our discord channel.

In this article, we'll explore an alternative method based on in-depth site analysis and the use of an HTTP client. We'll go through the entire process from analyzing a dynamic website to implementing an efficient web crawler using the Crawlee for Python framework.

How to scrape dynamic websites in Python

Current problems and mistakes of web scraping in Python and tricks to solve them!

· 15 min read
Max
Community Member of Crawlee and web scraping expert

Introduction

Greetings! I'm Max, a Python developer from Ukraine, a developer with expertise in web scraping, data analysis, and processing.

My journey in web scraping started in 2016 when I was solving lead generation challenges for a small company. Initially, I used off-the-shelf solutions such as Import.io and Kimono Labs. However, I quickly encountered limitations such as blocking, inaccurate data extraction, and performance issues. This led me to learn Python. Those were the glory days when requests and lxml/beautifulsoup were enough to extract data from most websites. And if you knew how to work with threads, you were already a respected expert :)

note

One of our community members wrote this blog as a contribution to Crawlee Blog. If you want to contribute blogs like these to Crawlee Blog, please reach out to us on our discord channel.

As a freelancer, I've built small solutions and large, complex data mining systems for products over the years.

Today, I want to discuss the realities of web scraping with Python in 2024. We'll look at the mistakes I sometimes see and the problems you'll encounter and offer solutions to some of them.

Let's get started.

Just take requests and beautifulsoup and start making a lot of money...

No, this is not that kind of article.

Building a Netflix show recommender using Crawlee and React

· 7 min read
Ayush Thakur
Community Member of Crawlee

In this blog, we'll guide you through the process of using Vite and Crawlee to build a website that recommends Netflix shows based on their categories and genres. To do that, we will first scrape the shows and categories from Netflix using Crawlee, and then visualize the scraped data in a React app built with Vite. By the end of this guide, you'll have a functional web show recommender that can provide Netflix show suggestions.

note

One of our community members wrote this blog as a contribution to Crawlee Blog. If you want to contribute blogs like these to Crawlee Blog, please reach out to us on our discord channel.

How to scrape Netflix using Crawlee and React to build a show recommender