Web scraping strategies for beginners

The internet is an endless treasure trove of valuable information, but finding gems in the dirt requires technical prowess. In most cases, the most beneficial and applicable data resides in the most popular sites that are constantly updated: social media networks, search engines, and online shops that keep changing prices.

Collecting and organizing these data sets into readable and understandable data sets that squeeze and concentrate tons of information. They help us see trends and patterns that could help predict the future or at least adapt to the present. If an average internet user tries to collect the same amount of knowledge through regular browsing sessions, these manual processes could take many days or months.

Fortunately, everything can be accelerated with web scraping – an accelerated and automatable method of data extraction. In this guide, we will talk about web scraping, data extraction techniques and the most popular use cases in 2023. As we go from collection basics to the most productive strategies, you should have general guidelines on how to approach scraping for both personal goals and commercial purposes.

For example, the Amazon scraper is a high-end tool for automatically tracking products and prices without restrictions. With high demand for effective data collection apps, Smartproxy is one of the leading companies offering robust scraping and privacy solutions related to bot activity. Check them out if you want to learn more about their Amazon scraper. For now, let’s cover the details of web scraping for users of all skill levels.

Web scraping basics

While intimidating at first glance, data scrapers are among the most primitive automatable tools on the web. Still, the functionality of used software can be greatly expanded to tackle more targets and bypass protection measures. A combination of a low-skill floor and a high skill ceiling makes data scraping one of the best skills to learn for beginners. A quick start covers the foundational basics of information collection scripts, while additional layers encourage further learning of IT and data science.

First, let’s split the average web scraping app into two parts: a scraper and a parser. While the term usually covers the entire process for simplicity, a web scraper is a simple tool that is similar to your web browser. While browsers extract and render the code for the visual and interactive representation of the site, scraper downloads and stores this file.

After that, the parser takes the extracted document and chips away the syntax and other useless components to end up with a set of values that is readable and understandable for both the users and dedicated analysis tools.

For example, if you extract information that sells furniture from different manufacturers, you can track prices for identical models and compare them among competitors. If collection tasks are performed frequently, the changes in the data sets will help you find the most affordable deals every time.

Data scraping techniques

If you want to learn about data collection strategies and techniques, here are the best ways to start building knowledge:

Web scraping with Python

If you want to learn web scraping, there is no better introduction than Python – the biggest programming language in 2023. Oriented at user simplicity, it has the most tutorials on data collection, with multiple variations, and the most powerful parsing libraries.

The sheer amount of active users exist for very good reasons: Python is just too versatile and effective and has many applications, especially data scraping. Even if one tutorial does not fit your needs, the web has tons of free sources that let you copy the main code and even include suggestions for further improvement.

For Python, the most popular parsing libraries are Scrapy and BeautifulSoup 4 (or BS4 for short). With their help, you can dissect the extracted code, often without special adjustments to fit the page. That being said, no solution will work on all targets.

Downloading data with cURL

While there is no denying the flexibility of Python, some targets willingly offer valuable public data. For them, running a Python script or any other complex scraper is not ethical nor recommended.

Instead, automated downloads can be executed with a command line script using cURL – a powerful data transmission tool widely used in digital gadgets and applications for over 25 years. With a focus on low-end computers and embedded systems, cURL commands are among the easiest yet customizable ways to download data or automate its transfer via command line scripts.

Outsourcing data scraping tasks

Here are the best ways to certain parts or the entire process of data scraping to third parties:

• Aggregator websites and data resellers. get the necessary data from data science experts that collect information for many business clients.
• Pre-built scrapers. Outsource the assembly and maintenance of scraping software to professionals, especially if you often target the same targets or extraction is not as frequent to call for bigger investments.

Summary

By understanding these common techniques, you can learn about web scraping and data science in no time. The level of necessary coding knowledge will depend on your chosen approach, so pick your priorities and start working on data collection today!