Basics techniques of big data extraction
Web scraping or web harvesting is a process of extraction a large sets of data from web pages for different profits. All the methods of web scraping can be divided in two groups: basics and advanced techniques.
- Basic techniques – allow you to gather information automatically from webpages using third party online services, applications or browser plugins.
Many sites have common and repetitive structure so it is possible to parse them step by step only setting up a couple of parameters and clicking a couple of buttons. Using basic techniques, instead of parsing site content yourself, you interact with some kind of clever «black box» which knows how to extract data from a website, crawl through links, analyze HTML code, get necessary text and download files or photos.
Pros and cons of Basics web scraping techniques:
- It is simple;
- It takes not much time;
- Special technical knowledge doesn’t required;
- Output data format can be different from what you expected;
- It is not suitable for highly specialized tasks;
- You have to pay for ready to use tools and applications in most cases.
- Advanced techniques – are focused on developing your own data extraction tools.
In fact it is not as hard as it sounds because you will use some third party modules, libraries and developer’s tools that make web harvesing really easy.
Pros and cons of Advanced web scraping techniques:
- Nobody tells you how to extract data – chose the format yourself;
- It does not matter if your task is highly specialized or not;
- You pay no one to get the content you need;
- It seems not simple for many people;
- It takes much time to learn and some more time to code your web scraping script;
- You have to reinvent the wheel in many cases.
Basics techniques of big data extraction
Let’s have a look at several online services that give you simple answer how to extract data from webpage without any programming skills.
|Online service or tool
|Incredible easy to use! Just give it a start page URL, explain with a keywords which pages you want to crawl through and select one of the parsing APIs to get your CSV or JSON data.
|Works well with online stores, retailers and real estates; collects goods, prices, text descriptions and download images; responses with a clean JSON data.
|Smart and scheduled scrapes without coding routine; accurate data in the format of your choice.
|Turns website content into datasets; has visual tools for scrapping settings; gives you result in CSV or Excel format.
|Allows you to control so called headless browser via API to concentrate on parsing data and get rid of the proxies changing problem.
|Similar to ScrapingBee – an API that handles you proxies, browsers and CAPTCHA bypass.
|Small easy-to-use Chrome extension for data mining. It facilitates online research and saves your data into spreadsheet.
Advanced techniques of big data extraction
In the table below we have gathered advanced techniques of web scrapping for those who want to know thoroughly how to extract information from a website.
|Parser, wrapping around htmlparser2. Fast analyze DOM-tree of a webpage; implements a subset of core jQuery, so if you are familiar with jQuery syntax you will easily work with Cheerio API.
|Powerful scraper that allows you to work with AJAX content and supports CSS 3.0 and XPath 1.0 selector hybrids. It also supports form submission, session cookies, custom headers, proxies and basic authentication.
|Node.js library provides the tools to scale a pool of headless browsers (Chrome or Chromium) and maintain URL queues for crawling.
|Node.js library that provides you control Chromium browser over DevTools Protocol. Many of the things than can be done by browser manually, you can perform with Puppeteer.
|Package for parsing HTML or XML documents in “pythonic” way. Allows you to reach all the elements of a specified kind on the page literally in one line of code. Uses html5lib and Lxml parsers, supports Unicode and automatically detects document encoding.
|Tool that gives you an instance of browser to control. Supports XPath selectors to wait until an HTML element is loaded and ready to be clicked, filled with text, scrolled et. c. Separately requires browser driver to be installed. Also can be used in headless mode.
|Unofficial Python port of JS library Puppeteer. Supports async functions.
|Binding for C libraries libxml2 and libxslt provides you ElementTree API for fast XML analyzing. BeautifulSoup uses Lxml as one of its parsers.
|Parser, working with DOM, extracting pages content and manipulating with HTML elements. Supports proxies.
|Headless browser control library, working with HTML and JSON data. Can execute HTTP GET or POST requests and interact with REST API. Uses its own selectors.
|Tool that gives you browser without GUI, emulating most of the common actions and events: clicks, scrolling, form submitting et cetera. Extracts data with XPath selectors.
How to extract data from website: summarize the experience
Remember that selection of web scrapping methods and instruments depends on your skills and requirements, but always try to select the scrapping technique appropriating your task.
Automated data extraction from webpages is a good way to save your time. Just make your choice among existing online parsing services or write your own script to get the information you need fast and easy.