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Web Scraping

Web scraping is commonly used as a means to collect and analyze data available on the web. In recent years, several web scraping frameworks have been released to help in this process and serve specific use cases as well. In this article, we will cover a list of leading open source scraping solutions apart from Scrapy.

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What is Scrapy?

Scrapy has long been counted as a very popular free and open source web scraping framework. Although initially, it was only supposed to crawl the web, it can also be used for extracting data using APIs. It uses the concept of multiple “spiders”- self-contained crawlers each having a set of instructions. Although it is a python library, it also has an interactive shell script for non-python developers, but then its coding opportunities are limited to Python.

Here are some key benefits of Scrapy:

  • Powerful performance
  • Efficient memory usage
  • Built-in blocks for various components of scraping
  • Easy to use features with exhaustive selectors support
  • Customizable system with option to add custom middleware or custom functionality pipeline
  • Portable
  • Offers its cloud environment for processes that consume significantly higher resource

However, a steep learning curve and it’s language based limitations has brought us to some other alternative ways to crawl data for your business.

Scrapy Alternatives

Here is a list of popular open source web scraping frameworks:

MechanicalSoup
This framework is quite capable of replicating behavior that humans perform on web pages. It has been built on top of a popular web parsing library called BeautifulSoup which is very efficient for simple sites.

Salient points:

  • Neat library with very less overhead of code
  • Blazing fast when it comes to parsing simpler pages
  • Ability to simulate human behavior
  • Support CSS & XPath selectors

MechanicalSoup is the right choice when you try to implement real user actions like waiting for a particular event or click exact items to open a popup instead of simply collecting data from web pages.

Portia

Portia, an open source visual scraping tool which uses annotations to extract data from web pages. No prior programming knowledge is required to use it. Annotating pages you’re interested in will enable Portia to create a spider to extract data from similar pages.

This visual scraping engine needs no knowledge of programming. If you are not a developer, it’s best for your web scraping needs to go directly with Portia. Without installing anything, you can try Portia for free, all you have to do is register for an account and use the hosted version.

Key pointers for Portia:

  • The time required for set up can be relatively high
  • You can select the XPath or CSS
  • Different user actions like clicking, waiting and scrolling can be configured

BeautifulSoup

Having personally used BeautifulSoup, I can vouch for the fact that this python library is a hit among developers scraping data from web pages. Using the requests library, one can request a web-page (while sending Chrome or Firefox headers to avoid detection), download the HTML page locally and then parse and crawl it using BeautifulSoup. The library basically converts an HTML page into a tree-like format and you can easily specify a particular node structure to extract all the data from similar nodes. It is a free and “open to all” library that is used in many experimental projects.

Key benefits of BeautifulSoup:

  • Ability to parse data from misconfigured XML and HTML
  • The leading parser in this particular use case
  • Straightforward integration with third-party solutions
  • Quite lightweight in terms of resource consumption
  • Out-of-the-box solution for filtering and searching functions

Selenium

Although hailed by most as a tool that automates browser functionalities, Selenium is also popular in the field of web scraping. Selenium helps in the automation of Python scripts that interact with a web browser. Using web driver for Chrome along with Selenium, it is easy to set up automated scraping algorithms as long as you have some basic knowledge of python and the intent to dive deep into the code.

Also, when it comes to websites that use a very complicated and unorganized code, first use a browser to generate all the page content. Selenium WebDriver uses a real web browser to access the website so that it does not appear like its activity is any different from a real person normally browsing web pages. The browser loads all the assets of the web pages via Web Driver and executes JavaScript. Also, it sends the complete HTTP response, its distinction from normal or real user browsing behavior becomes very difficult.

Things to consider with Selenium:

  • Very useful from extracting data web pages that predominantly use JavaScript
  • A strong and massive user base
  • Easy to follow and comprehensive knowledge base suitable for novice users
  • Difficult to update the project based on website page structure changes
  • Resource intensive (processing power) framework

Jauntium

Jauntium is a relatively new Java library that helps you easily automate Chrome, Firefox, Safari, Edge, IE, and other modern web browsers. With Jauntium, Java programs can perform web-scraping and web-automation with full javascript support. The library is named ‘Jauntium’ because it builds on both Jaunt and Selenium to address the issues of each.

Here are the key benefits of Jauntium:

  • create web-bots or web-scraping programs
  • search/manipulate the DOM
  • work with tables and forms
  • write automated tests
    enhance your existing Selenium project

node-crawler

Nodecrawler is a famous NodeJS web crawler, making it a crawling solution that is very quick. If you favor JavaScript engineering, or you’re mainly working with a Javascript project, Nodecrawler will be the most appropriate web crawler to use. Its setup is also quite easy. It is used for server-side rendering by JSDOM and Cheerio (used mostly for HTML parsing), with JSDOM being more powerful.

Its primary benefit is its ease of use and efficiency in handling server-side JavaScript along with JQuery.

Puppeteer

Puppeteer is a node library that offers you with a strong but easy API to control the headless Chrome browser of Google. A headless browser implies that you have a browser capable of sending and receiving applications, but without a GUI. It operates in the background, as instructed by an API, performing activities. You can replicate the experience of the user, to the point of typing and clicking.

The best scenario to use Puppeteer for web scraping is if you use a mixture of API data and Javascript code to generate the information you want. A headless browser is a excellent instrument for automated testing and server settings where there is no need for a visible shell of the UI. you might want to run some experiments on a genuine web page, generate a PDF, or just check how the browser makes a URL. Puppeteer can also be configured to open a web browser and take screenshots of web pages that are noticeable by default.

Puppeteer’s API works similar to Selenium WebDriver, but compatible only with Google Chrome unlike WebDriver. Puppeteer should be your preferred framework if you are working with Chrome as it has strong support for Chrome.

PyQuery

PyQuery is a jquery-like library for python, that allows you to make queries on XML documents, using LXML for fast XML and HTML manipulation. It works in a manner similar to BeautifulSoup, where you download the HTML page into your local system and then extract certain parts of it using python code.

Web-Harvest

Web-harvest an open source web data extraction tool written in Java. It uses techniques of text and XML manipulations like XSLT, XQuery, and Regular Expressions. Its main use is in HTML/XML based web sites that still make up most of the web content. At the same time, you could use other Java libraries in conjunction with it, to boost its capabilities.

Go_Spider

Go_spider is an open source web scraping framework written in a more recent programming language- Golang (also called GO, and developed by Google).

Its benefits include:

  • Supports concurrency
  • Better fit for verticals
  • Flexible and modular
  • Written in Native GO
  • Can be customised based on a company’s requirements.

Conclusion

So you can see that there are multiple free web crawling frameworks available in the market. However, setting up a dedicated crawling team and maintaining it is tough, leave alone the infrastructure requirements and cost.
It is much better to take the help of a service provider to whom you will hand over your requirements, and who will, in turn, get back to you with the data in a useable and plug and play format. This is where PromptCloud comes in. PromptCloud is a unique web crawling service that prefers to call itself a DaaS provider. We have an online requirement submission engine called CrawlBoard which you can use to specify your web scraping requirements and the rest will be taken care of by our team. We pride ourselves in building the end to end pipeline – from building and maintaining the crawler to cleaning, normalising and maintaining the quality of the data.

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