Web scraping is one of the most important skills you need to hone as a data scientist; you need to know how to look for, collect and clean your data so your results are accurate and meaningful. When you want to choose a tool to scrape the web, there are some factors you need to consider such as API integration and large-scale scraping extendability. This article presents you with six tools that you can use for different data collection projects.
6 Free Web Scraping Tools
- Common Crawl
- Content Grabber
The good news is that web scraping doesn’t have to be tedious; you don’t even need to spend much time doing it manually. Using the correct tool can help save you a lot of time, money and effort. Moreover, these tools can be beneficial for analysts or people without much (or any) coding experience.
It’s worth noting that the legality of web scraping has been called into question, so before we dive deeper into tools that can help your data extraction tasks, let’s make sure that your activity is fully legal. In 2020, the US court fully legalized web scraping publicly available data. That is, if anyone can find the data online (such as in Wiki articles), then it’s legal to scrape it.
Is Your Web Scraping Legal?
- Don’t reuse or republish the data in a way that violates copyright.
- Respect the terms of services for the site you’re trying to scrape.
- Have a reasonable crawl-rate.
- Don’t try to scrape private areas of the website.
As long as you don’t violate any of those terms, your web scraping activity should be on the legal side. But don’t take my word for it.
If you’ve ever constructed a data science project using Python, then you probably used BeatifulSoup to collect your data and Pandas to analyze it. This article will present you with six web scraping tools that don’t include BeatifulSoup, but will help you collect the data you need for your next project, for free.
1. Common Crawl
The creator of Common Crawl developed this tool because they believe everyone should have the chance to explore and analyze the world around them to uncover patterns. They offer high-quality data that was previously only available for large corporations and research institutes to any curious mind free of charge to support the open-source community.
This means, if you are a university student, a person navigating your way in data science, a researcher looking for your next topic of interest or just a curious person that loves to reveal patterns and find trends, you can use Common Crawl without worrying about fees or any other financial complications.
Common Crawl provides open data sets of raw web page data and text extractions. It also offers support for non-code based usage cases and resources for educators teaching data analysis.
Crawly is another amazing choice, especially if you only need to extract basic data from a website or if you want to extract data in CSV format so you can analyze it without writing any code.
All you need to do is input a URL, your email address (so they can send you the extracted data) and the format you want your data (CSV or JSON). Voila! The scraped data is in your inbox for you to use. You can use the JSON format and then analyze the data in Python using Pandas and Matplotlib, or in any other programming language.
Although Crawly is perfect if you’re not a programmer, or you’re just starting with data science and web scraping, it has its limitations. Crawly can only extract a limited set of HTML tags including, title, author, image URL and publisher.
3. Content Grabber
Content Grabber is one of my favorite web scraping tools because it’s very flexible. If you want to scrape a webpage and don’t want to specify any other parameters you can do so using their simple GUI (graphical user interface). However, if you want to have full control over the extraction parameters, Content Grabber gives you the option to do that, too
One of Content Grabber’s advantages is you can schedule it to scrape information from the web automatically. As we all know, most webpages update regularly, so having a regular content extraction can be quite beneficial.
Content Grabber also offers a wide variety of formats for the extracted data, from CSV to JSON to SQL Server or MySQL.
Webhose.io is a web scraper that allows you to extract enterprise-level, real-time data from any online resource. The data collected by Webhose.io is structured, clean, contains sentiment and entity recognition, and available in different formats such as XML, RSS and JSON.
Webhose.io offers comprehensive data coverage for any public website. Moreover, it offers many filters to refine your extracted data so you can perform fewer cleaning tasks and jump straight into the analysis phase.
The free version of Webhose.io provides 1000 HTTP requests per month. Paid plans offer more calls, power over the extracted data and more benefits such as image analytics, geolocation and up to 10 years of archived historical data.
ParseHub is a potent web scraping tool that anyone can use free of charge. It offers reliable, accurate data extraction with the click of a button. You can also schedule scraping times to keep your data up to date.
One of ParseHub’s strengths is that it can scrape even the most complex of webpages hassle free. You can even instruct it to search forms, menus, login to websites and even click on images or maps for a further collection of data.
You can also provide ParseHub with various links and some keywords, and it will extract relevant information within seconds. Finally, you can use REST API to download the extracted data for analysis in either JSON or CSV formats. You can also export the data collected as a Google Sheet or Tableau.
Scrapingbee can be used in one of three ways:
- General Web Scraping such as extracting stock prices or customer reviews
- Search Engine Result Page (SERP), which you can use for SEO or keyword monitoring
- Growth Hacking, which can include extracting contact information or social media information
Scrapingbee offers a free plan that includes 1000 credits and paid plans for unlimited use.
Collecting data for your projects is perhaps the least fun and most tedious step during a data science project workflow. This task could be quite time consuming. If you work in a company or even freelance, you know that time is money, which always means that if there’s a more efficient way to do something, you better do it.