If you are a beginner to web scraping with Python, check out my guides on Extracting Data from HTML with BeautifulSoup and Crawling the Web with Python and Scrapy. Choose the Right Tool Choosing the right tool depends on the type of project you are working on, since Python has a wide variety of libraries and frameworks for web scraping. Web scraping is one of the tools at a developer’s disposal when looking to gather data from the internet. While consuming data via an API has become commonplace, most of the websites online don’t have an API for delivering data to consumers. Since Scrapy and Beautiful Soup are top 2 web scraping framework developed by python, I will mainly focus on talking about Beautiful Soup and Scrapy here.
Web scraping, web crawling, html scraping, and any other form of web data extraction can be complicated. Between obtaining the correct page source, to parsing the source correctly, rendering javascript, and obtaining data in a usable form, there’s a lot of work to be done. Different users have very different needs, and there are tools out there for all of them, people who want to build web scrapers without coding, developers who want to build web crawlers to crawl large sites, and everything in between. Here is our list of the 10 best web scraping tools on the market right now, from open source projects to hosted SAAS solutions to desktop software, there is sure to be something for everyone looking to make use of web data!
1. Scraper API
NET Framework 4.7.1 or higher Important Twitter may restrict search results, so it is suggested to use very specific search criteria to get more, deeper & better results while scraping data from it. Scrapy is the most popular and arguably the best web scraping framework publicly available as an open-source tool. It was created and still being managed extensively by Scrapinghub. Scrapy is a complete framework as it takes care of both sending requests and parsing the required data out of.
Website: https://www.scraperapi.com/
Who is this for: Scraper API is a tool for developers building web scrapers, it handles proxies, browsers, and CAPTCHAs so developers can get the raw HTML from any website with a simple API call.
Why you should use it: Scraper API is a tool for developers building web scrapers, it handles proxies, browsers, and CAPTCHAs so developers can get the raw HTML from any website with a simple API call. It doesn’t burden you with managing your own proxies, it manages its own internal pool of over a hundreds of thousands of proxies from a dozen different proxy providers, and has smart routing logic that routes requests through different subnets and automatically throttles requests in order to avoid IP bans and CAPTCHAs. It’s the ultimate web scraping service for developers, with special pools of proxies for ecommerce price scraping, search engine scraping, social media scraping, sneaker scraping, ticket scraping and more! If you need to scrape millions of pages a month, you can use this form to ask for a volume discount.
2. ScrapeSimple
Website: https://www.scrapesimple.com
Who is this for: ScrapeSimple is the perfect service for people who want a custom scraper built for them. Web scraping is made as simple as filling out a form with instructions for what kind of data you want.
Why you should use it: ScrapeSimple lives up to its name with a fully managed service that builds and maintains custom web scrapers for customers. Just tell them what information you need from which sites, and they will design a custom web scraper to deliver the information to you periodically (could be daily, weekly, monthly, or whatever) in CSV format directly to your inbox. This service is perfect for businesses that just want a html scraper without needing to write any code themselves. Response times are quick and the service is incredibly friendly and helpful, making this service perfect for people who just want the full data extraction process taken care of for them.
3. Octoparse
Website: https://www.octoparse.com/
Who is this for: Octoparse is a fantastic tool for people who want to extract data from websites without having to code, while still having control over the full process with their easy to use user interface.
Why you should use it: Octoparse is the perfect tool for people who want to scrape websites without learning to code. It features a point and click screen scraper, allowing users to scrape behind login forms, fill in forms, input search terms, scroll through infinite scroll, render javascript, and more. It also includes a site parser and a hosted solution for users who want to run their scrapers in the cloud. Best of all, it comes with a generous free tier allowing users to build up to 10 crawlers for free. For enterprise level customers, they also offer fully customized crawlers and managed solutions where they take care of running everything for you and just deliver the data to you directly.
4. ParseHub
Website: https://www.parsehub.com/
Who is this for: Parsehub is an incredibly powerful tool for building web scrapers without coding. It is used by analysts, journalists, data scientists, and everyone in between.
Why you should use it: Parsehub is dead simple to use, you can build web scrapers simply by clicking on the data that you want. It then exports the data in JSON or Excel format. It has many handy features such as automatic IP rotation, allowing scraping behind login walls, going through dropdowns and tabs, getting data from tables and maps, and much much more. In addition, it has a generous free tier, allowing users to scrape up to 200 pages of data in just 40 minutes! Parsehub is also nice in that it provies desktop clients for Windows, Mac OS, and Linux, so you can use them from your computer no matter what system you’re running.
5. Scrapy
Website: https://scrapy.org
Who is this for: Scrapy is a web scraping library for Python developers looking to build scalable web crawlers. It’s a full on web crawling framework that handles all of the plumbing (queueing requests, proxy middleware, etc.) that makes building web crawlers difficult.
Why you should use it: As an open source tool, Scrapy is completely free. It is battle tested, and has been one of the most popular Python libraries for years, and it’s probably the best python web scraping tool for new applications. It is well documented and there are many tutorials on how to get started. In addition, deploying the crawlers is very simple and reliable, the processes can run themselves once they are set up. As a fully featured web scraping framework, there are many middleware modules available to integrate various tools and handle various use cases (handling cookies, user agents, etc.).
6. Diffbot
Website: https://www.diffbot.com
Who is this for: Enterprises who who have specific data crawling and screen scraping needs, particularly those who scrape websites that often change their HTML structure.
Why you should use it: Diffbot is different from most page scraping tools out there in that it uses computer vision (instead of html parsing) to identify relevant information on a page. This means that even if the HTML structure of a page changes, your web scrapers will not break as long as the page looks the same visually. This is an incredible feature for long running mission critical web scraping jobs. While they may be a bit pricy (the cheapest plan is $299/month), they do a great job offering a premium service that may make it worth it for large customers.
7. Cheerio
Website: https://cheerio.js.org
Who is this for: NodeJS developers who want a straightforward way to parse HTML. Those familiar with jQuery will immediately appreciate the best javascript web scraping syntax available.
Why you should use it: Cheerio offers an API similar to jQuery, so developers familiar with jQuery will immediately feel at home using Cheerio to parse HTML. It is blazing fast, and offers many helpful methods to extract text, html, classes, ids, and more. It is by far the most popular HTML parsing library written in NodeJS, and is probably the best NodeJS web scraping tool or javascript web scraping tool for new projects.
8. BeautifulSoup
Website: https://www.crummy.com/software/BeautifulSoup/
Who is this for: Python developers who just want an easy interface to parse HTML, and don’t necessarily need the power and complexity that comes with Scrapy.
Why you should use it: Like Cheerio for NodeJS developers, Beautiful Soup is by far the most popular HTML parser for Python developers. It’s been around for over a decade now and is extremely well documented, with many web parsing tutorials teaching developers to use it to scrape various websites in both Python 2 and Python 3. If you are looking for a Python HTML parsing library, this is the one you want.
9. Puppeteer
Website: https://github.com/GoogleChrome/puppeteer
Who is this for: Puppeteer is a headless Chrome API for NodeJS developers who want very granular control over their scraping activity.
Why you should use it: As an open source tool, Puppeteer is completely free. It is well supported and actively being developed and backed by the Google Chrome team itself. It is quickly replacing Selenium and PhantomJS as the default headless browser automation tool. It has a well thought out API, and automatically installs a compatible Chromium binary as part of its setup process, meaning you don’t have to keep track of browser versions yourself. While it’s much more than just a web crawling library, it’s often used to scrape website data from sites that require javascript to display information, it handles scripts, stylesheets, and fonts just like a real browser. Note that while it is a great solution for sites that require javascript to display data, it is very CPU and memory intensive, so using it for sites where a full blown browser is not necessary is probably not a great idea. Most times a simple GET request should do the trick!
10. Mozenda
Website: https://www.mozenda.com/
Who is this for: Enterprises looking for a cloud based self serve webpage scraping platform need look no further. With over 7 billion pages scraped, Mozenda has experience in serving enterprise customers from all around the world.
Why you should use it: Mozenda allows enterprise customers to run web scrapers on their robust cloud platform. They set themselves apart with the customer service (providing both phone and email support to all paying customers). Its platform is highly scalable and will allow for on premise hosting as well. Like Diffbot, they are a bit pricy, and their lowest plans start at $250/month.
Honorable Mention 1. Kimura
Website: https://github.com/vifreefly/kimuraframework
Who is this for: Kimura is an open source web scraping framework written in Ruby, it makes it incredibly easy to get a Ruby web scraper up and running.
Why you should use it: Kimura is quickly becoming known as the best Ruby web scraping library, as it’s designed to work with headless Chrome/Firefox, PhantomJS, and normal GET requests all out of the box. It’s syntax is similar to Scrapy and developers writing Ruby web scrapers will love all of the nice configuration options to do things like set a delay, rotate user agents, and set default headers.
Honorable Mention 2. Goutte
Website: https://github.com/FriendsOfPHP/Goutte
Who is this for: Goutte is an open source web crawling framework written in PHP, it makes it super easy extract data from the HTML/XML responses using PHP.
Why you should use it: Goutte is a very straight forward, no frills framework that is considered by many to be the best PHP web scraping library, as it’s designed for simplicity, handling the vast majority of HTML/XML use cases without too much additional cruft. It also seamlessly integrates with the excellent Guzzle requests library, which allows you to customize the framework for more advanced use cases.
The open web is by far the greatest global repository for human knowledge, there is almost no information that you can’t find through extracting web data. Because web scraping is done by many people of various levels of technical ability and know how, there are many tools available that service everyone from people who don’t want to write any code to seasoned developers just looking for the best open source solution in their language of choice.
Hopefully, this list of tools has been helpful in letting you take advantage of this information for your own projects and businesses. If you have any web scraping jobs you would like to discuss with us, please contact us here. Happy scraping!
C# is still a popular backend programming language, and you might find yourself in need of it for scraping a web page (or multiple pages). In this article, we will cover scraping with C# using an HTTP request, parsing the results, and then extracting the information that you want to save. This method is common with basic scraping, but you will sometimes come across single-page web applications built in JavaScript such as Node.js, which require a different approach. We’ll also cover scraping these pages using PuppeteerSharp, Selenium WebDriver, and Headless Chrome.
Note: This article assumes that the reader is familiar with C# syntax and HTTP request libraries. The PuppeteerSharp and Selenium WebDriver .NET libraries are available to make integration of Headless Chrome easier for developers. Also, this project is using .NET Core 3.1 framework and the HTML Agility Pack for parsing raw HTML.
Part I: Static Pages
Setup
If you’re using C# as a language, you probably already use Visual Studio. This article uses a simple .NET Core Web Application project using MVC (Model View Controller). After you create a new project, go to the NuGet Package Manager where you can add the necessary libraries used throughout this tutorial.
In NuGet, click the “Browse” tab and then type “HTML Agility Pack” to find the dependency.
Install the package, and then you’re ready to go. This package makes it easy to parse the downloaded HTML and find tags and information that you want to save.
Finally, before you get started with coding the scraper, you need the following libraries added to the codebase:
Making an HTTP Request to a Web Page in C#
Imagine that you have a scraping project where you need to scrape Wikipedia for information on famous programmers. Wikipedia has a page with a list of famous programmers with links to each profile page. You can scrape this list and add it to a CSV file (or Excel spreadsheet) to save for future review and use. This is just one simple example of what you can do with web scraping, but the general concept is to find a site that has the information you need, use C# to scrape the content, and store it for later use. In more complex projects, you can crawl pages using the links found on a top category page.
Using .NET HTTP Libraries to Retrieve HTML
.NET Core introduced asynchronous HTTP request libraries to the framework. These libraries are native to .NET, so no additional libraries are needed for basic requests. Before you make the request, you need to build the URL and store it in a variable. Because we already know the page that we want to scrape, a simple URL variable can be added to the HomeController’s Index() method. The HomeController Index() method is the default call when you first open an MVC web application.
Add the following code to the Index() method in the HomeController file:
Using .NET HTTP libraries, a static asynchronous task is returned from the request, so it’s easier to put the request functionality in its own static method. Add the following method to the HomeController file:
Let’s break down each line of code in the above CallUrl() method.
This statement creates an HttpClient variable, which is an object from the native .NET framework.
If you get HTTPS handshake errors, it’s likely because you are not using the right cryptographic library. The above statement forces the connection to use the TLS 1.3 library so that an HTTPS handshake can be established. Note that TLS 1.3 is deprecated but some web servers do not have the latest 2.0+ libraries installed. For this basic task, cryptographic strength is not important but it could be for some other scraping requests involving sensitive data.
This statement clears headers should you decide to add your own. For instance, you might scrape content using an API request that requires a Bearer authorization token. In such a scenario, you would then add a header to the request. For example:
The above would pass the authorization token to the web application server to verify that you have access to the data. Next, we have the last two lines:
These two statements retrieve the HTML content, await the response (remember this is asynchronous) and return it to the HomeController’s Index() method where it was called. The following code is what your Index() method should contain (for now):
The code to make the HTTP request is done. We still haven’t parsed it yet, but now is a good time to run the code to ensure that the Wikipedia HTML is returned instead of any errors. Make sure you set a breakpoint in the Index() method at the following line:
This will ensure that you can use the Visual Studio debugger UI to view the results.
You can test the above code by clicking the “Run” button in the Visual Studio menu:
Visual Studio will stop at the breakpoint, and now you can view the results.
If you click “HTML Visualizer” from the context menu, you can see a raw HTML view of the results, but you can see a quick preview by just hovering your mouse over the variable. You can see that HTML was returned, which means that an error did not occur.
Parsing the HTML
With the HTML retrieved, it’s time to parse it. HTML Agility Pack is a common tool, but you may have your own preference. Even LINQ can be used to query HTML, but for this example and for ease of use, the Agility Pack is preferred and what we will use.
Before you parse the HTML, you need to know a little bit about the structure of the page so that you know what to use as markers for your parsing to extract only what you want and not every link on the page. You can get this information using the Chrome Inspect function. In this example, the page has a table of contents links at the top that we don’t want to include in our list. You can also take note that every link is contained within an <li> element.
From the above inspection, we know that we want the content within the “li” element but not the ones with the tocsection class attribute. With the Agility Pack, we can eliminate them from the list.
We will parse the document in its own method in the HomeController, so create a new method named ParseHtml() and add the following code to it:
In the above code, a generic list of strings (the links) is created from the parsed HTML with a list of links to famous programmers on the selected Wikipedia page. We use LINQ to eliminate the table of content links, so now we just have the HTML content with links to programmer profiles on Wikipedia. We use .NET’s native functionality in the foreach loop to parse the first anchor tag that contains the link to the programmer profile. Because Wikipedia uses relative links in the href attribute, we manually create the absolute URL to add convenience when a reader goes into the list to click each link.
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Exporting Scraped Data to a File
The code above opens the Wikipedia page and parses the HTML. We now have a generic list of links from the page. Now, we need to export the links to a CSV file. We’ll make another method named WriteToCsv() to write data from the generic list to a file. The following code is the full method that writes the extracted links to a file named “links.csv” and stores it on the local disk.
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The above code is all it takes to write data to a file on local storage using native .NET framework libraries.
The full HomeController code for this scraping section is below.
Part II: Scraping Dynamic JavaScript Pages
In the previous section, data was easily available to our scraper because the HTML was constructed and returned to the scraper the same way a browser would receive data. Newer JavaScript technologies such as Vue.js render pages using dynamic JavaScript code. When a page uses this type of technology, a basic HTTP request won’t return HTML to parse. Instead, you need to parse data from the JavaScript rendered in the browser.
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Dynamic JavaScript isn’t the only issue. Some sites detect if JavaScript is enabled or evaluate the UserAgent value sent by the browser. The UserAgent header is a value that tells the web server the type of browser being used to access pages (e.g. Chrome, FireFox, etc). If you use web scraper code, no UserAgent is sent and many web servers will return different content based on UserAgent values. Some web servers will use JavaScript to detect when a request is not from a human user.
You can overcome this issue using libraries that leverage Headless Chrome to render the page and then parse the results. We’re introducing two libraries freely available from NuGet that can be used in conjunction with Headless Chrome to parse results. PuppeteerSharp is the first solution we use that makes asynchronous calls to a web page. The other solution is Selenium WebDriver, which is a common tool used in automated testing of web applications.
Using PuppeteerSharp with Headless Chrome
For this example, we will add the asynchronous code directly into the HomeController’s Index() method. This requires a small change to the default Index() method shown in the code below.
In addition to the Index() method changes, you must also add the library reference to the top of your HomeController code. Before you can use Puppeteer, you first must install the library from NuGet and then add the following line in your using statements:
Now, it’s time to add your HTTP request and parsing code. In this example, we’ll extract all URLs (the <a> tag) from the page. Add the following code to the HomeController to pull the page source in Headless Chrome, making it available for us to extract links (note the change in the Index() method, which replaces the same method in the previous section example):
Similar to the previous example, the links found on the page were extracted and stored in a generic list named programmerLinks. Notice that the path to chrome.exe is added to the options variable. If you don’t specify the executable path, Puppeteer will be unable to initialize Headless Chrome.
Using Selenium with Headless Chrome
If you don’t want to use Puppeteer, you can use Selenium WebDriver. Selenium is a common tool used in automation testing on web applications, because in addition to rendering dynamic JavaScript code, it can also be used to emulate human actions such as clicks on a link or button. To use this solution, you need to go to NuGet and install Selenium.WebDriver and (to use Headless Chrome) Selenium.WebDriver.ChromeDriver. Note: Selenium also has drivers for other popular browsers such as FireFox.
Add the following library to the using statements:
Now, you can add the code that will open a page and extract all links from the results. The following code demonstrates how to extract links and add them to a generic list.
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Notice that the Selenium solution is not asynchronous, so if you have a large pool of links and actions to take on a page, it will freeze your program until the scraping completes. This is the main difference between the previous solution using Puppeteer and Selenium.
Conclusion
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Web scraping is a powerful tool for developers who need to obtain large amounts of data from a web application. With pre-packaged dependencies, you can turn a difficult process into only a few lines of code.
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One issue we didn’t cover is getting blocked either from remote rate limits or blocks put on bot detection. Your code would be considered a bot by some applications that want to limit the number of bots accessing data. Our web scraping API can overcome this limitation so that developers can focus on parsing HTML and obtaining data rather than determining remote blocks.