- Online Web Scraper
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Web scraping tools are designed to grab the information needed on the website. Such tools can save a lot of time for data extraction.
Here is a list of 10 recommended tools with better functionality and effectiveness.
1. ScrapeStorm
How to use Web Scraper? There are only a couple of steps you will need to learn in order to master web scraping: 1. Install Web Scraper and open Web Scraper tab in developer tools (which has to be placed at the bottom of the screen for Web Scraper to be visible); 2. Create a new sitemap; 3. Add data extraction selectors to the sitemap; 4. Web Scraper allows you to build Site Maps from different types of selectors. This system makes it possible to tailor data extraction to different site structures. Export data in CSV, XLSX and JSON formats. Build scrapers, scrape sites and export data in CSV format directly from your browser. Use Web Scraper Cloud to export data in CSV, XLSX. Data Scraper is a simple and free web scraping tool for extracting data from a single page into CSV and XSL data files. It is a personal browser extension that helps you transform data into a clean table format. You will need to install the plugin in a Google Chrome browser.
ScrapeStorm is an AI-Powered visual web scraping tool，which can be used to extract data from almost any websites without writing any code.
It is powerful and very easy to use. You only need to enter the URLs, it can intelligently identify the content and next page button, no complicated configuration, one-click scraping.
ScrapeStorm is a desktop app available for Windows, Mac, and Linux users. You can download the results in various formats including Excel, HTML, Txt and CSV. Moreover, you can export data to databases and websites.
Features:
1) Intelligent identification
2) IP Rotation and Verification Code Identification
Octoparse is a free web scraper tool. It allows you to extract data from websites without coding and turn webpages into structured data within clicks. Web Scraper utilizes a modular structure that is made of selectors, which instructs the scraper on how to traverse the target site and what data to extract. Thanks to this structure, Web Scraper is able to extract information from modern and dynamic websites such as Amazon, Tripadvisor, eBay, and so on, as well as from smaller, lesser-known.
3) Data Processing and Deduplication
4) File Download
5) Scheduled task
6) Automatic Export
7) RESTful API and Webhook
8) Automatic Identification of E-commerce SKU and big images
Pros:
1) Easy to use
2) Fair price
3) Visual point and click operation
4) All systems supported
Cons:
No cloud services
2.ScrapingHub
Scrapinghub is the developer-focused web scraping platform to offer several useful services to extract structured information from the Internet.
Scrapinghub has four major tools – Scrapy Cloud, Portia, Crawlera, and Splash.
Features:
1) Allows you to converts the entire web page into organized content
2) JS on-page support toggle
3) Handling Captchas
Pros:
1) Offer a collection of IP addresses covered more than 50 countries which is a solution for IP ban problems
2) The temporal charts were very useful
3) Handling login forms
4) The free plan retains extracted data in cloud for 7 days
Cons:
1) No Refunds
2) Not easy to use and needs to add many extensive add-ons
3) Can not process heavy sets of data
3.Import.io
Import.io is a platform which facilitates the conversion of semi-structured information in web pages into structured data, which can be used for anything from driving business decisions to integration with apps and other platforms.
They offer real-time data retrieval through their JSON REST-based and streaming APIs, and integration with many common programming languages and data analysis tools.
Features:
1) Point-and-click training
2) Automate web interaction and workflows
3) Easy Schedule data extraction
Pros:
1) Support almost every system
2) Nice clean interface and simple dashboard
3) No coding required
Cons:
1) Overpriced
2) Each sub-page costs credit
4.Dexi.io
Web Scraping & intelligent automation tool for professionals. Dexi.io is the most developed web scraping tool which enables businesses to extract and transform data from any web source through with leading automation and intelligent mining technology.
Dexi.io allows you to scrape or interact with data from any website with human precision. Advanced feature and APIs helps you transform and combine data into powerfull datasets or solutions.
Features:
1) Provide several integrations out of the box
2) Automatically de-duplicate data before sending it to your own systems.
3) Provide the tools when robots fail
Pros:
1) No coding required
2) Agents creation services available
Cons:
1) Difficult for non-developers
2) Trouble in Robot Debugging
5.Diffbot
Diffbot allows you to get various type of useful data from the web without the hassle. You don’t need to pay the expense of costly web scraping or doing manual research. The tool will enable you to exact structured data from any URL with AI extractors.
Features:
1) Query with a Powerful, Precise Language
2) Offers multiple sources of data
3) Provide support to extract structured data from any URL with AI Extractors
4) Comprehensive Knowledge Graph
Pros:
1) Can discover relationship between entities
2) Batch Processing
3) Can query and get the exact answers you need
Cons:
1) Initial output is complex
2) Require a lot of cleaning before being usable
6.Mozenda
Mozenda provides technology, delivered as either software (SaaS and on-premise options) or as a managed service, that allows people to capture unstructured web data, convert it into a structured format, then “publish and format it in a way that companies can use.”
Mozenda Provides: 1) Cloud-hosted software 2) On-premise software 3) Data Services Over 15 years of experience, Mozenda enables you to automate web data extraction from any website.
Features:
1) Scrape websites through different geographical locations.
2) API Acces
3) Point-and-click interface
4) Receive email alerts when agents run successfully
Pros:
1) Visual interface
2) Comprehensive Action Bar
3) Multi-threaded extraction and smart data aggregation
Cons:
1) Unstable when dealing with large websites
2) A bit expensive
7.ParseHub
ParseHub is a visual data extraction tool that anyone can use to get data from the web. You’ll never have to write a web scraper again and can easily create APIs from websites that don’t have them. ParseHub can handle interactive maps, calendars, search, forums, nested comments, infinite scrolling, authentication, dropdowns, forms, Javascript, Ajax and much more with ease. ParseHub offer both a free plan for everyone and custom enterprise plans for massive data extraction.
Features:
1) Scheduled Runs
2) Automatic IP rotation
3) Interactive websites (AJAX & JavaScript)
4) Dropbox integration
5) API & Web-hooks
Pros:
1) Dropbox, S3 integration
2) Support multiple systems
3) Data aggregation from multiple websites
Cons:
1) Free Program Limited
2) Complex user interface
8.Webhose.io
The Webhose.io API provides easy to integrate, high quality data and meta-data, from hundreds of thousands of global online sources like message boards, blogs, reviews, news and more.
Available either by query based API or via firehose, Webhose.io API provides low latency with high coverage data, with an efficient dynamic ability to add new sources at record time.
Features:
1) Get structured, machine-readable datasets in JSON and XML formats
2) Helps you to access a massive repository of data feeds without paying any extra fees
3) Can conduct granular analyze
Pros:
1) Query system is simple to use and consistent across data providers
2) Consistent across data providers
Cons:
1) Has a bit of learning curve
2) Not for businesses and Enterprises
9.WebHarvy
WebHarvy lets you easily extract data from websites to your computer. No programming/scripting knowledge required, WebHarvy works with all websites. You may use WebHarvy to extract data from product listings/eCommerce websites, yellow pages, real estate listings, social networks, forums etc. WebHarvy lets you select the data which you need using mouse clicks, its incredibly easy to use. Scrapes data from multiple pages of listings, following each link.
Features:
1) Point and click interface
2) Safeguard Privacy
Pros:
1) Visual interface
2) No coding required
Cons:
1) Slow speed
2) May lose data after several days of scrapping
3) Scrapping stop from time to time
10. Outwit
OutWit Hub is a Web data extraction software application designed to automatically extract information from online or local resources. It recognizes and grabs links, images, documents, contacts, recurring vocabulary and phrases, rss feeds and converts structured and unstructured data into formatted tables which can be exported to spreadsheets or databases.
Features:
1) Recognition and extraction of links, email addresses, structured & non-structured data, RSS news
2) Extraction & download of images and documents
3) Automated browsing with user-defined Web exploration rules
4) Macro automation
5) Periodical job execution
Pros:
1) No coding required
2) simplistic graphic user interface
Cons:
1) Lack of a point-and-click interface
2) Tutorials need to be improved
11. Scraping-Bot.io
Scraping-Bot.io is an efficient tool to scrape data from a URL. It works particularly well on product pages where it collects all you need to know: image, product title, product price, product description, stock, delivery costs, EAN, product category, brand, colour, etc… You can also use it to check your ranking on google and improve your SEO. Use the Live test on their Home page to test without coding.
Features:
1) JS rendering (Headless Chrome)
2) High quality proxies
3) Full Page HTML
4) Geotargeting
Pros:
1) Allows for large bulk scraping needs
2) Free basic usage monthly plan
3) Parsed data for ecommerce product pages (price, currency, EAN, etc.)
Cons:
1) Not adapted for non-developers
2) API: No user interface
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.
Online Web Scraper
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.
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.
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
Best Web Scraper Free
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.
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
Best Web Scraper Software
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.
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.
Best Web Scraper Library
Conclusion
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.
Best Web Scraper Language
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.