Top 17 Web Scraping Tools for Data Extraction in 2023. 2023 Top 10 Best Web Scraping Tools for Data Extraction | Web Scraping Tool | ScrapeStorm

Top 17 Web Scraping Tools for Data Extraction in 2023. 2023 Top 10 Best Web Scraping Tools for Data Extraction | Web Scraping Tool | ScrapeStorm

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Abstract： This article will introduce the top10 best web scraping tools in 2023. ScrapeStorm Free Download

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

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

3) Data Processing and Deduplication

4) File Download

5) Scheduled task

6) Automatic Export

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.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

4.Diffbot

https://www.youtube.com/embed/qH9VYKxU1NI
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.

Scrapy. Introducing Scrapy

A framework is a reusable, “semi-complete” application that can be specialized to produce custom applications. (Source: Johnson & Foote, 1988 )

In other words, the Scrapy framework provides a set of Python scripts that contain most of the code required to use Python for web scraping. We need only to add the last bit of code required to tell Python what pages to visit, what information to extract from those pages, and what to do with it. Scrapy also comes with a set of scripts to setup a new project and to control the scrapers that we will create.

It also means that Scrapy doesn’t work on its own. It requires a working Python installation (Python 2.7 and higher or 3.4 and higher - it should work in both Python 2 and 3), and a series of libraries to work. If you haven’t installed Python or Scrapy on your machine, you can refer to the setup instructions . If you install Scrapy as suggested there, it should take care to install all required libraries as well.

scrapy version

in a shell. If all is good, you should get the following back (as of February 2017):

Scrapy 2.1.0

If you have a newer version, you should be fine as well.

To introduce the use of Scrapy, we will reuse the same example we used in the previous section. We will start by scraping a list of URLs from the list of faculty of the Psychological & Brain Sciences and then visit those URLs to scrape detailed information about those faculty members.