Top 10 Web scraping tools in 2023. What Is Web Scraping?

Top 10 Web scraping tools in 2023. What Is Web Scraping?

Web scraping is a method to collect or extract data from any website. Webscraper extracts HTML structure, tables, images, and text from the website and stores it in the format of choice.

Web Scraping can be used for multiple use cases like competitive intelligence, creating a database, maintaining real-time updates, and more. Web scraping tools help businesses and individuals automate the entire web scraping process while using advanced features like IP proxy rotation, automated data enhancement, and integrations.

Scrape any webpage in seconds using the Nanonets website scraping tool . It’s free. Try now.

Given below are the best web scraper tools :

#1. Smartproxy

Smartproxy is one of the best web scraper tools that extract data and content from websites instantly and effortlessly. It provides the data in the form of raw HTML from websites. It accomplishes this task by sending an API request. Not only this, but this tool also keeps on sending requests so that the data or content required by the company should be extracted with utmost accuracy.

Key Features of Smartproxy:

• Provides real-time data collection
• Provides real-time proxy-like integration
• Data extracted in raw HTML

Pros of Smartproxy:

• Global proxies power this tool.
• Provides live customer support to the users
• No CAPTCHAs as it comes with advanced proxy rotation

Cons of Smartproxy:

• It does not allow for web elements to be rendered
• Expensive plan
• Should incorporate more auto extractors
• Requests could get a timeout

#2. Nanonets Web Scraping Tool

Nanonets has a powerful OCR API that can scrape webpages with 100% accuracy. It can detect images, tables, text and characters with highest accuracy. What differentiates Nanonets from other tools is the ability to automate web scraping using automated workflows.

Users can set up workflows to automatically scrape webpages, format the extracted data and then export the scraped data to 500+ integrations at a click of a button.

Key Features of Nanonets:

• Provides real-time data extraction from any kind of webpage
• Extracts HTML tables with high accuracy
• Format data automatically

Pros of Nanonets:

• 24×7 live support
• Can extract data from all types of webpages – Java, Headless or Static Pages
• No-code user interface
• Workflow automation is possible

Cons of Nanonets:

• Can’t scrape images and videos

#3. Scraper API

Scraper API allows easy integration; you just need to get a request and a URL. Moreover, users can get more advanced use cases in the documentation. It also provides geo-located rotating proxies, which help route the request through the proxies.

Features of Scraper API:

• Allows easy integration
• Allows users to scrape JavaScript-rendered pages as well

Pros of Scraper API:

• Easy to use
• Completely customizable
• It is fast and reliable

Cons of Scraper API:

• There are some websites where this tool does not function
• It is a bit costly
• Some features, such as javascript scraping, are very expensive
• Should enhance the ability to scale the plan’s calls

#4. Web Scraper

Web Scraper is a web scraping provides a cloud-based platform for accessing the extracted data. It has an easy-to-use interface, so it can also be used by beginners. Also, it allows extracting data or content even from dynamic websites.

Video Scraper. Vget for YouTube:

Although there are loads of plugins for Chrome browser you can use to download videos from YouTube, like this one saveFrom Hleper which I’m using. It’s quite versatile, not only for YouTube,but also for any online video-site else and quite well get along with the browser. Just like this:

Two new buttons attached on the page. However, the shortage is that you have to manually download the videos one by one. If you want to download a channel’s all videos the arduous work emerged. ———– What I want it is using the YouTube API to retrieve all the videos’ address and input them into program and analysis their addresses and download. After searching in Google, I found Vget Home which is what I want. You can read through examples list on that page. Essentially, this lib using YouTubeParser.java to extract video link via matching regex.

Video Scraper. Vget for YouTube:

Although there are loads of plugins for Chrome browser you can use to download videos from YouTube, like this one saveFrom Hleper which I’m using.

It’s quite versatile, not only for YouTube, but also for any online video-site else and quite well get along with the browser.

Just like this:

However, the shortage is that you have to manually download the videos one by one.

If you want to download a channel’s all videos, the arduous work emerged.

———–

What I want is using the YouTube API to retrieve all the videos’ addresses and input them into a program and analyze their addresses and download.

After searching in Google, I found Vget Home which is what I want.

You can read through examples list on that page.

Essentially, this lib using YouTubeParser.java to extract video link via matching regex.

How to get data from website. 16 tools to extract data from website

In today's business world, smart data-driven decisions are the number one priority. For this reason, companies track, monitor, and record information 24/7. The good news is there is plenty of public data on servers that can help businesses stay competitive.

The process of extracting data from web pages manually can be tiring, time-consuming, error-prone, and sometimes even impossible. That is why most web data analysis efforts use automated tools.

Web scraping is an automated method of collecting data from web pages. Data is extracted from web pages using software called web scrapers, which are basically web bots.

What is data extraction, and how does it work?

Data extraction or web scraping pursues a task to extract information from a source, process, and filter it to be later used for strategy building and decision-making. It may be part of digital marketing efforts, data science, and data analytics. The extracted data goes through the ETL process (extract, transform, load) and is then used for business intelligence (BI). This field is complicated, multi-layered, and informative. Everything starts with web scraping and the tactics on how it is extracted effectively.

Before automation tools, data extraction was performed at the code level, but it was not practical for day-to-day data scraping. Today, there are no-code or low-code robust data extraction tools that make the whole process significantly easier.

What are the use cases for data extraction?

To help data extraction meet business objectives, the extracted data needs to be used for a given purpose. The common use cases for web scraping may include but are not limited to:

• Online price monitoring: to dynamically change pricing and stay competitive.
• Real estate: data for building real-estate listings.
• News aggregation: as an alternative data for finance/hedge funds.
• Social media: scraping to get insights and metrics for social media strategy.
• Review aggregation: scraping gathers reviews from predefined brand and reputation management sources.
• Lead generation: the list of target websites is scraped to collect contact information.
• Search engine results: to support SEO strategy and monitor SERP.

Is it legal to extract data from websites?

Web scraping has become the primary method for typical data collection, but is it legal to use the data? There is no definite answer and strict regulation, but data extraction may be considered illegal if you use non-public information. Every tip described below targets publicly available data which is legal to extract. However, it is still illegal is to use the scrapped data for commercial purposes.

How to extract data from a website

Manually extracting data from a website (copy/pasting information to a spreadsheet) is time-consuming and difficult when dealing with big data. If the company has in-house developers, it is possible to build a web scraping pipeline. There are several ways of manual web scraping.

1. Code a web scraper with Python

It is possible to quickly build software with any general-purpose programming language like Java, JavaScript, PHP, C, C#, and so on. Nevertheless, Python is the top choice because of its simplicity and availability of libraries for developing a web scraper.

2. Use a data service

Data service is a professional web service providing research and data extraction according to business requirements. Similar services may be a good option if there is a budget for data extraction.

3. Use Excel for data extraction

This method may surprise you, but Microsoft Excel software can be a useful tool for data manipulation. With web scraping, you can easily get information saved in an excel sheet. The only problem is that this method can be used for extracting tables only.

4. Web scraping tools

Modern data extraction tools are the top robust no-code/low code solutions to support business processes. With three types of data extraction tools – batch processing, open-source, and cloud-based tools – you can create a cycle of web scraping and data analysis. So, let's review the best tools available on the market.

Web scraping online. 12 лучших сервисов для скрапинга данных

Существует ряд программных решений, которые позволяют извлекать, экспортировать и анализировать различные данные. Их основное направление – веб-скрапинг, а клиенты таких сервисов собирают данные с сайтов и конвертируют их в нужный формат.

Что такое веб-скрапинг, кому он нужен и какие сервисы для извлечения данных считаются лучшими – расскажу в сегодняшней статье.

Что такое скрапинг данных

Веб-скрапинг – это извлечение данных с сайта или приложения в понятном для обычного человека формате. Обычно эти данные сохраняются в таблицу или файл.

Такими данными могут быть:

• изображения;
• каталог товаров;
• текстовый контент;
• контактные данные: адреса электронной почты, телефоны и так далее.

Все эти данные полезны для поиска потенциальных клиентов, сбора информации конкурирующих компаний, выявления тенденции развития рынка, маркетингового анализа и прочего.

Эта процедура сбора данных не запрещена, однако некоторые недобросовестные компании используют возможности скрапинга незаконно. Так, в октябре 2020 года Facebook подал в суд на две организации, которые распространяли вредоносное расширение для Chrome. Оно позволяло выполнять веб-скрапинг из социальных сетей без авторизации: в собранных данных содержался контент как публичного, так и непубличного характера. В последующем вся полученная информация продавалась маркетинговым компаниям, что является строгим нарушением закона.

Ну а для тех, кто собирается использовать веб-скрапинг для развития бизнеса, ниже я расскажу о лучших сервисах, которые предоставляют данную услугу.

Топ-12 сервисов для скрапинга данных

Большинство сервисов для скрапинга данных – это платное решение для сложных задач, но есть и условно-бесплатные, которые подойдут для простых проектов. В этом разделе мы рассмотрим и те, и другие варианты.

ScraperAPI

ScraperAPI позволяет получить HTML-содержимое с любой страницы через API. С его помощью можно работать с браузерами и прокси-серверами, обходя проверочный код CAPTCHA .

Его легко интегрировать – нужно только отправить GET-запрос к API с API-ключом и URL. Кроме того, ScraperAPI практически невозможно заблокировать, так как при каждом запросе он меняет IP-адреса, автоматически повторяет неудачные попытки и решает капчу.

Особенности:

• рендеринг JS;
• геотеги;
• пул мобильных прокси для скрапинга цен, результатов поиска, мониторинга соцсетей и прочего.

Стоимость: есть пробная версия, платные тарифы начинаются от $29 в месяц

Официальная страница: ScraperAPI

ScrapingBee

ScrapingBee использует API для скрапинга веб-страниц, который обрабатывает headless-браузеры и управляет прокси-серверами, обходя все типы блокировки. У сервиса также есть специальный API для парсинга поиска Google.

Особенности:

• рендеринг JS;
• ротация прокси;
• отлично взаимодействует с Google Sheets и Google Chrome.

Стоимость: от $49 в месяц

Официальная страница: ScrapingBee

ScrapingBot

ScrapingBot – это мощный API для извлечения HTML-содержимого. Компания предлагает API-интерфейсы для сбора данных в области розничной торговли и недвижимости, включая описание продукта, цену, валюту, отзывы, цену покупки или аренды, площадь, местоположение. Вполне доступные тарифные планы, JS-рендеринг, парсинг с веб-сайтов на Angular JS, Ajax, JS, React JS, а также возможность геотаргетинга делают этот продукт незаменимым помощником для сбора данных.

Особенности:

• рендеринг JS;
• качественный прокси;
• до 20 одновременных запросов;
• геотеги;
• есть расширение Prestashop, которое синхронизируется с сайтом для мониторинга цен конкурентов.

Стоимость: бесплатно или от €39 в месяц

Официальная страница: ScrapingBot

Scrapestack

Scrapestack – это REST API для скрапинга веб-сайтов в режиме реального времени. С его помощью можно молниеносно собирать данные с сайтов, используя миллионы прокси и обходя капчу.

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.

Web scraping open source. Scrapy

Scrapy is an open source web scraping framework in Python used to build web scrapers. It gives you all the tools you need to efficiently extract data from websites, process them as you want, and store them in your preferred structure and format. One of its main advantages is that it’s built on top of a Twisted asynchronous networking framework. If you have a large web scraping project and want to make it as efficient as possible with a lot of flexibility then you should definitely use Scrapy. 

Scrapy has a couple of handy built-in export formats such as JSON, XML, and CSV. Its built for extracting specific information from websites and allows you to focus on the data extraction using CSS selectors and choosing XPath expressions. Scraping web pages using Scrapy is much faster than other open source tools so its ideal for extensive large-scale scaping. It can also be used for a wide range of purposes, from data mining to monitoring and automated testing.  What stands out about Scrapy is its ease of use and  . If you are familiar with Python you’ll be up and running in just a couple of minutes.  It runs on Linux, Mac OS, and Windows systems.

Scrapy is under BSD license.

Scraping Bot. What Is a Scraper Bot

Scraper bots are tools or pieces of code used to extract data from web pages. These bots are like tiny spiders that run through different web pages in a website to extract the specific data they were created to get.

The process of extracting data with a scraper bot is called web scraping . At the final stage of web scraping, the scraper bot exports the extracted data in the desired format (e.g JSON, Excel, XML, HTML, etc.) of the user.

As simple as this process might sound, there are a few web scraping challenges , and you can face that could hinder you from getting the data you want.

The practical uses of scraping bots

Scraper bots help people retrieve small-scale data from multiple websites. With these data, online directories like Job boards, Sports websites, and Real estate websites can be built. Aside from these, so much more can still be done with a scraper bot. Some of the popular practical uses we see include:

Market Research: Many online retailers rely on web scraping bots to help them understand their competitors and overall market dynamics. That way, they can develop strategies that will help them stay ahead of the competition.

Stock Market Analysis: For stock traders to predict the market, they need data and many of them get that data with web scraping. Stock price prediction and stock market sentiment analysis with web scraping is becoming a trending topic. If you are a stock trader, this is something you have to know about.

Search Engine Optimization (SEO): SEO companies rely heavily on web scraping for many things. First, in order to monitor the competitive position of their customers or their indexing status, web scraping is needed. Also, to find the right keywords for content, a scraper bot is used. With web scraping, there are so many actionable SEO hacks that can be implemented to optimize a web page.