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Everything You Need To Know About Automated Web Scraping In Python

Are you looking for ways to extract data from the web? Web scraping is a common and effective process for collecting information easily. By using Scrapestack and Python, you can easily pull a large amount of data from websites quickly. But is it legal to scrape sites? Can the businesses be benefitted in terms of competitive intelligence? In this post, you will find all the details.  

What is Web Scraping?

Web Scraping is an automated process of collecting large amounts of data from websites by utilizing algorithms or programs. It enables you to collect multiple data points from thousands of web pages in just a few minutes. So, it can save you time and money. You can download and export the data as an excel sheet or JSON file for further analyzing the information conveniently. Another great API to use with web scraping is an ipaddress api so you can find the physical location of an IP address.

What can you do with web scraping?

Compare Prices: You can use web scraping services, like ParseHub, to extract and compare prices from online stores easily.

Generate Leads: Many companies extract data from YellowPages to generate leads by utilizing web scraping.

Research Markets: With web scraping, you can pull financial data from different websites easily. You can use the information to research the market and reveal key insights conveniently.

Find the Trending Topics: You can find out what’s trending online by extracting useful data from social media channels, like Facebook and Twitter. 

Gather Large Scientific Data: Web Scraping allows you to collect large scientific data sets from websites easily. So, you can carry out your research and development projects conveniently.

Web Scraping for Competitive Intelligence: How does it transform business intelligence?

Every company follows different strategies to improve the business. One of them is analyzing the market competition. By utilizing business intelligence, companies can monitor the marketing tactics of competitors. By analyzing their strategy, the businesses can make accurate decisions at the right time.

In this scenario, web scraping comes to play. It helps you to collect large volumes of data from the competitor websites within a short period. You can use the extracted information to compare prices between the items of your company and the competitors. Also, you can perform sentiment analysis to get a clear idea about the customers’ feelings about a specific product. By using this information, you can make necessary improvements to your market strategy and generate better sales. Overall, web scrapping enables you to stay ahead in the business competition.

Is it legal to scrape web pages?

You can scrape web pages if the website allows you to do it. However, some sites don’t permit web scraping. If you try to scrape their web pages, you will face legal issues. This is a complicated topic and depends a lot on jurisdiction as well (your local laws).

However, there is a way of determining whether the website allows web scraping programmatically or not. Simply follow these steps:

How to Know Whether a Site Allows Web Scraping or Not

1. Go to the site’s robots.txt file. You can view it by simply appending “/robots.txt” to the URL that you want to scrape. For example: https://www.apple.com/robots.txt.

2. If you find this line, you should stay away from scrapping it, as it prohibits the use of automatic crawler:

3. However, if you find this line, you can crawl all the pages of the site without any legal issue:

Which is the best programming language for web scraping?

You can scrape web pages using different languages, including PHP and JavaScript. However, Python is the best language for web scrapping because of the following reasons:

Easy to Use: Unlike C++ or JavaScript, Python doesn’t force you to use semi-colons or curly braces. As a result, it has become one of the easiest programming languages to use on the planet.

Huge Collection of Libraries: Python supports a large number of libraries, including Pandas and Matplotlib, which help you to further manipulate the data after scraping.

Highly Efficient: Python enables you to perform large tasks by writing just a few lines of code. Thanks to the short syntax and a large number of libraries.

Support for Advanced Web Scraping Frameworks: Python is compatible with a large number of web scraping frameworks, including Beautiful Soup, Scrapy, and Selenium. By offering advanced features, they have made Python the most popular language for scraping web pages.   

How to Use Python and Scrapestack for Web Scraping

Scrapestack is an API service for scraping websites. It enables you to pull data and extract information without worrying about technical issues, including IP blocks and proxies. By using Python and Scraptestack, you can scrap websites easily within a short period. Simply follow these steps:

1. You need to find the access key for Scrapestack. You can get it for free by signing up here.

2. Now, use these codes to extract the HTML codes from Apple’s website:

The codes print an unrendered HTML page from Apple.com.

Should I really use Scrapestack for web scraping?

Scrapestack makes it very easy for you to extract data from websites. All you have to do is to get the API key and add a valid URL. Scrapestack will do the rest and return full HTML content. So, you should consider using it for web scraping.

Scrapestack is an easy-to-use API for scraping websites. Try it now for free.

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