Start Your Project with Us

Whatever your project size is, we will handle it well with all the standards fulfilled! We are here to give 100% satisfaction.

  • Any feature, you ask, we develop
  • 24x7 support worldwide
  • Real-time performance dashboard
  • Complete transparency
  • Dedicated account manager
  • Customized solutions to fulfill data scraping goals
Careers

For job seekers, please visit our Career Page or send your resume to hr@actowizsolutions.com.

How-to-Scrape-Yelp-Data-and-Yelp-Reviews-Using-BeautifulSoup-and-Python

Web scraping is a method that helps programmers to attach to a site using code and scrape JavaScript and HTML hosted on a website. Then, the code is analyzed using a few libraries which can help with the data extraction we want.

The benefit of web scraping with programming languages like Python is that we are not restricted to data extraction from one page; however, if a website's logic is steady enough, we can repeat through all website pages to scrape the maximum data possible.

Web Scraping Limitations

Web scraping is not a foolproof method. Like all other instruments, there are situations or limitations where it couldn't work correctly. If we are fortunate enough, we may not face these problems when mining. Each website has its weird structure and protection systems; therefore, it is a new challenge.

 You can't download all the codes with BeautifulSoup

Tactlessly, there is no probability of getting a workaround while the problem arises using the code. It might happen that a site has allowed protections which prevent BeautifulSoup from having a connection. If some sites identify that you are sending GET requests without utilizing a browser interface, they might block you. It is uncertain that any other libraries would work in a similar scenario.

 You can't parse the code

At times, the software could still use the HTML, but for a few reasons, a code can't get parsed or converted into well-structured BeautifulSoup objects. If we can't parse that, we can't use any methods given by a BeautifulSoup library for scraping information; it makes the automation process impossible.

 Website structure without any logic

You may discover other times when the code is correctly accessed, downloaded, and parsed; a website might have a poor design which is not possible to recognize a general structure in similar pages. Indeed, this rarely happens, but we had to cope with a problem sometimes, resulting in numerous pieces of data getting lost as the retrieval procedure might not get adequately automated.

 It is too difficult

We hope you never deal with this problem, although a few websites can overcome you with quantities of code that are impossible to decode correctly. At times, information is snuggled in the structures secreted by JavaScript and hashes, and although all the data you require is hidden within the code, you can't get a way of simply extracting it.

Scraping Yelp

Scraping-Yelp

In this blog, we will concentrate on extracting the reviews of the same restaurant.

To do a correct data scraping, we will follow these steps:

  • Ensure that we can download the HTML of a single page
  • Ensure that there is any logic in a website that allows iterations
  • Extract the initial page
  • Get the data we wish to scrape
  • Scrape the information and position them on the list
  • Create a cycle that applies similar algorithms to different pages
  • Export the results

The procedure is very spontaneous and could be summarized in this way: before, we observe if we can do the web scraping; if yes, then we do it on a single page, and we extend a code to many pages.

Checking if you can download the HTML

Checking-if-you-can-download-the-HTML

At the start, we thought there wasn't any hope. It took us a while to know all reviews were limited to that one line of HTML code that we needed to analyze.

Check if a website has some logic

Check-if-a-website-has-some-logic-2

The next challenge was to see if there were any evidence of the logic which might have permitted us to repeat through different pages about a similar restaurant.

Luckily, the logic is straightforward. Once we have identified the restaurant we want to extract, we can change the number given in a link divided by 10 like an indicator for a review page. Repeating through various pages is very easy.

Coding

Here is the Python code to follow:

Import Libraries

Import-Libraries

Repeat through the whole website

Repeat-through-the-whole-website

Scrape reviews and include them in the list

Scrape-reviews-and-include-them-in-the-list

During downloading data, a code will show us the development made and downloaded data.

Exporting results

Exporting-results

Exporting results from a list is straightforward. We can do that using the text file; however, we prefer CSV to help the data movement using other software.

As you can see in the screenshot, we have successfully exported all the reviews in a single CSV file.

As-you-can-see-in-the-screenshot

Conclusion

We can do many cool things to make the best value of the data we have just downloaded. We could clear it and then do a sentiment analysis of this data. After that, we could download data from different restaurants and envisage the best stations in the area; it entirely depends on our imagination.

Still, want to know more? Contact Actowiz Solutions now! You can also reach us for all your mobile app scraping and web scraping services requirements.

Recent Blog

View More

Restaurant Guru Data Scraping in Makati Philippines - A Comprehensive Guide

Explore comprehensive Restaurant Guru data scraping in Makati, Philippines, for valuable insights into the local restaurant scene and market trends..

How to Make Data Collection from Swiggy Instamart, Zepto, and Blinkit?

Learn how to collect data from Swiggy Instamart, Zepto, and Blinkit using web scraping techniques for market analysis and optimization.

Research And Report

View More

Actowiz Solutions Growth Report

Actowiz Solutions: Empowering Growth Through Innovative Solutions. Discover our latest achievements and milestones in our growth report.

Analysis of Trulia Housing Data

Comprehensive research report analyzing trends and insights from Trulia housing data for informed decision-making in real estate.

Case Studies

View More

Case Study - Empowering Price Integrity with Actowiz Solutions' MAP Monitoring Tools

This case study shows how Actowiz Solutions' tools facilitated proactive MAP violation prevention, safeguarding ABC Electronics' brand reputation and value.

Case Study - Revolutionizing Retail Competitiveness with Actowiz Solutions' Big Data Solutions

This case study exemplifies the power of leveraging advanced technology for strategic decision-making in the highly competitive retail sector.

Infographics

View More

Maximize Growth with Price Sensitivity and Price Matching in 2024

Maximize growth in 2024 with insights on price sensitivity, price matching, price scraping, and effective pricing data collection techniques.

Unleash the power of e-commerce data scraping

Leverage the power of e-commerce data scraping to access valuable insights for informed decisions and strategic growth. Maximize your competitive advantage by unlocking crucial information and staying ahead in the dynamic world of online commerce.