Web Scraping for Dummies – A Quick Guide for Newbies
Data Sources for BusinessesIntroduction to Web ScrapingWeb Data Scraping Use CasesTypes of Web ScrapingWrapping up
Welcome to the most interesting (and fun! ) blog post on web scraping for dummies. Mind you, this is not a typical web scraping tutorial. You will learn the whys and hows of data scraping along with a few interesting use-cases and fun facts. Let’s dig in.
It is a universal fact that businesses thrive on data. There are many use-cases where businesses generate revenue by using data. I’ll discuss these in a while. But first, let’s try to understand the value of data through a recent Facebook-WhatsApp controversy. A couple of months ago, WhatsApp data privacy policy update made waves among the masses. The update revealed that WhatsApp shares users’ data (business accounts) with its parent company Facebook. Why would Facebook need this data? Facebook uses this data for targeted marketing and revenue generation. There is a reason why this social media giant provides us free service – 97. 9% of Facebook’s earnings are from advertisement, and the user data helps Facebook to optimize its advertising efforts! Yes, nothing is free in this world.
Fun (or not-so-fun) fact: WhatsApp was already sharing your data before the privacy policy. They just informed you recently because of Apple’s new data disclosure requirements!
Now, coming to the point – we have understood that data is precious for businesses, right? We are not Facebook, so where is our precious data?
Data is the Dragon
Data Sources for Businesses
There are two main sources of data: Internal Sources and External Sources. The internal sources include HR data, financial documents, sales data, etc. Organizations use data analytics and business intelligence to find Key Performance Indicators (KPIs) for their business growth. On the other hand, there is an immense amount of open-source data (read big data! ) available on the internet from which businesses can gain valuable information. How do you collect data from these external sources? (Hint: read the title again – Data and Web Scraping for Dummies). Yes, you got it right! We get the data through web scraping.
You might want to read how businesses put big data to work and a gentle introduction to business intelligence and data analytics.
Introduction to Web Scraping
Web scraping helps you to collect and transform the publicly available data on the web for further analytics. According to Wikipedia:
“Web scraping, web harvesting, or web data extraction is data scraping used for extracting data from websites. Web scraping software may access the World Wide Web directly using the Hypertext Transfer Protocol, or through a web browser. While web scraping can be done manually by a software user, the term typically refers to automated processes implemented using a bot or web crawler. It is a form of copying, in which specific data is gathered and copied from the web, typically into a central local database or spreadsheet, for later retrieval or analysis. ”
Quite a complicated definition, right? Don’t worry – I have tried to simplify web scraping for dummies. Web scraping comprises of following three main processes:
Web Data Collection
In this step, data is collected and extracted from the websites. You would first have to do some sort of web crawling to conduct web scraping. This data is initially collected in an unstructured format.
Data Parsing and Transformation
The unstructured data collected from the internet cannot be used directly for further analytics. Therefore, this collected data is parsed and transformed into a structured/understandable format. These include CSV, Excel, or JSON data formats. These datasets are cleaned and transformed for further usage. For this purpose, regular expressions, string manipulation, and various search methods are utilized.
Data Storage
You can scrape data from the website and store it into a CSV, JSON, or XML file. Data scraping and storage depend on the amount of data and the nature of performed tasks. For instance, for a huge amount of data, you might want to consider the big data cloud service and storage option.
Fun fact (or nerd fact? ): Web scraping and web crawling are not the same. Web crawlers just collect data from the web, while web scrapers not only collect the data but also transform and parse it for further processing!
Enjoying this article so far? You will also like our featured article: Why is Elixir Making Headlines?
Web Data Scraping Use Cases
Web data scraping can do wonders for your business! I am sharing a just few interesting use cases here:
Search Engines
Google is the biggest use case of web scraping. This tech giant wouldn’t have existed without web crawling and scraping. Every search engine uses web crawling and scraping techniques.
ML and Data Science
ML and data science cannot work without the data. They require a large volume and variety of data to give quality outputs. Web scraping can help ML engineers and data scientists to build high-quality datasets for ML models. For example, GPT-3 is a powerful text generation tool that is trained on web data scraping.
Marketing and SEO
Web scraping is the favorite tool of the marketing and SEO team. For example, web and data scraping can help in lead generation. Businesses generate leads by finding valuable public information such as details of companies, addresses, contacts, etc. Web scraping can reduce your time and effort in collecting and storing such information from the Internet. It’s also the favorite tool of SEOs, they can get valuable information through web scraping such as high-ranking keywords, competitor analysis, etc. The significance of web scraping has been discussed in detail on this SEO giant MOZ’s blog.
Fun fact: Because we are talking about SEO here, readers might have noticed – I have used the term web scraping for dummies quite a few times in this article. This will help Google to scrape and rank my article, so bear with me
Threat Intelligence
Publically available data can also help in pro-active open-source threat intelligence. For example, we can find threats from darknet markets using specialized web scraping and data analytic techniques. Finding this idea fascinating? Read more about it on my Hacker Noon blog post.
Types of Web Scraping
There are three main ways to scrape data from websites – writing a simple code for smaller tasks, professional custom web scraping, or using automated tools and software for web scraping. If you want to start with writing your own web scraping program, try this detailed and easy-to-follow tutorial on data scraping in python by Felix Revert. Now let’s explore other two options:
Custom Web Scraping Services
There are various challenges in the way of large-scale data scraping. You need to manage captchas and site blocking tactics. You can use custom web and data scraping services from an expert outsourcing service provider. Outsourcing your data project to an expert web scraping company can cut both time and costs.
Fun fact: A good software outsourcing company can cost you even less than handling freelancers! Always check expertise, reviews, and rates before finalizing your tech outsourcing partner!
Web Scraping Tools
There are a variety of automated tools out there that can help you in web data scraping. Here is a list of a few web scraping tools with their key features:
BeautifulSoup
Language: Python
Easier, interactive interface.
HTML parser
Well documented tool
Tutorials easily available
Mozenda
Cloud-based service
Amazing customer support
Ideal for big data scraping
Scrapy
A powerful, open-source tool
One of the oldest among scrapers – you can find many tutorials
Well documented
Powered by python
Octoparse
A GUI-based, easy-to-use tool
Point and click screen scraper
Option for the cloud
Customization options available
Wrapping up
“We’re entering a new world in which data may be more important than software. ” – Tim O’Reilly, founder, O’Reilly Media.
I have written web scraping for dummies keeping in mind that my readers get a general idea of web scraping in a fun way. I’ll end this article with an important message. There are always legal and ethical implications in gathering, storing, and using information (even publicly available information). So it is wise to contact experts in the domain before using data for business. Happy web scraping!
A Beginner’s Guide to learn web scraping with python! – Edureka
Last updated on Sep 24, 2021 641. 9K Views Tech Enthusiast in Blockchain, Hadoop, Python, Cyber-Security, Ethical Hacking. Interested in anything… Tech Enthusiast in Blockchain, Hadoop, Python, Cyber-Security, Ethical Hacking. Interested in anything and everything about Computers. 1 / 2 Blog from Web Scraping Web Scraping with PythonImagine you have to pull a large amount of data from websites and you want to do it as quickly as possible. How would you do it without manually going to each website and getting the data? Well, “Web Scraping” is the answer. Web Scraping just makes this job easier and faster. In this article on Web Scraping with Python, you will learn about web scraping in brief and see how to extract data from a website with a demonstration. I will be covering the following topics: Why is Web Scraping Used? What Is Web Scraping? Is Web Scraping Legal? Why is Python Good For Web Scraping? How Do You Scrape Data From A Website? Libraries used for Web Scraping Web Scraping Example: Scraping Flipkart Website Why is Web Scraping Used? Web scraping is used to collect large information from websites. But why does someone have to collect such large data from websites? To know about this, let’s look at the applications of web scraping: Price Comparison: Services such as ParseHub use web scraping to collect data from online shopping websites and use it to compare the prices of products. Email address gathering: Many companies that use email as a medium for marketing, use web scraping to collect email ID and then send bulk emails. Social Media Scraping: Web scraping is used to collect data from Social Media websites such as Twitter to find out what’s trending. Research and Development: Web scraping is used to collect a large set of data (Statistics, General Information, Temperature, etc. ) from websites, which are analyzed and used to carry out Surveys or for R&D. Job listings: Details regarding job openings, interviews are collected from different websites and then listed in one place so that it is easily accessible to the is Web Scraping? Web scraping is an automated method used to extract large amounts of data from websites. The data on the websites are unstructured. Web scraping helps collect these unstructured data and store it in a structured form. There are different ways to scrape websites such as online Services, APIs or writing your own code. In this article, we’ll see how to implement web scraping with python. Is Web Scraping Legal? Talking about whether web scraping is legal or not, some websites allow web scraping and some don’t. To know whether a website allows web scraping or not, you can look at the website’s “” file. You can find this file by appending “/” to the URL that you want to scrape. For this example, I am scraping Flipkart website. So, to see the “” file, the URL is in-depth Knowledge of Python along with its Diverse Applications Why is Python Good for Web Scraping? Here is the list of features of Python which makes it more suitable for web scraping. Ease of Use: Python is simple to code. You do not have to add semi-colons “;” or curly-braces “{}” anywhere. This makes it less messy and easy to use. Large Collection of Libraries: Python has a huge collection of libraries such as Numpy, Matlplotlib, Pandas etc., which provides methods and services for various purposes. Hence, it is suitable for web scraping and for further manipulation of extracted data. Dynamically typed: In Python, you don’t have to define datatypes for variables, you can directly use the variables wherever required. This saves time and makes your job faster. Easily Understandable Syntax: Python syntax is easily understandable mainly because reading a Python code is very similar to reading a statement in English. It is expressive and easily readable, and the indentation used in Python also helps the user to differentiate between different scope/blocks in the code. Small code, large task: Web scraping is used to save time. But what’s the use if you spend more time writing the code? Well, you don’t have to. In Python, you can write small codes to do large tasks. Hence, you save time even while writing the code. Community: What if you get stuck while writing the code? You don’t have to worry. Python community has one of the biggest and most active communities, where you can seek help Do You Scrape Data From A Website? When you run the code for web scraping, a request is sent to the URL that you have mentioned. As a response to the request, the server sends the data and allows you to read the HTML or XML page. The code then, parses the HTML or XML page, finds the data and extracts it. To extract data using web scraping with python, you need to follow these basic steps: Find the URL that you want to scrape Inspecting the Page Find the data you want to extract Write the code Run the code and extract the data Store the data in the required format Now let us see how to extract data from the Flipkart website using Python, Deep Learning, NLP, Artificial Intelligence, Machine Learning with these AI and ML courses a PG Diploma certification program by NIT braries used for Web Scraping As we know, Python is has various applications and there are different libraries for different purposes. In our further demonstration, we will be using the following libraries: Selenium: Selenium is a web testing library. It is used to automate browser activities. BeautifulSoup: Beautiful Soup is a Python package for parsing HTML and XML documents. It creates parse trees that is helpful to extract the data easily. Pandas: Pandas is a library used for data manipulation and analysis. It is used to extract the data and store it in the desired format. Subscribe to our YouTube channel to get new updates..! Web Scraping Example: Scraping Flipkart WebsitePre-requisites: Python 2. x or Python 3. x with Selenium, BeautifulSoup, pandas libraries installed Google-chrome browser Ubuntu Operating SystemLet’s get started! Step 1: Find the URL that you want to scrapeFor this example, we are going scrape Flipkart website to extract the Price, Name, and Rating of Laptops. The URL for this page is 2: Inspecting the PageThe data is usually nested in tags. So, we inspect the page to see, under which tag the data we want to scrape is nested. To inspect the page, just right click on the element and click on “Inspect” you click on the “Inspect” tab, you will see a “Browser Inspector Box” 3: Find the data you want to extractLet’s extract the Price, Name, and Rating which is in the “div” tag respectively. Learn Python in 42 hours! Step 4: Write the codeFirst, let’s create a Python file. To do this, open the terminal in Ubuntu and type gedit
from BeautifulSoup import BeautifulSoup
import pandas as pdTo configure webdriver to use Chrome browser, we have to set the path to chromedriverdriver = (“/usr/lib/chromium-browser/chromedriver”)Refer the below code to open the URL: products=[] #List to store name of the product
prices=[] #List to store price of the product
ratings=[] #List to store rating of the product
(“)
Now that we have written the code to open the URL, it’s time to extract the data from the website. As mentioned earlier, the data we want to extract is nested in
soup = BeautifulSoup(content)
for a in ndAll(‘a’, href=True, attrs={‘class’:’_31qSD5′}):
(‘div’, attrs={‘class’:’_3wU53n’})
(‘div’, attrs={‘class’:’_1vC4OE _2rQ-NK’})
(‘div’, attrs={‘class’:’hGSR34 _2beYZw’})
()
Step 5: Run the code and extract the dataTo run the code, use the below command: python 6: Store the data in a required formatAfter extracting the data, you might want to store it in a format. This format varies depending on your requirement. For this example, we will store the extracted data in a CSV (Comma Separated Value) format. To do this, I will add the following lines to my code:df = Frame({‘Product Name’:products, ‘Price’:prices, ‘Rating’:ratings})
_csv(”, index=False, encoding=’utf-8′)Now, I’ll run the whole code again. A file name “” is created and this file contains the extracted data. I hope you guys enjoyed this article on “Web Scraping with Python”. I hope this blog was informative and has added value to your knowledge. Now go ahead and try Web Scraping. Experiment with different modules and applications of Python. If you wish to know about Web Scraping With Python on Windows platform, then the below video will help you understand how to do Scraping With Python | Python Tutorial | Web Scraping Tutorial | EdurekaThis Edureka live session on “WebScraping using Python” will help you understand the fundamentals of scraping along with a demo to scrape some details from a question regarding “web scraping with Python”? You can ask it on edureka! Forum and we will get back to you at the earliest or you can join our Python Training in Hobart get in-depth knowledge on Python Programming language along with its various applications, you can enroll here for live online Python training with 24/7 support and lifetime access.
Is Web Scraping Easy? How to Scrape Data without Coding Skills
Mastering web scraping can be incredibly all, web scraping will give you instant access to valuable datasets such as competitor product details, stock prices, market data, you name it! However, web scraping might seem intimidating for some people. Specially if you’ve never done any coding in your ever, they are way simpler ways to automate your data gathering process without having to write a single line of is Web Scraping? As you may already know, web scraping refers to the extraction of data from a this can be done manually, most people will use a software tool to run their web scraping jobs. Unfortunately, many of these web scraping tools will still require custom coding from the terested in learning more about web scraping? Read our in-depth guide on web to Scrape Data without Coding SkillsLuckily, there are many web scraping tools that are made with ease-of-use in many in fact, that we have written a guide on what features make the best web scraping tool for your specific use obviously recommend ParseHub, a free and easy-to-use web scraper with the following features:User-friendly UI: ParseHub boasts a super friendly user interface. Load the website you’re looking to scrape data from and simply click on the data you’re looking to with any website: ParseHub works with any website, including modern dynamic sites that some web scrapers cannot scraping: ParseHub only runs on your computer to build your scrape jobs, the actual scraping occurs on the cloud. That means that ParseHub does not eat up at your device’s resources while running large scrape and JSON exports: Export your data as a CSV or JSON file, or take a step further and connect your scrape jobs to a Google Sheets to see it in action? Here’s our video guide on how to use ParseHub to scrape any website on to an excel spreadsheet:What can Web Scraping be used for? Now that you have tested out ParseHub and know how to scrape any website on to an excel spreadsheet, you might be wondering what you could use ParseHub ckily, we have written an in-depth guide on how companies use web scraping to boost their business you’re not yet ready to tackle a complex project, try these simple project ideas to get started with web scraping.
Frequently Asked Questions about web scraping for dummies
How do you scrape a website for beginners?
Let’s get started!Step 1: Find the URL that you want to scrape. For this example, we are going scrape Flipkart website to extract the Price, Name, and Rating of Laptops. … Step 3: Find the data you want to extract. … Step 4: Write the code. … Step 5: Run the code and extract the data. … Step 6: Store the data in a required format.Sep 24, 2021
Is Web scraping easy?
However, web scraping might seem intimidating for some people. Specially if you’ve never done any coding in your life. However, they are way simpler ways to automate your data gathering process without having to write a single line of code.Feb 10, 2020
What is Web scraping for dummies?
“Web scraping, web harvesting, or web data extraction is data scraping used for extracting data from websites. Web scraping software may access the World Wide Web directly using the Hypertext Transfer Protocol, or through a web browser.