Learn Web Scraping using Python

The importance of extracting information from the web is becoming increasingly loud and clear. Every few weeks, I realize myself in a situation where we need to extract information from the web to create a machine learning model. We have to pull or extract a large amount of information from websites and we would like to do it as quickly as possible. How would we do it without manually going to every web site and getting the data? Web Scraping simply makes this job easier and faster.

Why is web scraping needed?

Web scraping is used to collect large information from websites. But why does someone have to collect such large data from websites? Let’s look at the applications of web scraping: 

  1. 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.
  2. Social Media Scraping: Web scraping is used to collect data from Social Media websites such as Twitter to find out what’s trending.
  3. 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.
  4. 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.
  5. 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 user.

 

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.

Why Python is best for Web Scraping

Features of Python which makes it more suitable for web scraping:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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 from.

How does web scraping work

To extract data using web scraping with python, you need to follow these basic steps:

  1. Find the URL that you want to scrape
  2. Inspecting the Page
  3. Find the data you want to extract
  4. Write the code
  5. Run the code and extract the data
  6. Store the data in the required format

Example: Scraping a website to get product details

Pre-requisite:

  • Python 2.x or Python 3.x
  • Selenium Library
  • BeautifulSoup Library
  • Pandas Library
  1. We are going scrape online shopping website to extract the Price, Name, and rating of products, go to products URL
  2. The data is usually nested in tags. So, we inspect the page to examine, under which tag the information we would like to scrape is nested. To inspect the page, just right click on the element and click on “Inspect”. When you click on the “Inspect” tab, you will see a “Browser Inspector Box” open.
  3. Let’s extract the Price, Name, and Rating which is nested in the “div” tag respectively.
  4. Write code:

#Let us import all the necessary libraries

from selenium import webdriver

from BeautifulSoup import BeautifulSoup

import pandas as pd

driver = webdriver.Chrome("/usr/lib/chromium-browser/chromedriver")

products=[] #List to store name of the product

prices=[] #List to store price of the product

ratings=[] #List to store rating of the product

driver.get("Product_URL")

content = driver.page_source

soup = BeautifulSoup(content)

for a in soup.findAll('a',href=True, attrs={'class':'.…'}):

name=a.find('div', attrs={'class': '….'})

price=a.find('div', attrs={'class':'….'})

rating=a.find('div', attrs={'class':'….'})

products.append(name.text)

ratings.append(rating.text)

df = pd.DataFrame({'Product Name':products,'Price':prices,'Rating':ratings})

df.to_csv('products.csv', index=False, encoding='utf-8')

 

To run the code, a file name “products.csv” is created and this file contains the extracted data.

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With more new programming languages being released day by day it is getting difficult for the programmers to keep track and learn every new programming language.

One must understand that decision to learn new programming language should solely be based on following 3's.

  • Your aspirations
  • Your organisation's need
  • Your project's need
  • In this article we are going to discuss top 5 programming languages recommended for 2019. We will also touch briefly on the importance of each language.

    Python

    A must learn programming language with AI, ML, data analytics, algorithm-based development suddenly catching loads of world attention. With high demands of automation in industry, Python has suddenly become extremely important for developers to acquire and learn.

    Python can be used develop a wide range of applications. 

    Python Applications

     

    Web Development:  Python is good for improving a web application without much complexity.  The language comes with a rich collection of libraries and internet protocols like

     

    • Requests - assigned to the HTTP client library
    • BeautifulSoup - used for HTML parser
    • Feedparser - used for parsing RSS/Atom feeds
    • Paramiko - used for performing the SSH2 protocol
    • Twisted Python - used for asynchronous network programming

    It also has a very active framework like Django, Pyramid and microframeworks like flask and bottle which serves users in swift and dynamic web development.       

     

    Data Analytics: Python is the most preferred language in the fields of data science, statistics, analytics, ML. Even facing tough competition from R (statistical language) Python has sustained as it is a customary purpose programming language and used not only for statistical programming, but is also well accommodated for building games, websites, business applications,  and much more.

     

    Science and Numeric Purposes: Python is widely used by most of the data scientists because of its library compilation which is devised for statistical and numerical analysis

     

    • SciPy - it is a collection of packages for mathematics, science, and engineering.
    • Pandas - A package extensively used for data analysis and modelling
    • IPython - A powerful shell designed for simple editing and recording of work concourses and supports visualisations and parallel computing.
    • NumPy - Helps in dealing with complex numerical calculations.

     

    ERP Progress: Python is being applied for developing business software which solves enterprise-level issues. Successful ERP like Odoo and Tryton is enduring small and important businesses in managing their entire administration and stock index.    

     

    Game Development: Programmers can develop games applying python even though most favoured structure for game development is Unity, python does have PyGame, PyKyra structures for game-development with Python. Users can get a mixture of 3D-rendering libraries to generate 3D games.

    GO

    Being an open source programming language Go makes it simple to create simple, secure, and productive software. It is also one of the latest players in the programming platform.Go was formulated in 2007 and officially published in 2012 and was ratified at Google to advance programming richness, in a period of multicore processors, computer networks, and large codebases. The designers aspired to fix general criticisms of other languages while retaining many of their valuable characteristics like:

     

    • Static typing and efficiency (offered by C++ or Java)
    • Richness and comfort of use (resembling Python or JavaScript)
    • Extraordinary performance networking and multiprocessing
    • Go encompass all the efficiency of python and performance of conventional languages like C++ and Java to help users build scalable applications.

    The language has raised lots of hope for the upcoming class of coding geeks.As it has features of Python, JS, Java. But it is slowly becoming one of the most assuring languages to study and adopt in the future.

     

    Importance Of Go: Go’s growing usage is anticipated, because of its lightweight, open source language revised for today’s microservices designs. Container Docker and Google’s container orchestration outcome Kubernetes are developed using Go. Go is also obtaining ground in data science, with depths that data scientists are studying for in overall execution.

    JavaScript

    For web developers, Javascript is the most favoured language and it will be very hard to find a job in the web development platform without knowledge of Javascript. It is an object-oriented programming language. It is one of the most conventional programming languages in this modern digital world.

     

    Besides HTML and CSS, JavaScript is quintessential to front-end web development. A majority of the web’s most successful sites, from Facebook and Twitter to Gmail and YouTube, rely on JavaScript to design interactive web pages and dynamically display content to users.

     

    In extension to absolute JavaScript, there are various libraries and frameworks designed to make JavaScript development easier. Some of the most accessible frameworks include Angular, React, Vue, Ember and jQuery. Professional JavaScript developers will likely need practice with one or more of these.

     

    Although JavaScript is fundamentally a front-end language run on the browser, it can also be practised on the server-side throughout Node.js to create scalable network applications. Node.js is congenial with Linux, SunOS, Mac OS X and Windows.JavaScript has an accepting, compliant syntax and works over all major browsers, it is one of the favourable programming languages for beginners.

     

    Use cases: Websites like WordPress, LinkedIn, Amazon, Microsoft etc utilise JavaScript language.

    Swift

    Swift is a comprehensive purpose language which was generated by Apple for applications that are applied to their multiple operating systems. Swift is assuredly the best programming language to learn if aspirants liked to acquire or work with Apple programs and applications. Although it was only published four years ago, in 2014, the demand for Swift developers has increased exponentially. It is now one of the most popularly used languages in the world, and aspirants job prospects will be bright if one decides to learn it.

     

    Due to the tremendous need for experienced Swift developers, the average programmer who knows how to use the language can expect huge pay cheque. The language has advantages like cleaner syntax and limited low-level juggling of pointers

    Scala

    Scala implements functional programming assistance and strong static type system, which makes it an excellent general purpose programming language.The user will be able to commence applying functional programming techniques to support user-developed applications and overcome issues that result from unintended consequences. The provision of shifting from mutable data structures to immutable data structures and from conventional methods to absolute functions that have no impact on their environment, user code will be maintained, more stable, and much simpler to comprehend.

     

    Our recommendation - If you are still new to these five programming languages then we will strongly recommend to learn Python in 2019. You can start by looking at basic python youtube tutorials.

    If you already know Python then go for GO Language. Start with this basic Go lang tutorial.

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