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Angelo B.Unity Game Developer, Philippines
$15 /hr
1 Years Exp.
0 Followers
I am a Unity Certified Developer with two years of experience developing for Android and PC VR. I also have experience developing games for HTML5, nat...Read More
Kaushal Student, India
$0 /hr
0 Years Exp.
0 Followers
Don't know who i am -_-
Muhammed Shafi Android Developer, India
$11 /hr
3 Years Exp.
0 Followers
I am an experienced android developer. I have 3 years of experience in android development. Professional works with quality is my motto. I have exper...Read More
Anand K.Project Manager, India
$25 /hr
13 Years Exp.
0 Followers
I am Anand Kumar carrying 12+ years experience in telecom Domain, VAS service, Routing application, Billing application development and designing, Lua...Read More
Padmanabh S.ui ux and branding designer, India
$7 /hr
6 Years Exp.
0 Followers
Hi, I am ui ux designer, I have 6.5 year's experience. I have dedicated Team ios , android and cross platform developers , experienced in mobile...Read More
Sangeeth K.senior software engineer, India
$50 /hr
6 Years Exp.
0 Followers
I have total 6+ in voip product development .I had developed a programmable Unified communication platform from strach using freeswitch,lua,php cass...Read More
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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.

Over the last year or so, programming languages have regularly been prefixed with a curious word: modern, Modern Java. But what exactly does modern mean when used in this way?

 

When someone talks about modern languages, they're really just talking about how refined, how advanced and how convenient a programming language is. This also means that the language is capable enough not just to solve problems of the present, but of the future as well. A long line of features like scalability, being cloud-ready, and supporting newer paradigms and architectures is expected of a "modern" programming language.

 

Today, in fact, java is the most used runtime platform on enterprise systems (more than 97% of desktops). But more than that, its virtual machine powers packages and custom business applications, and a wide array of mobile and other embedded platforms.

 

Currently, according to Oracle, more than 3 billion devices run Java in some form. Most major companies use Java for some of their functions and Java server applications are processing tens of millions of requests each day.

 

Why java is so popular?

One of the most important reasons why Java is so popular is the platform independence. Java is a concurrent, class-based, and object-oriented programming language. It was initially designed to have as few implementation dependencies as possible, which lead to the term "write once, run anywhere" (WORA). This means that compiled Java code can run on all platforms with no need for recompiling the code.

 

Java-based applications are known for their speed and scalability. Its efficient processing speeds are used in software, computer games, and mobile Apps. Java supports Multithreading. Multithreading means handling more than one job at a time, so get more process get done in less time than it could with just one thread. Java is also a statically typed language, so that it brings a much greater degree of safety and stability to its programs compared to other popular languages. This safety and stability is a necessity for companies who require major bandwidth in their software and apps.

 

Is Java worth learning?

Java is still a relevant programming language that shows no sign of declining in popularity. Most developers choose it up as their initial programming language because it's reasonably simple to learn.

 

Since the language has an English-like syntax with minimum special characters, Java could be learned in a very short time span and used to build appropriate applications. It is part of a family of languages that are heavily influenced by C++ (as well as C#), thus learning Java offers vast benefits when learning these alternative two languages.

 

"Developing programs is a kind of making art, once you learn clearly and spend your time with full involvement; the creation of art became so easy and simple."

 

General Advantages of Using Java for Business Applications:

Programming with Java is incredibly common for banking and web applications. Compared to other programming languages, Java definitely stands out in terms of security functionality and environment. It comes with certain built-in security features such as:

 

Java apps are able to manage their own use by multiple users at the same time, creating threads for each use within the program itself, rather than having to run multiple copies of the programming in the same hardware. Each thread is tracked until the "work" is finished.

 

Java is so versatile and provides robust customized solutions for almost any type of business need. This "referred position" shows no signs of declining, especially now that Java 10 is on the horizon. It just keeps getting better.

 

Advanced Authentication and Access Control that allows incorporating a range of secure login mechanisms, along with creating the custom security policy and enforce a well-defined permission access policy to sensitive data.

 

Cryptography

Advanced Authentication and Access Control that allows incorporating a range of secure login mechanisms, along with creating the custom security policy and enforce a well-defined permission access policy to sensitive data.

 

Java apps are able to manage their own use by multiple users at the same time, creating threads for each use within the program itself, rather than having to run multiple copies of the programming in the same hardware. Each thread is tracked until the "work" is finished.

 

Java is so versatile and provides robust customized solutions for almost any type of business need. This "referred position" shows no signs of declining, especially now that Java 10 is on the horizon. It just keeps getting better.

 

 

Python is one of the fastest growing programming languages. It has undergone more than 28 years of the successful span. Python itself reveals its success story and a promising future ahead. Python programming language is presently being used by a number of high traffic websites including Google, Yahoo Groups, Yahoo Maps, Shopzilla, Web Therapy, Facebook, NASA, Nokia, IBM, SGI Inc, Quora, Dropbox, Instagram and Youtube. Similarly, Python also discovers a countless use for creating gaming, financial, scientific and instructive applications.

 

Python is a fast, flexible, and powerful programing language that's freely available and used in many application domains. Python is known for its clear syntax, concise code, fast process, and cross-platform compatibility.

 

Python is considered to be in the first place in the list of all AI and machine learning development languages due to the simplicity. The syntaxes belonging to python are terribly easy and can be easily learn. Therefore, several AI algorithms will be easily implemented in it. Python takes short development time as compared to different languages like Java, C++ or Ruby. Python supports object oriented, functional as well as procedure oriented styles of programming. There are lots of libraries in python that make our tasks easier.

 

Some technologies relying on python:

Python has become the core language as far as the success of following technologies is concerned. Let’s dive into the technologies which use python as a core element for research, production and further developments.

 

  1. Networking: Networking is another field in which python has a brighter scope in the future. Python programming language is used to read, write and configure routers and switches and perform other networking automation tasks in a cost-effective and secure manner.
  2. Big Data: The future scope of python programming language can also be predicted by the way it has helped big data technology to grow. Python has been successfully contributing in analyzing a large number of data sets across computer clusters through its high-performance toolkits and libraries.
  3. Artificial Intelligence (AI): There are plenty of python frameworks, libraries, and tools that are specifically developed to direct Artificial Intelligence to reduce human efforts with increased accuracy and efficiency for various development purposes. It is only the Artificial Intelligence that has made it possible to develop speech recognition system, interpreting data like images, videos etc.

 

Why Choose Python for Artificial Intelligence and Machine Learning?

Whether a startup or associate MNC, Python provides a large list of benefits to all. The usage of Python is specified it cannot be restricted to only one activity. Its growing popularity has allowed it to enter into some of the most popular and complicated processes like artificial intelligence (AI), Machine Learning (ML), natural language process, data science etc. The question is why Python is gaining such momentum in AI? And therefore the answer lies below:

 

Flexibility: Flexibility is one of the core advantages of Python. With the option to choose between OOPs approach and scripting, Python is suitable for every purpose. It works as a perfect backend and it also suitable for linking different data structures together.

 

Platform agnostic: Python provides developer with the flexibility to provide an API from the existing programming language. Python is also platform independent, with just minor changes in the source codes, you can get your project or application up and running on different operating systems.

 

Support: Python is a completely open source with a great community. There is a host of resources available which can get any developer up to speed in no time. Not to forget, there is a huge community of active coders willing to help programmers in every stage of developing cycle.

 

Prebuilt Libraries: Python has a lot of libraries for every need of your AI project. Few names include Numpy for scientific computation, Scipy for advanced computing and Pybrain for machine learning.

 

Less Code: Python provides ease of testing - one of the best among competitors. Python helps in easy writing and execution of codes. Python can implement the same logic with as much as 1/5th code as compared to other OOPs languages.

 

Applications of Python:

There are so many applications of Python in the real world. But over time we’ve seen that there are three main applications for Python

Web Development: Web frameworks that are based on Python like Django and Flask have recently become very popular for web development.

Data Science (including Machine Learning): Machine Learning with Python has made it possible to recognize images, videos, speech recognition and much more.

Data Analysis/Visualization: Python is also better for data manipulation and repeated tasks. Python helps in the analysis of a large amount of data through its high-performance libraries and tools. One of the most popular Python libraries for the data visualization is Matplotlib.

 

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