Hire the best
Curl Freelancers

Top 30 Curl Freelancers on 21 Jul 2019 on Toogit. Curl Freelancers on Toogit are highly skilled and talented. Hiring Curl Freelancers on Toogit is quite affordable as compared to a full-time employee and you can save upto 50% in business cost by hiring Curl Freelancers on Toogit. Hiring Curl Freelancers on Toogit is 100% safe as the money is released to the Freelancer only after you are 100% satisfied with the work.

Get Started

Explore Toogit’s top Curl Freelancers

 
 
 
Chaitanya Machine Learning Engineer, India
$17 /hr
2 Years Exp.
0 Followers
Research and development experience of 2 yeras in the field of ADAS, Computer vision, Deep Learning and High Performance Computing. Publish over 4 pap...Read More
Amit R.Software Engineer, India
$5 /hr
2 Years Exp.
0 Followers
Contact me if you want an end to end development of a project.
Yogesh Jaiswal J.Web Scraping/Python developer, India
$6 /hr
7 Years Exp.
0 Followers
Welcome to my profile. I love to do automation. My capabilities the following: Web scraping, crawling - Data Extraction - Data manipulations - Python...Read More
To view more profile join Toogit

Get Started
 

How it works

Post a job

Post a Job

List your project requirement with us. Anything you want to get developed or want to add to your business. Toogit connects you to Top freelancers around the world.

Hire

Hire

Invite and interview your preferred talent to get work done. Toogit Instant Connect helps you if you need your project started immediately.

Work

Work

Define Tasks, use Toogit's powerful project management tool, stay updated with real time activity logs

Payment

Pay

Review work, track working hours. Pay freelancers only if you are 100% satisfied with the work done.

Popular How-To's in Curl category


 
How to Update Node.js to Latest Version (Linux, Ub...
Other - Software Development

As with so many open-source technologies, Node.js is a fast-moving project. Minor updates come out every few weeks to boost stability and security among all version branches.Method...

Read More

Reviews From Our Users

Skills related to Curl

Articles Related To Curl


Python and Java both lay claims to being among the top five most popular programming languages at any given time, with Java usually just ahead of Python. However, Python’s popularity is growing at a tremendous rate, and Python overtake Java in 2018.

 

Python is a high-level, interpreted, interactive and object-oriented scripting language. Python was designed to be highly readable which uses English keywords frequently whereas other languages use punctuation and it has fewer syntactical constructions than other languages.

 

Java and Python have many similarities. Both languages have strong cross-platform support and extensive standard libraries. They both treat (nearly) everything as objects. Both languages compile to bytecode, but Python is (usually) compiled at runtime.

 

Python versus Java:

  1. Java language is more about syntax, if one can forget to add curly braces or semicolon in the end then this will show error as your output. But there is nothing like that with python there is no need of semicolon and curly braces in the end but python follows indentation process so that it will make your code readable.
  2. Java programming is statically typed means that one has to explicitly mention the data type of variable. If datatype (int, float, double, character) isn’t mentioned then the error can occur in program. Python is dynamically typed means if one has directly assigned a value to a variable at the runtime then it'll assume data type.
  3. Java codes are more complex than python codes. Try to write a hello world program in both then you'll observe the complexness of the code, four lines of code in Java and same hello world program in python are of 1-line code.
  4. Python has a large and robust standard library makes Python score over other programming languages. The standard library allows you to choose from a wide range of modules according to your precise needs. Each module further enables you to add functionality to the Python application without writing additional code.
  5. Python is an open source programing language, Python helps you to curtail software system development cost significantly. You’ll even use many open source Python frameworks, libraries and development tools to curtail development time without increasing development cost. You even have choice to select from a wide range of open source Python frameworks and development tools per your precise needs.
  6. Interpreted, with tools like IDLE, you can also interpret Python instead of compiling it. While this reduces the program length, and boosts productivity, it also results in slower overall execution.
  7. Python is considered to be the most favorable language for Machine Learning, Artificial Intelligence, IoT and much more.
  8. Python has a more unified support model than Java for the first time, and open source developers are focusing their efforts on the latest version of the language.
  9. After working on large projects in both languages, I feel secure saying that Python’s syntax is more concise than Java’s. It’s easier to get up and running quickly with a new project in Python than it is in Java.
  10. The most two popular frameworks for Python are Django and Flask. Flask is a micro web framework, it gives you the basic functionalities you’d need like routing requests without much overhead. Django is a more featured option and can help you build a powerful backend while capitalizing on efficiency and security, Django is equipped with a powerful ORM layer which facilitates dealing databases and performing different operations on the data.

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.

Articles Related To Curl


Is Python better than JAVA?
Is Python better than JAVA?
Other - Software Development

Python and Java both lay claims to being among the top five most popular programming languages at any given time, with Java usually just ahead of Python. However, Python’s pop...

Read More
 
Learn Web Scraping using Python
Web Development

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...

Read More

Other Freelancers In Similar Categories

Amit R.


Contact me if you want an end to end development of a project.

Yogesh Jaiswal...


Welcome to my profile. I love to do automation. My capabilities the following: Web scraping, crawling - Data E...