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What is a web scraping?

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.

Web scraping a web page involves fetching it and extracting from it. Fetching is the downloading of a page (which a browser does when you view the page). Therefore, web crawling is a main component of web scraping, to fetch pages for later processing. Once fetched, then extraction can take place. The content of a page may be parsed, searched, reformatted, its data copied into a spreadsheet, and so on. Web scrapers typically take something out of a page, to make use of it for another purpose somewhere else. An example would be to find and copy names and phone numbers, or companies and their URLs, to a list (contact scraping).

 

What you can do with data scraping?

Web scraping is used for content scraping, and as a component of applications used for web indexing, web mining and data mining, online price change monitoring and price comparison, product review scraping (to watch the competition), gathering real estate listings, weather data monitoring, website change detection, research, tracking online presence and reputation, web mashup and, web data integration.

Using data scraping you can build sitemaps that will navigate the site and extract the data. Using different type selectors you will navigate the site and extract multiple types of data - text, tables, images, links and more.

 

What role scraper should play for you?

Web scraping is the process of automatically mining data or collecting information from the World Wide Web. It is a field with active developments sharing a common goal with the semantic web vision, an ambitious initiative that still requires breakthroughs in text processing, semantic understanding, artificial intelligence and human-computer interactions. Current web scraping solutions range from the ad-hoc, requiring human effort, to fully automated systems that are able to convert entire web sites into structured information, with limitations.

 

Below are the ways for scraping data:

  • Human Copy Paste : Sometimes even the best web-scraping technology cannot replace a human’s manual examination and copy-and-paste, and sometimes this may be the only workable solution when the websites for scraping explicitly set up barriers to prevent machine automation.
  • Text Pattern Matching : A simple yet powerful approach to extract information from web pages can be based on the UNIX grep command or regular expression-matching facilities of programming languages
  • HTTP programming : Static and dynamic web pages can be retrieved by posting HTTP requests to the remote web server using socket programming.
  • HTML parsing : Many websites have large collections of pages generated dynamically from an underlying structured source like a database. Data of the same category are typically encoded into similar pages by a common script or template. In data mining, a program that detects such templates in a particular information source, extracts its content and translates it into a relational form, is called a wrapper. Wrapper generation algorithms assume that input pages of a wrapper induction system conform to a common template and that they can be easily identified in terms of a URL common scheme.Moreover, some semi-structured data query languages, such as Xquery and the HTQL, can be used to parse HTML pages and to retrieve and transform page content.
  • DOM parsing: By embedding a full-fledged web browser, such as the Internet Explorer or the Mozilla browser control, programs can retrieve the dynamic content generated by client-side scripts. These browser controls also parse web pages into a DOM tree, based on which programs can retrieve parts of the pages.
  • Vertical aggregation : There are several companies that have developed vertical specific harvesting platforms. These platforms create and monitor a multitude of “bots” for specific verticals with no "man in the loop" (no direct human involvement), and no work related to a specific target site. The preparation involves establishing the knowledge base for the entire vertical and then the platform creates the bots automatically. The platform's robustness is measured by the quality of the information it retrieves (usually number of fields) and its scalability (how quick it can scale up to hundreds or thousands of sites). This scalability is mostly used to target the Long Tail of sites that common aggregators find complicated or too labor-intensive to harvest content from.
  • Semantic annotation recognizing : The pages being scraped may embrace metadata or semantic markups and annotations, which can be used to locate specific data snippets. If the annotations are embedded in the pages, as Microformat does, this technique can be viewed as a special case of DOM parsing. In another case, the annotations, organized into a semantic layer,are stored and managed separately from the web pages, so the scrapers can retrieve data schema and instructions from this layer before scraping the pages.
  • Computer vision web-page analysis : There are efforts using machine learning and computer vision that attempt to identify and extract information from web pages by interpreting pages visually as a human being would.

 

Key Features of Web Scraping

In order to remain competitive, businesses must be able to act quickly and assuredly in the markets. Web Scraping plays a big role in the development of various business organizations that use the services. 

The benefits of these services are: 

  1. Low Cost: Web Scraping service saves hundreds of thousands of man-hours and money as the use of scraping service completely avoids manual work.
  2. Less Time: Scraping solution not only helps to lower the cost, it also reduces the time involved in data extraction task. This tool ensures and gathers fast results required by people.
  3. Accurate Results: Web Scraping solutions help to get the most accurate and fast results that cannot be collected by human beings. It generates correct product pricing data, sales leads, duplication of online database, captures real estate data, financial data, job postings, auction information and many more.
  4. Time to Market Advantage: Fast and accurate results help businesses to save time, money and labor and get an obvious time-tomarket advantage over the competitors.
  5. High Quality: A Web Scraping solution provides access to clean, structured and high quality data through scraping APIs so that the fresh data can be integrated into the systems.

Finding and hiring expert scraper/crawler

It’s important to note that not all scraper will be ideal fits for every project. For example, those with highly analytical backgrounds in software engineering would be ideal for developing algorithms but may not be the right fit for a data scraping project. That’s why it’s so important to understand what type of scraping expert will bring the most benefit to your company and business goals.

Here are some questions to consider:

What is the overall learning you hope to find? 

By including your goal in the project description, it allows professionals to better understand what type of work is required.

 

What core skills will scraping experts need to complete the project? 

The answer will revolve around your current data infrastructure and the processes used to extract information.

 

Would you benefit from someone with highly specialized skills in a few areas of data scraping, or would a well-rounded expert serve you better?

 

Are there any time constraints to consider with this project?

Let professionals know the amount of hours of work that might be involved.

 

What kind of budget will this project have? 

The more experience and expertise a data scraper has, the higher they expect to be compensated. Higher budgets will more likely give top-tier experts a reason to submit a proposal.

 

Web scraping project template

Below is a sample of how a project description may look. Keep in mind that many people use the term “job description,” but a full job description is only needed for employees. When engaging a freelancer as an independent contractor, you typically just need a statement of work, job post, or any other document that describes the work to be done.

<Job/Project Title>

ABC Company is looking for a web scraping expert to help us study our website traffic patterns and find areas of improvement. This project is estimated to require approximately 20-25 hours per week for the next few months to achieve the following goals

  • Reporting findings in a weekly summary
  • Split testing underperforming pages and recording results
  • Discovering which pages currently perform best
  • Organizing site data into spreadsheets

The following skills are required:

The ideal freelancer will be a creative problem solver with an excellent work history on Toogit. To submit a proposal, please send a short summary of similar projects you’ve completed and why we should consider you for this project.

  • Excellent technical abilities
  • Knowledge of quantitative split testing
  • Experience with WordPress and Google Analytics
  • A thorough understanding of MySQL databases
  • Expertise or extensive experience with Python

 

Hiring the right Web Scraping talent

Remember that technical ability is only a small portion of what makes an excellent web scraper. Great web scrapers are inquisitive—they want to ensure that they’re seeking the right types of answers, plus they’ll take an interest in your business to better understand it. The ideal professional will also be able to advise you on additional metrics to analyze and compare in order to help you meet your goals.

Also, keep in mind that communication is always a key consideration in the data science field. A brief interview can allow you to gauge how strong each professional is in expressing ideas and explaining their process. The more you speak to each professional by phone, email, or chat, the better you’ll be able to gauge their professionalism and communication skills and determine whether they’re right for your project.

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.

As you know, JavaScript is the top programming language in the world, the language of the web, of mobile hybrid apps (like PhoneGap or Appcelerator), of the server side (like NodeJS or Wakanda) and has many other implementations. It’s also the starting point for many new developers to the world of programming, as it can be used to display a simple alert in the web browser but also to control a robot (using nodebot, or nodruino). The developers who master JavaScript and write organized and performant code have become the most sought after in the job market.

 

In this article, I’ll share a set of JavaScript tips, tricks and best practices that should be known by all JavaScript developers regardless of their browser/engine or the SSJS (Server Side JavaScript) interpreter.

 

Don’t forget var” keyword when assigning a variable’s value for the first time.

Assignment to an undeclared variable automatically results in a global variable being created. Avoid global variables.

Use “===” instead of “==”

The == (or !=) operator performs an automatic type conversion if needed. The === (or !==) operator will not perform any conversion. It compares the value and the type, which could be considered faster than ==

[10] === 10    // is false

[10]  == 10    // is true

'10' == 10     // is true

'10' === 10    // is false

 []   == 0     // is true

 [] ===  0     // is false

 '' == false   // is true but true == "a" is false

 '' ===   false // is false 

undefined, null, 0, false, NaN, '' (empty string) are all falsy.

 

Use Semicolons for line termination

The use of semi-colons for line termination is a good practice. You won’t be warned if you forget it, because in most cases it will be inserted by the JavaScript parser. For more details about why you should use semi-colons.

 

Create an object constructor

function Person(firstName, lastName){

    this.firstName =  firstName;

    this.lastName = lastName;        

}  

var Khalid = new Person("Khalid", "Ansari");

 

Be careful when using typeof, instanceof and constructor.

typeof: a JavaScript unary operator used to return a string that represents the primitive type of a variable, don’t forget that typeof null will return “object”, and for the majority of object types (Array, Date, and others) will return also “object”.

constructor: is a property of the internal prototype property, which could be overridden by code.

 

instanceof: is another JavaScript operator that check in all the prototypes chain the constructor it returns true if it’s found and false if not.

 

var arr = ["a", "b", "c"];

typeof arr;   // return "object" 

arr  instanceof Array // true

arr.constructor();  //[]

 

Define a Self-calling Function

This is often called a Self-Invoked Anonymous Function or Immediately Invoked Function Expression (IIFE). It is a function that executes automatically when you create it, If you want to use this function you can write in the following way: 

 

(function(){

    // some private code that will be executed automatically

})();  

(function(p,q){

    var r = p+q;

    return r;

})(40,50);

 

Get a random item from an array

var items_array = [12, 548 , 'a' , 2 , 5478 , 'toogit' , 8852, , 'freelance' , 2145 , 119];

var  randomItem = items[Math.floor(Math.random() * items.length)];

 

Get a random number in a specific range

This code snippet can be useful when trying to generate fake data for testing purposes, such as a salary between min and max.

var x = Math.floor(Math.random() * (max - min + 1)) + min;

 

Generate an array of numbers with numbers from 0 to max

var numbersArray = [] , max = 100;

for( var i=1; numbersArray.push(i++) < max;);  // numbers = [1,2,3 ... 100] 

 

Generate a random set of alphanumeric characters

function generateRandomAlphaNum(len) {

    var rdmString = "";

    for( ; rdmString.length < len; rdmString  += Math.random().toString(36).substr(2));

    return  rdmString.substr(0, len);

}

 

Shuffle an array of numbers

var numbers = [5, 458 , 120 , -215 , 228 , 400 , 122205, -85411];

numbers = numbers.sort(function(){ return Math.random() - 0.5});

 

A better option could be to implement a random sort order by code (e.g. : Fisher-Yates shuffle), than using the native sort JavaScript function

 

A string trim function

The classic trim function of Java, C#, PHP and many other language that remove whitespace from a string doesn’t exist in JavaScript, so we could add it to the String object.

String.prototype.trim = function(){return this.replace(/^s+|s+$/g, "");};  

A native implementation of the trim() function is available in the recent JavaScript engines.

 

Append an array to another array

var array1 = [12 , "foo" , {name "Joe"} , -2458];

var array2 = ["Doe" , 555 , 100];

Array.prototype.push.apply(array1, array2);

 

Transform the arguments object into an array

var argArray = Array.prototype.slice.call(arguments);

 

Verify that a given argument is a number

function isNumber(n){

    return !isNaN(parseFloat(n)) && isFinite(n);

}

 

Verify that a given argument is an array

function isArray(obj){

    return Object.prototype.toString.call(obj) === '[object Array]' ;

}

Note that if the toString() method is overridden, you will not get the expected result using this trick.

Or Use..

Array.isArray(obj); // its a new Array method

You could also use instanceofif you are not working with multiple frames. However, if you have many contexts, you will get a wrong result.

var myFrame = document.createElement('iframe');

document.body.appendChild(myFrame);

var myArray = window.frames[window.frames.length-1].Array;

var arr = new myArray(a,b,10); // [a,b,10]  

// instanceof will not work correctly, myArray loses his constructor 

// constructor is not shared between frames

arr instanceof Array; // false

 

Get the max or the min in an array of numbers

var  numbers = [5, 458 , 120 , -215 , 228 , 400 , 122205, -85411]; 

var maxInNumbers = Math.max.apply(Math, numbers); 

var minInNumbers = Math.min.apply(Math, numbers);

 

Empty an array

var myArray = [12 , 222 , 1000 ];  

myArray.length = 0; // myArray will be equal to [].

 

Don’t use delete to remove an item from array

Use splice instead of using delete to delete an item from an array. Using delete replaces the item with undefined instead of the removing it from the array.

Instead of…

var items = [12, 548 ,'a' , 2 , 5478 , 'foo' , 8852, , 'Doe' ,2154 , 119 ]; 

items.length; // return 11 

delete items[3]; // return true 

items.length; // return 11 

Use

var items = [12, 548 ,'a' , 2 , 5478 , 'foo' , 8852, , 'Doe' ,2154 , 119 ]; 

items.length; // return 11 

items.splice(3,1) ; 

items.length; // return 10 

 

Clearing or truncating an array

An easy way of clearing or truncating an array without reassigning it is by changing its length property value:

const arr = [11,22,33,44,55,66];

// truncanting

arr.length = 3;

console.log(arr); //=> [11, 22, 33]

// clearing

arr.length = 0;

console.log(arr); //=> []

console.log(arr[2]); //=> undefined

 

Simulating named parameters with object destructuring

Chances are high that you’re already using configuration objects when you need to pass a variable set of options to some function, like this:

doSomething({ foo: 'Hello', bar: 'Toogit!', baz: 42 });

function doSomething(config) {  

const foo = config.foo !== undefined ? config.foo : 'Hi';  const bar = config.bar !== undefined ? config.bar : 'Me!';  const baz = config.baz !== undefined ? config.baz : 13;  // ...

}

This is an old but effective pattern, which tries to simulate named parameters in JavaScript. The function calling looks fine. On the other hand, the config object handling logic is unnecessarily verbose. With ES2015 object destructuring, you can circumvent this downside:

function doSomething({ foo = 'Hello', bar = 'Toogit!', baz = 13 }) {  // ...}

And if you need to make the config object optional, it’s very simple, too:

function doSomething({ foo = 'Hello', bar = 'Toogit!', baz = 13 } = {}) {  // ...}

 

Object destructuring for array items

Assign array items to individual variables with object destructuring:

const csvFileLine = '1997,John Doe,US,john@doe.com,New York';const { 2: country, 4: state } = csvFileLine.split(',');

 

 

What is the difference between Java and JavaScript?

 

These are two different programming languages.

 

Javascript is a language that has gained tremendous popularity as a language on the web browsers to create dynamic and interactive web pages.

 

Java is a language that has got a similar popularity when you build a “backend” system, which is a fancy word for “almost anything”.

 

Despite the common prefix, they are not related; there creators are different and so are their origin stories (as highlighted by other answers). 

- JavaScript is a genius marketing scam that polluted the world of browsers exceptionally well. The browser reads JavaScript’s code line by line and executes it.

 

- Java is a general purpose language that is used almost everywhere, from Android mobile apps and cryptography to OS and cloud computing. Java’s code is stored in bytecoded format and then gets JIT compiled before the actual execution. In other words, it translates the bytecode to machine code.

 

- Java is class based. JS is prototype based. All objects, like Array or Function inherit from the Object.prototype which remains on top of the chain.

 

- JavaScript uses dynamic type checking (checks the variables while the code executes), unlike Java’s static checking system (variables are verified at compile time), which is more bug free.

 

- The word “Script.” It’s a joke, in case you didn’t get it.

 

 

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