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Java & Scala developer
Madhu

Java & Scala developer  


Scala sql Java 
$10 /hr
Belgium
Data Scientist
Joydeep Mukherjee

Data Scientist  


Scala Statistics Analysts Predictive Analytics 
$25 /hr
India
Big Data Company
Datalamp Technologies

Big Data Company  


Scala Akka mysql 
$20 /hr
India
Big Date Expert
Soufiane Maguerra

Big Date Expert  


Scala Cassandra Java 
$30 /hr
Morocco
Big Data Developer
Rajat Pancholi

Big Data Developer  


Scala sql Spark 
$6 /hr
India
Senior software engineer
Gururaj Gm

Senior software engineer  


Scala Java Spark 
$3 /hr
India
Software Consultant
Charmy

Software Consultant  


Scala Java Spark 
$10 /hr
India
Web developer
Ramkumar

Web developer  


Scala AngularJS mysql 
$10 /hr
India
Senior Software Engineer
Basant Jain

Senior Software Engineer  


Scala Spark Hadoop 
$20 /hr
India
Quality Analyst
Arbind Kumar

Quality Analyst  


Scala Calculus Hadoop 
$15 /hr
India
BigData Engineer
Samy Nathan

BigData Engineer  


Scala Social Media Java 
$0 /hr
India
Bigdata Developer
Balakrishna Janamala

Bigdata Developer  


Scala sql Core Java 
$11 /hr
India
Solution Architect
Jyoti Patidar

Solution Architect  


Scala Java Spark 
$20 /hr
India
Developer
Abhishek Agrawal

Developer  


Scala SAP Hana Java 
$12 /hr
India
Senior Software Engineer
Harhsit Jain

Senior Software Engineer  


Scala Java Spark 
$15 /hr
India
Full stack developer
Saket Puranik

Full stack developer  


Scala Java AngularJS 
$40 /hr
India
Data Analysis
Kundan

Data Analysis  


Scala Java Spark 
$2 /hr
India
Big Data Developer
Suraj

Big Data Developer  


Scala AWS Lambda Java 
$25 /hr
India
Data engineer
Deepa Dileep

Data engineer  


Scala Hadoop Apache Spark 
$56 /hr
India
Software Developer
Shrikant

Software Developer  


Scala Java Hadoop 
$20 /hr
India
Data Engineer
Sahil Chutani

Data Engineer  


Scala Hadoop Apache Kafka 
$25 /hr
India
DevOps Consultant
Gaurav Chaudhary

DevOps Consultant  


Scala AWS Lambda Java 
$20 /hr
India
Product Designer
Maek Twain

Product Designer  


Scala Java Data Science & Analytics 
$40 /hr
India
BigData Analyst
Sachin Tiwari-jaane

BigData Analyst  


Scala Hadoop Apache Spark 
$10 /hr
India
Big Data Technical Consultant / Specialist
Karthik Kannan

Big Data Technical Consultant / Specialist  


Scala Core Java Apache Cassandra 
/hr
India
Big Data Developer
Lokesh Yadav

Big Data Developer  


Scala Spark Hadoop 
$20 /hr
India
Web Developer/ Software Developer
Dunhill Dimaapi

Web Developer/ Software Developer  


Scala Java Android 
$3 /hr
Philippines
Big Data Consultant
Srikanth Srungarapu

Big Data Consultant  


Scala Java Spark 
$34 /hr
India
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Articles Related To Scala


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.

 

 

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.

Now a days, the popularity of scientific computing environments such as IDL, Maple, Mathematica, Matlab and R has increased considerably. Engineer simply feel more productive in such environments. One reason is the simple and clean syntax of command languages in these environments. Another factor is tight integration of simulation and visualization in Maple, R and similar environments you can quickly and conveniently visualize what you just have computed. One problem with the mentioned environments is that they do not work, at least not in an easy way, with other types of numerical software and visualization systems. Many of the environment specific programming languages are also quite simple or primitive. At this point scripting in Python comes in.

 

Python offers the clean and simple syntax of the popular scientific computing environments, the language is very powerful, and there are lots of tools for simulation, visualization, and data analysis programs. Python allows you to build your own Matlab like scientific computing environment, tailored to your specific needs and based on your favorite high performance FORTRAN, C, or C++ codes.

 

Scientific Computing Is More Than Number Crunching: Many computational scientists work with their own numerical software development and realize that much of the work is not only writing computationally intensive number-crunching loops. Very often programming is about shuffling data in and out of different tools, converting one data format to another, extracting numerical data from a text, and administering numerical experiments involving a large number of data files and directories. Such tasks are much faster to accomplish in a language like Python than in FORTRAN, C, C++, and C#.

 

Scripting is particularly attractive for building demos related to teaching or project presentations. Such demos benefit greatly from a GUI, which offers input data specification, calls up a simulation code, and visualizes the results. The simple and intuitive syntax of Python encourages users to modify and extend demos on their own, even if you are newcomers to Python.

 

Python has some clear advantageous over Matlab and similar environments:

  • The Python programming language is more powerful.
  • The Python environment is completely open and made for integration with external tools.
  • A complete toolbox/module with lots of functions and classes can be contained in a single file.
  • Transferring functions as arguments to functions is simpler.
  • Nested, heterogeneous data structures are simple to construct and use.
  • Object-oriented programming is more convenient.
  • Interfacing C, C++, and FORTRAN code is better supported and therefore simpler.
  • Scalar functions work with array arguments to a larger extent (without modifications of arithmetic operators).
  • The source is free and runs on more platforms.

 

How to run Python script

One of the most important skills you need to build as a Python developer is to be able to run Python scripts and code. This is going to be the only way for you to know if your code works as you planned. It’s even the only way of knowing if your code works at all!

 

A Python script is a reusable set of code which is essentially a Python program or a sequence of Python instructions contained in a file. You can run the program by specifying the name of the script file to the interpreter. 

 

This step-by-step will guide you through a series of ways to run Python scripts, depending on your environment, platform, needs, and skills as a programmer. When you try to run Python scripts, a multi-step process begins. 

 

  1. Run Python Scripts Using the Command-Line: A Python interactive session will allow you to write a lot of lines of code, but once you close the session, you lose everything you’ve written. That’s why the usual way of writing Python programs is by using plain text files. By convention, those files will use the .py extension. Open a command-line and type in the word ‘python’ followed by the path to script file and press enter. You’ll see output on your screen.
  2. Run Python Scripts Interactively: It is also possible to run Python scripts and modules from an interactive session. This option offers you a variety of possibilities.
    • Taking advantage of import
    • Use importlib and imp
    • Use runpy.run_module()
    • Hacking exec()
    • Use execfile()
  3. Run Python Scripts from an IDE or a Text Editor: IDE offer the possibility of running your scripts from inside the environment itself. It is common for them to include a Run or Build command, which is usually available from the tool bar or from the main menu.
  4. Run Python Scripts From a File Manager: Running a script by double-clicking on its icon in a file manager is another possible way to run your Python scripts. This option may not be widely used in the development stage, but it may be used when you release your code for production.

 

After you play around with Python on your own or in an online tutorial, I highly recommend to you to write small scripts to strengthen your knowledge. To stay motivated, choose a program that is in some way useful to you, so you can gain insight while figuring out Python. Below are a few ways you can begin to build your expert level in Python script:

 

  • Python Documentation
  • Google and stackoverflow
  • Ask an experience person

 

First, create a very basic version end-to-end. It is much less frustrating than trying to build a super-duper version from scratch. A big plus is that you will have something you can use very fast. Then iterate and add more complex functionality one by one.

 

Second, decompose large problems to smaller ones by introducing functions. Small, cohesive functions are easy to understand, test and debug.

 

Last, but probably the most important thing to keep in mind, is practice makes perfect. Start small, be patient and practice. Happy coding!

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