Firstly, Python is an interpreted high-level programming language with dynamic semantics and object-oriented programming designed to be easy to read and implement. It is a scripting language like Perl/ruby and used for creating web applications too. Java-Script is an object-oriented programming language which allows you to create dynamic web pages and got standardized in ECMAScript language specification. Java-Script supports different programming paradigm as object-oriented, functional, and imperative programming but not procedural programming.

What is Python?

Particularly, Python supports different programming paradigm as object-oriented programming, functional programming, imperative programming, and procedural programming. It came up with huge built-in modules and packages. It allows programmers to use different program styles for simple and complex programs.  now we will discuss the Python vs Javascript.

What is Java-Script?

Secondly, Java-Script is an object-oriented programming language. It is highly used in browsers to provide dynamic functionality which we cannot achieve through normal HTML and CSS. It has support for standard applications with text, regular expressions, and dates.

Lets us start with the comparison: Python vs JavaScript

Direct Comparison

Key Differences between Python and JavaScript

In summary, lets us see some of the points that shows the Differences Between Python vs JavaScript

• Python is strongly typed – no implicit conversion between types whereas JavaScript is weakly typed.
• The synchronous and blocking code is standard in JavaScript whereas python as de-facto as default.
• JavaScript can be used to run on frontend whereas python is on server side programming or backend.
• Python has procedural programming whereas Java-Script does not have.
• Java-Script has; as statement terminator whereas python has a newline.
• Python is a better-designed language which makes it easy to maintain whereas JavaScript is poor.
• Python is not good for mobile development whereas Java-Script is good.
• Python is slow to run comparatively to JavaScript.
• Python provides huge standard library whereas JavaScript has a limited standard library.
• Python heavily relies on assignment with no difference between variable and assignment whereas JavaScript doesn’t relay.
• Python has many libraries for scientific computing, data analytics, and machine learning whereas JavaScript does not.

Recommended Read: Laravel VS Python VS NodeJS

• Python has support for many numeral data types like int, float, fixed-point decimal whereas Java-Script mainly works on floating point variables.
• Python has inbuilt REPL whereas JavaScript does not have.
• JavaScript runs on both browser and server whereas python is mostly used for server-side programming.
• Python is easy to get started comparatively to JavaScript.
• Python is easy to find new jobs comparatively to JavaScript in this year.
• Python object-based is nearly equal to JavaScript and python supports programming style which uses simple functions and variables.
• JavaScript is most complex modern programming language comparatively to python.
• Python and JavaScript both use a lexical scope with small differences.
• Python has a Self-argument as the first argument for each method whereas JavaScript has accessed the object using “this”.
• Unlike JavaScript, python does not have a way to inherit from instances.
• Python is good if we do data analytics, machine learning or math-intensive operations whereas JavaScript is good for building a website or native applications as it took less time for UI work.

Also Read: PHP vs Python

Firstly, for any kind of web development, as a web developer its better to go with PHP and Laravel over Python and Django. But they’re both great pairings of powerful tools with long futures. Let’s get into the pluses and minuses.

In summary, if you compare the two language wise, PHP is a language designed for the web. It’s made from the ground up specifically for web development and the fastest development language in that environment. PHP 7 also seems to be much more efficient than Python 3. It needs less VPS memory overhead in order to achieve and accomplish the same task. As long as we’re talking about web tasks. (PHP is more performant though, Laravel does not necessarily share that performance.)

Convenience for Web development

Python 3, on the other hand, is useful to know far beyond the web development spectrum.  If you are also into other things. Much like C# is known as the language for modern video game development. Or any kind of cross-platform mobile development. Python is known increasingly as the language for Big Data and AI.  It is also used for machine learning analysis and predictive analysis. the more you are going to use Python with Django, the better suited and abled you will be for these other useful areas in the near future.

There are going to be more web development jobs and tasks for PHP coders. But there are more jobs in general for Python coders as well. It depends on how dedicated you are to the web, as most PHP jobs or gigs will be related to WordPress or, increasingly now, Laravel. PHP is all web designing and development, all the time.

Framework-wise, Laravel also makes you and enables the use of classic, traditional OOPs (object-oriented programming) as well as the MVC (model-view-controller) patterns. You will be very ready to use other robust and solid MVC frameworks. Examples  (like say .NET) after mastering and gaining insights for Laravel. Django is less so, as it’s a little more quirky as well as unique with its MVT patttern (model-view-template) approach. It is a bit less married to the OOP paradigm per se.

Google Trends Comparison-

PHP with Laravel or Python with Django

Laravel also has gained a huge amount of considerable momentum over Django as of 2018. Let’s see the Google Trends results for how many people are seeking info on Laravel these days. How many (fewer) are checking out Django. I also used Ruby on Rails for good measure, which was #1 in this comparison.  It faired recently through 2013 and 2016 but is now #3 out of 3 as of 2018.

Laravel first passed over the Django framework overall in developer “interest” two years ago in April 2016, then passed Ruby on Rails in December 2016, and has gradually increased its lead over both the frameworks through every month of 2017 and, so far, and as of 2018. There is actually a bit lesser new interest in Django or Rails today than there was over five years ago on May 1, 2013. Meanwhile, if you see there exists a 700% more interest in Laravel today than there was on May 1, 2013.
The math is coming up Laravel.

Recommended Read: PHP vs Python

You can not really go wrong with either of these frameworks, but if you are equally proficient and have mastered PHP and Python, Laravel has the momentum as well as the stricter (or at least more traditional) adherence to certain “best practices” that exists in the field of web programmings such as OOPs and MVC. And, language-wise, PHP powers much of the websites that are out there.,(thanks in part to WordPress) and there will undoubtedly be plenty of such kind of open opportunities in PHP web development for decades into the future.

Primarily for the above listed three reasons, Laravel and PHP are probably going to be your best bets for web development as of 2018 and looking toward the 2020s.

Frameworks Popularity

We are also adding the caveat that we saw on TechEmpower.If you compare this with raw PHP, you will find that Laravel does not perform better. For a basic web app that is going to have hundreds of users, Laravel is a joy to use. But for something much larger and scalable, an upgrade to the similar (by way of MVC and OOP) yet slightly more complex .NET Framework may be in your future.

If you are building a really large or high traffic website that has tens of thousands of users, I’d maybe consider Django for the job after all, or more likely make the use of ASP.net Core 2 or Node.js instead of either. That being said, Laravel is able to handle whatever you’d throw at it. You’d just need to upgrade the hardware. We can also have expectations that Laravel will make performance improvements, as it’s still relatively new compared to each of these much more mature frameworks.

Also Read: Django vs Laravel: Which Web Application Framework to Choose?

If you are looking to build your website, web application or mobile application with PHP with Laravel or Python with Django or want to hire developers then contact us on enquiry@nimapinfotech.com

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In this article we are going to compare as well as contrast two major technologies, that is NodeJS and Python. Let’s us jump right into the basics:

1) What is NodeJS and What is Python?

Before we start discussing the basics of these technologies and platforms, we need to clarify what exactly these are that we are comparing.

Python is a computer programming language. Node JS is not. The language used for NodeJS is JavaScript. Node Js is a runtime environment for JavaScript.

The main key difference between Python and NodeJS means that when you do coding inside of NodeJS you are using the same basic language (JavaScript) for both the frontend and the backend.

Lets us deep dive into the breakdown of these technologies.

2) The advantages provided by Python to developers is as follows

Python is very friendly to junior developers and inexperienced developers.

Python is a very beginner-friendly language. This is why it is much likely to be the most popular introductory language in US universities. Major mistakes made by junior developers in some frameworks are easily forgivable, and they are less of a hindrance moving forward in development.

On the other hand, inexperienced developers tend to get slowed down by making mistakes in development. These mistakes are common to people who do not fully understand some of the more advanced concepts and the inner workings of JavaScript.
This phenomenon can be easily attributed to the way JavaScript has advanced over the years. Concepts such as object-oriented programming have been receiving meaningful traction only after plenty of much less elegant code snippets and tutorials have been spread online.

Most of the Python frameworks do not require a very high skill level from the developer’s point of view.
A very good example of this is the Django framework, that has a mature ecosystem and allows you to write quality code swiftly.

Python is more versatile as well as universal
Python can be used for desktop app development, and all the credit goes to electronJS, the main use case that is favorable to node js is the web. The applications of Python have known to go far beyond the web.

Python is the main candidate to become the next level programming language for data science. This is a great asset to system administrators because it allows them to write small one-off scripts and on top of that it provides large system admin tools such as Ansible

A good example that has used Python is Dropbox, one of the most common desktop apps written in Python.

Python is simpler as well as easy to use, better documented and better covered.
This is proven to give Python an edge over NodeJS, even after both technologies are admittedly fast to write in.
NodeJS is a JavaScript implementation, this is a language with a long history and a predominantly a front end tool. Therefore solutions that involve, NodeJS can be easily found online. But these may be inadequate for backend use and they rely on inaccessible interfaces

This use-case cannot be overstated, because each JavaScript framework or runtime environment tends to have a slight deviation on how it was implemented using JavaScript.

This situation has been improved over the years. But it is still a long way off from Python where CPython being a single implementation that is used in a vast majority of Python projects.

3) The advantages of Node JS are as follows

Node JS developers are more flexible

Since we have the same language that is used for both the front end as well as the back end, you need to be a JavaScript developer to use NodeJS. This functionality can come handy when you most needed it. The fact remains that when you have a solid understanding of the project and have the right people to build it, you cannot go wrong with JavaScript and NodeJS.

The development environment of NodeJS is less opinionated

Numerous NodeJS packages are simple, single-purpose libraries and micro frameworks that force the developers to make conscious decisions on what to use them for and when.

This makes NodeJS much more demanding. It requires a high level of advancement on the developer’s front than what it takes to generate code in Python on top of Django using built-in solutions for ORM, cache abstraction, and so on.

With NodeJS you can use JavaScript for coding any functionality

NodeJS allows you to code both the backend as well as frontend using JavaScript. This implies that you do not need to know different technologies and that shows that your developers do not need to learn a different implementation of the same programming paradigms.

At the stage of assembling your development team, you do not know how many, Python or JavaScript developers you will be required, your needs will also differ in sprints, depending on your goals.

Using the same language for the entire project removes the risks from the equation. You can also share a part of the code with the front and the back ends. This is a huge benefit to not having to do the same thing twice.

The NodeJS community is very large and JavaScript is one of the most dynamic and fastest-growing programming languages out there

JavaScript has been growing at an exponential rate. There are more than 500 packages for JavaScript being introduced every day. Python has no longer the advantage of numerous libraries that it once in time used to have. JavaScript has caught up with NodeJS in this aspect.

Read More: PHP vs Python

4) The problem with NodeJS and JavaScript

JavaScript has been developing super fast now. But this was not the case earlier.
In the beginning, the language was constructed haphazardly, and it has been struggling with issues caused with its older versions as well as the compatibility issues that bring with it.

JavaScripts recent rise in popularity has also brought another major downside to it.
So many developers have turned to the language in such a short period of time that it has been pretty difficult to keep up with the latest updates in the languages

The swift and rapidly grown happening to the language also brings another problem with it. This problem is that there is no proper and detailed documentation for these libraries that have been coming up for Node JS. This results in the poor quality of programs for Node JS programs.

Sadly this is nothing new for JavaScript as it has been very typical. If history has taught us anything it is that Python is much more reliable.

5) Main aspects to consider

Here are 3 main aspects that shed light on the different aspect of the story, this will help you to make an important decision:

Trending Technologies:

Python has been a major player in Machine Learning applications in the field of data science and it provides tested libraries for ML
It is far easier to find ML experts who are well versed in Python than JavaScript
MicroPython-a lighter and smaller version of Python can be run with much less resources and less power thus making it a perfect fit for IoT devices.

On the other hand, NodeJS is much more comfortable to be used in the Internet of Things (IoT)
When you compare the most popular libraries for Python and JavaScript

Speed and Performance:

One major drawback of Node JS is its inability to multitask., It cannot do many things at the same time unless you write very well code for it. Both Python and NodeJS pretend to do a lot of stuff at once, but Python applications tend to use a much simpler and traditional multiprocessing model approach instead of a more advanced asynchronous paradigm.

When written correctly, your software will send information to the Operating system that it needs to perform a certain task and move on, while the system works on that. But if you did not code the application efficiently, the app will wait for the system to complete the task and does not do anything in the meantime.

Team Composition:

The truth is that Python is well suited for some projects and JavaScript for others. Lets not that building software is a fluid process. The most important thing is team composition. If you have good python developers, then use python. Or if you have good JavaScript developers then use JavaScript.

Recommended reading: Ruby vs Python

Conclusion

At the end of the day, it depends on what features do you want to implement in your project and how you want your overall application to behave. You can and you should choose the technology that best fits your requirements and fulfills all your objects, it does not matter whether this is achieved using Python or NodeJS JavaScript for that matter.

If you’re looking to hire node JS developers or looking to hire python developers then drop us an email with your requirements. We have experienced developers who have profound knowledge of implementing web systems using node JS or python. You can share your requirements with us at enquiry@nimapinfotech.com.

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Whenever a new technology comes in. This is to determine which technology is able to solve all our programming and designing problems and provide us with the most optimum solutions. The technology that is able to do this is valued at a much higher rate and we give the preference to it. The technology is also suggested to others because we encountered a seamless and a less difficult experience with it. Technologies comes and goes but the best experience always remains at the back of our minds. We are even motivated to suggest these technologies to our peers, friends and colleagues. Simply because we got a good experience with it.

Often there are computer technologies that have matured fully to provide stability and benefits for the developers to solve computing problems. In this article, we are going to discuss as well as compare two very much mature technologies and see how do they stack side by side. These technologies are Ruby and the other one is Python. We are going to compare and contrast as well as highlight the features of these two languages.
 

Let’s start by listing down the similarities as well as the differences between the two languages:

Similarities between Ruby VS Python

These languages are also Cross-Platform which means that it is convenient for distribution teams where people use Linux or Windows on their computers.

Both these languages are dynamically typed languages. This means that you are free to use a variable without declaring it first.
These languages also support Object-Oriented Programming right out of the box

Differences between Ruby Vs Python

Ruby is commonly used in organizations that create web applications. Programs written using Ruby enables teams to swiftly and rapidly develop as well as focus on business processes instead of coding functions from scratch. Ruby is able to provide an excellent Model-View-Controller (MVC) structure so you are able to strictly separate your user interface, data as well as the business functions.

When you compare Ruby using Python, Django is Python’s most popular MVC framework, not only this, but python is also popular beyond the domain of web applications. For example, consider the Pandas library, which is used for data munging and preparation along with other math libraries such as stats-model and numpy. Tensorflow is popular for any kind of machine learning tasks, and Matplotlib is powerful for data visualizations. There is also another library called SciPy.  This library has resources in order to solve math functions.

Flexibility

When it comes to the Flexibility part of Ruby, it has adopted the Perl’s philosophy that there is more than one way to do it. Because of this you will find many different application methods in order to accomplish a certain task in Ruby. Depending on who is writing the code, this can lead to unnecessary complexity as well as obfuscation

On the other hand, Python uses a different approach where simplicity has more preferences and value than complexity. Hence its philosophy is that there should be only one way to do the task. So although Python code will not be the most flexible, it has a very good chance to be readable to an inexperienced programmer.

Read More:  PHP vs Python

Popularity

Over the past few years, we have witnessed the Use of Ruby slowing down and slowly declining from the list of the top ten languages, from fifth place in 2014 to the tenth place in 2018. Comparatively, Python has maintained its spot as well as it shows an improvement in its Rankings moving from the 4th position in 2014 up to the 3rd position in 2015 where it maintained its rankings till the end of 2018.

We can also check the job opportunities for these languages. Stack overflow returned twice as many results compared to Ruby. If you use LinkedIn, Python is leading by up to 20% over Ruby. Therefore if you want a skill set high in demand then you should go for Python as your preferred skill set. But if you prefer something niche with higher pay in the long run, then you should opt for Ruby.

Know More: 5 Reasons Why You Should Choose Python for Big Data

Reusable Code

When the question is about Reusable code, publicly available and ready-to-use code is an important factor when deciding on a programming language. Python is used to call them as Modules. These are available via PyPI where you can search from over 150000 modules. Reusable code in Ruby is called Gems. There are close to 150000 gems. But the most differentiation between these is the ability to filter them. PyPI allows filtering by categories like “development status” and this can be much more straightforward when manually comparing libraries and manually evaluating the code.

When the case is about packaging and automatic dependency resolution, both these languages offer a painless installation of dependencies in the development environment. An advantage on the python’s side is virtualenv enables you to isolate different versions of the Python interpreter. Ruby also has a similar feature through rbenv or rvm, but this can be a little cumbersome to use.

Learning Curve

Python is much easier and user-friendly as well as quicker to learn for beginners who are new to programming. The syntax is the easiest to understand and is much more readable to the average beginner. But beyond that, you need to make decisions on what framework you should use to supplement the bare-bones Python.

This is because it has inbuilt features like scaffolding and Active Record in order to accelerate your development. As soon as you know about them you will be able to build a CRUD application using API access in a matter of minutes.

Testing and Troubleshooting

Testing the code in the early phases of development is important and has to be done during the code development stages only.  Even though PyTest and unit test have been present, there has not been a single framework for Behavior Driven Development (BDD) in Python. RSpec plays this role in Ruby and behaves seem to show some results but it does not look mature as RSpec.

Recommended Reading: Java Vs Python

Ruby VS Python Direct Comparison

Conclusion:

Ruby and Python are the two most mature language frameworks that have provided many benefits. These benefits are for web development and made the overall development effort a whole lot easier and flexible. If you’re looking to hire Ruby Developers or to hire python developers then contact us at enquiry@nimapinfotech.com with your requirements. Our representatives will get back to you within 24 hrs.

Hope you like this comparison on Ruby vs Python.

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What is NLP?

NLP stands for natural language processing. It is the field of computer science and artificial intelligence that deals with the communication between a human and a machine. NLP helps machines to interpret the human language and extract the intent, context, and meaning of the message and come up with proper response based on analysis that is similar to a human being. Over a period of training, it can be used to personalize and enhance the user experience.
 

What is chatbot?

It is a program built using artificial intelligence that responds to the user using text or sound. Chatbots are generally used in customer support, seat reservation, product ordering and making appointments. The famous example of chatbots is Alexa, Siri, Google assistant. Chatbots provide 24×7 assistance to the user. Today almost every company has a chatbot to engage with its users. Find out more about chatbots – read what is a chatbot.
 

How NLP works?

The first step in NLP is tokenization. Tokenization mean splitting sentences into words. We can just split the words where space occurs. For the example purposes, consider the following sentence “Delhi is the capital of India”. After tokenization, we get a set of words {“Delhi”, “is”, “the”, “capital”, “of”, “India”}

The next step is identifying the parts of speech of each token. For example, “Delhi” and “India” are proper nouns. Thus, the knowledge gained from this step is that Delhi and India are proper nouns so the sentence must be talking about them.

Next step is to identify the stop words. Stop word is nothing but a list of words that frequently occurs in a sentence. So NLP filters out these stop words. In the given above example “is”, “the”, “of” is primarily the stop words. Stop words can be identified by just by checking a hard-coded list of the available stop words.

The following step includes dependency parsing where the NLP determines how all the words are related to each other. Next step is NER (Named Entity Recognition) which detects and label these nouns with the real-world concepts that they represent. For example “Delhi” and “India” represents the location.

These above steps are just a short summary of how NPL extracts information from messages and uses it for further analysis.
 

You may also want to know more: Artificial Intelligence

Why NLP is required in the chatbot?

The main reason why chatbots are developed is to provide human-like assistance to the user and help him to achieve his/her goal. NLP helps the chatbot to understand the user’s message and respond appropriately. For example, if you send a message “Hi”, it is the NLP that lets the chatbot understand, that the message is a standard greeting. Thus using AI functionality the chatbot will respond with a return greeting.

Many chatbots are of little or no value without NLP. Only with NLP the chatbots understand messages and respond appropriately. The system is powerful enough to make or break a chatbot’s success as well as make it popular. With NLP chatbots can connect to queries and identify entities as well as the sentiments to generate own intelligent responses. Without NLP a chatbot cannot meaningfully understand the context of the message. The message is just a text input for a chatbot. It’s the natural language processing that helps to extract the context and meaning of the message.

NLP empowers bots with personality. It enhances the functions of chatbots for all businesses. It elevates their scripted and sequential conversations of chatbots to that of humans. Assessing, analyzing and communicating skills of NLP based chatbots makes this possible.
 

Read More: Creating Chatbot with Deep Learning

 
NLP understands and enables the needs of the customer with better clarity as well as the accuracy. It gains importance in the business world in order to provide better user experience across applications like chatbots, speech recognition, social media listening & texting, voice-enabled applications and devices. NLP with its translational and other features are the need of the hour. NLP based chatbots improve customer experience. You can fulfil the Expectations of today’s millennial business people around the globe with NLP’s business intelligence.

Want to build your own business app with cool development hacks? We at Nimap Infotech have experienced Python developers to take your business one step closer to your goals. Hire Python developers to experience the best full-stack python web development services. Contact us to offer you the most optimized solutions for web and mobile technologies.