JAVA V/S PYTHON-STRATEGIC ANALYSIS

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The everlasting high-octane programming fracas catches eye of another blog page! 
Python and Java have been brawling for their supremacy for a long time, with Python firing all cylinders in the last few years whereas Java strongholds its reliability.

For every successful development, finding a perfect language is of umpteen importance. Depending on what that language is capable of, developers can squeeze it out to its optimum performance. Thus, it is necessary to formulate and devise a strategy beforehand by picking the best of the lot. We’ll bifurcate our analysis in different segments by explaining both language and key characteristics, their undeniable monopoly in the programming world and other major characteristics to understand before picking one for your programming aspirations.

Java:
Java is a statically typed WORA (write once run anywhere) programming language, which is object-oriented and concurrent in nature. Java was designed to run on any platform and with Java Virtual Machine (JVM)to back it up, it is achievable with as few dependencies as possible.

Python:
Python is a dynamically-typed general purpose programming language. It is based on a design philosophy that emphasizes code readability, notably using significant whitespace.

Similarities:

The biggest similarity is their “(almost) everything is an object” design and their reputation for excellent cross-platform support, as well as things like immutable strings and deep, relatively standard libraries.

Both are powerful programming languages, for example, with large, devoted communities and a huge array of libraries supported by legions of developers. If you unable do something with the native language itself, it is very easy find a library that provides the required support.

Both languages are compiled down to bytecodes that run on virtual machines, although Python generally does this automatically at runtime and Java has a separate program (javac) to perform the same.

Differences:

Compilation-
The phrase “dynamically typed” means that Python performs type checking at runtime, while statically typed languages like Java perform type checking at compile time. Python can compile even if they contain errors that would prevent the script from running properly. On the other hand, when Java contains errors, it will not compile until the errors have been fixed.

Speed-
Languages don’t have speed; they have only semantics. You can add Python implementations without this restriction, but they can negatively affect portability assumptions within the Python code. Therefore, when it comes to sheer speed performance, Java has the edge.

Declaration-
Java requires you to declare the data types of your variables before using them, while Python does not. Because it is statically typed, it expects its variables to be declared before they can be assigned values. Python is more flexible and can save you time and space when running scripts. However, it can cause you issues at runtime.

Adaptability-
Java in the enterprise world is a more verbose coding style, which means that these systems are often larger and more numerous than Python legacy. The latter language is more common among enterprise code that glues their IT infrastructure together, making it more effective in adapting legacy systems.

Industrial Acceptance-
Big Data, Data Mining, and Data Science have emerged on the market for their different types of operations and applications, such as obtaining data from the data warehouse or the native database. For example, in the Stock Exchange, there is a large amount of available data that must be analyzed and visualized in real time. Python provides immense and integrated support, as it is rich in this aspect. To do this in Java is a bit hectic and Java does not provide a fluid library for this.

Mobile Application Development-
Java so far dominates the market by serving as the official programming language for Android or iOS. Python still does not have the privilege of mobile applications that can be developed using Python, but it is still in process.

Big Data Compatibility-
Big Data, Data Mining, and Data Science have emerged as hot properties due to their different types of operations and applications, viz. obtaining data from the data warehouse or the native database. For example, in the Stock Exchange, there is a large amount of available data that must be analyzed and visualized in real time. Python provides immense and integrated support, as it is rich in this aspect. Java has a bit hectic of visualizing the same and does not provide a fluid library for this.

Security:
Java’s popularity, meanwhile, may have been hurt by its below par security reputation. The Register (one of the leading Tech news site) ruptured Java claiming that 88% of Java apps have security issues. Undeniably, problems with the Java browser plug-in plays a major role in stabbing Java. Although Python’s own security record is in jeopardy, Python’s ease of use can make it easier for less-experienced developers to secure their code, thus giving a cushion to its security measures.

Coding Complexity and Syntax-
Given below is a basic program of hello world:
In Java-

public class HelloWorld {

public static void main(String[] args) {

System.out.println(“Hello, World”);

}

}

In Python

print (‘Hello, World!’)

The two languages are also written differently. When creating a structure in Java, you enclose it in braces. Python uses indentation to perform the same tasks. Python codes are defined as “neat, readable, and well structured. Proper indentation is not just for beauty here — it determines code execution.” Due to easy to understand syntax, many schools have opted for Python as first programming language. Even International Business Times recently noted that Python has overtaken French as the most taught “language” in primary schools.

Stardom-
According to Stackoverflow’s 2018 developer survey, Python became the fastest growing programming language by zooming past C# in 2018 and PHP in 2017. But Python has only won the battle, not the war. Java is still ranked above Python in popularity index with 45% of developers in favor as compared to Python’s 39%. Although, this void is shrinking day by day due to unprecedent acceptance of Python in the world of AI and ML. 
Data scientists and data analysts are hailed as hot job titles for the past few years. Most data scientists are using R or Python, not Java. As this role becomes more prominent, and big data continues its upward trend, it will help Python more than Java. Also, A recent survey from the Association for Computing Machinery (ACM) revealed that Python has surpassed Java as the most popular language to introduce students to programming.

Ongoing Trend-

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Java is still the most popular programming language by virtually any measure even though it is not as trendy as it use to be. Python’s growth has been exponential, especially in developed, high-income countries. Developer productivity, language flexibility, library support, community support, and ease of learning are factors responsible for this progress.

Summarizing Analysis
On a personal upfront, my bet is that the future development trends are going to revolve around Python. The Python community benefits from easy code readability for efficient peer review amplifying the ease by which ideas can be turned into functional apps, therefore outshining Java as a rapid prototyping tool. Although we don’t know what development languages will gain strength, we are sure that a vast pool of people will be armed with Python programming skills. Whether or not those preferences hold true for you, hopefully this comparison is helpful in making your own choices of programming languages. The stage is all set for your views!!

AUTHOR : ABHYUDAYA SINGH PANWAR

MANAGEMENT ENGINEER , CONSULTADD INC 

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