Python Vs Java

Introduction:

I would suggest that the future will be illuminated with the development in Python. Python is a large heavily bodied nonvenomous constructor snake where java is a coffee. Seriously, even though I have been using Java for a long time and on just started putting my hands on python, I found python really easy and interesting programming language.

Python Vs Java:

Iron Man Vs Captain America. Star Wars Vs Star Trek. Coke Vs Pepsi. India Vs Pakistan. The choice between Python Vs Java isn’t really that kind of rivalry — the two languages typically have different use cases and fan bases.

 

Both are powerful programming languages, e.g., with large, devoted communities and a huge array of libraries supported by legions of developers.

Python and Java  are very different from a number of perspectives. Some of these differences are objective and not open to debate, while others are a matter of opinion, usage preference, or programming environment,e.g., Java is a compiled language and Python is an interpreted language. This difference gives each language particular benefits and drawbacks. Even as arguments rage over whether compiled code is faster to execute than interpreted code, e.g., the truth is typically more nuanced. Whether one language is faster than another depends-among other things-on the environment in which they’re used.

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. FreeCodeCamp calls Python code “neat, readable, and well structured. Proper indentation is not just for beauty here – it determines code execution.”

These structural differences can affect how programmers view the languages and the speed at which a programmer can type them. Theoretically, they also have an impact on the skill level required to learn the language.

Python is more productive language than Java. Python is an interpreted language with elegant syntax and makes it a very good option for scripting and rapid application development in many areas.Python is a dynamically typed programming language where there is no necessity of declaring variables whereas java is a statically typed programming language wherein variables are to be explicitly declared.

Python code is much shorter, even though some Java “class shell” is not listed. This might be one reason why Python can be more productive.

In python, when you extend a base class, there is no requirement such as defining an explicit constructor for implicit super constructor.

There are a  lot of string related functions in Python which is as good as or better than Java, e.g., lstrip(), rstrip(), etc.

There are a lot of classes we need to import to simply read a file and we have to handle the exception thrown by some methods. In Python, it is just two lines.

Python Distribution:

In linux distribution like Fedora or Debian, the dynamic language interpreters will be Python and Perl.

In multimedia development, Python will be a core part of your toolset, and Python is the key open source competitor to proprietary toolsets in the scientific community. The Natural Language Toolkit is a hugely powerful resource for many data mining applications, and Python is entwined deeply into the core of the financial sector as well.

Apple has expressed their support for Python by building tools that rely on it. Python being the only dynamic language interpreter shipped as part of Mac OS X.  Microsoft ship their Python Tools for Visual Studio bundle.

Google, of course, famously chose Python as the only dynamic language supported on their App Engine platform (and they employed Guido van Rossum and a number of other Python core developers).

gcc and gdb both let you write plugins, and your language choices are C/C++ or Python (plus Lisp in the gcc case). Many other infrastructure level tools are going the same way. Fedora’s infrastructure is almost entirely written in Python, as is OpenStack.

Many years ago a lot of formal education program switched from C to C++ (or Pascal or Ada, etc) and C++ to Java for introductory programming courses. Now switching to Python, pushing Java into the role of an enterprise language used only for large and complex applications where the development overhead can be justified to some degree.

Informal education programs are also favoring Python as the first “real world” application language that people are introduced to.

Conclusion:

Python’s future is looking very bright from where we see and assume that its future is assured. Python is far from perfect, and the same can be said for the ecosystem around us. So yes, there are plenty of areas where Python should probably will, improve. But we shouldn’t lose sight of the fact that many of the problems with Python (like binary distribution, dependency management and concurrency) are problems with software development generally, so there’s nowhere for people to go that will magically make those issues disappear.

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