The Java vs. Python debate is much like comparing apples with oranges. You’re examining two dissimilar programming languages that enjoy vastly differing user profiles and fan following. Since both are hugely popular, it’s worthwhile knowing what makes them similar, where the differences lie, and how they advantage or disadvantage you in many ways. It’s possible to decide the ideal user scenarios for Java and Python when you’ve fully understood the subtle nuances that structure these popular programming languages.
Both are strong languages boasting powerful libraries, packing enough ammunition to arm the creative developer. You’ll find these libraries providing the backbone for many of the larger applications we routinely use.
Java is a compiled language with the Java source code being compiled down to bytecode before execution by the Java Virtual Machine (JVM). Python follows the bytecode interpretation path, executing freely without compiling first. To the question which is faster – compiled code or interpreted code – the answer is simple; it depends where the language is used. Python runs smoothly in a massively parallel mode when you’re using graphics processors (GPUs). This is true of machine learning applications where faster processing is welcome.
Naturally, both languages differ in syntax with Java opting for curly braces for defining blocks of code. In Python, you follow line-indentation to demarcate blocks of code, which in some ways improves the structure and readability of code. These issues are becoming irrelevant with developers increasingly turning to Integrated Development Environment (IDE) software applications.
Java’s static typing does have its advantages, but a growing legion of developers insist that Python’s dynamic typing is faster and boosts productivity. In the ultimate analysis, it’s the developer’s language learning curve, skill, and experience that merges into a particular viewpoint.
Java vs. Python: What the Future Indicates
Java’s popularity among die-hard supporters notwithstanding, Python has grown by leaps and bounds. The reasons are not hard to find; its flexibility as a language, strong library, a growing community, excellent support, and Python being easier on the novice. Python is scoring high in process-intensive machine learning environments like Artificial Intelligence.
Though much has been made of Java app security flaws, the real problem lies with the Java browser plug-in. It’s not that Python’s security record is flawless, but there’s a strong and supportive community, and Python’s user-friendliness tilts the scales in its favor.
Developers are steadily working on Java, making it compact, faster and more flexible. Java’s acceptability is still high: 90 percent of Fortune companies use it in their coding and most of the larger apps we know are built on Java. Moreover, Java’s cross-compatibility on different platforms is still valuable. This makes it difficult to ignore Java, not that anybody is even trying.
Java vs. Python: The Learning Curve
It goes without saying that knowing C, C++, or JavaScript makes it much easier to code using Java. But for a novice, Python is unbeatable because the learning curve is shorter and the robust structure permits faster coding. This singular feature explains why Python is widely adopted by the scientific and academic community to create applications.
Java’s strength lies in its simple syntax. This makes it easier for developers and machines to tinker with applications. Java works beautifully for large heavy-duty applications. But what do you do if developing applications is not the sole agenda? What happens if people with very different skill sets demand a shorter learning curve?
Python excels in the literate programming approach where a document that describes a program also functions as the source code for the program itself.
This makes Python very useful in research, teaching and presentation fields. You can use Python as it supports literate programming through IDEs like Leo and Jupyter Notebook.
Java vs. Python: The Performance Graph
Language speed comparisons are subjective because the environments using the language may differ. The same holds true if the libraries you access and coding styles you opt vary with the environment.
Another metric affecting speed comparisons is the version of the language that you’re using. When you turn to Java, you’ll notice that most traditional apps resting on the Java platform are two to three versions behind the latest Java version. On the Python side, programmers still use Python 2.x and Python 3.x, preferring one over the other when you’re aiming to optimize a specific library.
So when it comes to the performance of the language, it’s how the language works in the field that should matter to you, forget the structural dynamics.
Java vs. Python: The Popularity Stakes
Ranking the languages by popularity is a subjective exercise because developers hold strong views regarding the tools they use. But most reviews place Python at the top of the heap in 2018. Python has opened up coding for a new generation of programmers.
Its neat syntax and user-friendly features attract people who have no exposure to coding. The Python community is also growing, and at last count boasted an 860,000 strong member base hosting regular PyCon events.
For a developer, a clear and simple line of code translating into easy machine understanding and faster application speed is the Holy Grail of coding endeavor. If you take the example of Artificial Intelligence applications, Python becomes an automatic choice because of the perception that it is leaner, meaner, and faster.
As IT specialists at http://ottawa-it-services.ca/ point out, flexibility is another factor that influences the popularity of the language. Java’s object-oriented approach might appear too cumbersome for beginners, requiring too much effort for a smaller result. Python allows the flexibility of using different models that suit each subtask within an application. This is more appealing than being tied down by a single model that slows down the overall project as in Java.
Use Java and Python to retain the upper hand in the coding universe
Though our review favors Python for its flexibility and ease of use, we would never suggest ignoring Java. Java still remains a brilliant language for server-side coding. It is important to understand that both languages are tools, and a developer uses tools appropriate to each task. A toolkit that packs both languages is most effective in tackling the growing requirements of new applications. Having said that, we may add that Python is conquering the universe because the number of applications that require Python is expanding, and the field carrying highest potential for Python is Artificial Intelligence and machine learning jobs.
