For many years, Python and Java have been one of the most commonly used general purpose programming languages, though Java is considered more popular than Python according to TIOBE Programming Community Index. Nowadays, developers use Python and Java for developing a variety of web and desktop applications. Both Python and Java are the most common languages for data science and machine learning.
Python is the only programming language that was designed to emphasize code readability, while Java’s design with the aim of enabling developers to build applications with least implementation dependencies. Additionally, Java is one of the only two official Android programming languages. Hence, the debate of Python vs Java has always been in developers’ cycles.
Nature of Programming Language
Python and Java are both high-level programming languages. However, Python is an interpreted programming language, meaning that developers require specific Python interpreters to execute the code. On the other hand, Java is a compiled programming language, which means Java code is compiled initially into bytecode that can run on any execution platform. The developers can also sort the code from one platform to another easily.
Both Python and Java support a variety of regularly used programming paradigms. Python also supports imperative, procedural and functional programming paradigms in addition to being an object-oriented language. Originally, Java was also an object-oriented, class-based and concurrent programming language, but it has evolved over the years. For example, Java 8 introduced the concept of first-class citizens to refer to functions while at the same time, still supporting important programming concepts such as lambda expressions.
Python was designed to emphasize on code readability unlike Java, and it even allows developers to keep the code base short, clean and readable. For this reason, a lot of programmers prefer Python over other programming languages. With Java, each update comes with sets of new features to enable developers to simplify their workflow. Taking Java 9 as an example, this version came with features that help accelerate software development by structuring applications with modules. Each module is then designed as a reusable group of code. But unlike Python, programmers have to put extra work to ensure the Java code is clean and workable.
Performance and Speed
Whereas both languages lack the ideal speed needed for high-performance computing, Java Virtual Machine (JVM) is used to speed up the execution of code via just-in-time compilation (JIT). JIT compiles quickly the Java bytecode to native machine code. Additionally, by supporting concurrency, Java makes applications to load faster. But that is not to say that their programs cannot be accelerated in fact, there are numerous programming language cross-overs that can help Python developers to accelerate their code execution. For example, programmers can use Cython, to compile code to C or C++ code, or Jython to compile code to Java code or bytecode. These implementations help developers to manage the execution of Python software applications.
Python has a large and comprehensive standard library that lift the burden off developers. Programmers can write a wide range of applications with the help of the standard library, as well as complete several software development projects. There are over 130,000 packages that developers can select, including database, web frameworks, graphical user interface, multimedia, testing frameworks, text processing, system administration, image processing, image processing, and scientific computing. On the other hand, Java also has a large collection of libraries that developers can choose from, like integration and user interface libraries. In this category, Python by far, scores over Java.
Mobile Application Development
Currently, Java is one of the two Android official programming languages, thus a large percentage of programmers uses Java to build mobile applications and games for the Android operating system. When it comes to Python language, developers can still build mobile applications but by using Python libraries such as Kivy. Even so, they will have to put in more efforts to ensure the applications built on Python provide an optimal user experience.
Machine Learning and Data Science
Python is the preferred programming language for big data, scientific computing, and artificial intelligence projects. Additionally, it is the most preferred language for data science and machine learning. In this category, although Python is the most preferred language, some machine learning scientist usually prefers Java when working on projects inclined to cyber-attack prevention, network security and fraud detection.
DevOps and Agile
Both Python and Java allow for the adoption of new project management systems like DevOps and agile. Python features dynamic type system that enables programmers to automate refactoring, while Java features a static type system. Python allows developers to experiment with different ideas which are easy and expressive syntax rules.
Ease of Learning
A study shows that Python is easy to learn for beginners than Java. With its simple and expressive syntax rules, it is easier for beginners to write software applications on Python as compared to Java. Java, on the other hand, requires extra effort to keep code clean and readable, something that can be troubling for beginners. Despite this, many learners still prefer Java to Python because of Android mobile applications.
Both Python and Java are popular and robust programming languages, which have been used successfully for machine learning, artificial intelligence, and data science. Hence, it is natural for the Python vs. Java debate to be discussed by developers to identify the specific needs of every software development task.