Asking developers to compare languages, it's often like throwing a grenade into a living room - the only certainty you can get from it is a huge mess. This is why focus on emphasizing the features that make them suitable for specific projects. Here we go.
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Source: StackOverflow Survey from 2022
The same languages with the exception of SQL are the most popular languages for people learning to code, though people learning to code are more likely than Professional Developers to report using Python (58% vs. 44%) which suggest that they consider it a very promising technology.
On the other hand, Java seems entrenched in its strong position as the language beloved by large-scale applications, so it would be difficult to replace it soon.
Python was created in the early 1990s by Guido van Rossum, among the first open-source believers. Being tired of the complexity of the long-forgotten ABC programming language but fully aware of its potential, he designed Python - a brand new language, yet strongly influenced by ABC. Compared to its predecessor, Python's syntax was improved and simplified to make it more friendly for beginners.
Then, the language (whose name was inspired by Monty Python's Flying Circus) hit the newly born GitHub. Its popularity increased, pushed by developers seeking something more consistent than Java, C++, or C. Since then, Python has evolved to become a whole ecosystem of tools used in various software development areas, such as machine learning, artificial intelligence, web development, mobile and desktop applications, scientific calculation, computer vision, and more.
Read more in the article: What is Python used for?
Today, given the media frenzy about AI, Python's future looks brighter than ever.
Python can be considered "Jack of all trades" but there are some industries are particularly benefited by using it, such as:
Thanks to extensive libraries and tools like NumPy, SciPy, Pandas, and Matplotlib, Python can handle tasks such as data cleaning, data visualization, machine learning, and statistical analysis.
Frameworks such as Django and Flask make Python well-suited also to develop web applications with minimal coding, and maximal readability.
AI-related areas such as simulation, optimization, and modeling can be dealt with libraries such as SymPy, SciPy, and PyBrain.
In the financial industry, libraries such as Pyfolio and Zipline, are particularly helpful to make use of Python.
Learn more about Python in Fintech.
Python is used in game development for tasks such as game logic and AI. It is used in libraries such as Pygame and PyOpenGL.
And what about Java? Java was created by James Gosling and his team of developers and released by Sun Microsystems in 1995. The language was initially developed specifically with digital devices such as set-top boxes and home appliances in mind, but it eventually evolved into platform-independent languages. The name "Java" was not the first idea, but developers decided to honor the coffee they drank while brainstorming ideas.
The platform-independency mentioned above was the main factor that made Java's popularity skyrocket. Developers were struggling with creating software that could run on multiple operating systems without requiring significant changes to the code, and Java with its "Write Once, Run Anywhere" (WORA) philosophy (it means that code written in Java can be run on any platform that has a Java Virtual Machine (JVM) installed) turned out to be the go-to direction.
In 2009, Sun Microsystems was acquired by Oracle Corporation, which has since continued to develop and support the Java platform.
Java is widely used for developing enterprises, such as customer relationship management (CRM), enterprise resource planning (ERP), and human resource management (HRM). Here, the frameworks such as Spring and Hibernate come in handy.
It is also the primary language used for developing Android applications.
Just as Python, Java can find itself useful in the financial services industry to build trading and risk management systems, algorithmic trading platforms, and payment processing systems, and gaming for developing mobile games, online games, and desktop games.
When it comes to web development, Java is used in web development for building complex web applications, e-commerce platforms, and content management systems (CMS). It is used in frameworks such as Spring, Struts, and JSF.
We are used to setting Python.js and Java on opposite corners, but in fact, they can't be considered rivals, as they are used for different kinds of projects, yet - having said this - it has to be emphasized that they also have some similarities.
Both are high-level languages, meaning they abstract away many low-level details of the computer hardware and provide a more human-readable syntax. They are also object-oriented and provide a modular, reusable, and easy-to-maintain code structure by representing real-world entities as objects with well-defined interfaces, which makes them suitable for a huge range of cross-platform applications.
Despite these similarities, the differences between these two major languages are hard to ignore. The first one, related to syntax, is visible in code snippets.
Python's syntax is considered more concise and readable as it uses obligatory indentation to indicate code blocks, while Java reaches out for curly braces (indentation is optional yet recommended). But that is just the tip of the iceberg, as there are more syntax-related differences.
Python does not require variable declarations and variables are dynamically typed, unlike statically-typed languages like Java, producing numerous consequences. When variables are created dynamically, and their type is inferred at runtime based on the value assigned to them, the code is easier to write and more flexible as they can change their type during runtime. Still, it can also lead to potential errors and debugging problems, and performance slugs.
Java is - in general - more restrictive and less forgiving. It enforces strict OOP (Object-Oriented Programming) principles, which means it emphasizes using objects, classes, inheritance, encapsulation, and polymorphism to build complex systems while using a strong-type system that requires variables to be declared with a specific type. Python, on the other hand, also supports functional programming, where functions can be used as first-class objects, as well as imperative and procedural programming styles.
Java is far more opinionated, while Python provides more flexibility.
Both Java and Python are among the most popular programming languages. Yet, Java's community is larger and more established because it has been around longer and widely used in enterprise environments.
However, Python's general-purpose nature and its strong position in recently skyrocketing fields related to gaming, Data Science and Artificial Intelligence put it at the center of the interests of developers worldwide, making the community around it rapidly growing, welcoming, and very diverse.
Java, as a compiled language, tends to perform better than interpreted ones because they undergo a compilation process during which the source code is translated into machine code or bytecode before execution. This compiled code is optimized for the specific architecture and platform it runs on, making it faster and more efficient.
In contrast, interpreted languages - and Python is one of them - execute the source code directly, bypassing a compilation step, which means the interpreter translates each line of code into machine code at runtime.
Java, commonly used in enterprise-scale applications, is known for its scalability, which is brought about mainly by its strong type system. Static typing can catch errors at compile time and ensure type safety at runtime. The Java Virtual Machine also allows for efficient memory management and garbage collection, which can help prevent memory leaks and improve performance.
As an interpreted language, Python can be slower than Java when handling large amounts of data or complex operations. However, thanks to a robust ecosystem of tools and libraries, such as NumPy and Pandas, to name just a few, it is possible to improve it, while gaining scalability, which makes Python well-suited for rapid prototyping and experimentation. It can be extremely helpful in the early stages of a project.
Java's superiority in terms of scalability is also related to its syntax, but indirectly. On the surface, this language, with its strict rules and a huge number of variables, can be perceived as more challenging and unfriendly. Still, these characteristics came with profound benefits due to stability. True, Java developers need to create, check, and then fix more extensive code bases, but - after the process - the chance the software will be stable and less error-prone rises significantly. That, in turn, favors the scalability of the systems that can be extended without the risk.
Don't get me wrong, not all Python programs are unstable, yet this language rarely serves as the foundation for critical enterprise-scale applications. While developing a large app based on Python, challenges must be addressed through careful design and optimization.
Python and Java have extensive online documentation, but as much as it is hard to compare their sizes, there are distinctive differences between their tone, format, and style. Given the community's character, it should come as no surprise that Python's documentation is more searchable and easy to navigate.
On the other hand, Java often has its documentation in a more traditional, corporate-style, downloadable format, such as a PDF, with a more conventional table of contents and index.
The format differences come hand in hand with style distinctions: Python's documentation is much more casual and example-oriented than Java's, which relies more on technical jargon.
On the surface, we can already see that Java is more suitable for large-scale applications. At the same time, Python is more general-purpose and can be used in minor web development, scientific computing, data analysis, and Artificial Intelligence.
In practice, Python can be used for quick prototyping and - then - changed to Java, known for its robustness, security, and scalability. With Python, as the project gets giant, bugs that span modules can be complicated to track down. Despite being a bit scary initially, Java deals much better with maintaining the app later.