Python vs Java: Top 7 Differences in 2025

A key feature in every Java program is the public static void main method, which serves as the entry point for execution. Java snippet examples, such as those demonstrating public static void main or java database connectivity (JDBC), are widely used to illustrate programming concepts and best practices. JDBC is essential for establishing seamless database connections and performing data operations within Java applications.

Java EE (Enterprise Edition) is a powerful framework for building large-scale, secure enterprise applications. Java is also a primary language for developing android apps, further increasing its relevance.

Java requires strict syntax rules, which leads to complex syntax and more verbose code compared to languages like Python. However, these strict rules, along with java's static typing, contribute to robust, stable, and maintainable code.

Python frameworks like Kivy and BeeWare enable mobile app development, allowing Python to be used for creating mobile applications. Python is also widely used as a scripting language for automation, web scraping, and utility scripts. Web developers favor Python for its simplicity and the power of frameworks like Django and Flask. Python's flexibility and ease of writing code make it a preferred choice for software developers, web developers, and those involved in mobile app development.

Thanks to Python’s elasticity, it can be used in different programming styles, such as functional or procedural programming. Thanks to this, Python is commonly used in many different domains such as data science, machine learning, and web development. Python is used by big companies, for example: Google, Facebook, Instagram, Spotify, and Dropbox.

Java is faster than Python, mainly because it is a statically typed and compiled language, while Python is a dynamically typed and interpreted language.

Interpreted languages execute code on the fly, line by line, while compiled languages need to be translated into machine-language instructions before we are able to run them. In compiled languages, errors make it impossible to run code, but in interpreted languages, debugging occurs at run-time. As a result, runtime errors are more common in Python due to its dynamic typing, while Java's static typing and compile-time error checking help reduce such issues. So, in compiled languages, compilation is needed before testing and it takes additional time.

Both Java and Python can use virtual machines for cross-platform compatibility. For example, to run Java code, the source is compiled into bytecode, which is then executed on the Java Virtual Machine (JVM), enabling platform independence and performance optimization. Python also relies on runtime compilation and can use variants like PyPy for improved performance.

Interpreted languages are usually more flexible than compiled languages, but the drawback is slower execution speed.

Another mentioned reason for Java being faster is static typing. This means that when creating a variable, you need to declare its data type. As Python is a dynamically typed language, data types do not need to be declared. Static typing makes the compiler aware of data types that are in use, and it usually makes code execution faster because of more optimized machine code produced by the compiler.

Additionally, both Java and Python use garbage collection for memory management, which automates the process of freeing unused memory. Java offers more control over garbage collection, while Python emphasizes simplicity and readability.

To sum it up, Python allows for quick iterative development without the need to recompile the project, but it runs slower. On the other hand, Java has to be compiled beforehand, but the resulting program executes faster.

As mentioned earlier, in Python there is no need to define data types of variables. This can increase development speed in Python, allowing developers to write code more quickly and supporting rapid development.

In recent years, Python is getting better support for type hints and they are used more often by developers. It makes Python more similar to Java, and the developer has to think about the data type of the variable and how that variable will be used later. But if we want to develop a working prototype as quickly as possible, we don’t need to use type hints.

Python code is more concise and clean than Java. Python programs are typically shorter and easier to maintain, making them ideal for fast prototyping. In Python, there are fewer things to take care of. Thanks to this, it is great for making prototypes and small projects. Developers can quickly deliver a basic version of a product that can be used by clients. Then, we can quickly gather feedback about the product and work on improving it. This is called the minimum viable product (MVP), which is the core of the Agile Methodology.

Python is well known for being easy to learn, especially thanks to its English-like syntax. In fact, Python is often chosen as a first programming language by beginners due to its simplicity and readability. As a matter of fact, among popular languages, it is one of the easiest to learn. This definitely contributes to its popularity. It is often used by people who are not software developers, for example: system admins or data analysts.

Learning Python or Java helps build foundational programming concepts and programming principles, which are essential for mastering any language. Both languages are widely used in computer science education, providing a strong base for understanding core computer science topics.

Java and Python are high-level languages, but Java is closer to low-level languages. This means that while using it we have more control, but we need to care about more things. This is one of the reasons why learning Java is harder than learning Python.

Python is the most popular language used for building machine learning models. There are several reasons for it. Python is clear, simple, and offers great readability. This is a great advantage when creating complex logics for machine learning. Developers do not need to focus on complexities of language and can use all resources to work on machine learning logic. This is also possible because code written in Python is concise, in contrast to Java. That means developers can quickly achieve what they want without writing much code.

Another reason for Python being great for machine learning is its extensive libraries for data analysis, data processing, and scientific computing. These extensive libraries are a key reason for Python's popularity in these domains, as they provide powerful tools and frameworks that support diverse tasks and improve productivity. There is also a great variety of libraries to choose from and the large community of people using Python for machine learning. This means excellent support for developers.

Java is also used for machine learning and is perceived as a good option, but not as good as Python, mainly because it is more difficult to read and understand.

When deciding on technology for your next project, it is important to choose the right programming language for your software development needs. Both Java and Python are object oriented languages, making them suitable for a wide range of applications and allowing for comparison with other programming languages like C++, Rust, and Haskell. Both Java and Python are widely used in software development and are popular among developers for their versatility and cross-platform capabilities.

Data structures play a crucial role in both Java and Python, forming the foundation for efficient algorithms and robust applications. Code examples can help illustrate the differences between the two languages, such as syntax, data types, and implementation details, making it easier to compare their usability and features.

Python and Java have their pros and cons and are suitable for development of products of different sizes and levels of complexity. If your project will involve machine learning, Python might be a better solution because it is great for creating complex logics. Moreover, Python secures fast development as there is no need to define data types of variables. However, you might choose Java, if you plan to build or scale a large application. Both Java and Python can be used for a variety of applications, from web development to enterprise solutions, and each offers unique advantages over other programming languages.