If you’re looking for where to begin in the world of programming, programming languages will be the first thing you encounter. A sea of semicolons, syntax and variables that can be expressed and controlled in hundreds of different ways.
In the debate of which language to start learning first, the question is always between two of the most popular languages: Python and Java. In this blog post, we’ll look at which language is better to start with, and what the differences are between Python and Java.
What is Python?
Python is a high-level, object-oriented programming language first released in 1991. It is an interpreted language, meaning that when the code is run, it executes line by line in the Python runtime. Under the hood, Python first compiles code into bytecode before execution.
Python is a general-use programming language, meaning that it can be used for a wide variety of applications. Everything from web applications to machine learning algorithms can be created using Python – though it’s easier to achieve some of these than others. It’s its simplicity which makes it so widely applicable.
What is Java?
Java – not to be confused with JavaScript – is also a high-level, object-oriented programming language. First released in 1995, this language is compiled, meaning that instead of the code executing directly as it is run, the code is first compiled into bytecode and then run on the Java Virtual Machine (JVM).
While Java is also a general-use language, it has some uses it is seen as more suited towards. For instance, Java remains widely used in Android apps, though Kotlin has been the preferred language since 2019. It is also often used in enterprise applications such as in the financial industry.
Static vs dynamic typing
One key difference between these two languages is the typing. In the context of programming languages, typing is the way in which different components of the code, such as variables or functions, are assigned a type.
Variables, for instance, can be defined to be a number of different types, such as ‘string’, ‘integer’, ‘float’, and ‘boolean’.
Python is a dynamically-typed language, meaning that the variables are checked as they are ‘encountered’ as the code is executed. Python is an interpreted language, so any variables are checked to ensure the type is correct only as the code is run. This allows for workable code to be produced more quickly, as the entire codebase doesn’t need to be checked before it’s executed, and there’s less boilerplate code to write before getting started. However, it can mean that some errors are left unfixed if the code never interprets the incorrect variable.
Java is statically typed – the compiling process which is required before Java code is executed involves every variable being checked for correct typing. If an incorrect type is found, the code will not run and an error will be thrown by the compiler. While this means that errors are drastically reduced from the get-go, it can make it difficult to start out with Java since none of the code will run until all typing errors have been fixed.
Python vs Java: syntax
Python is unusual in that it employs significant indentation, meaning that the way in which lines of code are indented affects how the code is interpreted as it executes.
The majority of programming languages use certain symbols to denote different functions and hierarchies in code, such as semi-colons or curly braces. Python uses how the lines are laid out, for example:
for i in range(1, 11):
print(i)
if i == 5:
break
In the above, the print command and if statement are nested under the for loop on the top line. This is denoted by using whitespace (usually four spaces) before the respective lines. If they did not contain this whitespace, the interpreter would not see them as being related to the for loop on the top line.
Java follows the most common guidelines for how different functions are separated – it uses curly braces ( {} ) to denote different blocks of code. For example:
public class MyClass {
public static void main(String[] args) {
for (int i = 1; i <= 11; i++) {
System.out.println(i);
if (i == 5) {
break;
}
}
}
}
In this example, the compiler knows that the function calling the for loop is to be executed when the “MyClass” class is executed, as it has its own set of curly braces surrounding it. There is indentation present here, but as Java does not employ significant indentation, it doesn’t have an effect on how the code is executed.
An advantage of Python’s use of significant indentation is that it encourages more readable code from the start. A common problem for new programmers is having messy code, which makes it difficult to improve on and learn from when being reviewed. Python’s laid out code gives it a universally-readable format, which is good practice to use in other languages even if the indentation is not required.
Python vs Java: usability
Python is widely seen as the quintessential beginner’s programming language. This is primarily due to its clear formatting which makes it easy to read and understand, unlike other languages such as C# which require far more knowledge to be able to read. It’s also concise, so more can be accomplished with less code. This allows for beginners to move onto other topics more quickly than they could with a more complex language.
Although it’s well-suited to beginners, this doesn’t mean that Python is only used for basic coding. In fact, the language is highly flexible, and with its built-in standard library, users can choose specific modules to include which tailor it to different tasks, such as making it able to utilise internet protocols for web apps. It also has specialist uses like being able to utilise frameworks such as NumPy and SciPy.
Java is also seen as a good language for beginners, just not quite to the same extent as Python is. However, Java has some key functionalities and use-cases which you might consider depending on what you intend to work on as a programmer.
As well as this, Java is seen as the go-to for building Android apps, and much of Android itself is built in Java. While Kotlin is the preferred modern option, Java remains essential for maintaining and integrating Android projects.
Java also performs better than Python in benchmark tests, which is great if performance is a key aim.
One of the other reasons Java has remained as one of the most popular programming languages is its portability. It uses a “Write Once, Run Anywhere” (WORA) philosophy, which means it can be developed on any device, compiled into a standard form of code called bytecode, and should be able to run on any device equipped with a Java virtual machine (JVM).
Performance in 2025
Traditionally, Java has the edge in performance because of its compiled nature and the optimisations of the JVM. This remains true in many enterprise scenarios.
However, Python has improved significantly in recent years:
- Python 3.11–3.13 introduced an adaptive interpreter and Just-in-Time (JIT) features that make code execution much faster than in older versions.
- Python 3.13 also includes an experimental free-threaded build that removes the Global Interpreter Lock (GIL), opening the door for true multi-core usage.
On the Java side, Java 25 (released September 2025) is the latest Long-Term Support (LTS) version, offering continued gains in garbage collection, runtime performance, and scalability.
Concurrency and scaling
Concurrency is how well a language handles tasks running at the same time. It matters in areas like web servers and finance, and also in large-scale data pipelines.
- Python:
Python’s concurrency story has long been shaped by the Global Interpreter Lock (GIL), which restricts execution to one thread at a time. This makes it harder to take advantage of multi-core CPUs with threads. Many developers use asyncio or the multiprocessing library as workarounds. They work well, but add complexity. With Python 3.13, an experimental “free-threaded” build removes the GIL, allowing true parallelism. While not the default yet, this signals a major change in Python’s future for high-performance, multi-threaded workloads.
- Java:
Java has always offered stronger concurrency support thanks to its threading model and the JVM’s mature scheduling. Threads in Java are mapped to operating system threads, enabling robust multi-core execution. In recent years, Project Loom has introduced virtual threads – lightweight alternatives to traditional threads. Virtual threads reduce the overhead of creating and managing tasks. This makes Java scale well for high-traffic servers or large enterprise apps.
Java is still the stronger option for heavy concurrency. Python is catching up with async frameworks and its new no-GIL build.
Ecosystem and tooling
The ecosystems of Python and Java shape what developers can build quickly and efficiently. Here’s how they compare in key areas:
|
Python |
Java |
|
|---|---|---|
| Web development |
Django, Flask, FastAPI (quick build, popular for startups) |
Spring Boot (enterprise-grade, scalable) |
| Data & AI |
pandas, NumPy, TensorFlow, PyTorch (dominates data science & ML) |
Apache Spark, Weka, Deeplearning4j (big data and enterprise ML) |
| Mobile apps |
Limited (via Kivy, BeeWare, but niche) |
Strong legacy in Android (alongside Kotlin) |
| Build & dependency tools |
pip, PyPI (simple, lightweight, but can fragment) |
Maven, Gradle (structured, powerful dependency management) |
| Community & libraries |
Very broad, especially in ML/AI |
Mature in enterprise, especially finance, telecoms, large systems |
