Python’s continuous rise in popularity comes at the expense of the decline in popularity of other important programming languages, such as C++. Java is at the time of writing, according to the TIOBE index, the world’s most widely used and popular programming language, with Python catching-up and taking third place from C++.
The TIOBE index is an indicator of the popularity of programming languages. The index is updated once a month. The ratings are based on the number of skilled engineers worldwide, courses, books, and third-party vendor support. The TIOBE index is not about which is the best programming language, but more about you being able to check whether your programming skills are still up-to-date and what strategic decisions should be adopted when starting to build a new software system.
Background of Python & Java
Python, originally released in 1991, is a dynamically-typed general-purpose programming language. Python’s early development began at a research institute and the motivation behind it was to create a higher-level language to bridge the gap between C and the shell, primarily because creating system administration utilities using C, at that time was not an easy feat. The syntax was inspired by a few languages like Algol68 and Pascal, and was meant to be readable and clean.
Java, originally released in 1996, is a statically typed general-purpose programming language, being object-oriented and concurrent by design. Java was meant to be a “write once, run anywhere” language, as it was designed to run on any platform and with as few dependencies as possible, with the help of the Java Virtual Machine (JVM).
Comparison Factors
Programming languages by definition, are not ones better than others. They are designed with specific goals in mind and they are governed by semantics.
Both Python and Java have similarities and differences which makes it more to select one out of the two.
The most common question asked by novice programmers is, if Python is better than Java, or vice versa. So, let’s begin by assessing and understanding various fundamental differences and comparison factors.
Fundamental Differences
Python |
Java |
Scripting Language that support Object Oriented Constructs | Natively Object Oriented by design |
Dynamically Typed |
Comparison Factors
Factor |
Python |
Java |
Syntax |
Short, concise |
Similar to a “C” language |
Speed | Slower (Interpreted) |
Faster (bytecode) |
Legacy Systems |
Less legacy issues |
Larger & Numerous |
Code |
Less code required |
More verbose |
Agility |
Better support for data science and machine learning |
Better support for refactoring due to its static typed design |
Trends |
Astronomical Growth |
#1 Programming Language |
Salary | Increased Demand for data science Roles |
Traditionally strong – Well paid |
While not as trendy as it once was, Java is still the world’s most popular programming language by any measure. However, Python’s growth has been astronomical, especially with developers, in high-income countries and its adoption for data science, DevOps automation, and machine learning. The reasons for Python’s amazing growth include developer productivity, language flexibility, a wide library support for data science and machine learning, pushed by broad vendor and community support, and ease of learning.
Now that we’ve explored some of the comparison factors between both, let’s understand some of the practical differences between them.
Looking at Code (Dynamic vs Static Typing)
Python and Java are both incredibly versatile and productive programming languages, but one major difference is that Java uses static types, while Python is dynamic. This is the most significant difference and affects how you design, write and troubleshoot applications written with both. Let’s look at some code examples to understand this better.
items = [“Hello World”, “Hi there folks”]
for i in items:
print(i)
The code above is written in Python. The first line creates an array. While the second line loops through the array and each element of the array is printed out on the third line. Now, let’s explore how that same code would be written in Java.
public class LoopArray {
public static void main(String args[]) {
String array[] = {“Hello World”, “Hi there folks”};
for (String i : array) {
System.out.println(i);
}
}
}
As you can immediately appreciate, there are some obvious differences. The first thing that stands out is that everything in Java needs to be part of a class. Second, the syntax is quite different, as the array is explicitly declared with its type (String array[]), and also curly braces ({ }) are used to identify the beginning and end of a code block, whereas in Python this is achieved by using indentation.
To further understand what dynamically and statically typed means, let’s take the same example and expand it. To do that, let’s add an integer to the beginning of the Python array.
items = [1, “Hello World”, “Hi there folks”]
As you can see, we’ve added the value of 1 to the array. This doesn’t affect the rest of our Python code, because it will still be able to loop through those items and print each one. So, adding that integer to the array doesn’t affect the rest of the code. Arrays in Python can contain different types.
Now, let’s try to do the same thing in Java.
String array[] = {1, “Hello World”, “Hi there folks”};
This will through an error once the code is compiled. In Java, different types cannot be mixed in the same array, as it is a statically typed language.
We could declare the array as containing Object instead of String types.
Object array[] = {1, “Hello World”, “Hi there folks”};
This would override Java’s type checking system. But, that’s not how any proficient Java developer would use the language.
In Python, it is not necessary to provide a type when we declare an array, thus we can add to it whatever values we need. It’s up to us to make sure we don’t try to misuse the contents during runtime, whereas with Java, that’s not the case.
The statically-typed nature of the Java programming language enforces these checks when we are writing the code, which is a bit more restrictive during development, however, during runtime this is beneficial. Let’s see how.
items = [1, “Hello, World”, “Hi there folks”]
for i in items:
print(i + ” some string…”)
Notice that we are back to our Python code and now on the third line, we are concatenating the value of i to ” some string…”.
Python doesn’t stop us from writing this code. From a syntax point of view, this is perfectly fine. However, when we run this code, a runtime exception will be produced. This is because the value of 1 is not a string and therefore it cannot be concatenated to the value of ” some string…”.
In Java, this would not have happened, as statically-typed checks would enforce this constraint during development. Static typing enforces a discipline that some developers love and appreciate from a programming language.
A compiler working on statically-typed code can optimize better for the target platform, which is the case with Java. Avoiding runtime type errors, adds another performance boost.
Code that’s written with dynamic types, such as with Python, tends to be less verbose than static languages, such as Java.
When using a dynamically-typed language like Python, you are responsible for the integrity of the code you write, and less of that responsibility relies on the compiler.
Code Readability & Brevity
As seen with the previous code sample, Python’s syntax relies heavily on indentation (white spaces) for the separation of code blocks, while Java ignores them.
Python uses tabs for nesting code blocks, and a full colon (:) to start loops and conditional block statements.
Java on the other hand fully ignores white spaces and uses semicolons (;) as line delimiters, and curly braces to signify the beginning ({) and end (}) of code blocks.
There are many arguments over which code is easier to read, like the debate about dynamic versus static typing, which to some extent are subjective debates, depending on your background and experience as a developer.
There is a group of developers that say Python code is more concise and uniform than Java with regards to syntax and how code is written, because formatting choices are more limited.
As we have seen, the Python code sample is quite a few lines shorter than the equivalent code in Java: a difference that adds up in larger programs, when it comes to actual lines of code written.
Most of the difference is because there are no opening or closing curly braces in Python. So, Python’s brevity—compared to Java’s—is deeper and allows faster code productivity.
Let’s have a look at both codes samples again. Below is the Python implementation.
items = [1, “Hello World”, “Hi there folks”]
for i in items:
print(i)
Notice that because we are not concatenating the value of i to a string, the code above will not produce a runtime exception any longer.
To overcome statically-type checking in Java, we would need to add the value of 1 as a string (“1”) to the Java array. This is what the code would look like.
public class LoopArray {
public static void main(String args[]) {
String array[] = {“1”, “Hello World”, “Hi there folks”};
for (String i : array) {
System.out.println(i);
}
}
}
Both the Python and Java code will now build and run as is, without any problems. Python will run the script from beginning to the end of the file, interpreting each line. Whereas Java requires at least one entry point, which is a static method called main. The Java Virtual Machine (JVM) runs the main method in the class LoopArray passed to it from the command line.
Writing a Python program tends to be faster and syntactically easier than doing the same in Java. This is especially true for programs that need to handle files, work with databases or retrieve data from web services.
Runtime Execution & Performance
Python and Java compile code to machine code and run their own virtual machines. This approach helps isolate code differences between operating systems, making essentially both languages cross-platform.
However, the way the code is executed during runtime is quite different. Python interprets the code and then compiles it to a machine-readable format during runtime. However, Java compiles it in advance (which is also known as Ahead-of-Time), and then executes the resulting machine code, which is more performant.
Most Java Virtual Machines perform Just-in-Time (JIT) compilation to all or part of the app’s code, to machine code, which significantly improves performance; as just the part of the code that is required to execute as machine code will be compiled. Python doesn’t do this, which makes the execution of a Python program slower compared to a Java application.
The difference in performance between applications created in Python and Java is sometimes significant in some cases. Data structures, such as Lists and Binary Trees runs many times faster in Java than in Python.
Comparison Takeaways
It’s important to get a complete perspective on each language and its capabilities to know how to approach them. Below are some key takeaways from both languages and their features.
Factor |
Python | Java |
Popularity |
Very popular | Very popular |
Syntax |
Ease to learn |
Learning curve |
Speed |
Slower than Java |
Very fast |
Cross-Platform | Yes |
Yes |
Important Libraries |
Tensorflow, Pytorch, Django | Mallet, Deeplearning4j, Spring |
Beginning Programming | Learn Python first |
Learn Java later |
Final Thoughts for Beginners
If you are starting with programming, Python is the best way to go. This is because Python is really easy and uses an English-like syntax, being widely used in many Computer Science introductory and online courses around the world.
However, if you are already an experienced programmer, and if your goal is to build enterprise-level applications coming from a C, C++ or C# world, then Java would probably feel pretty familiar and would be easier to dive-in than Python. However, if you are an experienced developer and would like to go into data science or machine learning, Python is the way to go.
After working on several projects using both languages, I feel confident enough to say that Python’s syntax is more concise than Java’s, making it easier to grasp, even though I come from a C, C++ and C# background. It’s easier to get up and running quickly with a new project in Python than in Java.
Java’s performance has substantial advantages over Python due to just-in-time compilation, which gives it an edge over Python’s interpreted mechanism. Java is still much faster than Python.
Having looked at all these consideration points, Python’s advantages outweigh its disadvantages, and it’s potentially the best way to get started with programming. If you are a beginner, give Python a serious look.