What is the difference between Java and Python?

Python and Java are the two primary programming languages we teach at CodingNomads, so this is one of the most common questions we get.

That’s because Python and Java are quite similar: they’re both decades-old, tried-and-true general purpose programming languages that can do just about anything you want. Their functionality and applications overlap quite a bit, as they share many of the same core engineering principles. So many people wonder – should you build your project using Python vs. Java? Or if you’re interested in learning to code, which is the better language for you?

This article explores Python vs. Java in terms of performance, syntax, popular uses, career opportunities, salaries, learning curve and more.

Similarities between Python and Java

As already mentioned, Python and Java have a lot in common.

Both Java and Python are:

  • Open source: They were built by the masses, for the masses. They have giant communities built around them, with extensive resources, libraries, and strong cross-platform support.
  • Server side (vs. client side): The code is built and executed in the server, rather than in the browser (the client).
  • General purpose: They can be used for just about anything you can think of, from building products like Spotify or your banking app, to slicing and dicing infinite amounts of data, to programming your remote control.
  • Battle tested: For decades, the uses for Java and Python have morphed alongside global innovation. They’ve consistently proved themselves useful and dependable despite modern competing languages, and therefore have cemented their relevance for decades to come.
  • In demand: Java and Python consistently top the list of the most in-demand programming languages for jobs, alongside languages like C, PHP, and JavaScript. Many – if not most industries use systems running on Java and/or Python, such as enterprise web applications, data management, data analysis, and more.

Python vs. Java: Performance

Both Java and Python are cross-platform languages, which means the code is compiled into bytecode and then run. However, Java is a compiled language, which compiles the code before running. Python is an interpreted language (which compiles code at runtime). 

In general, compiled languages are faster than interpreted languages, giving Java the lead in a Python vs. Java performance competition. The benchmark at benchmarks-game provides numbers to support this claim. See the screenshot below of the comparison between the fastest programs, with Java taking the lead in 2 out of 3 metrics.

Obviously, the Python vs. Java performance metric is complex and depends on various factors – the environment, how the code is written, what libraries are used, etc. However as a general rule, Java will outperform Python in a speed race.

Python vs. Java Performance

Image source: Benchmarks Game


One of the biggest differences between Python vs. Java is their syntax – how they are written.

Formatting / Readability

In Java, you create a block of code by enclosing it in {braces}, while in Python you use colons and indentation (tabs / spaces) to do the same. 

Java requires semicolons at the end of each programming statement, and you can put multiple statements on a single line with a semicolon. Python does not require semicolons at the end of each statement, so each statement must be in a line by itself. Therefore Python creates more whitespace, and is generally considered easier to read than Java.

While Java developers have historically debated the best way to format Java code, Python takes away the guessing game by enforcing indentation as a part of the code itself – another bonus for Python.

In the example below, we demonstrate a simple comparison of two numbers in both Python and Java to demonstrate the syntactic difference.


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Typing: Dynamic vs. Static

Python is a dynamically typed language. This means you don’t need to declare variable types in Python, because the interpreter will automatically infer these types at runtime. On the other hand, Java is a statically typed language. This means you need to explicitly declare each of your variable types, otherwise your program will show an error at compile time.

For example, in Python you can have a list with both strings and numbers, while in Java you cannot.

Python: Dynamically Typed

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Java: Statically Typed

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Static and dynamic typing each have their advantages and disadvantages. While some programmers believe that dynamic typing increases productivity, others argue the exact opposite. That’s because although dynamic typing requires less code, errors may arise at runtime due to mixed types. An example of this in Python:

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This will throw an error when processing the number 3, because you cannot concatenate a string and a number. Java will not have the same issue, since such errors will be caught at compile time rather than runtime. Die-hard Java programmers prefer to take the extra step and define the variable type, rather than deal with potential errors at runtime.

Therefore in terms of Dynamic (Python) vs. Static (Java), we’d call this one a tie.


Dynamically typed code tends to be less verbose than static languages, since dynamic typing does not require new variable declarations. For example, in the code below we demonstrate that in Python you can reuse the variable “var1”, even with different data types. Whereas in Java, “var1” cannot first be a String and then an int. In the Java example, we need to create a second variable “var2” of type int to hold the value 6.


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In general, Python code is less verbose than Java code. For example, writing “Hello World!” requires 4 lines of Java code vs. just one line of Python code. This may seem minor, but over the course of a project with multiple files and multiple classes, it can add up to a lot. So in terms of brevity, Python is the winner.


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Project Completion Time

One of the most significant advantages that Python has over Java is that it takes a very short time to build cool stuff. Thanks to Python’s simpler syntax and ease of reading, you can quickly get started with the language and build something impressive within a week or two. 

In addition, even large, complex projects can be completed in a short amount of time. Case in point, this workflow automation system for NASA which was written in Python by one person in less than a year. So in terms of quick development time – including prototyping, Python would be more ideal than Java.

Career Paths in Python vs. Java

Programming is in such high demand because it is being adopted by just about every industry. Python and Java are used by companies in data analytics, financial services, marketing, education, healthcare, recruiting and many more. 

Once again, there is a lot of overlap in Python and Java career paths – especially in terms of general software development and web development. The main career paths where these two languages diverge are Python’s dominance in Data Science / Machine Learning, and Java’s dominance in mobile development for Android, and the Internet of Things. 

For more examples of career paths in Python and Java – such as data engineer, database administrator, product manager and more, check out our blog – Software Engineer Career Paths.

RELATED: Jobs you can do with software engineering skills

General Software Development

Python is great for quick prototyping, hence is used extensively by startups to build their first minimum viable product (MVP). However, Python’s use is not limited to smaller companies. Netflix discussed how they use Python in many of their major projects such as their Content Delivery Network (CDN) and monitoring systems. Python is also used by companies like Google, Netflix, Stripe, Robinhood and Revolut.

Meanwhile, 90 percent of Fortune 500 companies use Java for their backend architecture. Oracle estimates that Java runs on over 3 billion devices worldwide – more than any other language. A virtually omnipresent language, Java is used in devices such as smartphones, automobiles, medical devices and E-readers. While both Python and Java are popular for general software development, Java arguably takes a lead here.

Web Development

Because of their robust and scalable nature, Python and Java are also commonly used for creating websites and web-based software applications. 

There are two parts to every website – the client side, which runs code on the internet browser of a user’s computer; and the server side, where the code runs on the web server. For example, JavaScript is a client-side language that runs on the browser, and enables user interaction on a website. Alternatively, Python and Java run on the server, and are responsible for processing the logic behind user inputs, interacting with databases and other servers, etc.

In order to build dynamic web applications without having to learn a client-side language like JavaScript, both Python and Java work with web frameworks that make full stack web development efficient.

Python has two major web frameworks – Django and Flask (which is a micro-framework). Python also has inbuilt modules that help deal with JSON, sockets, http-requests and more, making the process of web development seamless.

Meanwhile, Java’s major web framework is the Spring Framework. Spring is an incredibly powerful and dynamic framework that dwarf’s Python’s Django and Flask Frameworks. Many of the world’s most prominent websites like eBay, Linkedin, Amazon, Facebook and Google run on Java and Spring. So while both Python and Java are commonly used for web development, Java and Spring take the lead as the more commonly used – and more powerful – web development stack.

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Data science / Machine Learning / AI

Over the last decade, many useful Python packages have been developed for data analysis, data science, machine learning and AI, leading to Python’s explosive recent growth. Python has always been used for scientific and numerical computing, which lends itself perfectly for data science & machine learning.

Python packages for DS/ML include numpy and pandas, which allow users to understand and transform data; tensorflow, which is used to code machine learning algorithms; and pyspark, an API for working with Spark – a framework for easily working with large data sets.

Java, while not as famous for working with machine learning, does have some libraries and frameworks for dealing with data, such as Weka and DeepLearning4j.  Spark also has an API in Java. 

However in the realm of Data Science & Machine Learning, Python is better than Java because of its ease of use, extensive libraries and resources, and community support.

Growing Community Interest in Python DS/ML Technologies

Image source: Stack Overflow Trends

Mobile development: Java

Java powers Android, which powers 85% of smartphones used worldwide (iOS powers the remaining 15%). This makes Android the most widely-used operating system on earth, further solidifying Java’s relevance, demand and staying power for the foreseeable future. 

The Android SDK comes with a huge amount of standard Java libraries, including data structures libraries, graphics libraries and other special libraries created for Android. Plus, there is a strong community of developers and resources for help, with over 200,000 questions on Stack Overflow with the tag “Java” and “Android”.

To develop mobile apps with Python, you need to utilize technologies like the PySide-based QML GUIs. This is slightly more complicated and therefore does not have such a large community as Java does. Therefore in terms of Python vs. Java for mobile development, Java is the winner.

Android vs. iOS Market Share: Historical and Projected

Image source: IDC

Automation Scripting: Python and Java

In addition to Data Science / ML, one of the main uses for Python is in scripting – writing small programs that perform a certain task automatically. Python was invented to be quick and easy to write, and allows you to create simple scripts to perform tasks that would take you hours if done manually. While Java is also used for automation, it is a bit more simple and common in Python.

Internet of Things: Java

The Internet of Things, or IoT, refers to the billions of physical devices that are embedded with sensors, software, and other technologies that allow them to collect and exchange data over the Internet. 

Nowadays we know IoT as anything “smart,” like your smart watch, smart phone, smart thermometer. But even before all this existed, the creators of Java had a vision for a language that could run on consumer appliances using a “write once, run everywhere” philosophy. The Java features that make it ideal for IoT include:

  • Portable: Java is hardware agnostic, meaning it is designed to be able to run on any device.
  • Open source: Java has an extensive built-in library of APIs that support IoT.
  • Secure and stable: Ideal for managing, operating, and automating devices remotely. 
  • Interoperable: Java is highly capable of interoperating between the diverse set of technologies that make up IoT, such as hardware devices, sensors, cloud computing, big data and more.

While Python can also be used for IoT, Java is by far the industry’s leading programming language in this arena.

Job Opportunities in Python vs. Java

Going hand-in-hand with the various career paths in both Python and Java are the ample job opportunities. Python and Java top the list for the most in-demand programming languages in terms of open jobs.

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Globally, 50% of hiring managers look for Python skills when hiring developers, compared to 44% that look for Java. These stats rank Python and Java in the top 3 languages that hiring managers desire.

Programming Skills Desired by Hiring Managers Globally

Image source: HackerRank

Salary Potential with Python vs. Java

It is no secret that developers are some of the highest paid employees around the world. Not only that, Python and Java developers are some of the highest paid developers in the market.

On average in the United States, a Python developer earns USD $119,082 per year, while a Java developer earns USD $104,544. The average salaries from 2017 to 2020 show that both Python and Java are consistently among the top 5 highest paid programming languages.

Average US developer salaries from 2017-2020

Python vs. Java developer salaries in the US

Data Source: DAXX


Java and Python each have more than 90,000 users collaborating on more than 1.5 million repositories on Github. According to GitHub’s 2020 Octoverse report, Python and Java are the second and third most used languages on Github for the fourth year in a row (Python took Java’s #2 spot in 2019). 

On Stack Overflow, the terms “Java” and “Python” are tagged in more than one million questions, demonstrating incredibly robust and active communities for both languages.

In addition to online communities, Python and Java both have strong offline presences too. Java User Groups and Python User Groups are places where developers can meet others working on the same language, share resources and solutions and discuss the latest and greatest developments.

Most popular programming languages on GitHub by repository contributors

Image source: GitHub

Popularity and Growth

The TIOBE Index is an indicator of a programming language’s popularity based on the quantity of search queries across 25 search engines, as well as the number of skilled engineers world-wide, courses, and third party vendors. 

Currently, Python is #3 in the TIOBE Index and Java is #2. TIOBE named Python the 2020 programming language of the year for gaining the most popularity of any language in one year. Notably, this is the fourth time Python earned this distinction, which is a record for TIOBE. Python made a positive jump of 2.01% in 2020 (source: TIOBE). On the other hand, Java previously held the #1 spot, but in 2021 slipped behind C.

While both languages have immense popularity and community support, Python’s exponential growth indicates it will soon eclipse Java on the TIOBE Index.

Most Popular Programming Language by Search Queries

Image source: TIOBE

Learning Curve

Python and Java rank #1 and #2 in the The PYPL PopularitY of Programming Language Index, which analyzes how often language tutorials are searched on Google. So as the 2 most desired programming languages to learn, how does the learning curve compare between the two?

For someone who already knows how to program in languages like C or C++, learning Java can be simple. For new developers, Java has a slightly steeper learning curve than Python. This is mainly because of Java’s syntax requirements mentioned in this article. Java has stricter typing requirements than Python, which requires that you learn more computer science fundamentals at the outset.

However, as discussed, this initial complexity can be preferred by experienced coders, as Java ensures that you learn the fundamentals correctly. Additionally, after you learn Java, learning other languages becomes much quicker and easier. In today’s multi-lingual world, where knowing more than one programming language is the norm rather than the exception, learning Java first would make learning Python afterwards a breeze, as well as many other programming languages.

On the other hand, Python was built to keep only the necessary and get rid of the complex. Thanks to this, Python is easier to read, write, and learn. The downside of learning the “simpler” Python first is that it can make learning Java and other languages seem more complex. 

In conclusion, if you want to get up and running fast, and don’t plan to learn another language in the near future, Python is the easier language to learn. If you plan to learn multiple languages over your career, learning Java will pay off in the long run.

Most Desired Programming Language to Learn by Tutorial Searches

Image source: PYPL

Why you Shouldn’t Learn Python or Java

Despite the ample benefits of learning Python or Java, it’s also worth noting that learning these languages is not for everyone! Here are a few reasons  why you wouldn’t want to learn Python or Java. 

  • You’re more interested in building visual design, UI, UX (learn HTML, CSS & JavaScript).
  • You want to build iPhone apps (learn Objective-C / Swift, or other Native languages).
  • You don’t enjoy working with data or numbers, problem solving, logic puzzles, continuous challenges, or figuring things out (total honesty: you might not enjoy coding either then!).

Summary: Python vs. Java

Python and Java are two of the world’s best programming languages in terms of versatility, career opportunities, salary potential, community and more. They are also very similar languages, and can be used for many of the same applications. With only a few exceptions (such as machine learning & mobile development), you really can’t go wrong with using (or learning) Python or Java.

Python Pros & Cons 

  • Python is the best choice if you’d like to work in machine learning, data science, data modeling and analysis.
  • Because of these growing industries, Python is the fastest growing language in terms of usage and demand.
  • Python is easier to read, easier to write, and less verbose. This makes it more intuitive to learn, easier to start building programs as a beginner, and faster to build programs overall. 
    • Con: This can allow for simple mistakes to cause significant problems. 
    • Con: Python doesn’t solidify CS fundamentals and best practices quite as well as Java. This means that it won’t be as easy to learn Java after Python, than if you learn Java first. 

For more info on why we <3 Python, check out our blog: Why Learn Python.

Java Pros & Cons

  • Java performs faster than Python. If speed is important, Java is the better bet.
  • Java is more ubiquitous than Python because of its use in Android and IoT. Most of the world’s largest and most sophisticated companies run on Java. It is a battle-tested and highly respected language that will open endless job opportunities.
  • Once you learn Java, learning other languages like Python, C, C++, will be much easier than if you learn Python first. Therefore Java skills can help you qualify for jobs in these other languages too.
  • Java is more verbose and enforces more rules.
    • Pro: This forces you to learn correctly, so Java is considered a better first language for solidifying computer science best practices. 
    • Con: Java requires more upfront learning time than Python before starting to build.

For more info on why we <3 Java, check out our blog: Why Learn Java.

Interested to learn Python or Java?

CodingNomads has extensive resources for learning Python and Java, from free tutorials to intensive beginner-to-professional programs. Click below to explore our language-specific courses that teach beginner-to-intermediate skills, and our Career Track courses that teach beginner-to-professional skills.