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Python vs Java

February 10, 2020


Python vs Java


Java is an object-oriented, concurrent and statically typed general-purpose programming language. Thanks to the Java Virtual Machine (JVM), Java was designed to run on any platform and with as few dependencies as possible.


Python is a dynamically-typed general-purpose programming language. Python’s development started in the Netherlands at a research institute CWI. The motivation behind it was to create a higher-level language to bridge the gap between C and the shell. The syntax was also inspired by a few languages like Algol68, Pascal, and ABC and was meant to be readable and clean.


As it can be seen in 2019, Python and Java were most popular languages [Source: statista]


Java vs. Python types

Java is a static types language, while Python is dynamic. This has impact on how you design, write, and troubleshoot programs. In case of dynamic typing, the types are checked run-time and in case of static, types are checked compile time.

Java way:

String array[] = {“I am the first”, “second”, “3”}

Python way:

array = [“I am the first”, “second”, 3]


Whitespace is fundamental part of Python’s syntax, while Java ignores it. Python uses tabs or spaces for nesting blocks and a full colon to start loops and conditional blocks. Java ignores whitespace and uses semicolons, parentheses and curly braces. The Python code is a few lines shorter than the Java code, and that adds up in longer programs. Mostly this is because there are no closing braces.

Usually Python is considered as an easier for beginners.


Java and Python compile to bytecode and run in their respective virtual machines. This isolates code from operating systems specifics and makes the languages cross-platform. Though there is a crucial difference. Python usually compiles code at runtime, and Java compiles it in advance, and produces the bytecode.

Most JVMs perform just-in-time compilation to native code, which significantly improves performance, sometimes up to 10 times comparing to Python. Also, Python threads can’t run in parallel on multiple CPU cores because of the global interpreter lock (GIL). Python threads can invoke multiple system calls in parallel. This allows us to do blocking I/O at the same time as computation.

Machine Learning

Python is syntactically very easy and good as a general-purpose programming language. It became a popular among the people from different fields who wanted to experiment with machine learning and use the power of AI into their respective domains. Aot of the development in AI and machine learning is done with Python and as a result the ecosystem is hude and there is a lot of supporting libraries.

Python is used in Tensorflow, Keras, Scikit-learn, Teapot, Pytorch and Java in Weka and DL4J.

Written by Vladimir Obradović who lives and works in The Hague, The Netherlands. Tech Coach, Startup Co-founder, Innovator and Disruptor You should follow him on Twitter