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Скачать или смотреть Are CPython IronPython Jython scripts compatible with each other

  • pyGPT
  • 2023-11-23
  • 6
Are CPython IronPython Jython scripts compatible with each other
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CPython, IronPython, and Jython are different implementations of the Python programming language, each designed to run on different platforms. CPython is the default and most widely used implementation, IronPython runs on the .NET Framework, and Jython runs on the Java Virtual Machine (JVM). In this tutorial, we will explore the compatibility of scripts written in these implementations and provide code examples to demonstrate their interoperability.
CPython is the reference implementation of Python and is widely used for general-purpose programming. Scripts written in CPython are expected to run on any system where CPython is installed.
IronPython is an implementation of Python that runs on the .NET Framework. This allows Python developers to integrate their code with .NET libraries and take advantage of the features provided by the framework.
Jython is an implementation of Python that runs on the Java Virtual Machine (JVM). It allows Python developers to seamlessly integrate with Java libraries and utilize Java's extensive ecosystem.
Let's explore the compatibility of scripts written in these implementations by creating a simple example that demonstrates interoperability.
Suppose you have a script written in CPython that defines a function, and you want to use this function in both IronPython and Jython scripts.
In this example, the example_script.py file contains a simple greet function. The ironpython_script.py and jython_script.py files import this function and use it in their respective environments.
The expected output for each script should be:
This demonstrates that the scripts are compatible with each other, allowing you to reuse code across different Python implementations.
In general, scripts written in CPython, IronPython, and Jython can be compatible with each other, especially for simple code. However, it's essential to be aware of potential differences in libraries and features supported by each implementation. Always test your code in the specific environment to ensure compatibility.
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