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Explore the dynamic world of Python and Jython

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探索 Python 和 Jython 的动态世界

  • Dynamic typing: Variables are typed according to their values ​​at runtime.
  • Interpreter: python The code is interpreted and executed line by line.
  • Extensive Library: Python has a huge library of standard and third-party libraries for a variety of tasks.

Jython

Jython is an implementation of Python designed to run on the Java Virtual Machine (JVM). It inherits many features of Python, but also has some unique advantages:

  • Interoperability with Java: Jython code can seamlessly interact with Java code and access Java classes and libraries.
  • JVM optimization: Jython runs on the JVM and utilizes Java's garbage collection and JIT compilation to optimize.
  • Cross-platform: Jython can be deployed on any platform that supports Java.

Compare

Syntax: The syntax of Python and Jython is basically the same, but Jython has some additional Java features.

Execution: Python uses an interpreter, while Jython runs on the JVM, providing better performance.

Libraries: Python has a broader standard library, while Jython has access to Java's libraries.

Uses: Python is used in a wide range of applications, including WEB development, data science, and machine learning. Jython is particularly suitable for scenarios that require Python functionality in a Java environment.

When to use Python

  • Requires rapid development of prototypes or scripts.
  • Requires a language with extensive library and community support.
  • No need to interoperate with Java.

When to use Jython

  • Requires interaction with Java code.
  • Requires Python functionality in a Java environment.
  • Need faster execution speed.

in conclusion

Both Python and Jython are powerful dynamic languages ​​with unique features. Choosing the most appropriate language depends on the specific requirements of the application. Jython is a great choice for scenarios that require interoperability with Java or are looking for higher performance. For applications that prioritize ease of learning and broad library support, Python is the better choice. By understanding the differences between the two languages, developers can make informed decisions to create efficient, flexible applications.

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