How Does Python Achieve Speed and Portability Despite Being Primarily Interpreted?

Is Python Interpreted or Compiled?

The distinction between interpreted and compiled languages lies in the implementation, not the language itself. While Python is widely regarded as an interpreted language, it employs a unique approach that involves compilation to an intermediate format known as bytecode.

Unlike traditional interpreters that convert source code directly into machine instructions, Python uses a compiler to translate its code into an intermediate bytecode format (.pyc). This intermediate code is then executed by a virtual machine known as the Python Virtual Machine (PVM).

The use of bytecode offers several advantages. First, it speeds up execution by eliminating the need to repeatedly parse and interpret the source code. Second, it improves portability by allowing Python scripts to run on any platform where the PVM is available.

However, the use of bytecode also introduces some limitations. Unlike true compiled languages, where the entire program is converted into machine code upfront, bytecode execution can be slower due to the extra step of interpreting the intermediate code.

Additionally, while the reference implementation of Python (CPython) interprets bytecode directly, other implementations like PyPy employ just-in-time (JIT) compilation to translate bytecode into optimized machine code during runtime. This hybrid approach further improves execution speed, bridging the gap between interpreted and compiled languages.

In summary, Python is neither purely interpreted nor compiled in the traditional sense. It employs a unique approach that involves compilation to bytecode and subsequent execution by a virtual machine. This approach offers a balance of speed, portability, and flexibility, making Python a versatile language suitable for a wide range of applications.

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