这似乎是语义上的问题。我想大多数人都会推断编译的结果通常是机器代码。考虑到这一点，我对自己说，python是没有编译的。不过我可能错了，因为compile实际上意味着转换到较低级别，所以从源代码转换到字节码也是编译。

你写的python代码被编译成python字节码，它会创建扩展名为.pyc的文件。如果是编译，问题又来了，为什么不是编译语言。

注意，这不是传统意义上的编译。通常，我们会说编译是采用高级语言并将其转换为机器代码。但它是某种汇编。编译到中间代码，而不是机器代码(希望你现在得到它)。

回到执行过程，在编译步骤中创建的pyc文件中的字节码，然后由相应的虚拟机(在我们的例子中是CPython VM)执行 时间戳(称为魔数)用于验证.py文件是否被更改，这取决于创建的新pyc文件。如果pyc是当前代码，那么它简单地跳过编译步骤。

根据Python官方网站，它是解释的。

https://www.python.org/doc/essays/blurb/

Python是一种解释性的、面向对象的高级编程语言……

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因为没有编译步骤…

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Python解释器和广泛的标准库是可用的…

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相反，当解释器发现错误时，它会引发 例外。当程序没有捕获异常时， 解释器输出堆栈跟踪。

First off, interpreted/compiled is not a property of the language but a property of the implementation. For most languages, most if not all implementations fall in one category, so one might save a few words saying the language is interpreted/compiled too, but it's still an important distinction, both because it aids understanding and because there are quite a few languages with usable implementations of both kinds (mostly in the realm of functional languages, see Haskell and ML). In addition, there are C interpreters and projects that attempt to compile a subset of Python to C or C++ code (and subsequently to machine code).

Second, compilation is not restricted to ahead-of-time compilation to native machine code. A compiler is, more generally, a program that converts a program in one programming language into a program in another programming language (arguably, you can even have a compiler with the same input and output language if significant transformations are applied). And JIT compilers compile to native machine code at runtime, which can give speed very close to or even better than ahead of time compilation (depending on the benchmark and the quality of the implementations compared).

But to stop nitpicking and answer the question you meant to ask: Practically (read: using a somewhat popular and mature implementation), Python is compiled. Not compiled to machine code ahead of time (i.e. "compiled" by the restricted and wrong, but alas common definition), "only" compiled to bytecode, but it's still compilation with at least some of the benefits. For example, the statement a = b.c() is compiled to a byte stream which, when "disassembled", looks somewhat like load 0 (b); load_str 'c'; get_attr; call_function 0; store 1 (a). This is a simplification, it's actually less readable and a bit more low-level - you can experiment with the standard library dis module and see what the real deal looks like. Interpreting this is faster than interpreting from a higher-level representation.

字节码要么被解释(请注意，在理论和实际性能上，直接解释和首先编译为一些中间表示并解释它之间存在差异)，就像参考实现(CPython)一样，要么在运行时被解释并编译为优化的机器代码，就像PyPy一样。

对于新手

在运行脚本之前，Python会自动将脚本编译为已编译的代码，即所谓的字节代码。

运行脚本不被认为是导入，也不会创建.pyc。

例如，如果你有一个脚本文件abc.py，它导入了另一个模块xyz.py，当你运行abc.py时，xyz.py, xyz.py。Pyc将被创建，因为xyz被导入，但没有abc。Pyc文件将被创建，因为abc.py没有被导入。

Python(解释器)被编译。

证明:它甚至不会编译你的代码，如果它包含语法错误。

示例1:

print("This should print") 
a = 9/0 

输出:

This should print
Traceback (most recent call last):
  File "p.py", line 2, in <module>
    a = 9/0
ZeroDivisionError: integer division or modulo by zero

代码编译成功。第一行执行(打印)，第二行抛出ZeroDivisionError(运行时错误)。

示例2:

print("This should not print")
/0         

输出:

  File "p.py", line 2
    /0
    ^
SyntaxError: invalid syntax

结论:如果代码文件包含SyntaxError，编译失败时什么都不会执行。