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。

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。

在我看来，Python被归入解释器类别，因为它被设计成能够完全处理(从Python代码到在cpu中执行)单个Python语句。也就是说，你写了一个语句，你可以执行它，如果没有错误，然后得到相应的结果。

Having an intermediate code (like bytecode) i believe doesnt make difference to categorize it overall as compiler. Though this component (intermediate code generation) is typically been part of compiler but it can also be used in interpreters. See wiki definition of interpreter https://en.m.wikipedia.org/wiki/Interpreter_(computing). Its a crucial piece to add efficiency in terms of execution speed. With cache its even more powerful so that if you havent changed code in current program scope you skip heavy processing steps like lexical, semantic analysis and even some of code optimization.

如果(你懂Java) { Python代码像java一样被转换成字节码。 每次您尝试访问该字节码时，都会再次执行它。 }其他{ Python代码最初被翻译成一种叫做字节码的东西 接近机器语言，但不是真正的机器代码 因此，每次我们访问或运行它时，字节码都会再次执行 ｝

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。