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。

CPU实际上只能理解机器代码。对于解释型程序，解释器的最终目标是将程序代码“解释”为机器代码。然而，现代解释语言通常不会直接解释人类代码，因为它效率太低。

Python解释器首先读取人类代码，并在将其解释为机器代码之前将其优化为一些中间代码。这就是为什么你总是需要另一个程序来运行Python脚本，不像在c++中，你可以直接运行编译后的可执行代码。例如，c:\Python27\python.exe或/usr/bin/python.

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.

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。

As sone one already said, "interpreted/compiled is not a property of the language but a property of the implementation." Python can be used in interpretation mode as well as compilation mode. When you run python code directly from terminal or cmd then the python interpreter starts. Now if you write any command then this command will be directly interpreted. If you use a file containing Python code and running it in IDE or using a command prompt it will be compiled first the whole code will be converted to byte code and then it will run. So it depends on how we use it.

几乎，我们可以说Python是一种解释型语言。但是我们在python中使用了一次性编译过程的一部分，将完整的源代码转换为类似java语言的字节码。