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。

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.

对于刚开始使用python的人来说，这是一个很大的困惑，这里的答案有点难以理解，所以我会让它更简单。

当我们指示Python运行我们的脚本时，在我们的代码实际开始处理之前，Python会执行几个步骤:

它被编译为字节码。 然后路由到虚拟机。

当我们执行一些源代码时，Python会将其编译成字节代码。编译是一个转换步骤，字节代码是源代码的底层平台独立表示。

注意，Python字节码不是二进制机器码(例如，英特尔芯片的指令)。

实际上，Python通过将源代码的每个语句分解为单独的步骤，将它们转换为字节码指令。执行字节码转换以加快执行速度。 字节代码的运行速度比原始源代码语句快得多。它有。Pyc扩展，它将被写入，如果它可以写入到我们的机器。

因此，下次我们运行相同的程序时，Python将加载.pyc文件并跳过编译步骤，除非它已被更改。Python自动检查源文件和字节码文件的时间戳，以知道何时必须重新编译。如果我们重新保存源代码，字节码将在下次程序运行时再次自动创建。

如果Python不能将字节代码文件写入我们的机器，我们的程序仍然可以工作。字节码在内存中生成，并在程序退出时简单地丢弃。但是由于.pyc文件加快了启动时间，我们可能希望确保它是为较大的程序编写的。

Let's summarize what happens behind the scenes. When Python executes a program, Python reads the .py into memory, and parses it in order to get a bytecode, then goes on to execute. For each module that is imported by the program, Python first checks to see whether there is a precompiled bytecode version, in a .pyo or .pyc, that has a timestamp which corresponds to its .py file. Python uses the bytecode version if any. Otherwise, it parses the module's .py file, saves it into a .pyc file, and uses the bytecode it just created.

字节代码文件也是传递Python代码的一种方式。Python仍然会运行一个程序，如果它能找到的都是。Pyc文件，即使原始的.py源文件不在那里。

Python虚拟机(PVM)

Once our program has been compiled into byte code, it is shipped off for execution to Python Virtual Machine (PVM). The PVM is not a separate program. It need not be installed by itself. Actually, the PVM is just a big loop that iterates through our byte code instruction, one by one, to carry out their operations. The PVM is the runtime engine of Python. It's always present as part of the Python system. It's the component that truly runs our scripts. Technically it's just the last step of what is called the Python interpreter.

这真的取决于所使用的语言的实现!不过，在任何实现中都有一个常见的步骤:您的代码首先被编译(翻译)为中间代码——介于您的代码和机器(二进制)代码之间的东西——称为字节码(存储在.pyc文件中)。注意，这是一个一次性步骤，除非修改代码，否则不会重复。

这个字节码在每次运行程序时都会被执行。怎么做?当我们运行程序时，这个字节码(在.pyc文件中)作为输入传递给虚拟机(VM)1——允许我们的程序被执行的运行时引擎——由虚拟机执行。

根据语言实现，VM将解释字节码(在CPython2实现的情况下)或JIT-compile3字节码(在PyPy4实现的情况下)。

注:

计算机系统的模拟

2字节码解释器;该语言的参考实现，用C和Python编写，使用最广泛

在程序执行期间(在运行时)进行的3个编译

4字节码JIT编译器;CPython的替代实现，用RPython (Restricted Python)编写——通常比CPython运行得更快

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。