为了加速加载模块，Python将模块的编译内容缓存在.pyc中。

CPython将源代码编译为“字节码”，出于性能考虑，当源文件发生更改时，CPython会将此字节码缓存到文件系统中。这使得Python模块的加载速度更快，因为可以绕过编译阶段。当你的源文件是foo.py时，CPython将字节代码缓存在foo.py文件中。Pyc文件就在源代码旁边。

在python3中，Python的导入机制被扩展为在每个Python包目录中的单个目录中写入和搜索字节码缓存文件。这个目录将被称为__pycache__。

下面是一个描述如何加载模块的流程图:

欲了解更多信息:

裁判:PEP3147 参考:“编译”的Python文件

它们包含字节代码，Python解释器将源代码编译为字节代码。这段代码随后由Python的虚拟机执行。

Python的文档是这样解释定义的:

Python是一种解释性语言，例如 而不是编译的 区别可能是模糊的，因为 字节码编译器的存在。 这意味着源文件可以 直接运行而不显式地运行 创建一个可执行文件，然后 运行。

Machines don't understand English or any other languages, they understand only byte code, which they have to be compiled (e.g., C/C++, Java) or interpreted (e.g., Ruby, Python), the .pyc is a cached version of the byte code. https://www.geeksforgeeks.org/difference-between-compiled-and-interpreted-language/ Here is a quick read on what is the difference between compiled language vs interpreted language, TLDR is interpreted language does not require you to compile all the code before run time and thus most of the time they are not strict on typing etc.

这是为初学者准备的，

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。

如果你需要为一个未导入的模块创建一个.pyc文件，你可以使用py_compile和compileall模块。

py_compile模块可以手动编译任何模块。一种方法是交互式地使用该模块中的py_compile.compile函数:

>>> import py_compile
>>> py_compile.compile('abc.py')

这将把.pyc写到与abc.py相同的位置(你可以用可选参数cfile重写它)。

您还可以使用compileall模块自动编译一个或多个目录中的所有文件。

python -m compileall

如果省略目录名(本例中的当前目录)，模块将编译sys.path上的所有内容

tldr;它是从源代码转换而来的代码，python虚拟机将其解释为执行。

自下而上的理解:任何程序的最后阶段都是在硬件/机器上运行/执行程序的指令。下面是执行前的几个阶段:

Executing/running on CPU Converting bytecode to machine code. Machine code is the final stage of conversion. Instructions to be executed on CPU are given in machine code. Machine code can be executed directly by CPU. Converting Bytecode to machine code. Bytecode is a medium stage. It could be skipped for efficiency, but sacrificing portability. Converting Source code to bytecode. Source code is a human readable code. This is what is used when working on IDEs (code editors) such as Pycharm.

现在来看实际的情节。在进行这些阶段的任何一个阶段时，有两种方法:一次性转换[或执行]代码(又名编译)和逐行转换[或执行]代码(又名解释)。

For example, we could compile a source code to bytecode, compile bytecode to machine code, interpret machine code for execution. Some implementations of languages skip stage 3 for efficiency, i.e. compile source code into machine code and then interpret machine code for execution. Some implementations skip all middle steps and interpret the source code directly for execution. Modern languages often involve both compiling an interpreting. JAVA for example, compiles source code to bytecode [that is how JAVA source is stored, as a bytecode, compile bytecode to machine code [using JVM], and interpret machine code for execution. [Thus JVM is implemented differently for different OSs, but the same JAVA source code could be executed on different OS that have JVM installed.] Python for example, compile source code to bytecode [usually found as .pyc files accompanying the .py source codes], compile bytecode to machine code [done by a virtual machine such as PVM and the result is an executable file], interpret the machine code/executable for execution. When can we say that a language is interpreted or compiled? The answer is by looking into the approach used in execution. If it executes the machine code all at once (== compile), then it's a compiled language. On the other hand, if it executes the machine code line-by-line (==interpret) then it's an interpreted language. Therefore, JAVA and Python are interpreted languages. A confusion might occur because of the third stage, that's converting bytecode to machine code. Often this is done using a software called a virtual machine. The confusion occurs because a virtual machine acts like a machine, but it's actually not! Virtual machines are introduced for portability, having a VM on any REAL machine will allow us to execute the same source code. The approach used in most VMs [that's the third stage] is compiling, thus some people would say it's a compiled language. For the importance of VMs, we often say that such languages are both compiled and interpreted.

为了加速加载模块，Python将模块的编译内容缓存在.pyc中。

CPython将源代码编译为“字节码”，出于性能考虑，当源文件发生更改时，CPython会将此字节码缓存到文件系统中。这使得Python模块的加载速度更快，因为可以绕过编译阶段。当你的源文件是foo.py时，CPython将字节代码缓存在foo.py文件中。Pyc文件就在源代码旁边。

在python3中，Python的导入机制被扩展为在每个Python包目录中的单个目录中写入和搜索字节码缓存文件。这个目录将被称为__pycache__。

下面是一个描述如何加载模块的流程图:

欲了解更多信息:

裁判:PEP3147 参考:“编译”的Python文件