HotSpot运行时被称为虚拟机，而CPython仅仅被称为解释器，这可能是有原因的

首先，CPython只是普通的、基于栈的字节码解释器。你向它输入Python操作码，CPython内部的软件堆栈机器就会计算你的代码，就像普通的解释器一样。

The Java HotSpot runtime is different. First and foremost, Java has 3 Just-in Time Compilers, C1, C2, and an experimental one that isn't in use yet. But that's not the main reason. The Interpreter inside the JVM is a very special kind of Interpreter called a Template Interpreter. Instead of just executing bytecode directly in a massive opcode switch case statement like CPython (And really almost every other interpreter does) does, the Template Interpreter inside the JVM contains an enormous arraylist. What does it contain? Key-value pairs of bytecodes and native CPU instructions! The arraylist is empty on startup and is filled with mappings of bytecodes pointing to native machine language to be directly run on the hardware just before your application starts up, what this means is that the "Interpreter" inside the JVM isn't actually an Interpreter at all- It's actually a discount Compiler! When Java bytecode is run, the "Interpreter" simply maps the input bytecode directly to native machine language and executes the native mapping directly, rather than implementing it in software. I'm not exactly sure why the JVM was made this way, but I suspect it was to easily execute "Interpreted" Code together with JIT Compiled Code seamlessly, and for speed/performance. If you pitted the JVM without JIT against CPython or most other interpreters it would still probably come out ahead of them, in virtue of its ingenious design which to my knowledge no other language has used before.

他们之间没有真正的区别，人们只是遵循创造者选择的惯例。

术语解释器是一个遗留术语，可以追溯到早期的shell脚本语言。由于“脚本语言”已经演变成功能齐全的语言，它们对应的平台也变得更加复杂和沙箱化，虚拟机和解释器(在Python意义上)之间的区别非常小，甚至不存在。

Python解释器仍然以与shell脚本相同的方式运行，从某种意义上说，它可以在不需要单独的编译步骤的情况下执行。除此之外，Python解释器(或Perl或Ruby的)和Java虚拟机之间的区别主要是实现细节。(有人可能会说Java比Python更加完全沙箱化，但两者最终都通过原生C接口提供对底层架构的访问。)

我认为两者之间的界限是模糊的，人们大多争论的是“解释器”这个词的含义，以及语言与“解释器……编译器”范围的每一方有多接近。然而，没有一个是100%的。我认为编写Java或Python实现是很容易的，这是频谱的任何价值。

目前Java和Python都有虚拟机和字节码，尽管一个操作具体的值大小(如32位整数)，而另一个必须确定每次调用的大小，在我看来，这并没有定义术语之间的边界。

Python没有正式定义的字节码，它只存在于内存中，这一论点也不能说服我，只是因为我计划开发只识别Python字节码的设备，编译部分将在浏览器JS机器中完成。

性能只与具体的实现有关。我们不需要知道对象的大小就能处理它，最后，在大多数情况下，我们处理的是结构，而不是基本类型。可以通过重用现有对象来优化Python VM，从而消除每次在表达式计算期间创建新对象的需要。一旦完成，在计算两个整数的和之间没有全局性能差异，这是Java的闪光点。

两者之间没有致命的区别，只有一些与最终用户无关的实现上的细微差别和缺乏优化，可能在她开始注意到性能滞后的时候，但这又是实现而不是架构的问题。

解释器，翻译源代码为一些有效的中间表示(代码)，并立即执行。

虚拟机，显式地执行存储的预编译代码，由编译器构建，它是解释器系统的一部分。

虚拟机的一个非常重要的特征是，在虚拟机内部运行的软件，受限于虚拟机提供的资源。确切地说，它无法跳出它的虚拟世界。想想远程代码的安全执行，Java applet。

在python的情况下，如果我们保留pyc文件，就像这篇文章的评论中提到的，那么这个机制将变得更像一个虚拟机，并且这个字节码执行得更快——它仍然会被解释，但从一个更计算机友好的形式。如果我们从整体上看，PVM是Python解释器的最后一步。

底线是，当我们提到Python解释器时，这意味着我们将其作为一个整体来引用，而当我们说PVM时，这意味着我们只是在谈论Python解释器的一部分，一个运行时环境。类似于Java，我们引用不同的部分，JRE, JVM, JDK等。

有关更多信息，请参阅维基百科条目:解释器和虚拟机。这里还有一个。在这里您可以找到应用程序虚拟机的比较。它有助于理解编译器，解释器和vm之间的区别。

HotSpot运行时被称为虚拟机，而CPython仅仅被称为解释器，这可能是有原因的

首先，CPython只是普通的、基于栈的字节码解释器。你向它输入Python操作码，CPython内部的软件堆栈机器就会计算你的代码，就像普通的解释器一样。

The Java HotSpot runtime is different. First and foremost, Java has 3 Just-in Time Compilers, C1, C2, and an experimental one that isn't in use yet. But that's not the main reason. The Interpreter inside the JVM is a very special kind of Interpreter called a Template Interpreter. Instead of just executing bytecode directly in a massive opcode switch case statement like CPython (And really almost every other interpreter does) does, the Template Interpreter inside the JVM contains an enormous arraylist. What does it contain? Key-value pairs of bytecodes and native CPU instructions! The arraylist is empty on startup and is filled with mappings of bytecodes pointing to native machine language to be directly run on the hardware just before your application starts up, what this means is that the "Interpreter" inside the JVM isn't actually an Interpreter at all- It's actually a discount Compiler! When Java bytecode is run, the "Interpreter" simply maps the input bytecode directly to native machine language and executes the native mapping directly, rather than implementing it in software. I'm not exactly sure why the JVM was made this way, but I suspect it was to easily execute "Interpreted" Code together with JIT Compiled Code seamlessly, and for speed/performance. If you pitted the JVM without JIT against CPython or most other interpreters it would still probably come out ahead of them, in virtue of its ingenious design which to my knowledge no other language has used before.