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。

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.

不，它们并不都解释字节码。

Python只在运行pypy时解释字节码。否则，它将被编译成C并在该级别上进行解释。

Java编译为字节码。

为了深入回答“为什么是Java虚拟机，而不是Python解释器?”这个问题，让我们尝试回到编译理论领域，作为讨论的起点。

程序编译的典型过程包括以下步骤:

Lexical analysis. Splits program text into meaningful "words" called tokens (as part of the process all comments, spaces, new-lines etc. are removed, because they do not affect program behavior). The result is an ordered stream of tokens. Syntax analysis. Builds the so-called Abstract Syntax Tree (AST) from the stream of tokens. AST establish relations between tokens and, as a consequence, defines an order of evaluation of the program. Semantic analysis. Verifies semantical correctness of the AST using information about types and a set of semantical rules of the programming language. (For example, a = b + c is a correct statement from the syntaxis point of view, but completely incorrect from the semantic point of view if a was declared as a constant object) Intermediate code generation. Serializes AST into the linearly ordered stream of machine independent "primitive" operations. In fact, code generator traverses AST and logs the order of evaluation steps. As a result, from the tree-like representation of the program, we achieve much more simple list-like representation in which order of program evaluation is preserved. Machine code generation. The program in the form of machine independent "primitive" bytecode is translated into machine code of particular processor architecture.

好的。现在我们来定义这些术语。

Interpreter, in the classical meaning of that word, assumes execution based on the program evaluation based on AST produced directly from the program text. In that case, a program is distributed in the form of source code and the interpreter is fed by program text, frequently in a dynamic way (statement-by-statement or line-by-line). For each input statement, interpreter builds its AST and immediately evaluates it changing the "state" of the program. This is a typical behavior demonstrated by scripting languages. Consider for example Bash, Windows CMD etc. Conceptually, Python takes this way too.

If we replace the AST-based execution step on the generation of intermediate machine-independent binary bytecode step in the interpreter we will split the entire process of program execution into two separate phases: compilation and execution. In that case what previously was an interpreter will become a bytecode compiler, which will transform the program from the form of the text into some binary form. Then the program is distributed in that binary form, but not in the form of source code. On the user machine, that bytecode is fed into a new entity -- virtual machine, which in fact interpret that bytecode. Due to this, virtual machines are also called bytecode interpreter. But put your attention here! A classical interpreter is a text interpreter, but a virtual machine is a binary interpreter! This is an approach taken by Java and C#.

最后，如果我们将机器代码生成添加到字节码编译器中，我们就实现了我们所说的经典编译器。经典编译器将程序源代码转换为特定处理器的机器码。然后，该机器代码可以直接在目标处理器上执行，而不需要任何额外的中介(不需要任何类型的解释器，无论是文本解释器还是二进制解释器)。

现在让我们回到最初的问题，考虑Java和Python。

Java was initially designed to have as few implementation dependencies as possible. Its design is based on the principle "write once, run anywhere" (WORA). To implement it, Java was initially designed as a programming language that compiles into machine-independent binary bytecode, which then can be executed on all platforms that support Java without the need for its recompilation. You can think about Java like about WORA-based C++. Actually, Java is closer to C++ than to the scripting languages like Python. But in contrast to C++, Java was designed to be compiled into binary bytecode which then is executed in the environment of the virtual machine, while C++ was designed to be compiled in machine code and then directly executed by the target processor.

Python was initially designed as a kind of scripting programing language which interprets scripts (programs in the form of the text written in accordance with the programming language rules). Due to this, Python has initially supported a dynamic interpretation of one-line commands or statements, as the Bash or Windows CMD do. For the same reason, initial implementations of Python had not any kind of bytecode compilers and virtual machines for execution of such bytecode inside, but from the start Python had required interpreter which is capable to understand and evaluate Python program text.

因此，在历史上，Java开发人员倾向于谈论Java虚拟机(因为最初，Java已经作为Java字节码编译器和字节码解释器——JVM的包出现)，而Python开发人员倾向于谈论Python解释器(因为最初Python没有任何虚拟机，是一种经典的文本解释器，直接执行程序文本，而不需要任何形式的编译或转换为任何形式的二进制代码)。

Currently, Python also has the virtual machine under the hood and can compile and interpret Python bytecode. And that fact makes an additional investment into the confusion "Why Java Virtual Machine, but Python interpreter?", because it seems that implementations of both languages contain virtual machines. But! Even in the current moment interpretation of program text is a primary way of Python programs execution. Python implementations exploit virtual machines under the hood exclusively as an optimization technique. Interpretation of binary bytecode in the virtual machine is much more efficient than a direct interpretation of the original program text. At the same time, the presence of the virtual machine in the Python is absolutely transparent for both Python language designers and Python programs developers. The same language can be implemented in interpreters with and without the virtual machine. In the same way, the same programs can be executed in interpreters with and without the virtual machine, and that programs will demonstrate exactly the same behavior and produce equally the same output from the equal input. The only observable difference will be the speed of program execution and the amount of memory consumed by the interpreter. Thus, the virtual machine in Python is not an unavoidable part of the language design, but just an optional extension of the major Python interpreter.

Java can be considered in a similar way. Java under the hood has a JIT compiler and can selectively compile methods of Java class into machine code of the target platform and then directly execute it. But! Java still uses bytecode interpretation as a primary way of Java program execution. Like Python implementations which exploit virtual machines under the hood exclusively as an optimization technique, the Java virtual machines use Just-In-Time compilers exclusively for optimization purposes. Similarly, just because of the fact that direct execution of the machine code at least ten times faster than the interpretation of Java bytecode. And like in the case of Python, the presence of JIT compiler under the hood of JVM is absolutely transparent for both Java language designers and Java program developers. The same Java programming language can be implemented by JVM with and without JIT compiler. And in the same way, the same programs can be executed in JVMs with and without JIT inside, and the same programs will demonstrate exactly the same behavior and produce equally the same output from the equal input on both JVMs (with and without JIT). And like in the case of Python, the only observable difference between them, will be in the speed of execution and in the amount of memory consumed by JVM. And finally, like in the case of Python, JIT in Java also is not an unavoidable part of the language design, but just an optional extension of the major JVM implementations.

From the point of view of design and implementation of virtual machines of Java and Python, they differ significantly, while (attention!) both still stay virtual machines. JVM is an example of a low-level virtual machine with simple basic operations and high instruction dispatch cost. Python in its turn is a high-level virtual machine, for which instructions demonstrate complex behavior, and instruction dispatch cost is not so significant. Java operates with very low abstraction level. JVM operates on the small well-defined set of primitive types and has very tight correspondence (typically one to one) between bytecode instructions and native machine code instructions. In contrary, Python virtual machine operates at high abstraction level, it operates with complex data types (objects) and supports ad-hoc polymorphism, while bytecode instructions expose complex behavior, which can be represented by a series of multiple native machine code instructions. For example, Python supports unbounded range mathematics. Thus Python VM is forced to exploit long arithmetics for potentially big integers for which result of the operation can overflow the machine word. Hence, one bytecode instruction for arithmetics in Python can expose into the function call inside Python VM, while in JVM arithmetic operation will expose into simple operation expressed by one or few native machine instructions.

因此，我们可以得出以下结论。Java虚拟机但Python解释器是因为:

The term of virtual machine assumes binary bytecode interpretation, while the term interpreter assumes program text interpretation. Historically, Java was designed and implemented for binary bytecode interpretation and Python was initially designed and implemented for program text interpretation. Thus, the term "Java Virtual Machine" is historical and well established in the Java community. And similarly, the term "Python Interpreter" is historical and well established in the Python community. Peoples tend to prolong the tradition and use the same terms that were used long before. Finally, currently, for Java, binary bytecode interpretation is a primary way of programs execution, while JIT-compilation is just an optional and transparent optimization. And for Python, currently, program text interpretation is a primary way of Python programs execution, while compilation into Python VM bytecode is just an optional and transparent optimization.

Therefore, both Java and Python have virtual machines are binary bytecode interpreters, which can lead to confusion such as "Why Java Virtual Machine, but Python interpreter?". The key point here is that for Python, a virtual machine is not a primary or necessary means of program execution; it is just an optional extension of the classical text interpreter. On the other hand, a virtual machine is a core and unavoidable part of Java program execution ecosystem. Static or dynamic typing choice for the programming language design affects mainly the virtual machine abstraction level only, but does not dictate whether or not a virtual machine is needed. Languages using both typing systems can be designed to be compiled, interpreted, or executed within the environment of virtual machine, depending on their desired execution model.

首先，你应该明白，编程或计算机科学一般不是数学，我们经常使用的大多数术语都没有严格的定义。

现在回答你的问题:

什么是解释器(计算机科学)

它按最小的可执行单元翻译源代码，然后执行该单元。

什么是虚拟机

对于JVM来说，虚拟机是一个包含解释器、类加载器、垃圾收集器、线程调度器、JIT编译器和许多其他东西的软件。

正如你所看到的，解释器是JVM的一部分，整个JVM不能被称为解释器，因为它包含许多其他组件。

为什么在谈论python时要用“解释器”这个词

在Java中，编译部分是显式的。 另一方面，Python的编译和解释过程不像Java那样明确，从最终用户的角度来看，解释是用于执行Python程序的唯一机制