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.

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。

不要忘记Python为x86提供了JIT编译器，这进一步混淆了问题。(见psyco)。

对“解释型语言”的更严格的解释只有在讨论VM的性能问题时才有用，例如，与Python相比，Ruby被认为更慢，因为它是一种解释型语言，不像Python——换句话说，上下文就是一切。

for posts that mention that python does not need to generate byte code, I'm not sure that's true. it seems that all callables in Python must have a .__code__.co_code attribute which contains the byte code. I don't see a meaningful reason to call python "not compiled" just because the compiled artifacts may not be saved; and often aren't saved by design in Python, for example all comprehension compile new bytecode for it's input, this is the reason comprehension variable scope is not consistent between compile(mode='exec, ...) and compile compile(mode='single', ...) such as between running a python script and using pdb

在本文中，“虚拟机”指的是进程虚拟机，不是指 系统虚拟机，如Qemu或Virtualbox。进程虚拟机为 一个简单的程序，它提供了一个通用的编程环境——程序 这是可以编程的。

Java has an interpreter as well as a virtual machine, and Python has a virtual machine as well as an interpreter. The reason "virtual machine" is a more common term in Java and "interpreter" is a more common term in Python has a lot to do with the major difference between the two languages: static typing (Java) vs dynamic typing (Python). In this context, "type" refers to primitive data types -- types which suggest the in-memory storage size of the data. The Java virtual machine has it easy. It requires the programmer to specify the primitive data type of each variable. This provides sufficient information for Java bytecode not only to be interpreted and executed by the Java virtual machine, but even to be compiled into machine instructions. The Python virtual machine is more complex in the sense that it takes on the additional task of pausing before the execution of each operation to determine the primitive data types for each variable or data structure involved in the operation. Python frees the programmer from thinking in terms of primitive data types, and allows operations to be expressed at a higher level. The price of this freedom is performance. "Interpreter" is the preferred term for Python because it has to pause to inspect data types, and also because the comparatively concise syntax of dynamically-typed languages is a good fit for interactive interfaces. There's no technical barrier to building an interactive Java interface, but trying to write any statically-typed code interactively would be tedious, so it just isn't done that way.

在Java世界中，虚拟机最引人注目，因为它运行程序 用一种可以编译成机器指令的语言编写， 结果就是速度和资源效率。可以执行Java字节码 通过Java虚拟机，性能接近编译 程序，相对来说。这是由于原始数据的存在 在字节码中键入信息。Java虚拟机将Java放在 自身类别:

可移植的解释静态类型语言

仅次于LLVM的是LLVM，但LLVM在不同的级别上运行:

可移植解释汇编语言

The term "bytecode" is used in both Java and Python, but not all bytecode is created equal. bytecode is just the generic term for intermediate languages used by compilers/interpreters. Even C compilers like gcc use an intermediate language (or several) to get the job done. Java bytecode contains information about primitive data types, whereas Python bytecode does not. In this respect, the Python (and Bash,Perl,Ruby, etc.) virtual machine truly is fundamentally slower than the Java virtual machine, or rather, it simply has more work to do. It is useful to consider what information is contained in different bytecode formats:

Llvm: CPU寄存器 原始数据类型 Python:用户定义类型

做一个现实世界的类比:LLVM使用原子，即Java虚拟机 Python虚拟机处理的是材料。 因为所有东西最终都必须分解成亚原子粒子(真实的 机器操作)，Python虚拟机有最复杂的任务。

Intepreters/compilers of statically-typed languages just don't have the same baggage that interpreters/compilers of dynamically-typed languages have. Programmers of statically-typed languages have to take up the slack, for which the payoff is performance. However, just as all nondeterministic functions are secretly deterministic, so are all dynamically-typed languages secretly statically-typed. Performance differences between the two language families should therefore level out around the time Python changes its name to HAL 9000.

The virtual machines of dynamic languages like Python implement some idealized logical machine, and don't necessarily correspond very closely to any real physical hardware. The Java virtual machine, in contrast, is more similar in functionality to a classical C compiler, except that instead of emitting machine instructions, it executes built-in routines. In Python, an integer is a Python object with a bunch of attributes and methods attached to it. In Java, an int is a designated number of bits, usually 32. It's not really a fair comparison. Python integers should really be compared to the Java Integer class. Java's "int" primitive data type can't be compared to anything in the Python language, because the Python language simply lacks this layer of primitives, and so does Python bytecode.

因为Java变量是显式类型的，所以可以合理地期望 比如Jython的性能在同一范围内 cPython的。另一方面，一个用Python实现的Java虚拟机 肯定比泥的速度要慢。不要指望Ruby, Perl等等， 为了更好的生活。它们的设计初衷不是这样的。它们是为 “脚本”，这是动态语言编程的称呼。

Every operation that takes place in a virtual machine eventually has to hit real hardware. Virtual machines contain pre-compiled routines which are general enough to to execute any combination of logical operations. A virtual machine may not be emitting new machine instructions, but it certainly is executing its own routines over and over in arbirtrarily complex sequences. The Java virtual machine, the Python virtual machine, and all the other general-purpose virtual machines out there are equal in the sense that they can be coaxed into performing any logic you can dream up, but they are different in terms of what tasks they take on, and what tasks they leave to the programmer.

Psyco for Python is not a full Python virtual machine, but a just-in-time compiler that hijacks the regular Python virtual machine at points it thinks it can compile a few lines of code -- mainly loops where it thinks the primitive type of some variable will remain constant even if the value is changing with each iteration. In that case, it can forego some of the incessent type determination of the regular virtual machine. You have to be a little careful, though, lest you pull the type out from under Psyco's feet. Pysco, however, usually knows to just fall back to the regular virtual machine if it isn't completely confident the type won't change.

这个故事的寓意是原始数据类型信息实际上是 有助于编译器/虚拟机。

最后，考虑以下情况:执行一个Python程序 由Python解释器/运行在Java上的Java虚拟机实现 解释器/虚拟机在LLVM中实现，运行在qemu虚拟中 在iPhone上运行的机器

永久链接

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。