很难给出一个实际的答案，因为差异在于语言定义本身。可以为每一种编译语言构建一个解释器，但不可能为每一种解释语言构建一个编译器。它主要是关于语言的正式定义。所以在大学里没有人喜欢理论信息学。

解释源代码相对于编译源代码的最大优势是可移植性。

如果你的源代码是编译的，你需要为你的程序运行在不同类型的处理器和/或平台编译不同的可执行文件(例如一个用于Windows x86，一个用于Windows x64，一个用于Linux x64，等等)。此外，除非您的代码完全符合标准，并且不使用任何特定于平台的函数/库，否则您实际上需要编写和维护多个代码库!

如果你的源代码是解释型的，你只需要编写一次，它就可以在任何平台上由合适的解释器解释和执行!它是便携!请注意，解释器本身是为特定平台编写和编译的可执行程序。

编译代码的一个优点是它向最终用户隐藏了源代码(可能是知识产权)，因为您部署的不是人类可读的原始源代码，而是一个模糊的二进制可执行文件。

简短的(不精确的)定义:

编译语言:将整个程序立即转换为机器代码，然后由CPU运行机器代码。

解释语言:逐行读取程序，一旦读取一行，CPU就会执行该行的机器指令。

但实际上，现在很少有语言是纯编译或纯解释的，它们通常是混合的。想要更详细的图片描述，请看这个帖子:

编译和解释的区别是什么?

或者是我后来的博客:

https://orangejuiceliberationfront.com/the-difference-between-compiler-and-interpreter/

开始用“过去的冲击波”来思考

很久很久以前，有一个计算机王国 解释器和编译器。的优点引起了各种各样的争论 一个比另一个。当时的普遍意见是这样的:

解释器:快速开发(编辑和运行)。执行速度慢，因为每个语句都必须被解释为 每次执行的机器代码(想想这对于执行了数千次的循环意味着什么)。 编译器:开发(编辑、编译、链接和运行)缓慢。编译/链接步骤可能会花费大量时间)。快 来执行。整个程序已经是原生机器代码了。

运行时有一到两个数量级的差异 解释程序和编译程序之间存在性能差异。其他的区别 点，例如代码的运行时可变性，也有一些兴趣，但主要是 区别围绕着运行时性能问题。

今天的情况已经发展到这样的程度，编译/解释的区别是 几乎无关紧要。许多 编译语言调用的运行时服务并非如此 完全基于机器代码。而且，大多数解释型语言都被“编译”成字节码 之前执行。字节码解释器非常高效，可以与一些编译器生成的解释器相匹敌 从执行速度的角度来看代码。

典型的区别是编译器生成本机机器码，解释器读取源代码 使用某种运行时系统动态生成机器代码。 如今，经典的诠释者已所剩无几——几乎全部 编译成字节码(或其他一些半编译状态)，然后在虚拟“机器”上运行。

从http://www.quora.com/What-is-the-difference-between-compiled-and-interpreted-programming-languages

There is no difference, because “compiled programming language” and “interpreted programming language” aren’t meaningful concepts. Any programming language, and I really mean any, can be interpreted or compiled. Thus, interpretation and compilation are implementation techniques, not attributes of languages. Interpretation is a technique whereby another program, the interpreter, performs operations on behalf of the program being interpreted in order to run it. If you can imagine reading a program and doing what it says to do step-by-step, say on a piece of scratch paper, that’s just what an interpreter does as well. A common reason to interpret a program is that interpreters are relatively easy to write. Another reason is that an interpreter can monitor what a program tries to do as it runs, to enforce a policy, say, for security. Compilation is a technique whereby a program written in one language (the “source language”) is translated into a program in another language (the “object language”), which hopefully means the same thing as the original program. While doing the translation, it is common for the compiler to also try to transform the program in ways that will make the object program faster (without changing its meaning!). A common reason to compile a program is that there’s some good way to run programs in the object language quickly and without the overhead of interpreting the source language along the way. You may have guessed, based on the above definitions, that these two implementation techniques are not mutually exclusive, and may even be complementary. Traditionally, the object language of a compiler was machine code or something similar, which refers to any number of programming languages understood by particular computer CPUs. The machine code would then run “on the metal” (though one might see, if one looks closely enough, that the “metal” works a lot like an interpreter). Today, however, it’s very common to use a compiler to generate object code that is meant to be interpreted—for example, this is how Java used to (and sometimes still does) work. There are compilers that translate other languages to JavaScript, which is then often run in a web browser, which might interpret the JavaScript, or compile it a virtual machine or native code. We also have interpreters for machine code, which can be used to emulate one kind of hardware on another. Or, one might use a compiler to generate object code that is then the source code for another compiler, which might even compile code in memory just in time for it to run, which in turn . . . you get the idea. There are many ways to combine these concepts.

The Python Book©2015 Imagine Publishing Ltd，简单地通过第10页中提到的以下提示来区分差异:

像Python这样的解释型语言是指将源代码转换为机器码，然后在每次程序运行时执行的语言。这与编译语言(如C)不同，后者只将源代码转换为机器代码一次——然后在程序每次运行时执行生成的机器代码。