who is having the special meaning in the python interpreter
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Byterun is a Python interpreter implemented in Python. Through my work on Byterun, I was surprised and delighted to discover that the fundamental structure of the Python interpreter fits easily into the 500-line size restriction. This chapter will walk through the structure of the interpreter and give you enough context to explore it further. The goal is not to explain everything there is to know about interpreters—like so many interesting areas of programming and computer science, you could devote years to developing a deep understanding of the topic.
Byterun was written by Ned Batchelder and myself, building on the work of Paul Swartz. Its structure is similar to the primary implementation of Python, CPython, so understanding Byterun will help you understand interpreters in general and the CPython interpreter in particular. (If you don't know which Python you're using, it's probably CPython.) Despite its short length, Byterun is capable of running most simple Python programs1.
A Python Interpreter
Before we begin, let's narrow down what we mean by "a Python interpreter". The word "interpreter" can be used in a variety of different ways when discussing Python. Sometimes interpreter refers to the Python REPL, the interactive prompt you get by typing python at the command line. Sometimes people use "the Python interpreter" more or less interchangeably with "Python" to talk about executing Python code from start to finish. In this chapter, "interpreter" has a more narrow meaning: it's the last step in the process of executing a Python program.
Before the interpreter takes over, Python performs three other steps: lexing, parsing, and compiling. Together, these steps transform the programmer's source code from lines of text into structured code objects containing instructions that the interpreter can understand. The interpreter's job is to take these code objects and follow the instructions.
You may be surprised to hear that compiling is a step in executing Python code at all. Python is often called an "interpreted" language like Ruby or Perl, as opposed to a "compiled" language like C or Rust. However, this terminology isn't as precise as it may seem. Most interpreted languages, including Python, do involve a compilation step. The reason Python is called "interpreted" is that the compilation step does relatively less work (and the interpreter does relatively more) than in a compiled language. As we'll see later in the chapter, the Python compiler has much less information about the behavior of a program than a C compiler does.
A Python Python Interpreter
Byterun is a Python interpreter written in Python. This may strike you as odd, but it's no more odd than writing a C compiler in C. (Indeed, the widely used C compiler gcc is written in C.) You could write a Python interpreter in almost any language.
Writing a Python interpreter in Python has both advantages and disadvantages. The biggest disadvantage is speed: executing code via Byterun is much slower than executing it in CPython, where the interpreter is written in C and carefully optimized. However, Byterun was designed originally as a learning exercise, so speed is not important to us. The biggest advantage to using Python is that we can more easily implement just the interpreter, and not the rest of the Python run-time, particularly the object system. For example, Byterun can fall back to "real" Python when it needs to create a class. Another advantage is that Byterun is easy to understand, partly because it's written in a high-level language (Python!) that many people find easy to read. (We also exclude interpreter optimizations in Byterun—once again favoring clarity and simplicity over speed.)
Building an Interpreter
Before we start to look at the code of Byterun, we need some higher-level context on the structure of the interpreter. How does the Python interpreter work?
The Python interpreter is a virtual machine, meaning that it is software that emulates a physical computer. This particular virtual machine is a stack machine: it manipulates several stacks to perform its operations (as contrasted with a register machine, which writes to and reads from particular m
Answer:
the answer is python keywords :)