Learn Python by Building a Lisp Interpreter

Introduction to Lisp language

Lisp, short for “List Processing”, is a functional programming language designed to easily process strings of data. Lisp is known for its simplicity and elegance in symbolic computation. Lisp programs are composed of expressions (lists), making them particularly suitable for recursive operations and the processing of symbolic data.

This guide will guide you through building a simplified Lisp interpreter using Python. By the end of the course, you'll have a working interpreter capable of evaluating basic Lisp expressions, defining functions, and performing conditional logic.

Lisp syntax example

Here is a simple Lisp program for calculating the cube of a number:

<code>(define square (lambda (x) (* x x)))
(square 4) 
输出：16</code>

In this example:

• define is used to create new variables or functions in Lisp. It associates a name with a value or function, allowing you to reference it in future code.
• lambda is used to create anonymous functions in Lisp. There are no predefined names for these functions. You can create them dynamically and assign them to variables (or pass them around).

If you want to learn Lisp programming in more depth, a great place to start is this tutorial [tutorial link should be inserted here].

Steps to build a Lisp interpreter

Create a new file named lis.py. This will be the main Python script for the interpreter.

1. Tokenization

This step splits the input string into smaller, more meaningful parts called tokens. For example, an expression like ( 1 2) is decomposed into a list ["(", " ", "1", "2", ")"]. This process makes analyzing and manipulating input easier for further processing.

<code class="language-python">def tokenize(source):
    """
    将输入源字符串分词：
    - 将开括号和闭括号替换为空格填充的版本，将它们视为单独的标记。
    - 按空格分割修改后的字符串以获得标记列表。

    参数：
    - source (str): 要分词的源代码。

    返回：
    - 字符串列表：表示源代码的标记列表。
    """
    return source.replace("(", " ( ").replace(")"," ) ").split()</code>

2. Parsing

After tokenization, the tags are converted into a structured format, usually a nested list. For example, ["(", " ", "1", "2", ")"] becomes [" ", 1, 2]. This structured representation allows expressions to be evaluated more easily by mapping them to a tree-like structure called an Abstract Syntax Tree (AST).

<code class="language-python">def read_from_tokens(tokens):
    # ... [代码与原文相同] ...</code>

3. Environment Setup

The environment acts as a dictionary in which variable names and functions are stored. It includes built-in functions like , -, *, /, etc., as well as user-defined variables and functions. This environment allows the interpreter to resolve symbols (such as x or ) when used in expressions.

<code class="language-python">class Env(dict):
    # ... [代码与原文相同] ...</code>

Why do we need the Env class?

The Env class is crucial because it acts as the backbone of the interpreter, managing variables, functions, and scopes. Here's why you need it:

• Variable Binding
• Function Storage
• Scoped Resolution
• Built-in Functions

4. Evaluation

The core logic of the interpreter, where parsed expressions are evaluated:

• Numbers (e.g., 1, 2.5) and variables (e.g., x, y) evaluate to their respective values.
• Function calls (e.g., ( 1 2)) are evaluated recursively. Operators ( ) and parameters (1, 2) use the environment for parsing and calculation.

<code>(define square (lambda (x) (* x x)))
(square 4) 
输出：16</code>

5. REPL (read-evaluate-print loop)

REPL is an interactive shell that allows users to enter and execute Lisp commands in real time. It reads user input (e.g., (define x 10)), evaluates it (e.g., assigns 10 to x), and prints the result.

<code class="language-python">def tokenize(source):
    """
    将输入源字符串分词：
    - 将开括号和闭括号替换为空格填充的版本，将它们视为单独的标记。
    - 按空格分割修改后的字符串以获得标记列表。

    参数：
    - source (str): 要分词的源代码。

    返回：
    - 字符串列表：表示源代码的标记列表。
    """
    return source.replace("(", " ( ").replace(")"," ) ").split()</code>

Conclusion

By following the steps above, you have created a basic Lisp interpreter that can handle arithmetic expressions, define functions, and even handle conditional logic. This is just a simple version, but as you explore further you can extend it with more features, such as advanced error handling, better scoping, and additional built-in functions.

If you're interested in diving deeper into the world of Lisp and learning more advanced concepts, I highly recommend checking out Peter Norvig's Lisp Interpreter Tutorial, which is an excellent resource for building the interpreter in this guide.

The above is the detailed content of Learn Python by Building a Lisp Interpreter. For more information, please follow other related articles on the PHP Chinese website!