# How to Build a Compiler or Interpreter from Scratch: A Complete Guide

> Learn to build a compiler or interpreter from scratch. Our guide covers tokenization, AST construction, semantic analysis, and code generation or execution.

- Repository: [Sonkeng/Best-websites-a-programmer-should-visit](https://github.com/sdmg15/Best-websites-a-programmer-should-visit)
- Tags: deep-dive
- Published: 2026-03-01

---

**Building a compiler or interpreter from scratch requires implementing a multi-stage pipeline that transforms source code into tokens, constructs an abstract syntax tree, performs semantic analysis, and either generates target code or executes the tree directly.**

Creating your own programming language implementation is one of the most rewarding challenges in computer science. The `sdmg15/Best-websites-a-programmer-should-visit` repository curates a comprehensive collection of resources specifically for developers who want to build a compiler or interpreter from scratch, covering everything from theoretical foundations to working code examples.

## Understanding the Fundamentals of Compiler Construction

Before writing code, you need to understand the theoretical underpinnings of language implementation. The repository references classic texts like the *Dragon Book* (Compilers: Principles, Techniques, and Tools) alongside modern tutorials that explain **lexical analysis**, **parsing algorithms**, **abstract syntax trees (ASTs)**, and **code generation strategies**.

## The Core Pipeline: From Source Code to Execution

Every compiler or interpreter follows a structured pipeline. The resources in the [`README.md`](https://github.com/sdmg15/Best-websites-a-programmer-should-visit/blob/main/README.md) file under the "Building a Simple Compiler/Interpreter" section break this down into six essential stages.

### Lexical Analysis (Tokenization)

The first stage converts raw source text into a stream of tokens. This involves writing a **lexer** that recognizes keywords, identifiers, operators, and literals using regular expressions or finite automata.

### Parsing and Abstract Syntax Trees

Next, a **parser** consumes the token stream to build an **abstract syntax tree (AST)**. This stage validates grammatical structure according to your language's formal grammar, typically defined in **EBNF** or using parser generators like **ANTLR** or **Bison**.

### Semantic Analysis

After parsing, the compiler performs **semantic analysis** to check type consistency, resolve variable scopes, and enforce language-specific validations before execution or code generation.

### Code Generation or Direct Interpretation

Finally, you either **generate target code** (transpiling to C, emitting LLVM IR, or producing machine code) or **interpret the AST directly** by walking the tree and evaluating nodes at runtime.

## Practical Resources in the Repository

The `sdmg15/Best-websites-a-programmer-should-visit` repository aggregates high-quality learning materials in its [`README.md`](https://github.com/sdmg15/Best-websites-a-programmer-should-visit/blob/main/README.md) file. These include:

- **Video tutorials**: YouTube playlists that demonstrate building a tiny expression interpreter in Python, walking through lexer and parser implementation.
- **Written guides**: Step-by-step articles that construct a minimal compiler for a C-like language, covering the full pipeline from tokens to assembly.
- **Open-source projects**: Links to GitHub repositories containing simple Lisp interpreters and tiny C-like compilers that you can clone, run, and extend.

## Hands-On Example: A Minimal Arithmetic Interpreter

To illustrate the concepts, here is a complete Python implementation of a recursive-descent interpreter for arithmetic expressions. This example demonstrates the lexing and parsing stages described in the repository's resources:

```python
import re

# Token specification

TOKEN_SPEC = [
    ("NUMBER",   r"\d+(\.\d*)?"),   # Integer or decimal number

    ("PLUS",     r"\+"),            # Addition

    ("MINUS",    r"-"),             # Subtraction

    ("TIMES",    r"\*"),            # Multiplication

    ("DIVIDE",   r"/"),             # Division

    ("LPAREN",   r"\("),            # Left parenthesis

    ("RPAREN",   r"\)"),            # Right parenthesis

    ("SKIP",     r"[ \t]+"),        # Skip whitespace

]

TOK_REGEX = "|".join("(?P<%s>%s)" % pair for pair in TOKEN_SPEC)
Token = re.Match

def lexer(text):
    for mo in re.finditer(TOK_REGEX, text):
        kind = mo.lastgroup
        if kind == "NUMBER":
            yield ("NUMBER", float(mo.group()))
        elif kind != "SKIP":
            yield (kind, mo.group())

# Recursive‑descent parser / evaluator

class Parser:
    def __init__(self, tokens):
        self.tokens = iter(tokens)
        self.current = None
        self.advance()

    def advance(self):
        self.current = next(self.tokens, ("EOF", None))

    def expr(self):
        value = self.term()
        while self.current[0] in ("PLUS", "MINUS"):
            op = self.current[0]
            self.advance()
            rhs = self.term()
            value = value + rhs if op == "PLUS" else value - rhs
        return value

    def term(self):
        value = self.factor()
        while self.current[0] in ("TIMES", "DIVIDE"):
            op = self.current[0]
            self.advance()
            rhs = self.factor()
            value = value * rhs if op == "TIMES" else value / rhs
        return value

    def factor(self):
        if self.current[0] == "NUMBER":
            val = self.current[1]
            self.advance()
            return val
        elif self.current[0] == "LPAREN":
            self.advance()
            val = self.expr()
            if self.current[0] != "RPAREN":
                raise SyntaxError("Missing ')'")
            self.advance()
            return val
        else:
            raise SyntaxError(f"Unexpected token: {self.current}")

def evaluate(expr):
    tokens = lexer(expr)
    parser = Parser(tokens)
    return parser.expr()

# Example usage

print(evaluate("3 + 4 * (2 - 1)"))   # → 7.0

```

This implementation follows the classic pipeline found in the repository's curated materials: **lexing** with regular expressions, **parsing** via recursive descent, and **evaluation** by traversing the implicit AST formed by the call stack.

## Navigating the Repository Structure

When exploring the `sdmg15/Best-websites-a-programmer-should-visit` repository, focus on these key files:

- **[`README.md`](https://github.com/sdmg15/Best-websites-a-programmer-should-visit/blob/main/README.md)**: Contains the "Building a Simple Compiler/Interpreter" section with all curated links to tutorials and projects.
- **[`package.json`](https://github.com/sdmg15/Best-websites-a-programmer-should-visit/blob/main/package.json)**: Project metadata for CI tooling.
- **[`_config.yml`](https://github.com/sdmg15/Best-websites-a-programmer-should-visit/blob/main/_config.yml)**: Jekyll configuration for the GitHub Pages site.
- **[`white_listed_sites.txt`](https://github.com/sdmg15/Best-websites-a-programmer-should-visit/blob/main/white_listed_sites.txt)**: URLs approved for the site's embed feature.

## Summary

Building a compiler or interpreter from scratch requires implementing a structured pipeline that transforms source code into executable behavior. Key takeaways from the curated resources include:

- Master the **fundamentals** of lexical analysis, parsing theory, and AST construction before writing code.
- Follow the **six-stage pipeline**: lexing, parsing, semantic analysis, and either code generation or direct interpretation.
- Leverage **parser generators** like ANTLR or Bison for complex grammars, or write **recursive-descent parsers** for simpler languages.
- Study the **open-source examples** linked in the repository's [`README.md`](https://github.com/sdmg15/Best-websites-a-programmer-should-visit/blob/main/README.md) to see working implementations of Lisp interpreters and C-like compilers.
- Start with an **arithmetic interpreter** (like the Python example above) to validate your understanding before tackling full language features.

## Frequently Asked Questions

### What programming language should I use to build a compiler?

You can build a compiler or interpreter in any Turing-complete language, but **Python, C++, and Rust** are popular choices. Python offers rapid prototyping for educational interpreters, while C++ and Rust provide memory safety and performance for production compilers. The repository links to examples in multiple languages, including JavaScript and Go.

### Do I need to know assembly language to build a compiler?

Knowing **assembly language** is only necessary if you are targeting machine code directly or writing a backend for a specific architecture. Many educational compilers target higher-level languages like C or LLVM IR, which abstracts away assembly details. However, understanding assembly helps optimize code generation and is valuable for systems programming roles.

### How long does it take to build a simple compiler from scratch?

A basic **arithmetic interpreter** can be built in a few hours, while a simple compiler for a C-like language typically takes **2–4 weeks** of focused effort. A production-quality compiler with optimizations, multiple backends, and standard libraries can take years of development. The repository's curated tutorials are designed to help you build a working prototype within a weekend.

### What is the difference between a compiler and an interpreter?

A **compiler** translates source code into target code (machine code, bytecode, or another high-level language) ahead of time, creating a standalone executable. An **interpreter** directly executes the source code or AST without prior translation, processing statements one at a time. Some languages use both: Java compiles to bytecode which is then interpreted or JIT-compiled by the JVM.