Project 15: Build Your Own ripgrep

A production-quality grep with: parallel directory traversal, .gitignore support, SIMD-accelerated literal search, regex support with literal extraction, colored output, context lines.

Quick Reference

Attribute Value
Primary Language Rust
Alternative Languages C++, Go
Difficulty Level 5: Master
Time Estimate 2-3 months
Knowledge Area Systems Programming / Everything Combined
Tooling Custom Implementation
Prerequisites All previous projects

What You Will Build

A production-quality grep with: parallel directory traversal, .gitignore support, SIMD-accelerated literal search, regex support with literal extraction, colored output, context lines.

Why It Matters

This project builds core skills that appear repeatedly in real-world systems and tooling.

Core Challenges

  • Integrating all previous components → maps to system architecture
  • Memory efficiency → maps to avoiding unnecessary allocations
  • Correctness edge cases → maps to handling binary files, encoding issues
  • User experience polish → maps to colors, progress, error messages

Key Concepts

  • Component Integration: How the pieces fit together
  • Error Handling: Graceful degradation on permission errors, encoding issues
  • Output Buffering: Line buffering vs block buffering for piped output
  • Configuration: Command-line argument parsing, config files

Real-World Outcome

$ ./mygrep "function.*async" ~/code --stats
Searching 150,234 files...

src/server/api.ts:145: async function handleRequest(req: Request) {
src/server/api.ts:234: export async function processData(data: Data) {
src/utils/fetch.ts:12: async function fetchWithRetry(url: string) {
...

Statistics:
  Files searched: 150,234
  Files matched: 1,234
  Lines matched: 5,678
  Time: 0.89s
  Throughput: 2.1 GB/s

$ hyperfine './mygrep TODO ~/code' 'rg TODO ~/code'
  mygrep: 0.95s ± 0.02s
  rg:     0.87s ± 0.02s

  Within 10% of ripgrep! 🎉

Implementation Guide

  1. Reproduce the simplest happy-path scenario.
  2. Build the smallest working version of the core feature.
  3. Add input validation and error handling.
  4. Add instrumentation/logging to confirm behavior.
  5. Refactor into clean modules with tests.

Milestones

  • Milestone 1: Minimal working program that runs end-to-end.
  • Milestone 2: Correct outputs for typical inputs.
  • Milestone 3: Robust handling of edge cases.
  • Milestone 4: Clean structure and documented usage.

Validation Checklist

  • Output matches the real-world outcome example
  • Handles invalid inputs safely
  • Provides clear errors and exit codes
  • Repeatable results across runs

References

  • Main guide: TEXT_SEARCH_TOOLS_DEEP_DIVE.md
  • ripgrep source code + all previous resources