DiskDelia

A 90s Cyberdelia-themed macOS storage analyzer.

"Hack the Planet... starting with your hard drive."

DiskDelia helps you find what's eating your disk space — with a special focus on developer bloat like node_modules, virtual environments, build caches, and Xcode's infamous DerivedData. It comes in two flavors: a retro-styled GUI app and a fast CLI tool.

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Features

• Developer-aware scanning — Automatically identifies 60+ programming-related directories (node_modules, .venv, target, DerivedData, .cargo, .conda, Docker data, and many more)
• System data probing — Checks macOS-specific paths like ~/Library/Caches, iOS backups, Simulator data, and iCloud local storage
• Large file detection — Finds files above a configurable size threshold
• Cleanup hints — Shows the exact command to clean up each identified item
• Drill-down navigation — Double-click any folder to scan deeper into it, with back button history
• Two interfaces — GUI (storage-app.py) and CLI (storage-analyzer.py)

Quick Start

No dependencies required — both tools use only the Python standard library.

GUI App

python3 storage-app.py

This launches the full Cyberdelia-themed interface with:

• Configurable scan target directory and minimum size threshold
• Color-coded results (yellow = dev, red = system, blue = large files, green = folders)
• One-click actions: Open, Open Parent, Copy Path, Scan Into
• Real-time scanning status with animated terminal aesthetics

CLI Tool

# Scan home directory for items >= 100 MB (default)
python3 storage-analyzer.py

# Scan a specific path with a custom threshold
python3 storage-analyzer.py /path/to/scan 50

The CLI outputs a color-coded terminal report grouped into:

1. Programming / Dev — safely reviewable for cleanup
2. Large Files — individual files above the threshold
3. Large Folders — non-programming directories worth investigating

What It Detects

Developer Tools & Caches

Category	Directories
JavaScript	node_modules, .npm, .yarn, .pnpm-store, .next, .nuxt
Python	venv, .venv, __pycache__, .tox, .mypy_cache, .pytest_cache, site-packages, .conda, anaconda3, miniconda3, .pyenv
Rust	.cargo, target, .rustup
Java/JVM	.gradle, .m2, target
Ruby	.bundle, .gem, .rbenv
Go	go (workspace/modules)
iOS/macOS	Pods, DerivedData, .cocoapods, Xcode Archives, iOS DeviceSupport, CoreSimulator
Other	.docker, .vagrant, .nvm, .sdkman, .julia, .ghcup, .stack, .opam, .pub-cache, .flutter
General	build, dist, vendor, .cache, .local, .Trash

macOS System Paths

• ~/Library/Caches — Browser, Xcode, Spotify caches
• ~/Library/Application Support — App data (check for removed apps)
• ~/Library/Developer/Xcode/DerivedData — Xcode build cache (often 10+ GB)
• ~/Library/Application Support/MobileSync/Backup — iOS device backups (10-50+ GB)
• ~/Library/Developer/CoreSimulator — iOS Simulator data
• ~/Library/Mobile Documents — iCloud Drive local cache
• ~/Library/Mail — Mail.app local storage
• ~/Library/Messages — iMessage attachments & history
• And more (system logs, temp files, diagnostic data)

Building a .app / .dmg

The included build-dmg.sh script packages the GUI into a standalone macOS application:

chmod +x build-dmg.sh
./build-dmg.sh

This will:

1. Create a Python virtualenv and install PyInstaller
2. Bundle storage-app.py into a .app using PyInstaller
3. Package the .app into a distributable .dmg with an Applications symlink

Output:

• dist/DiskDelia.app — The application bundle
• dist/DiskDelia-1.0.dmg — The disk image installer

Requirements for building: Python 3.11 via pyenv (~/.pyenv/versions/3.11.8/bin/python3.11)

How It Works

1. Phase 1 — Runs du -d 3 -k on the target directory to quickly map disk usage up to 3 levels deep
2. Phase 2 — In parallel:
   • Probes known macOS system data paths with du -sk
   • Runs find for individual large files up to 6 levels deep
3. Classification — Matches directory names against the known developer tool patterns and tags them by type
4. Display — Results are sorted by size (largest first) and color-coded by category

The GUI uses threaded scanning so the interface stays responsive during analysis.

Tips

• Start with your home directory (~) and a 100 MB minimum to get a broad overview
• Drill into large folders to find what's actually taking space inside them
• Safe quick wins that almost always free significant space:
  • rm -rf node_modules in old/unused projects
  • Delete .venv/venv in abandoned Python projects
  • rm -rf ~/Library/Developer/Xcode/DerivedData (Xcode rebuilds this as needed)
  • brew cleanup --prune=all
  • docker system prune -a (if you use Docker)
  • Empty your Trash

Requirements

• macOS (uses du, find, and open commands)
• Python 3.11+ with tkinter
• No third-party packages needed

License

MIT