Embedded Filesystem Visualizer (EFV)

A comprehensive tool for analyzing mounted rootfs filesystems (ext4, squashfs, etc.) and providing detailed insights about file sizes, permissions, init scripts, and bloat analysis.

Features

🔍 Filesystem Analysis

• File Statistics: Complete file size, permission, and metadata analysis
• Directory Sizing: Recursive directory size calculation with percentage breakdown
• File Type Detection: Automatic detection of binaries, scripts, and various file types
• Mount Information: Filesystem mount point and type detection

🚀 Init/Startup Script Detection

• Pattern Matching: Detects init scripts using common naming patterns
• Shebang Analysis: Identifies executable scripts by interpreter
• Permission Analysis: Shows script permissions and execution rights
• Interpreter Detection: Identifies the interpreter used by each script

📊 Bloat Analysis

• Large File Detection: Identifies files larger than 10MB
• Duplicate Detection: Finds potential duplicate files by size
• Age Analysis: Identifies old files (>1 year)
• Space Usage: Detailed breakdown of what's consuming space

🖥️ User Interfaces

• Terminal Interface: Rich, colored terminal output with progress indicators
• GUI Interface: Modern tkinter-based graphical interface with tabs
• Export Options: Save reports as text or JSON format

Installation

Prerequisites

• Python 3.7 or higher
• Linux system (for filesystem analysis)

Install from PyPI (when published)

pip install efv

Install from Source

# Clone the repository
git clone https://github.com/osamakader/efv.git
cd efv

# Install in development mode
pip install -e .

# Or install with development dependencies
pip install -e ".[dev]"

Install Dependencies Only

pip install -r requirements.txt

Usage

Terminal Interface

Basic Analysis

# Analyze the current root filesystem
efv

# Analyze a specific path
efv /path/to/rootfs

# Analyze with output to file
efv /path/to/rootfs -o report.txt

Command Line Options

efv [PATH] [OPTIONS]

Options:
  PATH                    Path to analyze (default: /)
  -o, --output FILE      Save report to file
  -v, --verbose          Verbose output
  -h, --help            Show help message

GUI Interface

Launch GUI

efv-gui

GUI Features

• Path Selection: Browse or enter filesystem path
• Tabbed Interface:
  • Overview: Filesystem summary and mount info
  • File Analysis: File type breakdown
  • Init Scripts: Startup script detection
  • Large Files: Top 20 largest files
  • Directory Analysis: Directory size breakdown
  • Bloat Analysis: Space optimization suggestions
• Export Options: Save reports as text or JSON

Output Examples

Terminal Output

================================================================================
EMBEDDED FILESYSTEM VISUALIZER REPORT
================================================================================

┌─ Filesystem Overview ─────────────────────────────────────────────────────────┐
│ Total Files: 45,231                                                          │
│ Total Size: 2.3GB                                                            │
│ Average File Size: 52.1KB                                                    │
└───────────────────────────────────────────────────────────────────────────────┘

┌─ Mount Information ──────────────────────────────────────────────────────────┐
│ Device: /dev/sda1                                                           │
│ Mountpoint: /                                                               │
│ Fstype: ext4                                                                │
│ Opts: rw,relatime                                                           │
└───────────────────────────────────────────────────────────────────────────────┘

┌─ File Type Analysis ────────────────────────────────────────────────────────┐
│ .so     │ 1,234 │ 2.7%  │                                                      │
│ .py     │ 890   │ 2.0%  │                                                      │
│ binary  │ 567   │ 1.3%  │                                                      │
│ script  │ 234   │ 0.5%  │                                                      │
└───────────────────────────────────────────────────────────────────────────────┘

┌─ Init/Startup Scripts ─────────────────────────────────────────────────────┐
│ /etc/init.d/network │ 2.1KB │ 755 │ /bin/bash                              │
│ /etc/rc.local       │ 1.8KB │ 755 │ /bin/bash                              │
│ /usr/bin/systemctl  │ 45KB  │ 755 │ N/A                                    │
└───────────────────────────────────────────────────────────────────────────────┘

┌─ Largest Files (Top 20) ──────────────────────────────────────────────────┐
│ 1  │ /usr/lib/libc.so.6        │ 2.1MB │                                    │
│ 2  │ /usr/bin/bash             │ 1.8MB │                                    │
│ 3  │ /usr/lib/libstdc++.so.6   │ 1.5MB │                                    │
└───────────────────────────────────────────────────────────────────────────────┘

┌─ Largest Directories ──────────────────────────────────────────────────────┐
│ /usr/lib     │ 856MB │ 37.2% │                                              │
│ /usr/bin     │ 234MB │ 10.2% │                                              │
│ /var/log     │ 123MB │ 5.3%  │                                              │
└───────────────────────────────────────────────────────────────────────────────┘

BLOAT ANALYSIS
────────────────────────────────────────
• Large binaries: 5 files > 10MB
• Potential duplicates: 45.2MB
• Old files (>1 year): 123.4MB

Use Cases

Embedded System Analysis

# Analyze a mounted embedded rootfs
python efv.py /mnt/embedded_rootfs

# Focus on init scripts for boot analysis
python efv.py /mnt/embedded_rootfs | grep -A 10 "Init/Startup Scripts"

Space Optimization

# Find largest directories for cleanup
python efv.py /path/to/rootfs | grep -A 15 "Largest Directories"

# Identify bloat sources
python efv.py /path/to/rootfs | grep -A 10 "BLOAT ANALYSIS"

Development Environment Analysis

# Analyze a development container
python efv.py /var/lib/docker/containers/container_id/rootfs

Development

Setup Development Environment

# Clone the repository
git clone https://github.com/osab270844/efv.git
cd efv

# Install in development mode with all dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run linting
flake8 efv/ tests/
mypy efv/

# Format code
black efv/ tests/

Available Make Commands

make help          # Show all available commands
make install       # Install in development mode
make install-dev   # Install with development dependencies
make test          # Run tests
make test-cov      # Run tests with coverage
make lint          # Run linting checks
make format        # Format code
make clean         # Clean build artifacts
make build         # Build the package
make demo          # Run the demo
make cli           # Run the CLI tool
make gui           # Run the GUI tool
make check         # Run all checks (format, lint, test)

Advanced Features

Custom Analysis

from efv import FilesystemAnalyzer

# Create analyzer
analyzer = FilesystemAnalyzer("/path/to/rootfs")

# Run analysis
report = analyzer.analyze_filesystem()

# Access specific data
print(f"Total files: {report['total_files']}")
print(f"Init scripts: {len(report['init_scripts'])}")
print(f"Large files: {len(report['large_files'])}")

JSON Export

# Export detailed report as JSON
efv-gui
# Use "Save as JSON" button in GUI

Troubleshooting

Permission Issues

# Run with sudo for protected filesystems
sudo python efv.py /path/to/rootfs

Large Filesystem Performance

# For very large filesystems, use verbose mode to monitor progress
python efv.py /path/to/rootfs -v

GUI Issues

# Ensure tkinter is available
python -c "import tkinter; print('GUI ready')"

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Roadmap

• Web-based interface
• Real-time monitoring
• Network filesystem support
• Advanced duplicate detection (content-based)
• Integration with package managers
• Automated cleanup suggestions
• Performance profiling
• Export to various formats (HTML, PDF, CSV)