# Folder Management Summary

**Author**: RSK World  
**Website**: https://rskworld.in  
**Email**: help@rskworld.in  
**Phone**: +91 93305 39277

## ✅ Completed Actions

### 1. __pycache__ Folder Management

**Status**: ✅ Configured and ready

- **.gitignore**: Already configured to ignore `__pycache__/` folders
- **Cleanup Scripts Created**:
  - `scripts/clean_cache.py` - Python script (cross-platform)
  - `scripts/cleanup.sh` - Shell script (Linux/Mac)
  - `scripts/cleanup.bat` - Batch script (Windows)

**Usage**:
```bash
# Python (recommended)
python scripts/clean_cache.py

# Windows
scripts\cleanup.bat

# Linux/Mac
bash scripts/cleanup.sh
```

### 2. Data Folder Management

**Status**: ✅ Configured and ready

- **.gitignore Updated**: 
  - Ignores generated files (`*.npy`, `*.csv`, `*.json`)
  - Keeps directory structure (`.gitkeep`)
  - Keeps documentation (`README.md`)

- **Data Generated**: 
  - Classification data (1000 samples)
  - Regression data (1000 samples)
  - Image data (200 images)
  - Sequence data (500 sequences)
  - Tabular data (1000 rows CSV)

**Current Data Folder Structure**:
```
data/
├── .gitkeep                    # Keeps folder in git
├── README.md                   # Documentation (tracked)
├── classification_X.npy        # Generated (ignored)
├── classification_y.npy         # Generated (ignored)
├── classification_metadata.json # Generated (ignored)
├── regression_X.npy            # Generated (ignored)
├── regression_y.npy            # Generated (ignored)
├── images_X.npy                # Generated (ignored)
├── images_y.npy                # Generated (ignored)
├── sequences_X.npy             # Generated (ignored)
├── sequences_y.npy             # Generated (ignored)
└── tabular.csv                 # Generated (ignored)
```

## 📋 .gitignore Configuration

### Current Settings:

```gitignore
# Python
__pycache__/
*.py[cod]
*.pyo
*.pyd

# Data
# Keep data directory structure but ignore generated files
data/*.npy
data/*.csv
data/*.json
data/visualizations/
!data/.gitkeep
!data/README.md
```

## 🛠️ Available Scripts

### Cleanup Scripts:
1. **clean_cache.py** - Main cleanup script (Python)
2. **cleanup.sh** - Shell script for Linux/Mac
3. **cleanup.bat** - Batch script for Windows

### Data Generation Scripts:
1. **generate_data_standalone.py** - Generate data without TensorFlow
2. **generate_data.py** - Full data generation (requires TensorFlow)

## 📝 Best Practices

### Before Committing:
1. Run cleanup script: `python scripts/clean_cache.py`
2. Verify no `__pycache__` folders are tracked
3. Verify generated data files are ignored

### Regular Maintenance:
- Clean `__pycache__` folders periodically
- Regenerate data if needed: `python scripts/generate_data_standalone.py`
- Keep data directory structure intact

### CI/CD Integration:
Add to your pipeline:
```yaml
- name: Clean __pycache__
  run: python scripts/clean_cache.py
```

## ✅ Verification

Run these commands to verify everything is set up correctly:

```bash
# Check __pycache__ folders (should return nothing)
find . -type d -name "__pycache__"

# Check .gitignore is working
git status --ignored

# Verify data files are ignored
git check-ignore data/*.npy
```

## 📚 Documentation

- **CLEANUP_GUIDE.md** - Detailed cleanup guide
- **DATA_GENERATION_SUMMARY.md** - Data generation documentation
- **data/README.md** - Data folder documentation

## Summary

✅ **__pycache__ folders**: Properly ignored and cleanup scripts available  
✅ **Data folder**: Properly configured with generated datasets  
✅ **.gitignore**: Updated to handle both folders correctly  
✅ **Scripts**: Created for easy maintenance  
✅ **Documentation**: Complete guides available  

Everything is ready and properly configured!
