Metadata-Version: 2.4
Name: data-sweeper-toolbelt
Version: 0.2.0
Summary: An automated system janitor, directory sorter, data cleansing suite, and privacy guard for Python.
Author: TOQP_WorldNot
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown

# Data Sweeper Toolbelt (data-sweeper-toolbelt)

A zero-dependency, automated system filesystem organizer, data cleansing engine, and cryptographic privacy guard for Python.

`data-sweeper-toolbelt` provides high-speed file utility engines to instantly sort cluttered desktop spaces into structured directories, calculate subfolder storage space distribution, purge empty ghost folders with self-healing OneDrive synchronization delay handlers, batch rename sequential assets, purge duplicate matrix entries, repair empty dataset records, and dynamically sanitize private fields.

## Installation

```bash
pip install data-sweeper-toolbelt
```

## Quick Start Guide

### 1. Sweep and Organize Cluttered Folders
```python
from data_sweeper import DataSweeper
sweeper = DataSweeper()

# Auto-sort an entire directory by file extension categories
sweeper.clean_directory("C:/Users/YourName/Downloads")
```

### 2. Purge Empty Ghost Folders (Self-Healing Sync Mode)
```python
from data_sweeper import DataSweeper
sweeper = DataSweeper()

# Traverses bottom-up to wipe empty directories without triggering Windows locks
sweeper.purge_empty_folders("C:/Users/YourName/Downloads")
```

### 3. Bulk Rename & Re-Index Messy Assets
```python
from data_sweeper import DataSweeper
sweeper = DataSweeper()

# Instantly sequences files (e.g., Asset_01.png, Asset_02.png)
sweeper.bulk_rename("C:/Users/YourName/Pictures", prefix="Project_Asset")
```

### 4. Sanitize and Mask Sensitive Data (Privacy Guard)
```python
from data_sweeper import DataSweeper
sweeper = DataSweeper()

raw_data = [
    {"name": "Alex Blake", "email": "alexb@school.edu", "phone": "803-555-0144"},
]

# Scrambles names, masks emails/phone numbers, leaving other columns intact
sanitized_data = sweeper.mask_sensitive_data(raw_data, target_keys=["name", "email", "phone"])
```

### 5. Vaporize Duplicate Data Rows
```python
from data_sweeper import DataSweeper
sweeper = DataSweeper()

records = [
    {"user": "Alex", "points": 10},
    {"user": "Alex", "points": 10}, # Duplicate
]
clean_records = sweeper.drop_duplicates(records)
```

### 6. Patch Up Missing Empty Values
```python
from data_sweeper import DataSweeper
sweeper = DataSweeper()

broken_data = [{"name": "Item A", "tag": ""}, {"name": "Item B", "tag": None}]
fixed_data = sweeper.fill_missing_values(broken_data, default_value="N/A")
```

### 7. Repair Numeric Strings into Ints & Floats
```python
from data_sweeper import DataSweeper
sweeper = DataSweeper()

messy_matrix = [{"item": "Laptop", "price": "999", "rating": "4.8"}]
repaired_matrix = sweeper.repair_data_types(messy_matrix)
```

## License
Distributed under the MIT License. Open-source assets are free for personal and commercial applications.
