Metadata-Version: 2.4
Name: soflytics
Version: 0.1.0
Summary: Zero-config data quality for humans. Profile, suggest rules, validate, and visualize — all in one call.
Author: Saman
License: MIT
Project-URL: Homepage, https://github.com/saman/soflytics
Project-URL: Repository, https://github.com/saman/soflytics
Keywords: data-quality,profiling,validation,data-engineering
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Software Development :: Quality Assurance
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: pandas>=1.5.0
Requires-Dist: fastapi>=0.100.0
Requires-Dist: uvicorn>=0.20.0
Requires-Dist: rich>=13.0.0
Requires-Dist: click>=8.0.0
Requires-Dist: jinja2>=3.1.0
Provides-Extra: dev
Requires-Dist: pytest>=7.0.0; extra == "dev"
Requires-Dist: pytest-cov>=4.0.0; extra == "dev"
Provides-Extra: db
Requires-Dist: sqlalchemy>=2.0.0; extra == "db"
Requires-Dist: pyodbc>=5.0.0; extra == "db"
Requires-Dist: pymssql>=2.2.0; extra == "db"
Requires-Dist: psycopg2-binary>=2.9.0; extra == "db"
Requires-Dist: pymysql>=1.1.0; extra == "db"
Provides-Extra: all
Requires-Dist: soflytics[db,dev]; extra == "all"

# 🩺 Soflytics

**Zero-config data quality for humans.**

Point it at any data source — a DataFrame, a CSV — and get instant profiling, smart validation rules, and a gorgeous visual health report. No YAML, no boilerplate.

## Installation

```bash
pip install soflytics
```

## Quickstart

```python
import soflytics

# Audit any data source
report = soflytics.audit("data.csv")       # CSV file
report = soflytics.audit(df)               # Pandas DataFrame

# View results
report.to_console()     # Pretty terminal output
report.show()           # Opens browser dashboard
report.to_html("report.html")  # Save standalone HTML

# Smart rule suggestions
rules = report.suggest()          # Auto-generated rules
result = report.validate(rules)   # Run validation
```

## CLI

```bash
# Audit a CSV file
soflytics audit data.csv

# Launch interactive dashboard
soflytics dashboard data.csv
```

## What You Get

- **🧠 Auto-Profiling** — Nulls, duplicates, outliers, type mismatches, pattern detection
- **🤖 Smart Rules** — Plain-English rule suggestions based on your data
- **📊 Visual Dashboard** — Per-column health grades, quality heatmaps, drill-down details
- **⚡ Dead Simple** — One function call. Zero configuration.

## License

MIT
