Zero-config data quality for humans. Profile, suggest rules, validate, and visualize — all in one call.
Project description
🩺 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
pip install soflytics
Quickstart
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
# 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
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