Overview

Lightweight reconciliation tests for DataFrames

Use Rec to compare two DataFrames (baseline vs candidate) with per-column checks (equality, absolute / relative tolerance, regex-driven selection) and clear summaries of failures.

Features

• Declarative column mapping
• Built-in checks: equality, absolute tolerance, relative tolerance
• Index integrity checks (missing / extra index values)
• Regex column selection (regex=True on checks)
• Compact textual summary
• Extensible: implement custom checks by subclassing ColumnCheck

Quick Example

import pandas as pd
from recx import Rec, EqualCheck, AbsTolCheck

baseline = pd.DataFrame({
    "price": [100.00, 200.00, 300.00],
    "status": ["active", "inactive", "active"]
})

candidate = pd.DataFrame({
    "price": [100.00, 200.00, 301.00],
    "status": ["active", "inactive", "active"]
})

rec = Rec(columns={
    "price": AbsTolCheck(tol=0.01),
    "status": EqualCheck(),
})

result = rec.run(baseline, candidate)
result.summary()

Next Steps

• Read the Getting Started guide.
• Browse the Usage examples.
• Dive into the API Reference.

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Feel free to open issues or PRs with suggestions or improvements.