mbox 0.1.2

M|BOX Python SDK

Identity resolution and explainable data matching for Python and Pandas. M|BOX provides fast, fault-tolerant matching for messy business data. Build reusable indexes, resolve identities with configurable matching rules, and inspect transparent field-level scores.

Quick Start

Transform any Pandas DataFrame into a fault-tolerant search index and start querying immediately.

import pandas as pd
from mbox import TableIndexer

### Dummy data for demonstration
df = pd.DataFrame({
    "full_name": ["Robert Smith", "Katharina Müller"],
    "city": ["Konstanz", "Berlin"]
})

#### 1. Create an index from your existing DataFrame
index = TableIndexer.create_index(df, index_columns=["full_name", "city"])

#### 2. Perform a fuzzy match with typos or variations
results = index.match(
    full_name="Bob Smit", 
    city="Konstanz", 
    include_field_scores=True
)

For more hands-on examples, check out the M|BOX Cookbook on GitHub.

Highlights

• Fuzzy, exact, and substring matching
• Explainable scores for every matched field
• Character mappings and aliases for data harmonization
• Configurable indexing and recall behavior
• Persistent binary indexes for fast reuse
• Pandas-friendly workflows

For installation details, configuration options, persistence, and advanced usage, see the M|BOX Python SDK documentation.

M|BOX is currently in beta status. Breaking changes may occur in minor releases until version 1.0.0.