tether¶

High-precision record linkage library implementing a 7-step pipeline with multi-pass support.

Contents:

API Reference
- Core
- Score
- Block
- Decide
- Filter
- Preprocess
- Deduplicate
- Inspect
- Multipass

Installation¶

pip install tether

Quick Start¶

import pandas as pd
from tether import Pipeline, StringComparison, ExactComparison

df_left = pd.DataFrame({
    "id": [1, 2, 3],
    "first_name": ["John", "Jane", "Bob"],
    "last_name": ["Smith", "Doe", "Johnson"],
    "state": ["CA", "NY", "CA"],
})

df_right = pd.DataFrame({
    "id": [101, 102, 103],
    "first_name": ["Jon", "Jane", "Robert"],
    "last_name": ["Smith", "Doe", "Johnson"],
    "state": ["CA", "NY", "CA"],
})

result = (
    Pipeline()
    .preprocess(normalize_unicode=True, lowercase=True)
    .block(on="state")
    .score(comparisons=[
        StringComparison("first_name", algorithm="jaro_winkler"),
        StringComparison("last_name", algorithm="jaro_winkler"),
    ])
    .filter(min_score=0.7)
    .decide(method="hungarian")
    .build()
    .link(df_left, df_right)
)

print(result.matches)

Indices and tables¶