reclink

reclink

Blazing-fast fuzzy matching and record linkage library powered by Rust.

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Features

  • 21 string similarity metrics — edit distance, token-based, subsequence, alignment, and hybrid metrics
  • 10 phonetic algorithms — Soundex, Metaphone, Double Metaphone, NYSIIS, Caverphone, Cologne, Beider-Morse, Phonex, MRA, Daitch-Mokotoff
  • Full record linkage pipeline — blocking, comparison, classification, and clustering
  • 11 blocking strategies — exact, phonetic, sorted neighborhood, q-gram, LSH, canopy, trie, numeric, date, hybrid (union/intersection)
  • 8 classifiers — threshold, weighted, bands, Fellegi-Sunter with EM estimation, logistic regression, decision tree
  • 5 clustering algorithms — connected components, hierarchical, DBSCAN, OPTICS, incremental
  • 7 index structures — BK-tree, VP-tree, N-gram index, memory-mapped N-gram, MinHash LSH, Bloom filter, inverted index
  • DataFrame integration — pandas and polars accessors, native Polars plugin
  • Parallel computation — Rayon-powered cdist and pipeline execution
  • Scoring presets & composite scorer — pre-tuned configs for name, address, and general-purpose matching
  • Extensible plugin system — register custom metrics, blockers, comparators, classifiers, and preprocessors
  • WASM bindings — run reclink in the browser

Installation

pip install reclink

Build from source

git clone https://github.com/ByteVeda/reclink.git
cd reclink
uv sync --extra dev
maturin develop --release

Quick Start

Record linkage pipeline

import pandas as pd
from reclink.pipeline import ReclinkPipeline

df = pd.DataFrame({
    "id": ["1", "2", "3"],
    "first_name": ["Jon", "John", "Jane"],
    "last_name": ["Smith", "Smyth", "Doe"],
})

pipeline = (
    ReclinkPipeline.builder()
    .preprocess("first_name", ["fold_case", "strip_punctuation"])
    .preprocess("last_name", ["fold_case"])
    .block_phonetic("last_name", algorithm="soundex")
    .compare_string("first_name", metric="jaro_winkler")
    .compare_string("last_name", metric="jaro_winkler")
    .classify_threshold(0.85)
    .build()
)

matches = pipeline.dedup(df)
print(matches)
#    left_id right_id     score            scores
# 0       1        2  0.921...  [0.832..., 1.0...]

Direct metric usage

from reclink import jaro_winkler, soundex, cdist

jaro_winkler("Jon", "John")  # 0.93...
soundex("Smith") == soundex("Smyth")  # True
cdist(["Jon", "Jane"], ["John", "Janet"], scorer="jaro_winkler")  # 2x2 numpy array

Documentation

Full documentation at docs.byteveda.org/reclink, including:

Performance

Pairwise comparison (10 string pairs, 500 iterations, microseconds per pair):

Metric reclink rapidfuzz jellyfish vs rapidfuzz vs jellyfish
levenshtein 0.55 0.18 1.28 3.0x slower 2.3x faster
jaro 0.31 0.20 0.68 1.6x slower 2.2x faster
jaro_winkler 0.31 0.20 0.68 1.5x slower 2.2x faster
damerau_levenshtein 0.93 0.24 2.41 3.9x slower 2.6x faster

Batch matching (1,000 candidates, 50 iterations, microseconds per candidate):

Operation reclink rapidfuzz thefuzz vs rapidfuzz vs thefuzz
match_batch (jaro_winkler) 0.32 0.13 1.60 2.4x slower 5.0x faster

Reproduce with python benchmarks/compare.py (requires pip install rapidfuzz jellyfish thefuzz).

Development

# Setup
uv sync --extra dev
uv run pre-commit install
maturin develop --release

# Rust
cargo test --workspace
cargo clippy -- -D warnings
cargo fmt --check

# Python
uv run pytest tests/python/ -v
uv run ruff check py_src/ tests/
uv run ruff format --check py_src/ tests/
uv run mypy py_src/reclink/

License

Apache-2.0

Project links

Data verified by PyPI on Mar 24, 2026
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Avatar for pratyush618 from gravatar.com pratyush618

Credits

Author: ByteVeda

GitHub Statistics

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License expression

Apache-2.0
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Requires

Python >=3.12

Provides Extra

dev pandas polars

Tags

fuzzy-matching record-linkage string-similarity deduplication entity-resolution

Classifiers

Metadata

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Data verified by PyPI on Mar 24, 2026
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  • Released:
Latest release

1 maintainer

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Avatar for pratyush618 from gravatar.com pratyush618

Credits

Author: ByteVeda

GitHub Statistics

Data verified by PyPI on Mar 24, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

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Data verified by PyPI on Mar 24, 2026
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Apache-2.0
View SPDX License List

Requires

Python >=3.12

Provides Extra

dev pandas polars

Tags

fuzzy-matching record-linkage string-similarity deduplication entity-resolution

Classifiers

Release files for reclink 0.1.1

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reclink-0.1.1-cp312-cp312-manylinux_2_28_x86_64.whl 2.0 MB With provenance CPython 3.12 CPython 3.12 Linux glibc 2.28+ x86-64 Details
reclink-0.1.1-cp312-cp312-manylinux_2_28_aarch64.whl 2.0 MB With provenance CPython 3.12 CPython 3.12 Linux glibc 2.28+ ARM64 Details
reclink-0.1.1-cp312-cp312-macosx_11_0_arm64.whl 1.8 MB With provenance CPython 3.12 CPython 3.12 macOS 11.0+ ARM64 Details
reclink-0.1.1-cp312-cp312-macosx_10_12_x86_64.whl 1.9 MB With provenance CPython 3.12 CPython 3.12 macOS 10.12+ x86-64 Details

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