{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/3"},{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic/2"},{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"}],"enrichment":{"capability":"Computes Damerau-Levenshtein edit distance between sequences using Cython for high performance, supporting strings, lists, tuples, and other sequence types with optional distance thresholds.","skillfed_tags":["string-matching","sequence-alignment","bioinformatics"],"use_cases":["Spell-checking and typo correction by computing distance between user input and dictionary words.","Fuzzy string matching in data deduplication and record linkage tasks.","DNA/protein sequence alignment in bioinformatics applications.","Search result ranking by scoring query similarity to indexed documents.","Duplicate detection in user-generated content or database records.","Phonetic matching and name variation handling in identity resolution."],"what_it_does":"pyxDamerauLevenshtein is a Cython-accelerated implementation of the Damerau-Levenshtein edit distance algorithm, which measures the minimum number of single-character edits (insertions, deletions, substitutions, or transpositions of adjacent characters) needed to transform one sequence into another. It runs in O(N*M) time using O(M) space and supports any sequence type including strings, lists, tuples, and ranges, with full Unicode support.\n\nThe package provides four main functions: raw edit distance between two sequences, normalized distance (ratio scaled to 0.0\u20131.0), and batch versions that compute distances against multiple sequences at once. All functions accept an optional max_distance threshold that short-circuits computation when the true distance exceeds it, avoiding unnecessary work. It is significantly faster than pure Python implementations and comparable to or faster than other C-based alternatives like jellyfish.","worth_installing":"Yes. The package is actively maintained, has no known vulnerabilities, uses a permissive BSD license, and provides a well-optimized implementation of a standard algorithm with broad applicability. Install friction is low due to prebuilt wheels. Suitable for production use in spell-checking, fuzzy matching, bioinformatics, and data deduplication workflows."},"id":"pyxdameraulevenshtein","links":{"html":"https://skillfed.io/packages/pyxdameraulevenshtein","md":"https://skillfed.io/packages/pyxdameraulevenshtein.md","pypi":"https://pypi.org/project/pyxdameraulevenshtein/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-18","license_spdx":null,"license_treatment":"permissive","name":"pyxDamerauLevenshtein","python_support":"supports_current","summary":"pyxDamerauLevenshtein implements the Damerau-Levenshtein (DL) edit distance algorithm for Python in Cython for high performance."},"popularity":{"monthly_downloads":153457,"position":10881,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.10.0"}