{"categories":[{"label":"Human Machine Interfaces","url":"https://skillfed.io/packages/category/scientific-engineering-human-machine-interfaces"}],"enrichment":{"capability":"Computes distance and similarity between text sequences using 30+ algorithms including Levenshtein, Jaro-Winkler, Hamming, and compression-based methods.","skillfed_tags":["string-similarity","sequence-alignment","fuzzy-matching"],"use_cases":["Fuzzy string matching to find similar product names or user entries despite typos or variations","Deduplication of text records by computing similarity scores between candidates","Spell-checking or autocorrect by ranking candidate corrections by edit distance","Record linkage in data integration by comparing field values across datasets","Phonetic matching for names that sound similar but are spelled differently"],"what_it_does":"TextDistance is a pure-Python library that implements a large collection of algorithms for measuring how different two or more text sequences are from each other. It provides both distance metrics (how far apart sequences are) and similarity metrics (how alike they are), with support for edit-based algorithms like Levenshtein and Damerau-Levenshtein, token-based methods like Jaccard and Cosine similarity, sequence-based approaches like longest common subsequence, compression-based distance, and phonetic matching. The library has zero runtime dependencies by default and offers optional numpy integration for speed on specific algorithms.\n\nYou use it by instantiating an algorithm class or calling a function directly, then invoking methods like `.distance()`, `.similarity()`, or `.normalized_distance()` to compare sequences. It's designed for straightforward use cases where you need to measure text similarity\u2014fuzzy matching, deduplication, spell-checking support, or record linkage\u2014without needing to implement these algorithms yourself.","worth_installing":"Yes. The package is stable, permissively licensed, has no dependencies, and provides a comprehensive toolkit for a common task. The aging maintenance status (last release 759 days ago) is a minor concern but not a blocker\u2014the library solves a well-defined problem with established algorithms, and the repository remains active and not archived. Install it if you need string distance or similarity computation."},"id":"textdistance","links":{"html":"https://skillfed.io/packages/textdistance","md":"https://skillfed.io/packages/textdistance.md","pypi":"https://pypi.org/project/textdistance/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2024-07-16","license_spdx":null,"license_treatment":"permissive","name":"textdistance","python_support":"supports_current","summary":"Compute distance between the two texts."},"popularity":{"monthly_downloads":2580088,"position":2991,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"4.6.3"}