{"categories":[{"label":"Text Processing","url":"https://skillfed.io/packages/category/text-processing/3"}],"enrichment":{"capability":"Generates simplified entity identifiers (fingerprints) from names and addresses for matching entities across different datasets, with built-in recognition of company legal forms.","skillfed_tags":["entity-matching","data-deduplication","unmaintained"],"use_cases":["Deduplicating entity records in compliance or sanctions databases by generating fingerprints for matching.","Normalizing company names across multiple data sources to identify the same legal entity.","Extracting and standardizing company legal forms from unstructured text for entity classification.","Building entity resolution pipelines where fingerprints serve as a first-pass matching key.","Preprocessing name data for downstream clustering or similarity matching algorithms."],"what_it_does":"Fingerprints is a library for generating normalized entity identifiers from names and addresses, designed to help match the same entity across different data sources. It takes messy input like 'Mr. Sherlock Holmes' or 'Siemens Aktiengesellschaft' and produces a canonical simplified form ('holmes sherlock', 'ag siemens') suitable for deduplication and cross-referencing. The library includes a database of company legal forms drawn from OCCRP, ISO 20275, and other sources, allowing it to recognize and standardize abbreviations like 'AG' for Aktiengesellschaft or '\u041e\u041e\u041e' for Russian limited liability companies.\n\nThe package depends on normality for text processing and installs as a pure Python wheel with low friction. However, as of May 2025, fingerprints is unmaintained\u2014the codebase has been superseded by rigour, which incorporates the next generation of this functionality. The repository remains available and the latest release is from August 2025, but no further development is planned.","worth_installing":"Yes, but with conditions. Install if you need entity fingerprinting now and can tolerate an unmaintained library; the code is stable and has no known vulnerabilities. However, for new projects, evaluate rigour first\u2014it is the maintained successor and likely has improvements. The low install friction and permissive MIT license make this a low-risk addition, but plan a migration path if long-term support matters."},"id":"fingerprints","links":{"html":"https://skillfed.io/packages/fingerprints","md":"https://skillfed.io/packages/fingerprints.md","pypi":"https://pypi.org/project/fingerprints/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-08-01","license_spdx":null,"license_treatment":"permissive","name":"fingerprints","python_support":"supports_current","summary":"A library to generate entity fingerprints."},"popularity":{"monthly_downloads":227342,"position":9182,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.3.1"}