{"categories":[{"label":"Text Processing","url":"https://skillfed.io/packages/category/text-processing/3"}],"enrichment":{"capability":"Rigour provides data cleaning and validation functions for business-world text: human and company names, language and territory codes, corporate identifiers, and addresses, with production-ready handling of edge cases.","skillfed_tags":["data-validation","business-intelligence","compliance"],"use_cases":["Normalize and validate company and individual names in financial crime compliance systems or sanctions screening workflows.","Standardize country, language, and territory codes in international business data pipelines.","Format addresses according to local customs for a given country in mail or document generation systems.","Validate corporate and tax identifiers (e.g., VAT numbers, registration IDs) in accounting or regulatory reporting systems.","Clean and deduplicate business entity records from multiple sources with varying name formats and conventions."],"what_it_does":"Rigour is a data validation and normalization library designed for the financial crime and business intelligence domain. It consolidates production-tested implementations for handling human names, company names, language codes, country and territory identifiers, corporate and tax identifiers, and address formatting. The package addresses the gap between simple text handling and the complex edge cases that emerge in production systems\u2014handling name variations, corporate entity formats, multilingual inputs, and standardized codes across jurisdictions.\n\nThe library depends on pyyaml, normality, prefixdate, orjson, python-stdnum, and jinja2 to provide its validation and normalization capabilities. It's actively maintained, supports Python 3.10 through 3.14, and includes pre-compiled wheels for macOS, Linux, and Windows architectures. The package is part of the OpenSanctions ecosystem and consolidates several older libraries (languagecodes, pantomime, fingerprints) into a single codebase.","worth_installing":"Yes. Rigour is actively maintained, has no known vulnerabilities, supports current Python versions, and provides production-tested implementations for a specific but important domain (business data validation). The medium install friction is offset by comprehensive platform coverage and the consolidation of multiple specialized libraries into one package. Install if you work with business entity data, compliance systems, or international business records."},"id":"rigour","links":{"html":"https://skillfed.io/packages/rigour","md":"https://skillfed.io/packages/rigour.md","pypi":"https://pypi.org/project/rigour/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-30","license_spdx":null,"license_treatment":"permissive","name":"rigour","python_support":"supports_current","summary":"Financial crime domain data validation and normalization library."},"popularity":{"monthly_downloads":135009,"position":11455,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.3.1"}