{"categories":[{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic"}],"enrichment":{"capability":"Converts numbers written in natural language (e.g., \"twenty three\") to their numeric equivalents, supporting cardinal numbers in English, Hindi, Spanish, Ukrainian, and Russian, plus English ordinals and fractions.","skillfed_tags":["nlp","multilingual","text-parsing"],"use_cases":["Extract and normalize written numbers from unstructured text or user input in multilingual documents.","Convert ordinal text (\"first\", \"second\", \"twenty third\") to integers for ranking or ordering tasks.","Parse fractional expressions written in words for mathematical or scientific data processing.","Preprocess text data for NLP or machine learning pipelines that require numeric normalization.","Build chatbots or voice assistants that accept spoken/written numbers and need to convert them to machine-readable form."],"what_it_does":"number-parser is a text-to-number converter that identifies and transforms written numbers in natural language into their numeric equivalents. It handles cardinal numbers (\"twenty three\" \u2192 23), ordinal numbers (\"twenty third\" \u2192 23), and fractions (\"one over two\" \u2192 \"1/2\") in English, and cardinal numbers in Hindi, Spanish, Ukrainian, and Russian. The library provides three main functions: parse() to convert numbers in-place within a text string, parse_number() to convert a single written number, and parse_ordinal() and parse_fraction() for specialized cases.\n\nThe package depends only on attrs and installs as a pure Python wheel with low friction. It is marked Production/Stable and supports Python 3.7 through 3.11. Maintenance is dormant (no releases since March 2023), though the repository remains active. The library handles ambiguous cases and language-specific nuances, making it suitable for data extraction, form processing, and NLP pipelines where written numbers must be normalized to numeric form.","worth_installing":"Yes\u2014if you need to parse written numbers in English, Hindi, Spanish, Ukrainian, or Russian. The library is stable, has no security vulnerabilities, and installs with minimal friction. Dormant maintenance is a minor concern for long-term support, but the code is straightforward and unlikely to break with Python updates. Not worth installing if you only need English and have simpler regex-based solutions in place, or if you need ordinal/fraction support in languages other than English."},"id":"number-parser","links":{"html":"https://skillfed.io/packages/number-parser","md":"https://skillfed.io/packages/number-parser.md","pypi":"https://pypi.org/project/number-parser/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2023-03-28","license_spdx":null,"license_treatment":"permissive","name":"number-parser","python_support":"unspecified","summary":"parse numbers written in natural language"},"popularity":{"monthly_downloads":680804,"position":5365,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.3.2"}