--- id: recognizers-text-number-with-unit version: "1.0.2a2" license: MIT license_treatment: permissive maintenance: active --- # recognizers-text-number-with-unit — recognizers-text-number-with-unit README License: permissive · Maintenance: active · Downloads: 99.7K/mo ## What it is and what it does This package extracts and normalizes numbers paired with units from natural language text. It handles quantities expressed in words by identifying the numeric value and its associated unit, then resolving both to a canonical form. The package is part of Microsoft's Recognizers-Text ecosystem and powers entity recognition in LUIS, Power Virtual Agents, and the Bot Framework. The module depends on recognizers-text and recognizers-text-number as its core runtime dependencies, plus regex for pattern matching. It supports full recognition in Chinese, English, French, Spanish, Portuguese, German, Italian, Turkish, Hindi, and Dutch, with partial support for Japanese, Korean, Arabic, and Swedish. The package is distributed as a pure-Python wheel with low installation friction. Use it for: - Extract currency amounts and units from financial documents or user input for chatbots and virtual assistants - Parse measurement specifications in product descriptions or technical documentation across multiple languages - Normalize age and other personal metrics from user-provided text in healthcare or fitness applications - Identify temperature readings and unit conversions in weather data or IoT sensor logs - Build multilingual NLP pipelines that need to recognize and standardize numeric quantities with units ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. Recognizes and extracts numbers with units (age, currency, dimensions, temperature) from text in multiple languages, resolving them to standardized values. Yes, with conditions. The package is permissively licensed, has low install friction, and addresses a real need for multilingual unit extraction. However, it is in alpha status with no releases since November 2019—verify that the recognition accuracy and language coverage meet your use case before committing to production. The active repository and 1793 stars suggest ongoing community interest, but the stale release cycle warrants caution. ## Install pip install recognizers-text-number-with-unit uv add recognizers-text-number-with-unit poetry add recognizers-text-number-with-unit ## Installing recognizers-text-number-with-unit Before you install: Low install friction with a pure-Python wheel. Actively maintained as of April 2026 with 1793 repository stars. However, the package is in alpha status (version 1.0.2a2) and has not received a release since November 2019, which may indicate limited recent development on this specific module. License in practice: MIT license permits unrestricted use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects. Quickstart: pip install recognizers-text-number-with-unit from recognizers_text_number_with_unit import recognize_number_with_unit results = recognize_number_with_unit("I am 25 years old", "en-us") Verify before relying: - Current stability and active maintenance status of the Python implementation, given the alpha version and 2019 release date - Whether partial language support (Japanese, Korean, Arabic, Swedish) is available in this specific module - Performance characteristics and accuracy benchmarks for unit recognition across supported languages - Specific numeric examples and edge cases handled by the recognizer ## Package facts - License: MIT (permissive) - Python support: unspecified - Install friction: low - Maintenance: active - Downloads: 99.7K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags number unit extraction, currency recognition, temperature parsing, multilingual entity recognition, dimension unit extraction, nlp entity extraction, entity-extraction, multilingual-nlp, unit-parsing [View on SkillFed](https://skillfed.io/packages/recognizers-text-number-with-unit) · [View on PyPI](https://pypi.org/project/recognizers-text-number-with-unit/)