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recognizers-text-number-with-unit

recognizers-text-number-with-unit README

With conditionsPyPI Artificial IntelligenceReleased Nov 201999.7K downloads / moMITPure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — recognizers_text_number_with_unit-1.0.2a2-py3-none-any.whl
v1.0.2a2 · released 2019-11-12 · 3 runtime deps: recognizers-text, recognizers-text-number, regex

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.AI-flagged interpretation of the facts on this page — verify before relying

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 · maintenance · safety

MIT (permissive) — MIT license permits unrestricted use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.

last release 2019-11-12 (2467 days) · last repo commit 2026-04-17 · 1,793 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 99,743 downloads/mo, #13,012 on PyPI

Verify before relying

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")
  • 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
Same gist for agents: .md · .json

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 on this page. Verify before relying on it.

With conditions

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

recognizers-text-number-with-unit on PyPI

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

LicenseMIT permissive
Python supportNot specified
Install frictionLow. Pure-Python wheel
Runtime dependencies
3 packages
recognizers-textrecognizers-text-numberregex
MaintenanceActively maintained 2,467 days since the last release
Last repo commit
First released
Downloads99,743 / month, #13,012 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 3 - AlphaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.6Topic :: Scientific/Engineering :: Artificial Intelligence

Evidence: recognizers_text_number_with_unit-1.0.2a2-py3-none-any.whl

Tags

Capabilities
number unit extractioncurrency recognitiontemperature parsingmultilingual entity recognitiondimension unit extractionnlp entity extraction
Topics
entity-extractionmultilingual-nlpunit-parsing
PyPI keywords
nlpnlp-entity-extractionentity-extractionparser-library

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See also quantulum3 · recognizers-text · recognizers-text-number · recognizers-text-choice · recognizers-text-date-time · num2words · number-parser · presidio-analyzer · date-spacy · cn2an