{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/9"},{"label":"Atmospheric Science","url":"https://skillfed.io/packages/category/scientific-engineering-atmospheric-science"}],"enrichment":{"capability":"cf-units provides units of measure as defined by the Climate and Forecast (CF) Metadata Conventions, enabling standardized unit handling for scientific data in atmospheric science, oceanography, and climate research.","skillfed_tags":["climate-data","earth-science","metadata-standards"],"use_cases":["Validate and standardize units in NetCDF climate datasets to ensure CF metadata compliance.","Convert between equivalent unit representations in atmospheric and oceanographic data pipelines.","Build data processing workflows that require consistent unit handling across multiple earth science sources.","Integrate CF-compliant unit metadata into scientific data analysis and visualization tools."],"what_it_does":"cf-units is a Python library that implements units of measure as specified by the Climate and Forecast Metadata Conventions, a standard used across earth science data formats like NetCDF. It depends on numpy for array operations, cftime for time-related units, and jinja2 for template rendering. The package is designed for scientists and researchers working with atmospheric, oceanographic, and climate data who need to ensure their measurements conform to CF standards.\n\nThe library handles unit representation, validation, and operations within the CF framework. It is actively maintained, supports Python 3.11\u20133.14, and provides pre-built wheels for common platforms (macOS, Linux, Windows), reducing installation complexity for most users. With no known security vulnerabilities and a permissive BSD-3-Clause license, it is suitable for both academic and commercial projects.","worth_installing":"Yes. cf-units is production-stable, actively maintained, has no known vulnerabilities, and carries a permissive license. Install friction is moderate but manageable via pre-built wheels. Install it if you work with CF-compliant earth science data (climate, oceanography, meteorology) and need standardized unit handling; otherwise it is not necessary."},"id":"cf-units","links":{"html":"https://skillfed.io/packages/cf-units","md":"https://skillfed.io/packages/cf-units.md","pypi":"https://pypi.org/project/cf-units/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-01-16","license_spdx":"BSD-3-Clause","license_treatment":"permissive","name":"cf-units","python_support":"supports_current","summary":"Units of measure as required by the Climate and Forecast (CF) metadata conventions"},"popularity":{"monthly_downloads":75415,"position":14718,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"3.3.1"}