{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis"}],"enrichment":{"capability":"cfgrib maps GRIB meteorological data files to the NetCDF Common Data Model following CF Conventions, exposing them as labeled multi-dimensional datasets via an engine interface.","skillfed_tags":["meteorological-data","grib-format"],"use_cases":["Decode ERA5 or other GRIB-formatted weather reanalysis data for climate analysis.","Merge multiple GRIB files into a single dataset for batch processing.","Process larger-than-memory meteorological datasets with distributed computation.","Convert GRIB files to NetCDF format via the command-line utility.","Read custom GRIB keys and translate coordinates to domain-specific naming conventions."],"what_it_does":"cfgrib is a Python interface that translates GRIB meteorological data files into datasets following the NetCDF Common Data Model and CF Conventions. It wraps the ECMWF ecCodes library to decode GRIB 1 and 2 files and expose their contents as labeled, multi-dimensional arrays with coordinates and attributes. The package reads data lazily and efficiently, supporting both memory-constrained and larger-than-memory workflows through integration with dask. It also provides low-level access to arbitrary GRIB keys via backend options, coordinate translation to custom data models, and a command-line utility for converting GRIB to NetCDF.\n\nDevelopment status is Beta for reading; writing support is Alpha/Broken. The main constraint is that eccodes (a compiled C library) must be installed separately on your system. The package depends on attrs, click, eccodes, and numpy.","worth_installing":"Yes. cfgrib is actively maintained, has no known vulnerabilities, and solves a specific problem: reading GRIB meteorological files. Install friction is low (pure Python wheel), and the Apache License Version 2.0 is permissive. The main prerequisite\u2014eccodes binary library\u2014is well-documented and available via conda-forge. Suitable for weather data analysis, climate research, and meteorological data pipelines."},"id":"cfgrib","links":{"html":"https://skillfed.io/packages/cfgrib","md":"https://skillfed.io/packages/cfgrib.md","pypi":"https://pypi.org/project/cfgrib/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-09-30","license_spdx":null,"license_treatment":"permissive","name":"cfgrib","python_support":"supports_current","summary":"Python interface to map GRIB files to the NetCDF Common Data Model following the CF Convention using ecCodes."},"popularity":{"monthly_downloads":929155,"position":4706,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.9.15.1"}