cfgrib
Python interface to map GRIB files to the NetCDF Common Data Model following the CF Convention using ecCodes.
Decision gist · record as of 2026-08-14
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—eccodes binary library—is well-documented and available via conda-forge. Suitable for weather data analysis, climate research, and meteorological data pipelines.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- The eccodes binary library must be installed on your system; cfgrib is a Python wrapper around it.
- Run `python -m cfgrib selfcheck` to verify your setup.
- Low friction: pure Python wheel with four runtime dependencies (attrs, click, eccodes, numpy).
License · maintenance · safety
Apache License Version 2.0 (permissive) — Apache License Version 2.0 (permissive): you may use, modify, and distribute cfgrib freely in commercial and private projects, provided you include a copy of the license and do not hold the authors liable.
last release 2025-09-30 (318 days) · last repo commit 2026-07-08 · 459 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 929,155 downloads/mo, #4,706 on PyPI
Alternatives
Verify before relying
pip install cfgrib
import cfgrib
ds = cfgrib.open_dataset('file.grib')
print(ds)- Whether coordinate system and gridType handling limitations affect your specific GRIB files.
- Performance characteristics for larger-than-memory datasets in your deployment environment.
- Completeness of GRIB 1 and 2 support for heterogeneous files beyond the documented Beta status.
- Compatibility with the engine interface for integration with external data tools.
What it is and 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.
Development 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.
Use it for
- 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.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
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—eccodes binary library—is well-documented and available via conda-forge. Suitable for weather data analysis, climate research, and meteorological data pipelines.
Install
cfgrib on PyPI
Before you install
Low friction: pure Python wheel with four runtime dependencies (attrs, click, eccodes, numpy). Actively maintained with recent commits and no known vulnerabilities. Requires eccodes binary library installed separately; the package provides a selfcheck command to verify system setup.
The eccodes binary library must be installed on your system; cfgrib is a Python wrapper around it. Run `python -m cfgrib selfcheck` to verify your setup.
License in practice
Apache License Version 2.0 (permissive): you may use, modify, and distribute cfgrib freely in commercial and private projects, provided you include a copy of the license and do not hold the authors liable.
Quickstart
pip install cfgrib
import cfgrib
ds = cfgrib.open_dataset('file.grib')
print(ds)Verify before relying
- Whether coordinate system and gridType handling limitations affect your specific GRIB files.
- Performance characteristics for larger-than-memory datasets in your deployment environment.
- Completeness of GRIB 1 and 2 support for heterogeneous files beyond the documented Beta status.
- Compatibility with the engine interface for integration with external data tools.
Package facts
| License | Apache License Version 2.0 permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesattrsclickeccodesnumpy |
| Maintenance | Actively maintained 318 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 929,155 / month, #4,706 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPy |
Evidence: cfgrib-0.9.15.1-py3-none-any.whl
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See also eccodes · eccodeslib · pdbufr · pygrib · earthkit-data · netCDF4 · liac-arff · herbie-data · cf-xarray · h5netcdf