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cfgrib
Python interface to map GRIB files to the NetCDF Common Data Model following the CF Convention using ecCodes.
- 0.9.14.1
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cfgrib: A Python interface to map GRIB files to the NetCDF Common Data Model following the CF Convention using ecCodes
.. image:: https://img.shields.io/pypi/v/cfgrib.svg :target: https://pypi.python.org/pypi/cfgrib/
Python interface to map GRIB files to the
Unidata's Common Data Model v4 <https://docs.unidata.ucar.edu/netcdf-java/current/userguide/common_data_model_overview.html>_
following the CF Conventions <http://cfconventions.org/>.
The high level API is designed to support a GRIB engine for xarray <http://xarray.pydata.org/>
and it is inspired by netCDF4-python <http://unidata.github.io/netcdf4-python/>_
and h5netcdf <https://github.com/shoyer/h5netcdf>.
Low level access and decoding is performed via the
ECMWF ecCodes library <https://confluence.ecmwf.int/display/ECC/> and
the eccodes python package <https://pypi.org/project/eccodes>_.
Features with development status Beta:
- enables the
engine='cfgrib'option to read GRIB files with xarray, - reads most GRIB 1 and 2 files including heterogeneous ones with
cfgrib.open_datasets, - supports all modern versions of Python 3.9, 3.8, 3.7 and PyPy3,
- the 0.9.6.x series with support for Python 2 will stay active and receive critical bugfixes,
- works wherever eccodes-python does: Linux, MacOS and Windows
- conda-forge package on all supported platforms,
- reads the data lazily and efficiently in terms of both memory usage and disk access,
- allows larger-than-memory and distributed processing via xarray and dask,
- supports translating coordinates to different data models and naming conventions,
- supports writing the index of a GRIB file to disk, to save a full-file scan on open,
- accepts objects implementing a generic Fieldset interface as described in
ADVANCED_USAGE.rst.
Work in progress:
- Beta install a
cfgributility that can convert a GRIB fileto_netcdfwith a optional conversion to a specific coordinates data model, see#40 <https://github.com/ecmwf/cfgrib/issues/40>_. - Alpha/Broken support writing carefully-crafted
xarray.Dataset's to a GRIB1 or GRIB2 file, see the Advanced write usage section below,#18 <https://github.com/ecmwf/cfgrib/issues/18>_ and#156 <https://github.com/ecmwf/cfgrib/issues/156>_.
Limitations:
- relies on ecCodes for the CF attributes of the data variables,
- relies on ecCodes for anything related to coordinate systems /
gridType, see#28 <https://github.com/ecmwf/cfgrib/issues/28>_.
Installation
The easiest way to install cfgrib and all its binary dependencies is via Conda <https://conda.io/>_::
$ conda install -c conda-forge cfgrib
alternatively, if you install the binary dependencies yourself, you can install the Python package from PyPI with::
$ pip install cfgrib
Binary dependencies
cfgrib depends on the eccodes python package <https://pypi.org/project/eccodes>_
to access the ECMWF ecCodes binary library,
when not using conda please follow the System dependencies section there.
You may run a simple selfcheck command to ensure that your system is set up correctly::
$ python -m cfgrib selfcheck
Found: ecCodes v2.20.0.
Your system is ready.
Usage
First, you need a well-formed GRIB file, if you don't have one at hand you can download our
ERA5 on pressure levels sample <https://get.ecmwf.int/repository/test-data/cfgrib/era5-levels-members.grib>_::
$ wget https://get.ecmwf.int/repository/test-data/cfgrib/era5-levels-members.grib
Read-only xarray GRIB engine
Most of cfgrib users want to open a GRIB file as a xarray.Dataset and
need to have xarray installed::
$ pip install xarray
In a Python interpreter try:
.. code-block:: python
>>> import xarray as xr
>>> ds = xr.open_dataset('era5-levels-members.grib', engine='cfgrib')
>>> ds
<xarray.Dataset>
Dimensions: (number: 10, time: 4, isobaricInhPa: 2, latitude: 61,
longitude: 120)
Coordinates:
* number (number) int64 0 1 2 3 4 5 6 7 8 9
* time (time) datetime64[ns] 2017-01-01 ... 2017-01-02T12:00:00
step timedelta64[ns] ...
* isobaricInhPa (isobaricInhPa) float64 850.0 500.0
* latitude (latitude) float64 90.0 87.0 84.0 81.0 ... -84.0 -87.0 -90.0
* longitude (longitude) float64 0.0 3.0 6.0 9.0 ... 351.0 354.0 357.0
valid_time (time) datetime64[ns] ...
Data variables:
z (number, time, isobaricInhPa, latitude, longitude) float32 ...
t (number, time, isobaricInhPa, latitude, longitude) float32 ...
Attributes:
GRIB_edition: 1
GRIB_centre: ecmf
GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts
GRIB_subCentre: 0
Conventions: CF-1.7
institution: European Centre for Medium-Range Weather Forecasts
history: ...
The cfgrib engine supports all read-only features of xarray like:
- merge the content of several GRIB files into a single dataset using
xarray.open_mfdataset, - work with larger-than-memory datasets with
dask <https://dask.org/>_, - allow distributed processing with
dask.distributed <http://distributed.dask.org>_.
Read arbitrary GRIB keys
By default cfgrib reads a limited set of ecCodes recognised keys from the GRIB files
and exposes them as Dataset or DataArray attributes with the GRIB_ prefix.
It is possible to have cfgrib read additional keys to the attributes by adding the
read_keys dictionary key to the backend_kwargs with values the list of desired GRIB keys:
.. code-block:: python
>>> ds = xr.open_dataset('era5-levels-members.grib', engine='cfgrib',
... backend_kwargs={'read_keys': ['experimentVersionNumber']})
>>> ds.t.attrs['GRIB_experimentVersionNumber']
'0001'
Translate to a custom data model
Contrary to netCDF the GRIB data format is not self-describing and several details of the mapping
to the Unidata Common Data Model are arbitrarily set by the software components decoding the format.
Details like names and units of the coordinates are particularly important because
xarray broadcast and selection rules depend on them.
cf2cfm is a small coordinate translation module distributed with cfgrib that make it easy to
translate CF compliant coordinates, like the one provided by cfgrib, to a user-defined
custom data model with set out_name, units and stored_direction.
For example to translate a cfgrib styled xr.Dataset to the classic ECMWF coordinate
naming conventions you can:
.. code-block:: python
>>> import cf2cdm
>>> ds = xr.open_dataset('era5-levels-members.grib', engine='cfgrib')
>>> cf2cdm.translate_coords(ds, cf2cdm.ECMWF)
<xarray.Dataset>
Dimensions: (number: 10, time: 4, level: 2, latitude: 61, longitude: 120)
Coordinates:
* number (number) int64 0 1 2 3 4 5 6 7 8 9
* time (time) datetime64[ns] 2017-01-01 ... 2017-01-02T12:00:00
step timedelta64[ns] ...
* level (level) float64 850.0 500.0
* latitude (latitude) float64 90.0 87.0 84.0 81.0 ... -84.0 -87.0 -90.0
* longitude (longitude) float64 0.0 3.0 6.0 9.0 ... 348.0 351.0 354.0 357.0
valid_time (time) datetime64[ns] ...
Data variables:
z (number, time, level, latitude, longitude) float32 ...
t (number, time, level, latitude, longitude) float32 ...
Attributes:
GRIB_edition: 1
GRIB_centre: ecmf
GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts
GRIB_subCentre: 0
Conventions: CF-1.7
institution: European Centre for Medium-Range Weather Forecasts
history: ...
To translate to the Common Data Model of the Climate Data Store use:
.. code-block:: python
>>> import cf2cdm
>>> cf2cdm.translate_coords(ds, cf2cdm.CDS)
<xarray.Dataset>
Dimensions: (realization: 10, forecast_reference_time: 4,
plev: 2, lat: 61, lon: 120)
Coordinates:
* realization (realization) int64 0 1 2 3 4 5 6 7 8 9
* forecast_reference_time (forecast_reference_time) datetime64[ns] 2017-01...
leadtime timedelta64[ns] ...
* plev (plev) float64 8.5e+04 5e+04
* lat (lat) float64 -90.0 -87.0 -84.0 ... 84.0 87.0 90.0
* lon (lon) float64 0.0 3.0 6.0 9.0 ... 351.0 354.0 357.0
time (forecast_reference_time) datetime64[ns] ...
Data variables:
z (realization, forecast_reference_time, plev, lat, lon) float32 ...
t (realization, forecast_reference_time, plev, lat, lon) float32 ...
Attributes:
GRIB_edition: 1
GRIB_centre: ecmf
GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts
GRIB_subCentre: 0
Conventions: CF-1.7
institution: European Centre for Medium-Range Weather Forecasts
history: ...
Filter heterogeneous GRIB files
xr.open_dataset can open a GRIB file only if all the messages
with the same shortName can be represented as a single hypercube.
For example, a variable t cannot have both isobaricInhPa and hybrid typeOfLevel's,
as this would result in multiple hypercubes for the same variable.
Opening a non-conformant GRIB file will fail with a ValueError: multiple values for unique key...
error message, see #2 <https://github.com/ecmwf/cfgrib/issues/2>_.
Furthermore if different variables depend on the same coordinate, for example step,
the values of the coordinate must match exactly.
For example, if variables t and z share the same step coordinate,
they must both have exactly the same set of steps.
Opening a non-conformant GRIB file will fail with a ValueError: key present and new value is different...
error message, see #13 <https://github.com/ecmwf/cfgrib/issues/13>_.
In most cases you can handle complex GRIB files containing heterogeneous messages by passing
the filter_by_keys key in backend_kwargs to select which GRIB messages belong to a
well formed set of hypercubes.
For example to open
US National Weather Service complex GRIB2 files <http://ftpprd.ncep.noaa.gov/data/nccf/com/nam/prod/>_
you can use:
.. code-block:: python
>>> xr.open_dataset('nam.t00z.awp21100.tm00.grib2', engine='cfgrib',
... backend_kwargs={'filter_by_keys': {'typeOfLevel': 'surface'}})
<xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] ...
step timedelta64[ns] ...
surface float64 ...
latitude (y, x) float64 ...
longitude (y, x) float64 ...
valid_time datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
gust (y, x) float32 ...
sp (y, x) float32 ...
orog (y, x) float32 ...
tp (y, x) float32 ...
acpcp (y, x) float32 ...
csnow (y, x) float32 ...
cicep (y, x) float32 ...
cfrzr (y, x) float32 ...
crain (y, x) float32 ...
cape (y, x) float32 ...
cin (y, x) float32 ...
unknown (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP...
history: ...
>>> xr.open_dataset('nam.t00z.awp21100.tm00.grib2', engine='cfgrib',
... backend_kwargs={'filter_by_keys': {'typeOfLevel': 'heightAboveGround', 'level': 2}})
<xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] ...
step timedelta64[ns] ...
heightAboveGround float64 ...
latitude (y, x) float64 ...
longitude (y, x) float64 ...
valid_time datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
t2m (y, x) float32 ...
r2 (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP...
history: ...
Automatic filtering
cfgrib also provides a function that automates the selection of appropriate filter_by_keys
and returns a list of all valid xarray.Dataset's in the GRIB file.
.. code-block:: python
>>> import cfgrib
>>> cfgrib.open_datasets('nam.t00z.awp21100.tm00.grib2')
[<xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
atmosphereSingleLayer float64 0.0
latitude (y, x) float64 ...
longitude (y, x) float64 ...
valid_time datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
pwat (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
cloudBase float64 0.0
latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
pres (y, x) float32 ...
gh (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
cloudTop float64 0.0
latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
pres (y, x) float32 ...
t (y, x) float32 ...
gh (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
heightAboveGround float64 10.0
latitude (y, x) float64 ...
longitude (y, x) float64 ...
valid_time datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
u10 (y, x) float32 ...
v10 (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
heightAboveGround float64 2.0
latitude (y, x) float64 12.19 12.39 12.58 ... 57.68 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 ... 308.5 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
t2m (y, x) float32 ...
r2 (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (heightAboveGroundLayer: 2, y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
* heightAboveGroundLayer (heightAboveGroundLayer) float64 1e+03 3e+03
latitude (y, x) float64 ...
longitude (y, x) float64 ...
valid_time datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
hlcy (heightAboveGroundLayer, y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (isobaricInhPa: 19, y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
* isobaricInhPa (isobaricInhPa) float64 1e+03 950.0 900.0 ... 150.0 100.0
latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
t (isobaricInhPa, y, x) float32 ...
u (isobaricInhPa, y, x) float32 ...
v (isobaricInhPa, y, x) float32 ...
w (isobaricInhPa, y, x) float32 ...
gh (isobaricInhPa, y, x) float32 ...
r (isobaricInhPa, y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (isobaricInhPa: 5, y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
* isobaricInhPa (isobaricInhPa) float64 1e+03 850.0 700.0 500.0 250.0
latitude (y, x) float64 ...
longitude (y, x) float64 ...
valid_time datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
absv (isobaricInhPa, y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
isothermZero float64 0.0
latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
gh (y, x) float32 ...
r (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
maxWind float64 0.0
latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
pres (y, x) float32 ...
u (y, x) float32 ...
v (y, x) float32 ...
gh (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
meanSea float64 0.0
latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
prmsl (y, x) float32 ...
mslet (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (pressureFromGroundLayer: 2, y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
* pressureFromGroundLayer (pressureFromGroundLayer) float64 9e+03 1.8e+04
latitude (y, x) float64 12.19 12.39 12.58 ... 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 ... 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
cape (pressureFromGroundLayer, y, x) float32 ...
cin (pressureFromGroundLayer, y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (pressureFromGroundLayer: 5, y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
* pressureFromGroundLayer (pressureFromGroundLayer) float64 3e+03 ... 1.5e+04
latitude (y, x) float64 12.19 12.39 12.58 ... 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 ... 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
t (pressureFromGroundLayer, y, x) float32 ...
u (pressureFromGroundLayer, y, x) float32 ...
v (pressureFromGroundLayer, y, x) float32 ...
r (pressureFromGroundLayer, y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
pressureFromGroundLayer float64 3e+03
latitude (y, x) float64 ...
longitude (y, x) float64 ...
valid_time datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
pli (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
pressureFromGroundLayer float64 1.8e+04
latitude (y, x) float64 ...
longitude (y, x) float64 ...
valid_time datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
4lftx (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
surface float64 0.0
latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
unknown (y, x) float32 ...
cape (y, x) float32 ...
sp (y, x) float32 ...
acpcp (y, x) float32 ...
cin (y, x) float32 ...
orog (y, x) float32 ...
tp (y, x) float32 ...
crain (y, x) float32 ...
cfrzr (y, x) float32 ...
cicep (y, x) float32 ...
csnow (y, x) float32 ...
gust (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP, <xarray.Dataset>
Dimensions: (y: 65, x: 93)
Coordinates:
time datetime64[ns] 2018-09-17
step timedelta64[ns] 00:00:00
tropopause float64 0.0
latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29
longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6
valid_time datetime64[ns] 2018-09-17
Dimensions without coordinates: y, x
Data variables:
t (y, x) float32 ...
u (y, x) float32 ...
v (y, x) float32 ...
trpp (y, x) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP...
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP]
Advanced usage
Write support
Please note that write support is Alpha.
Only xarray.Dataset's in canonical form,
that is, with the coordinates names matching exactly the cfgrib coordinates,
can be saved at the moment:
.. code-block:: python
>>> from cfgrib.xarray_to_grib import to_grib
>>> ds = xr.open_dataset('era5-levels-members.grib', engine='cfgrib').sel(number=0)
>>> ds
<xarray.Dataset>
Dimensions: (time: 4, isobaricInhPa: 2, latitude: 61, longitude: 120)
Coordinates:
number int64 0
* time (time) datetime64[ns] 2017-01-01 ... 2017-01-02T12:00:00
step timedelta64[ns] ...
* isobaricInhPa (isobaricInhPa) float64 850.0 500.0
* latitude (latitude) float64 90.0 87.0 84.0 81.0 ... -84.0 -87.0 -90.0
* longitude (longitude) float64 0.0 3.0 6.0 9.0 ... 351.0 354.0 357.0
valid_time (time) datetime64[ns] ...
Data variables:
z (time, isobaricInhPa, latitude, longitude) float32 ...
t (time, isobaricInhPa, latitude, longitude) float32 ...
Attributes:
GRIB_edition: 1
GRIB_centre: ecmf
GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts
GRIB_subCentre: 0
Conventions: CF-1.7
institution: European Centre for Medium-Range Weather Forecasts
history: ...
>>> to_grib(ds, 'out1.grib', grib_keys={'edition': 2})
>>> xr.open_dataset('out1.grib', engine='cfgrib')
<xarray.Dataset>
Dimensions: (time: 4, isobaricInhPa: 2, latitude: 61, longitude: 120)
Coordinates:
number ...
* time (time) datetime64[ns] 2017-01-01 ... 2017-01-02T12:00:00
step timedelta64[ns] ...
* isobaricInhPa (isobaricInhPa) float64 850.0 500.0
* latitude (latitude) float64 90.0 87.0 84.0 81.0 ... -84.0 -87.0 -90.0
* longitude (longitude) float64 0.0 3.0 6.0 9.0 ... 351.0 354.0 357.0
valid_time (time) datetime64[ns] ...
Data variables:
z (time, isobaricInhPa, latitude, longitude) float32 ...
t (time, isobaricInhPa, latitude, longitude) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: ecmf
GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts
GRIB_subCentre: 0
Conventions: CF-1.7
institution: European Centre for Medium-Range Weather Forecasts
history: ...
Per-variable GRIB keys can be set by setting the attrs variable with key prefixed by GRIB_,
for example:
.. code-block:: python
>>> import numpy as np
>>> import xarray as xr
>>> ds2 = xr.DataArray(
... np.zeros((5, 6)) + 300.,
... coords=[
... np.linspace(90., -90., 5),
... np.linspace(0., 360., 6, endpoint=False),
... ],
... dims=['latitude', 'longitude'],
... ).to_dataset(name='skin_temperature')
>>> ds2.skin_temperature.attrs['GRIB_shortName'] = 'skt'
>>> to_grib(ds2, 'out2.grib')
>>> xr.open_dataset('out2.grib', engine='cfgrib')
<xarray.Dataset>
Dimensions: (latitude: 5, longitude: 6)
Coordinates:
time datetime64[ns] ...
step timedelta64[ns] ...
surface float64 ...
* latitude (latitude) float64 90.0 45.0 0.0 -45.0 -90.0
* longitude (longitude) float64 0.0 60.0 120.0 180.0 240.0 300.0
valid_time datetime64[ns] ...
Data variables:
skt (latitude, longitude) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: consensus
GRIB_centreDescription: Consensus
GRIB_subCentre: 0
Conventions: CF-1.7
institution: Consensus
history: ...
Dataset / Variable API
The use of xarray is not mandatory and you can access the content of a GRIB file as an hypercube with the high level API in a Python interpreter:
.. code-block:: python
>>> ds = cfgrib.open_file('era5-levels-members.grib')
>>> ds.attributes['GRIB_edition']
1
>>> sorted(ds.dimensions.items())
[('isobaricInhPa', 2), ('latitude', 61), ('longitude', 120), ('number', 10), ('time', 4)]
>>> sorted(ds.variables)
['isobaricInhPa', 'latitude', 'longitude', 'number', 'step', 't', 'time', 'valid_time', 'z']
>>> var = ds.variables['t']
>>> var.dimensions
('number', 'time', 'isobaricInhPa', 'latitude', 'longitude')
>>> var.data[:, :, :, :, :].mean()
262.92133
>>> ds = cfgrib.open_file('era5-levels-members.grib')
>>> ds.attributes['GRIB_edition']
1
>>> sorted(ds.dimensions.items())
[('isobaricInhPa', 2), ('latitude', 61), ('longitude', 120), ('number', 10), ('time', 4)]
>>> sorted(ds.variables)
['isobaricInhPa', 'latitude', 'longitude', 'number', 'step', 't', 'time', 'valid_time', 'z']
>>> var = ds.variables['t']
>>> var.dimensions
('number', 'time', 'isobaricInhPa', 'latitude', 'longitude')
>>> var.data[:, :, :, :, :].mean()
262.92133
GRIB index file
By default cfgrib saves the index of the GRIB file to disk appending .idx
to the GRIB file name.
Index files are an experimental and completely optional feature, feel free to
remove them and try again in case of problems. Index files saving can be disable passing
adding indexpath='' to the backend_kwargs keyword argument.
Geographic Coordinate Caching
By default, cfgrib caches computed geography coordinates for each record in the GRIB
file when opening a dataset, which significantly speeds up dataset creation.
This cache can theoretically grow unboundedly in memory in long-lived
applications which read many different grid types. Should it be necessary,
caching can be disabled by passing backend_kwargs=dict(cache_geo_coords=False)
to xarray.open_dataset(), cfgrib.open_dataset(), or
cfgrib.open_datasets().
Project resources
============= ========================================================= Development https://github.com/ecmwf/cfgrib Download https://pypi.org/project/cfgrib User support https://stackoverflow.com/search?q=cfgrib Code quality .. image:: https://codecov.io/gh/ecmwf/cfgrib/branch/master/graph/badge.svg :target: https://codecov.io/gh/ecmwf/cfgrib :alt: Coverage status on Codecov ============= =========================================================
Contributing
The main repository is hosted on GitHub, testing, bug reports and contributions are highly welcomed and appreciated:
https://github.com/ecmwf/cfgrib
Please see the CONTRIBUTING.rst document for the best way to help.
Lead developers:
Iain Russell <https://github.com/iainrussell>_ -ECMWF <https://ecmwf.int>_Baudouin Raoult <https://github.com/b8raoult>_ - ECMWF
Main contributors:
Alessandro Amici <https://github.com/alexamici>_ -B-Open <https://bopen.eu>_Aureliana Barghini <https://github.com/aurghs>_ - B-OpenLeonardo Barcaroli <https://github.com/leophys>_ - B-Open
See also the list of contributors <https://github.com/ecmwf/cfgrib/contributors>_ who participated in this project.
License
Copyright 2017-2021 European Centre for Medium-Range Weather Forecasts (ECMWF).
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Changelog for cfgrib
0.9.14.1 (2024-09-12)
- Fixed compatibility with xarray 2024.09.0
See
#401 <https://github.com/ecmwf/cfgrib/pull/401>_.
0.9.14.0 (2024-07-19)
-
Added
coords_as_attributesargument toopen_dataset()to allow selected dimensions to be stored as attributes rather than dimensions, allowing more heterogeneous data to be encoded as an xarray dataset. See#394 <https://github.com/ecmwf/cfgrib/pull/394>_. -
Added valid_month dimension if monthlyVerificationDate and validityTime are available. See
#393 <https://github.com/ecmwf/cfgrib/pull/393>_. -
Added uvRelativeToGrid to list of GRIB keys read by default. See
#379 <https://github.com/ecmwf/cfgrib/pull/379>_.
0.9.13.0 (2024-06-27)
-
Allow users to pass of list of values to filter a key by. See
#384 <https://github.com/ecmwf/cfgrib/pull/384>_. -
Functionality to ignore keys when reading a grib file See
#382 <https://github.com/ecmwf/cfgrib/pull/382>_. -
Preserve coordinate encoding in cfgrib.open_datasets See
#381 <https://github.com/ecmwf/cfgrib/pull/381>_.
0.9.12.0 (2024-05-26)
- fixed issue where GRIB messages with non-hourly steps could not be read
See
#370 <https://github.com/ecmwf/cfgrib/pull/370>_.
0.9.11.0 (2024-04-05)
-
added automatic caching of geographic coordinates for improved performance See
#341 <https://github.com/ecmwf/cfgrib/pull/341>_. -
fixed issue where to_grib() could crash if given a dataset with a single-valued dimension See
#347 <https://github.com/ecmwf/cfgrib/issues/347>_. -
fixed issue where values could not be extracted when alternativeRowScanning=1 and grid is not represented as 2D See
#358 <https://github.com/ecmwf/cfgrib/issues/358>_. -
fixed issue where the
grib_errorsparameter was not being handled correctly. This parameter has now been renamed toerrors. See#349 <https://github.com/ecmwf/cfgrib/issues/349>_. -
dropped support for Python 3.6. See
#363 <https://github.com/ecmwf/cfgrib/issues/363>_.
0.9.10.4 (2023-05-19)
- added --var-encoding-json (or -v) option to the to_netcdf tool, e.g.
cfgrib to_netcdf -v '{"dtype": "float", "scale_factor": 0.1}' -o $OUTFILE $INFILESee#334 <https://github.com/ecmwf/cfgrib/pull/334>_. - fix issue where xarrays derived from Gaussian grids did not have the correct
geometry when written back out as GRIB
See
#330 <https://github.com/ecmwf/cfgrib/issues/330>_. - fix issue where open_datasets() could merge different GRIB fields
that have the same data values
See
#336 <https://github.com/ecmwf/cfgrib/issues/336>_.
0.9.10.3 (2022-11-24)
-
large reduction in memory leak See
#320 <https://github.com/ecmwf/cfgrib/pull/320/>_. -
Replaced
distutils.versionbypackaging.versionand added description and url to the xarray plugin. See#318 <https://github.com/ecmwf/cfgrib/pull/318/>_.
0.9.10.2 (2022-10-04)
- added --netcdf_kwargs_json option to 'cfgrib to_netcdf'
See
#294 <https://github.com/ecmwf/cfgrib/pull/294/>_. - fixed support for GRIB files with alternativeRowScanning=1
See
#296 <https://github.com/ecmwf/cfgrib/pull/296/>_. - fixed support for missing values
See
#313 <https://github.com/ecmwf/cfgrib/issues/313>_.
0.9.10.1 (2022-03-16)
- Fix failure to read index files.
See
#292 <https://github.com/ecmwf/cfgrib/issues/292>_. - Allow backend kwargs to be provided in the to_netcdf executable,
either via a json format string, or a path to a json file via -b.
See
#288 <https://github.com/ecmwf/cfgrib/pull/288/>_. - Fixed issue where the use of relpath() could cause a problem on Windows.
See
#284 <https://github.com/ecmwf/cfgrib/issues/284>_. - Fix passing of pathlib.Path.
See
#282 <https://github.com/ecmwf/cfgrib/issues/282>_. - Fixed issue where writing an ensemble number into a GRIB file caused an error.
See
#278 <https://github.com/ecmwf/cfgrib/issues/278>_.
0.9.10.0 (2022-01-31)
- Big internal refactor to add support for a generic
Fieldsetsimilar to Metview. See#243 <https://github.com/ecmwf/cfgrib/issues/243>_.
0.9.9.1 (2021-09-29)
- Fix the plugin interface that was missing
extra_coords. See#231 <https://github.com/ecmwf/cfgrib/issues/231>_. - Fix the crash when
extra_coordsreturn a scalar. See#238 <https://github.com/ecmwf/cfgrib/issues/238>_. - Improve type-hints.
Needed by
#243 <https://github.com/ecmwf/cfgrib/issues/243>_.
0.9.9.0 (2021-04-09)
- Depend on the ECMWF
eccodes python package <https://pypi.org/project/eccodes>_ to access the low level ecCodes C-library, dropping all other GRIB decoding options. See:#95 <https://github.com/ecmwf/cfgrib/issues/95>,#14 <https://github.com/ecmwf/cfgrib/issues/14>.#204 <https://github.com/ecmwf/cfgrib/issues/204>,#147 <https://github.com/ecmwf/cfgrib/issues/147>and#141 <https://github.com/ecmwf/cfgrib/issues/141>_. - Many performance improvements during the generation of the index and during data access.
See:
#142 <https://github.com/ecmwf/cfgrib/issues/142>_ and#197 <https://github.com/ecmwf/cfgrib/issues/197>_. filter_by_keysnow can select on all keys known to ecCodes without the need to add non default ones toread_keysexplicitly. See:#187 <https://github.com/ecmwf/cfgrib/issues/187>_.- Include support for
engine="cfgrib"using xarray 0.18+ new backend API. See:#216 <https://github.com/ecmwf/cfgrib/pull/216>_. - Fixed issue where could not load a GRIB message that has only one grid point.
See:
#199 <https://github.com/ecmwf/cfgrib/issues/199>_. - Decode
levelcoordinates as float in all cases, fixed issue with non-int levels. See:#195 <https://github.com/ecmwf/cfgrib/issues/195>_.
0.9.8.5 (2020-11-11)
- Simpler and clearer messages in the event of errors.
- Use
ECCODES_DIRenvironment variable if present. Ported from eccodes-python by xavierabellan. See:#162 <https://github.com/ecmwf/cfgrib/issues/162>_. - Fix using current ecCodes bindings when setting
CFGRIB_USE_EXTERNAL_ECCODES_BINDINGS=1.
0.9.8.4 (2020-08-03)
- Use
ecmwflibsif present to find the ecCodes installation.
0.9.8.3 (2020-06-25)
- Added support for
indexingDate,indexingTimetime coordinates. lambert_azimuthal_equal_areagrids are now returned as 2D arrays. See:#119 <https://github.com/ecmwf/cfgrib/issues/119>_.
0.9.8.2 (2020-05-22)
- Add support for MULTI-FIELD messages used in some GRIB products to store
uandvcomponents of wind (e.g. GFS, NAM, etc). This has been the single most reported bug in cfgrib with two failed attempts at fixing it already. Let's see if the third time's a charm. Please test! See:#45 <https://github.com/ecmwf/cfgrib/issues/45>,#76 <https://github.com/ecmwf/cfgrib/issues/76>and#111 <https://github.com/ecmwf/cfgrib/issues/111>_.
0.9.8.1 (2020-03-13)
- Always open GRIB files in binary mode, by @b8raoult
0.9.8.0 (2020-03-12)
- Add support of experimental pyeccodes low-level driver by @b8raoult
0.9.7.7 (2020-01-24)
- Add support for
forecastMonthincf2cdm.translate_coords.
0.9.7.6 (2019-12-05)
- Fix the README.
0.9.7.5 (2019-12-05)
- Deprecate
ensure_valid_timeand the config optionpreferred_time_dimensionthat are now better handled viatime_dims.
0.9.7.4 (2019-11-22)
- Add more options to
time_dimsforecasts products may be represented as('time', 'verifying_time')or('time', 'forecastMonth'). See:#97 <https://github.com/ecmwf/cfgrib/issues/97>_.
0.9.7.3 (2019-11-04)
- Add support for selecting the time coordinates to use as dimensions via
time_dims. Forecasts products may be represented as('time', 'step')(the default),('time', 'valid_time')or('valid_time', 'step'). See:#97 <https://github.com/ecmwf/cfgrib/issues/97>_. - Reduce the in-memory footprint of the
FieldIndexand the size of.idxfiles.
0.9.7.2 (2019-09-24)
- Add support to read additional keys from the GRIB files via
read_keys, they appear in the variableattrsand you canfilter_by_keyson them. This is a general solution for all issues where users know the name of the additional keys they are interested in. See:#89 <https://github.com/ecmwf/cfgrib/issues/89>_ and#101 <https://github.com/ecmwf/cfgrib/issues/101>_.
0.9.7.1 (2019-07-08)
- Fix a bytes-in-the-place-of-str bug when attempting to write a GRIB on Windows.
See:
#91 <https://github.com/ecmwf/cfgrib/issues/91>_. - Honor setting
indexpathinopen_datasets, See:#93 <https://github.com/ecmwf/cfgrib/issues/93>_.
0.9.7 (2019-05-27)
- Much improved
cfgrib.open_datasetsheuristics now reads many more heterogeneous GRIB files. The function is now a supported API. See:#63 <https://github.com/ecmwf/cfgrib/issues/63>,#66 <https://github.com/ecmwf/cfgrib/issues/66>,#73 <https://github.com/ecmwf/cfgrib/issues/73>_ and#75 <https://github.com/ecmwf/cfgrib/issues/75>_. - Fix conda dependencies on Python 2 only package,
See:
#78 <https://github.com/ecmwf/cfgrib/issues/78>_.
0.9.7rc1 (2019-05-14)
- Drop support for Python 2, in line with xarray 0.12.0.
The 0.9.6.x series will be supported long term for Python 2 users.
See:
#69 <https://github.com/ecmwf/cfgrib/issues/69>_. - Sync internal ecCodes bindings API to the one in eccodes-python.
See:
#81 <https://github.com/ecmwf/cfgrib/issues/81>_. - Source code has been formatted with
black -S -l 99. - Added initial support for spectral coordinates.
0.9.6.2 (2019-04-15)
- Improve merging of variables into a dataset.
See:
#63 <https://github.com/ecmwf/cfgrib/issues/63>_.
0.9.6.1.post1 (2019-03-17)
- Fix an issue in the README format.
0.9.6.1 (2019-03-17)
- Fixed (for real) MULTI-FIELD messages,
See:
#45 <https://github.com/ecmwf/cfgrib/issues/45>_. - Added a protocol version to the index file. Old
*.idxfiles must be removed.
0.9.6.post1 (2019-03-07)
- Fix an important typo in the README. See:
#64 <https://github.com/ecmwf/cfgrib/issues/64>_.
0.9.6 (2019-02-26)
- Add support for Windows by installing ecCodes via conda.
See:
#7 <https://github.com/ecmwf/cfgrib/issues/7>_. - Added conda-forge package.
See:
#5 <https://github.com/ecmwf/cfgrib/issues/5>_.
0.9.5.7 (2019-02-24)
- Fixed a serious bug in the computation of the suggested
filter_by_keysfor non-cubic GRIB files. As a resultcfgrib.xarray_store.open_datasetswas not finding all the variables in the files. See:#54 <https://github.com/ecmwf/cfgrib/issues/54>_. - Fixed a serious bug in variable naming that could drop or at worse mix the values of variables.
Again see:
#54 <https://github.com/ecmwf/cfgrib/issues/54>_. - Re-opened
#45 <https://github.com/ecmwf/cfgrib/issues/45>_ as the fix was returning wrong data. Now we are back to dropping all variable in a MULTI-FIELD except the first.
0.9.5.6 (2019-02-04)
- Do not set explicit timezone in
unitsto avoid crashing some versions of xarray. See:#44 <https://github.com/ecmwf/cfgrib/issues/44>_.
0.9.5.5 (2019-02-02)
- Enable ecCodes implicit MULTI-FIELD support by default, needed for NAM Products by NCEP.
See:
#45 <https://github.com/ecmwf/cfgrib/issues/45>_. - Added support for
depthBelowLandcoordinate.
0.9.5.4 (2019-01-25)
- Add support for building
valid_timefrom a badtime-stephypercube.
0.9.5.3 (2019-01-25)
- Also convert is
valid_timecan index all times and steps intranslate_coords.
0.9.5.2 (2019-01-24)
- Set
valid_timeas preferred time dimension for the CDS data model. - Fall back to using the generic
GRIB2ecCodes template when no better option is found. See:#39 <https://github.com/ecmwf/cfgrib/issues/39>_.
0.9.5.1 (2018-12-27)
- Fix the crash when using
cf2cdm.translate_coordson datasets with non-dimension coordinates. See:#41 <https://github.com/ecmwf/cfgrib/issues/41>_. - Added a
cfgribscript that can translate GRIB to netCDF. See:#40 <https://github.com/ecmwf/cfgrib/issues/40>_.
0.9.5 (2018-12-20)
- Drop support for xarray versions prior to v0.11 to reduce complexity.
(This is really only v0.10.9).
See:
#32 <https://github.com/ecmwf/cfgrib/issues/32>_. - Declare the data as
CF-1.7compliant via theConventionsglobal attribute. See:#36 <https://github.com/ecmwf/cfgrib/issues/36>_. - Tested larger-than-memory and distributed processing via dask and dask.distributed.
See:
#33 <https://github.com/ecmwf/cfgrib/issues/33>_. - Promote write support via
cfgrib.to_gribto Alpha. See:#18 <https://github.com/ecmwf/cfgrib/issues/18>_. - Provide the
cf2cdm.translate_coordsutility function to translate the coordinates between CF-compliant data models, defined byout_name,unitsandstore_direction. See:#24 <https://github.com/ecmwf/cfgrib/issues/24>_. - Provide
cfgrib.__version__. See:#31 <https://github.com/ecmwf/cfgrib/issues/31>_. - Raise with a better error message when users attempt to open a file that is not a GRIB.
See:
#34 <https://github.com/ecmwf/cfgrib/issues/34>_. - Make 2D grids for
rotated_llandrotated_gggridType's. See:#35 <https://github.com/ecmwf/cfgrib/issues/35>_.
0.9.4.1 (2018-11-08)
- Fix formatting for PyPI page.
0.9.4 (2018-11-08)
- Saves one index file per set of
index_keysin a much more robust way. - Refactor CF-encoding and add the new
encode_cfoption tobackend_kwargs. See:#23 <https://github.com/ecmwf/cfgrib/issues/23>_. - Refactor error handling and the option to ignore errors (not well documented yet).
See:
#13 <https://github.com/ecmwf/cfgrib/issues/13>_. - Do not crash on
gridTypenot fully supported by the installed ecCodes See:#27 <https://github.com/ecmwf/cfgrib/issues/27>_. - Several smaller bug fixes and performance improvements.
0.9.3.1 (2018-10-28)
- Assorted README fixes, in particular advertise index file support as alpha.
0.9.3 (2018-10-28)
- Big performance improvement: add alpha support to save to and read from disk
the GRIB index produced by the full-file scan at the first open.
See:
#20 <https://github.com/ecmwf/cfgrib/issues/20>_.
0.9.2 (2018-10-22)
- Rename coordinate
air_pressuretoisobaricInhPafor consistency with all other verticallevelcoordinates. See:#25 <https://github.com/ecmwf/cfgrib/issues/25>_.
0.9.1.post1 (2018-10-19)
- Fix PyPI description.
0.9.1 (2018-10-19)
- Change the usage of
cfgrib.open_datasetto allign it withxarray.open_dataset, in particularfilter_by_keymust be added into thebackend_kwargsdictionary. See:#21 <https://github.com/ecmwf/cfgrib/issues/21>_.
0.9.0 (2018-10-14)
- Beta release with read support.
Keywords
FAQs
Python interface to map GRIB files to the NetCDF Common Data Model following the CF Convention using ecCodes.
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