xarray.backends.NetCDF4DataStore¶
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class
xarray.backends.NetCDF4DataStore(manager, lock=CombinedLock([<SerializableLock: 8b6c36c0-2947-41e6-b24c-e2f739b2b28b>, <SerializableLock: 4f55aa16-c85e-471b-a52d-d2273db52b1f>]), autoclose=False)¶ Store for reading and writing data via the Python-NetCDF4 library.
This store supports NetCDF3, NetCDF4 and OpenDAP datasets.
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__init__(manager, lock=CombinedLock([<SerializableLock: 8b6c36c0-2947-41e6-b24c-e2f739b2b28b>, <SerializableLock: 4f55aa16-c85e-471b-a52d-d2273db52b1f>]), autoclose=False)¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__(manager[, lock, autoclose])Initialize self. close(**kwargs)encode(variables, attributes)Encode the variables and attributes in this store encode_attribute(a)encode one attribute encode_variable(variable)encode one variable get(k[,d])get_attrs()get_dimensions()get_encoding()get_variables()items()keys()load()This loads the variables and attributes simultaneously. open(filename[, mode, format, group, …])open_store_variable(name, var)prepare_variable(name, variable[, …])set_attribute(key, value)set_attributes(attributes)This provides a centralized method to set the dataset attributes on the data store. set_dimension(name, length[, is_unlimited])set_dimensions(variables[, unlimited_dims])This provides a centralized method to set the dimensions on the data store. set_variable(k, v)set_variables(variables, check_encoding_set, …)This provides a centralized method to set the variables on the data store. store(variables, attributes[, …])Top level method for putting data on this store, this method: store_dataset(dataset)in stores, variables are all variables AND coordinates in xarray.Dataset variables are variables NOT coordinates, so here we pass the whole dataset in instead of doing dataset.variables sync()values()Attributes
attrsdimensionsdsvariables-