xarray.backends.NetCDF4DataStore

class xarray.backends.NetCDF4DataStore(netcdf4_dataset, mode='r', writer=None, opener=None, autoclose=False, lock=<SerializableLock: d9d3b33d-5465-4f9f-8d27-82471afa633f>)

Store for reading and writing data via the Python-NetCDF4 library.

This store supports NetCDF3, NetCDF4 and OpenDAP datasets.

__init__(netcdf4_dataset, mode='r', writer=None, opener=None, autoclose=False, lock=<SerializableLock: d9d3b33d-5465-4f9f-8d27-82471afa633f>)

Methods

__init__(netcdf4_dataset[, mode, writer, …])
assert_open()
close()
encode(variables, attributes)
encode_attribute(a)	encode one attribute
encode_variable(variable)
ensure_open([autoclose])	Helper function to make sure datasets are closed and opened at appropriate times to avoid too many open file errors.
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(*args, **kwargs)
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
sync()
values()