xarray.backends.NetCDF4DataStore#

class xarray.backends.NetCDF4DataStore(manager, group=None, mode=None, lock=CombinedLock([<SerializableLock: 0decbb17-3652-4d3c-b471-969e4fbcbf4a>, <SerializableLock: f65a2a35-6cb1-4f96-b0f8-80e5ff0d6182>]), autoclose=False)[source]#

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

This store supports NetCDF3, NetCDF4 and OpenDAP datasets.

__init__(manager, group=None, mode=None, lock=CombinedLock([<SerializableLock: 0decbb17-3652-4d3c-b471-969e4fbcbf4a>, <SerializableLock: f65a2a35-6cb1-4f96-b0f8-80e5ff0d6182>]), autoclose=False)[source]#

Methods

__init__(manager[, group, mode, lock, autoclose])

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_attrs()

get_dimensions()

get_encoding()

get_variables()

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()

Attributes

autoclose

format

is_remote

lock

ds