xarray.backends.NetCDF4DataStore#
- class xarray.backends.NetCDF4DataStore(manager, group=None, mode=None, lock=CombinedLock([<SerializableLock: ead52e76-f363-4452-a816-dc2a67c6b44b>, <SerializableLock: f8f7979b-7f4c-46f8-96a1-a7935ac10660>]), 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: ead52e76-f363-4452-a816-dc2a67c6b44b>, <SerializableLock: f8f7979b-7f4c-46f8-96a1-a7935ac10660>]), autoclose=False)[source]#
Methods
__init__(manager[, group, mode, lock, autoclose])close(**kwargs)encode(variables, attributes)Encode the variables and attributes in this store
encode one attribute
encode_variable(variable[, name])encode one variable
get_parent_dimensions()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