xarray.backends.ScipyDataStore

class xarray.backends.ScipyDataStore(filename_or_obj, mode='r', format=None, group=None, writer=None, mmap=None, autoclose=False)

Store for reading and writing data via scipy.io.netcdf.

This store has the advantage of being able to be initialized with a StringIO object, allow for serialization without writing to disk.

It only supports the NetCDF3 file-format.

__init__(filename_or_obj, mode='r', format=None, group=None, writer=None, mmap=None, autoclose=False)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(filename_or_obj[, mode, format, …]) Initialize self.
assert_open()
close()
encode(variables, attributes) Encode the variables and attributes in this store
encode_attribute(a) encode one attribute
encode_variable(variable) encode one 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_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
sync()
values()

Attributes

attrs
dimensions
variables