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Determines if in index is 'trivial' meaning that it is
equivalent to np.arange(). This is determined by
checking if there are any attributes or encodings,
if ndims is one, dtype is int and finally by comparing
the actual values to np.arange()
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Robustly index an array, using retry logic with exponential backoff if any
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With the default settings, the maximum delay will be in the range of 32-64
seconds.
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This loads the variables and attributes simultaneously.
A centralized loading function makes it easier to create
data stores that do automatic encoding/decoding.
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class SuffixAppendingDataStore(AbstractDataStore):
def load(self):
variables, attributes = AbstractDataStore.load(self)
variables = {'%s_suffix' % k: v
for k, v in iteritems(variables)}
attributes = {'%s_suffix' % k: v
for k, v in iteritems(attributes)}
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This function will be called anytime variables or attributes
are requested, so care should be taken to make sure its fast.
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