def _mode_local_aware_key_looper(self, local: bool) -> Iterable[KeyType]:
"""Generate keys for iteration with dict update safety ensured.
Parameters
----------
local : bool
True if keys should be returned which only exist on the local machine.
Fale if remote sample keys should be excluded.
Returns
-------
Iterable[KeyType]
Sample keys conforming to the `local` argument spec.
"""
_islocal_func = op_attrgetter('islocal')
if local:
if self._mode == 'r':
yield from valfilter(_islocal_func, self._samples).keys()
else:
yield from tuple(valfilter(_islocal_func, self._samples).keys())
else:
if self._mode == 'r':
yield from self._samples.keys()
else:
yield from tuple(self._samples.keys())
def remote_reference_keys(self) -> Tuple[KeyType]:
"""Compute sample names whose data is stored in a remote server reference.
Returns
-------
Tuple[KeyType]
list of sample keys in the column whose data references indicate
they are stored on a remote server.
"""
_islocal_func = op_attrgetter('islocal')
return tuple(valfilterfalse(_islocal_func, self._samples).keys())
def contains_remote_references(self) -> bool:
"""Bool indicating if all samples in column exist on local disk.
The data associated with samples referencing some remote server will
need to be downloaded (``fetched`` in the hangar vocabulary) before
they can be read into memory.
Returns
-------
bool
False if at least one sample in the column references data stored
on some remote server. True if all sample data is available on the
machine's local disk.
"""
_islocal_func = op_attrgetter('islocal')
return not all(map(_islocal_func, self._samples.values()))