def __call__(
path=None,
dataset=None,
recursive=False,
check=True,
if_dirty='save-before'):
refds = require_dataset(dataset, check_installed=True,
purpose='uninstall')
res_kwargs = dict(action='uninstall', logger=lgr, refds=refds.path)
if not path:
# if no path is given, ie. refds is supposed to be uninstalled
# check if refds is a subdataset itself, if not die
# we only need to test that for the refds, everything else
# will be guaranteed to be a subdataset
parentds = refds.get_superdataset(
datalad_only=False,
topmost=False,
# unless it is properly registered we have no way of
# reinstalling it
registered_only=True)
if parentds is None:
yield dict(
res_kwargs,
path=refds.path,
type='dataset',
status='error',
message="will not uninstall top-level dataset "
"(consider `remove` command)",
)
return
saw_subds = False
for ds in itertools.chain(Subdatasets.__call__(
# it is critical to pass the dataset arg as-is
# to not invalidate the path argument semantics
# in subdatasets()
dataset=dataset,
path=path,
fulfilled=True,
# makes no sense to ignore subdatasets further down
recursive=True,
# important to start at the bottom for proper deinit
bottomup=True,
# doesn't make sense for uninstall
#recursion_limit=recursion_limit,
return_type='generator',
result_renderer='disabled',
result_xfm='datasets') if path or recursive else [],
[refds] if not path else []):
if ds != refds:
saw_subds = True
# TODO generator
# this should yield what it did
handle_dirty_dataset(ds, mode=if_dirty)
# we confirmed the super dataset presence above
for r in _uninstall_dataset(ds, check=check, has_super=True,
**res_kwargs):
yield r
# there is nothing to save at the end
if path and not saw_subds:
lgr.warning(
'path constraints did not match an installed subdataset: %s',
path)
def __call__(
path=None,
source=None,
dataset=None,
recursive=False,
recursion_limit=None,
get_data=True,
description=None,
reckless=None,
jobs='auto',
):
refds_path = Interface.get_refds_path(dataset)
if not (dataset or path):
raise InsufficientArgumentsError(
"Neither dataset nor target path(s) provided")
if dataset and not path:
# act on the whole dataset if nothing else was specified
path = refds_path
# we have to have a single dataset to operate on
refds = require_dataset(dataset,
check_installed=True,
purpose='get content')
content_by_ds = {}
# use subdatasets() to discover any relevant content that is not
# already present in the root dataset (refds)
for sdsres in Subdatasets.__call__(
contains=path,
# maintain path argument semantics and pass in dataset arg
# as is
dataset=dataset,
# always come from the top to get sensible generator behavior
bottomup=False,
# when paths are given, they will constrain the recursion
# automatically, and we need to enable recursion so we can
# location path in subdatasets several levels down
recursive=True if path else recursive,
recursion_limit=None if path else recursion_limit,
return_type='generator',
on_failure='ignore'):
if sdsres.get('type', None) != 'dataset':
# if it is not about a 'dataset' it is likely content in
# the root dataset
if sdsres.get('status', None) == 'impossible' and \
sdsres.get('message', None) == \
'path not contained in any matching subdataset':
target_path = Path(sdsres['path'])
if refds.pathobj != target_path and \
refds.pathobj not in target_path.parents:
yield dict(
action='get',
path=str(target_path),
status='error',
message=('path not associated with dataset %s',
refds),
)
continue
# check if we need to obtain anything underneath this path
# the subdataset() call above will only look _until_ it
# hits the targetpath
for res in _install_targetpath(
refds,
Path(sdsres['path']),
recursive,
recursion_limit,
reckless,
refds_path,
description,
jobs=jobs,
):
# fish out the datasets that 'contains' a targetpath
# and store them for later
if res.get('status', None) in ('ok', 'notneeded') and \
'contains' in res:
dsrec = content_by_ds.get(res['path'], set())
dsrec.update(res['contains'])
content_by_ds[res['path']] = dsrec
if res.get('status', None) != 'notneeded':
# all those messages on not having installed anything
# are a bit pointless
# "notneeded" for annex get comes below
yield res
else:
# dunno what this is, send upstairs
yield sdsres
# must continue for both conditional branches above
# the rest is about stuff in real subdatasets
continue
# instance of the closest existing dataset for this result
ds = Dataset(sdsres['parentds'] if sdsres.get('state', None) ==
'absent' else sdsres['path'])
assert 'contains' in sdsres
# explore the unknown
for target_path in sdsres.get('contains', []):
# essentially the same as done above for paths in the root
# dataset, but here we are starting from the closest
# discovered subdataset
for res in _install_targetpath(
ds,
Path(target_path),
recursive,
recursion_limit,
reckless,
refds_path,
description,
jobs=jobs,
):
known_ds = res['path'] in content_by_ds
if res.get('status', None) in ('ok', 'notneeded') and \
'contains' in res:
dsrec = content_by_ds.get(res['path'], set())
dsrec.update(res['contains'])
content_by_ds[res['path']] = dsrec
# prevent double-reporting of datasets that have been
# installed by explorative installation to get to target
# paths, prior in this loop
if res.get('status', None) != 'notneeded' or not known_ds:
yield res
if not get_data:
# done already
return
# and now annex-get, this could all be done in parallel now
for ds, content in content_by_ds.items():
for res in _get_targetpaths(Dataset(ds), content, refds.path,
source, jobs):
if res['path'] not in content_by_ds:
# we had reports on datasets and subdatasets already
# before the annex stage
yield res