def handle_dirty_dataset(ds, mode, msg=None):
"""Detect and treat unsaved changes as instructed by `mode`
Parameters
----------
ds : Dataset or None
Dataset to be inspected. Does nothing if `None`.
mode : {'fail', 'ignore', 'save-before'}
How to act upon discovering unsaved changes.
msg : str or None
Custom message to use for a potential commit.
Returns
-------
None
"""
if ds is None:
# nothing to be handled
return
if msg is None:
msg = '[DATALAD] auto-saved changes'
if mode == 'ignore':
return
elif mode == 'fail':
if not ds.repo or ds.repo.repo.is_dirty(index=True,
working_tree=True,
untracked_files=True,
submodules=True):
raise RuntimeError('dataset {} has unsaved changes'.format(ds))
elif mode == 'save-before':
if not ds.is_installed():
raise RuntimeError('dataset {} is not yet installed'.format(ds))
Save.__call__(dataset=ds, message=msg, auto_add_changes=True)
else:
raise ValueError("unknown if-dirty mode '{}'".format(mode))
def handle_dirty_dataset(ds, mode, msg=None):
"""Detect and treat unsaved changes as instructed by `mode`
Parameters
----------
ds : Dataset or None
Dataset to be inspected. Does nothing if `None`.
mode : {'fail', 'ignore', 'save-before'}
How to act upon discovering unsaved changes.
msg : str or None
Custom message to use for a potential commit.
Returns
-------
None
"""
if ds is None:
# nothing to be handled
return
if msg is None:
msg = '[DATALAD] auto-saved changes'
# make sure that all pending changes (batched annex operations, etc.)
# are actually reflected in Git
if ds.repo:
ds.repo.precommit()
if mode == 'ignore':
return
elif mode == 'fail':
if not ds.repo or ds.repo.is_dirty(index=True,
untracked_files=True,
submodules=True):
raise RuntimeError('dataset {} has unsaved changes'.format(ds))
elif mode == 'save-before':
if not ds.is_installed():
raise RuntimeError('dataset {} is not yet installed'.format(ds))
from datalad.interface.save import Save
Save.__call__(dataset=ds, message=msg)
else:
raise ValueError("unknown if-dirty mode '{}'".format(mode))
def handle_dirty_dataset(ds, mode, msg=None):
"""Detect and treat unsaved changes as instructed by `mode`
Parameters
----------
ds : Dataset or None
Dataset to be inspected. Does nothing if `None`.
mode : {'fail', 'ignore', 'save-before'}
How to act upon discovering unsaved changes.
msg : str or None
Custom message to use for a potential commit.
Returns
-------
None
"""
if ds is None:
# nothing to be handled
return
if msg is None:
msg = '[DATALAD] auto-saved changes'
# make sure that all pending changes (batched annex operations, etc.)
# are actually reflected in Git
if ds.repo:
ds.repo.precommit()
if mode == 'ignore':
return
elif mode == 'fail':
if not ds.repo or ds.repo.is_dirty(index=True,
untracked_files=True,
submodules=True):
raise RuntimeError('dataset {} has unsaved changes'.format(ds))
elif mode == 'save-before':
if not ds.is_installed():
raise RuntimeError('dataset {} is not yet installed'.format(ds))
from datalad.interface.save import Save
Save.__call__(dataset=ds, message=msg)
else:
raise ValueError("unknown if-dirty mode '{}'".format(mode))
def __call__(
path=None,
dataset=None,
# support passing this through in a path by path basis
to_git=None,
save=True,
message=None,
message_file=None,
recursive=False,
recursion_limit=None,
ds2super=False,
git_opts=None,
annex_opts=None,
annex_add_opts=None,
jobs=None):
# parameter constraints:
if not path:
raise InsufficientArgumentsError(
"insufficient information for adding: requires at least a path")
refds_path = Interface.get_refds_path(dataset)
common_report = dict(action='add', logger=lgr, refds=refds_path)
if message and message_file:
raise ValueError("Both a message and message file were specified")
if message_file:
with open(message_file, "rb") as mfh:
message = assure_unicode(mfh.read())
to_add = []
subds_to_add = {}
ds_to_annotate_from_recursion = {}
got_nothing = True
for ap in AnnotatePaths.__call__(
path=path,
dataset=dataset,
# never recursion, need to handle manually below to be able to
# discover untracked content
recursive=False,
action='add',
# speed things up by using Git's modification detection, if there
# is a repo with at least one commit
modified='HEAD' \
if dataset and \
GitRepo.is_valid_repo(refds_path) and \
GitRepo(refds_path).get_hexsha() \
else None,
unavailable_path_status='impossible',
unavailable_path_msg="path does not exist: %s",
nondataset_path_status='impossible',
return_type='generator',
on_failure='ignore'):
got_nothing = False
if ap.get('status', None):
# this is done
yield ap
continue
if ap.get('parentds', None) is None and ap.get('type', None) != 'dataset':
yield get_status_dict(
status='impossible',
message='"there is no dataset to add this path to',
**dict(common_report, **ap))
continue
if ap.get('type', None) == 'directory' and \
ap.get('state', None) == 'untracked' and \
GitRepo.is_valid_repo(ap['path']):
# this is an untracked wannabe subdataset in disguise
ap['type'] = 'dataset'
if recursive and \
(ap.get('raw_input', False) or
ap.get('state', None) in ('added', 'modified', 'untracked')) and \
(ap.get('parentds', None) or ap.get('type', None) == 'dataset'):
# this was an actually requested input path, or a path that was found
# modified by path annotation, based on an input argument
# we need to recurse into all subdirs to find potentially
# unregistered subdatasets
# but only if this path has a parent, or is itself a dataset
# otherwise there is nothing to add to
_discover_subdatasets_recursively(
ds_to_annotate_from_recursion,
ap['path'], [ap['parentds'] if 'parentds' in ap else ap['path']],
recursion_limit)
# get the file content of the root dataset of this search added too
# but be careful with extreme recursion_limit settings
if recursion_limit is None or recursion_limit > 0:
ap['process_content'] = True
# record for further processing
if not ap['path'] in ds_to_annotate_from_recursion:
# if it was somehow already discovered
to_add.append(ap)
if got_nothing:
# path annotation yielded nothing, most likely cause is that nothing
# was found modified, we need to say something about the reference
# dataset
yield get_status_dict(
'add',
status='notneeded',
path=refds_path,
type='dataset',
logger=lgr)
return
for subds in ds_to_annotate_from_recursion:
if subds not in subds_to_add:
# always prefer the already annotated path
subds_to_add[subds] = ds_to_annotate_from_recursion[subds]
if dataset:
# we have a base dataset, discover any intermediate datasets between
# the base and any already discovered dataset
discovered = {}
discover_dataset_trace_to_targets(
# from here
dataset.path,
# to any dataset we are aware of
subds_to_add.keys(),
[],
discovered)
for parentds in discovered:
for subds in discovered[parentds]:
subds_to_add[subds] = subds_to_add.get(
subds,
dict(path=subds, parentds=parentds, type='dataset'))
# merge custom paths and discovered dataset records, paths needs to go first,
# because we know most about then, and subsequent annotation call we skip the
# later duplicate ones
to_add.extend(subds_to_add.values())
# and compact, this should be OK as all the info is in each ap dict
to_add = unique(to_add, lambda x: x['path'])
if not to_add:
# nothing left to do, potentially all errored before
return
# now re-annotate all paths, this will be fast for already annotated ones
# and will amend the annotation for others, it will also deduplicate
annotated_paths = AnnotatePaths.__call__(
path=to_add,
dataset=dataset,
# never recursion, done already
recursive=False,
action='add',
unavailable_path_status='impossible',
unavailable_path_msg="path does not exist: %s",
nondataset_path_status='impossible',
return_type='generator',
# if there is an error now, we made this mistake in here
on_failure='stop')
content_by_ds, ds_props, completed, nondataset_paths = \
annotated2content_by_ds(
annotated_paths,
refds_path=refds_path)
assert(not completed)
if not content_by_ds:
# we should have complained about any inappropriate path argument
# above, so if nothing is left, we can simply exit
return
# simple loop over datasets -- save happens later
# start deep down
to_save = []
for ds_path in sorted(content_by_ds, reverse=True):
ds = Dataset(ds_path)
torepoadd = {}
respath_by_status = {}
for ap in content_by_ds[ds_path]:
# we have a new story
ap.pop('status', None)
torepoadd[ap['path']] = ap
# skip anything that doesn't look like a wannabe subdataset
if not ap.get('type', None) == 'dataset' or \
ap['path'] == ds_path:
continue
if ap.get('registered_subds', False):
# subdataset that might be in this list because of the
# need to save all the way up to a super dataset
respath_by_status['success'] = \
respath_by_status.get('success', []) + [ap['path']]
yield get_status_dict(
status='notneeded',
message="already known subdataset",
**dict(common_report, **ap))
continue
subds = Dataset(ap['path'])
subds_relpath = relpath(ap['path'], ds_path)
# Register the repository in the repo tree as a submodule
try:
ds.repo.add_submodule(subds_relpath, url=None, name=None)
except (CommandError, InvalidGitRepositoryError) as e:
yield get_status_dict(
ds=subds, status='error', message=e.stderr,
**dict(common_report, **ap))
continue
# queue for saving using the updated annotated path
ap['registered_subds'] = True
# I hope this is true in direct mode too
# TODO this is disabled, because in some circumstances
# staging just doesn't happen, and it is unclear when
# exactly -- the case that prompted disabling was a submodule
# that had no content except for other submodules was not staged,
# whereas another submodule on the same level in the same
# superdataset which also has one file in it was staged
# disable to work correctly, while paying a little bit of
# slow down
#ap['staged'] = True
to_save.append(ap)
# report added subdatasets -- `annex add` below won't do it
yield get_status_dict(
ds=subds,
status='ok',
message='added new subdataset',
**dict(common_report, **ap))
# make sure that .gitmodules is added to the list of files
gitmodules_path = opj(ds.path, '.gitmodules')
# for git
torepoadd[gitmodules_path] = dict(path=gitmodules_path)
# and for save
to_save.append(dict(
path=gitmodules_path,
parentds=ds_path,
type='file'))
# make sure any last minute additions make it to the saving stage
# XXX? should content_by_ds become OrderedDict so that possible
# super here gets processed last?
lgr.debug('Adding content to repo %s: %s', ds.repo, torepoadd)
is_annex = isinstance(ds.repo, AnnexRepo)
add_kw = {'jobs': jobs} if is_annex and jobs else {}
added = ds.repo.add_(
list(torepoadd.keys()),
git=to_git if is_annex else True,
**add_kw
)
for a in added:
res = annexjson2result(a, ds, type='file', **common_report)
success = success_status_map[res['status']]
respath_by_status[success] = \
respath_by_status.get(success, []) + [res['path']]
# produce best possible path/result annotation
if res['path'] in torepoadd:
# pull out correct ap for any path that comes out here
# (that we know things about), and use the original annotation
# instead of just the annex report
res = dict(torepoadd[res['path']], **res)
# override this in all cases to be safe
res['parentds'] = ds.path
if success:
# this was successfully added, queue for saving this very path
# in the dataset
ap = {k: v for k, v in res.items() if k != 'status'}
ap['staged'] = True
# strip any status and state info (e.g. save will refuse to save
# stuff that is marked state='untracked'
to_save.append({k: v for k, v in res.items()
if k not in ('status', 'state')})
if a['file'] == '.gitmodules':
# filter out .gitmodules, because this is only included for
# technical reasons and has nothing to do with the actual content
continue
if GitRepo.is_valid_repo(res['path']):
# more accurate report in case of an added submodule
# mountpoint.
# XXX Actually not sure if this can really happen
# (depends on what our low-level code would do)
# but worst case is that we loose a little bit of
# coverage...
res['type'] = 'dataset'
res['message'] = 'added new state as submodule'
yield res
for r in results_from_annex_noinfo(
ds, torepoadd, respath_by_status,
dir_fail_msg='could not add some content in %s %s',
noinfo_dir_msg='nothing to add from %s',
noinfo_file_msg='already included in the dataset',
action='add',
logger=lgr,
refds=refds_path):
if r['path'] in torepoadd:
# pull out correct ap for any path that comes out here
# (that we know things about), and use the original annotation
# instead of just the annex report
r = dict(r, **torepoadd[r['path']])
if r['status'] == 'notneeded':
# this could be a file that was staged already, it doesn't need
# to be added, but it should be saved/commited if so desired
to_save.append({k: v for k, v in r.items()
if k not in ('status', 'state')})
# XXX something is fishy with the next one, rethink when sober....
if r['path'] == ds_path and r['status'] == 'ok':
# this is for the entire dataset itself which was explicitly requested
# make sure to save all
r['type'] = 'dataset'
r['process_content'] = True
to_save.append({k: v for k, v in r.items() if k != 'status'})
yield r
if refds_path and ds_path != refds_path and len(respath_by_status.get('success', [])):
# TODO XXX we have an issue here when with `add('.')` and annex ignores any
# dotfiles. In this case we end up not saving a dataset completely, because
# we rely on accurate reporting. there is an issue about this already
# TODO look up the issue ID
# if there is a base dataset, but we are below it, and we have anything done to this
# dataset -> queue dataset itself for saving its state in the parent
ds_ap = dict(
path=ds.path,
# we have to look for the parent here, as we must save the
# subdataset in the parent and not the whole subdataset itself
type='dataset')
parentds = get_dataset_root(normpath(opj(ds.path, pardir)))
if parentds:
ds_ap['parentds'] = parentds
if dataset:
ds_ap['refds'] = refds_path
to_save.append(ds_ap)
if not save:
lgr.debug('Not calling `save` as instructed')
return
# TODO tell save what was staged already! Set 'staged=True' for
# respective annotated paths that are fed into `save`
# do not reuse any of the sorting done in here for saving, but instead
# pass on all the annotated paths to have `save` figure out what to do with
# them -- this is costs something, but should be safer, and frankly is
# more comprehensible
for res in Save.__call__(
# hand-selected annotated paths
path=to_save,
dataset=refds_path,
message=message if message else '[DATALAD] added content',
return_type='generator',
result_xfm=None,
result_filter=None,
on_failure='ignore'):
yield res
def __call__(
path=None,
dataset=None,
# support passing this through in a path by path basis
to_git=None,
save=True,
message=None,
recursive=False,
recursion_limit=None,
ds2super=False,
git_opts=None,
annex_opts=None,
annex_add_opts=None,
jobs=None):
# parameter constraints:
if not path:
raise InsufficientArgumentsError(
"insufficient information for adding: requires at least a path"
)
refds_path = Interface.get_refds_path(dataset)
common_report = dict(action='add', logger=lgr, refds=refds_path)
to_add = []
subds_to_add = {}
ds_to_annotate_from_recursion = {}
got_nothing = True
for ap in AnnotatePaths.__call__(
path=path,
dataset=dataset,
# never recursion, need to handle manually below to be able to
# discover untracked content
recursive=False,
action='add',
# speed things up by using Git's modification detection, if there
# is a repo with at least one commit
modified='HEAD' \
if dataset and \
GitRepo.is_valid_repo(refds_path) and \
GitRepo(refds_path).get_hexsha() \
else None,
unavailable_path_status='impossible',
unavailable_path_msg="path does not exist: %s",
nondataset_path_status='impossible',
return_type='generator',
on_failure='ignore'):
got_nothing = False
if ap.get('status', None):
# this is done
yield ap
continue
if ap.get('parentds', None) is None and ap.get('type',
None) != 'dataset':
yield get_status_dict(
status='impossible',
message='"there is no dataset to add this path to',
**dict(common_report, **ap))
continue
if ap.get('type', None) == 'directory' and \
ap.get('state', None) == 'untracked' and \
GitRepo.is_valid_repo(ap['path']):
# this is an untracked wannabe subdataset in disguise
ap['type'] = 'dataset'
if recursive and \
(ap.get('raw_input', False) or
ap.get('state', None) in ('added', 'modified', 'untracked')) and \
(ap.get('parentds', None) or ap.get('type', None) == 'dataset'):
# this was an actually requested input path, or a path that was found
# modified by path annotation, based on an input argument
# we need to recurse into all subdirs to find potentially
# unregistered subdatasets
# but only if this path has a parent, or is itself a dataset
# otherwise there is nothing to add to
_discover_subdatasets_recursively(
ds_to_annotate_from_recursion, ap['path'],
[ap['parentds'] if 'parentds' in ap else ap['path']],
recursion_limit)
# get the file content of the root dataset of this search added too
# but be careful with extreme recursion_limit settings
if recursion_limit is None or recursion_limit > 0:
ap['process_content'] = True
# record for further processing
if not ap['path'] in ds_to_annotate_from_recursion:
# if it was somehow already discovered
to_add.append(ap)
# TODO check if next isn't covered by discover_dataset_trace_to_targets already??
if dataset and ap.get('type', None) == 'dataset':
# duplicates not possible, annotated_paths returns unique paths
subds_to_add[ap['path']] = ap
if got_nothing:
# path annotation yielded nothing, most likely cause is that nothing
# was found modified, we need to say something about the reference
# dataset
yield get_status_dict('add',
status='notneeded',
path=refds_path,
type='dataset',
logger=lgr)
return
for subds in ds_to_annotate_from_recursion:
if subds not in subds_to_add:
# always prefer the already annotated path
subds_to_add[subds] = ds_to_annotate_from_recursion[subds]
if dataset:
# we have a base dataset, discover any intermediate datasets between
# the base and any already discovered dataset
discovered = {}
discover_dataset_trace_to_targets(
# from here
dataset.path,
# to any dataset we are aware of
subds_to_add.keys(),
[],
discovered)
for parentds in discovered:
for subds in discovered[parentds]:
subds_to_add[subds] = subds_to_add.get(
subds,
dict(path=subds, parentds=parentds, type='dataset'))
# merge custom paths and discovered dataset records, paths needs to go first,
# because we know most about then, and subsequent annotation call we skip the
# later duplicate ones
to_add.extend(subds_to_add.values())
# and compact, this should be OK as all the info is in each ap dict
to_add = unique(to_add, lambda x: x['path'])
if not to_add:
# nothing left to do, potentially all errored before
return
# now re-annotate all paths, this will be fast for already annotated ones
# and will amend the annotation for others, it will also deduplicate
annotated_paths = AnnotatePaths.__call__(
path=to_add,
dataset=dataset,
# never recursion, done already
recursive=False,
action='add',
unavailable_path_status='impossible',
unavailable_path_msg="path does not exist: %s",
nondataset_path_status='impossible',
return_type='generator',
# if there is an error now, we made this mistake in here
on_failure='stop')
content_by_ds, ds_props, completed, nondataset_paths = \
annotated2content_by_ds(
annotated_paths,
refds_path=refds_path)
assert (not completed)
if not content_by_ds:
# we should have complained about any inappropriate path argument
# above, so if nothing is left, we can simply exit
return
# simple loop over datasets -- save happens later
# start deep down
to_save = []
for ds_path in sorted(content_by_ds, reverse=True):
ds = Dataset(ds_path)
torepoadd = {}
respath_by_status = {}
for ap in content_by_ds[ds_path]:
# we have a new story
ap.pop('status', None)
torepoadd[ap['path']] = ap
# skip anything that doesn't look like a wannabe subdataset
if not ap.get('type', None) == 'dataset' or \
ap['path'] == ds_path:
continue
if ap.get('registered_subds', False):
# subdataset that might be in this list because of the
# need to save all the way up to a super dataset
respath_by_status['success'] = \
respath_by_status.get('success', []) + [ap['path']]
yield get_status_dict(status='notneeded',
message="already known subdataset",
**dict(common_report, **ap))
continue
subds = Dataset(ap['path'])
# check that the subds has a commit, and refuse
# to operate on it otherwise, or we would get a bastard
# submodule that cripples git operations
if not subds.repo.get_hexsha():
yield get_status_dict(
ds=subds,
status='impossible',
message='cannot add subdataset with no commits',
**dict(common_report, **ap))
continue
subds_relpath = relpath(ap['path'], ds_path)
# make an attempt to configure a submodule source URL based on the
# discovered remote configuration
remote, branch = subds.repo.get_tracking_branch()
subds_url = subds.repo.get_remote_url(
remote) if remote else None
# Register the repository in the repo tree as a submodule
try:
ds.repo.add_submodule(subds_relpath,
url=subds_url,
name=None)
except CommandError as e:
yield get_status_dict(ds=subds,
status='error',
message=e.stderr,
**dict(common_report, **ap))
continue
# queue for saving using the updated annotated path
ap['registered_subds'] = True
# I hope this is true in direct mode too
# TODO this is disabled, because in some circumstances
# staging just doesn't happen, and it is unclear when
# exactly -- the case that prompted disabling was a submodule
# that had no content except for other submodules was not staged,
# whereas another submodule on the same level in the same
# superdataset which also has one file in it was staged
# disable to work correctly, while paying a little bit of
# slow down
#ap['staged'] = True
to_save.append(ap)
_fixup_submodule_dotgit_setup(ds, subds_relpath)
# report added subdatasets -- `annex add` below won't do it
yield get_status_dict(ds=subds,
status='ok',
message='added new subdataset',
**dict(common_report, **ap))
# make sure that .gitmodules is added to the list of files
gitmodules_path = opj(ds.path, '.gitmodules')
# for git
torepoadd[gitmodules_path] = dict(path=gitmodules_path)
# and for save
to_save.append(
dict(path=gitmodules_path, parentds=ds_path, type='file'))
# make sure any last minute additions make it to the saving stage
# XXX? should content_by_ds become OrderedDict so that possible
# super here gets processed last?
lgr.debug('Adding content to repo %s: %s', ds.repo, torepoadd)
is_annex = isinstance(ds.repo, AnnexRepo)
add_kw = {'jobs': jobs} if is_annex and jobs else {}
added = ds.repo.add(list(torepoadd.keys()),
git=to_git if is_annex else True,
**add_kw)
for a in added:
res = annexjson2result(a, ds, type='file', **common_report)
success = success_status_map[res['status']]
respath_by_status[success] = \
respath_by_status.get(success, []) + [res['path']]
# produce best possible path/result annotation
if res['path'] in torepoadd:
# pull out correct ap for any path that comes out here
# (that we know things about), and use the original annotation
# instead of just the annex report
res = dict(torepoadd[res['path']], **res)
# override this in all cases to be safe
res['parentds'] = ds.path
if success:
# this was successfully added, queue for saving this very path
# in the dataset
ap = {k: v for k, v in res.items() if k != 'status'}
ap['staged'] = True
# strip any status and state info (e.g. save will refuse to save
# stuff that is marked state='untracked'
to_save.append({
k: v
for k, v in res.items() if k not in ('status', 'state')
})
if a['file'] == '.gitmodules':
# filter out .gitmodules, because this is only included for
# technical reasons and has nothing to do with the actual content
continue
if GitRepo.is_valid_repo(res['path']):
# more accurate report in case of an added submodule
# mountpoint.
# XXX Actually not sure if this can really happen
# (depends on what our low-level code would do)
# but worst case is that we loose a little bit of
# coverage...
res['type'] = 'dataset'
res['message'] = 'added new state as submodule'
yield res
for r in results_from_annex_noinfo(
ds,
torepoadd,
respath_by_status,
dir_fail_msg='could not add some content in %s %s',
noinfo_dir_msg='nothing to add from %s',
noinfo_file_msg='already included in the dataset',
action='add',
logger=lgr,
refds=refds_path):
if r['path'] in torepoadd:
# pull out correct ap for any path that comes out here
# (that we know things about), and use the original annotation
# instead of just the annex report
r = dict(r, **torepoadd[r['path']])
if r['status'] == 'notneeded':
# this could be a file that was staged already, it doesn't need
# to be added, but it should be saved/commited if so desired
to_save.append({
k: v
for k, v in r.items() if k not in ('status', 'state')
})
# XXX something is fishy with the next one, rethink when sober....
if r['path'] == ds_path and r['status'] == 'ok':
# this is for the entire dataset itself which was explicitly requested
# make sure to save all
r['type'] = 'dataset'
r['process_content'] = True
to_save.append(
{k: v
for k, v in r.items() if k != 'status'})
yield r
if refds_path and ds_path != refds_path and len(
respath_by_status.get('success', [])):
# TODO XXX we have an issue here when with `add('.')` and annex ignores any
# dotfiles. In this case we end up not saving a dataset completely, because
# we rely on accurate reporting. there is an issue about this already
# TODO look up the issue ID
# if there is a base dataset, but we are below it, and we have anything done to this
# dataset -> queue dataset itself for saving its state in the parent
ds_ap = dict(
path=ds.path,
# we have to look for the parent here, as we must save the
# subdataset in the parent and not the whole subdataset itself
type='dataset')
parentds = get_dataset_root(normpath(opj(ds.path, pardir)))
if parentds:
ds_ap['parentds'] = parentds
if dataset:
ds_ap['refds'] = refds_path
to_save.append(ds_ap)
if not save:
lgr.debug('Not calling `save` as instructed')
return
# TODO tell save what was staged already! Set 'staged=True' for
# respective annotated paths that are fed into `save`
# do not reuse any of the sorting done in here for saving, but instead
# pass on all the annotated paths to have `save` figure out what to do with
# them -- this is costs something, but should be safer, and frankly is
# more comprehensible
for res in Save.__call__(
# hand-selected annotated paths
path=to_save,
dataset=refds_path,
message=message if message else '[DATALAD] added content',
return_type='generator',
result_xfm=None,
result_filter=None,
on_failure='ignore'):
yield res
def __call__(path=None,
dataset=None,
merge_native='init',
recursive=False,
recursion_limit=None,
save=True):
refds_path = Interface.get_refds_path(dataset)
# it really doesn't work without a dataset
ds = require_dataset(dataset,
check_installed=True,
purpose='metadata aggregation')
# always include the reference dataset
path = assure_list(path)
path.append(ds.path)
agginfo_db = {}
to_save = []
to_aggregate = set()
for ap in AnnotatePaths.__call__(
dataset=refds_path,
path=path,
recursive=recursive,
recursion_limit=recursion_limit,
action='aggregate_metadata',
# uninstalled subdatasets could be queried via aggregated metadata
# -> no 'error'
unavailable_path_status='',
nondataset_path_status='error',
return_type='generator',
on_failure='ignore'):
if ap.get('status', None):
# this is done
yield ap
continue
ap_type = ap.get('type', None)
ap_state = ap.get('state', None)
assert ('parentds' in ap or ap_type == 'dataset')
if ap_type == 'dataset' and ap_state != 'absent':
# a present dataset, we can take directly from it
aggsrc = ap['path']
lgr.info('Aggregate metadata for dataset %s', aggsrc)
else:
# everything else needs to come from the parent
aggsrc = ap['parentds']
if ap_state == 'absent':
lgr.info(
'Attempt to use pre-aggregate metadata for absent %s from dataset at %s',
ap['path'], aggsrc)
else:
lgr.info('Aggregate metadata for %s from dataset at %s',
ap['path'], aggsrc)
to_aggregate.add(aggsrc)
if ap_state == 'absent':
# key thought: recursive is done by path annotation, hence
# once we hit an absent dataset, we are 100% certain that
# there is nothing to recurse into on the file system
# hence we only have to look into the aggregated metadata
# of the last available dataset in the dataset tree edge
#
# if there is nothing at this path, we need to look into the
# parentds and check if we know anything about this path
# if we do, we need to grab all the info and objects
# if not, we need to error
res = _get_dsinfo_from_aggmetadata(aggsrc, ap['path'],
recursive, agginfo_db)
if not isinstance(res, list):
yield get_status_dict(status='impossible',
message=res,
action='aggregate_metadata',
path=ap['path'],
logger=lgr)
continue
# cue for aggregation
to_aggregate.update(res)
else:
# actually aggregate metadata for this dataset, immediately place
# generated objects into the aggregated or reference dataset,
# and put info into DB to get the distributed to all datasets
# that need to be updated
errored = _extract_metadata(ds, Dataset(aggsrc), agginfo_db,
merge_native, to_save)
if errored:
yield get_status_dict(
status='error',
message=
'Metadata extraction failed (see previous error message)',
action='aggregate_metadata',
path=aggsrc,
logger=lgr)
# at this point we have dumped all aggregated metadata into object files
# somewhere, we know what needs saving, but having saved anything, and
# we know about the states of all aggregated dataset in the DB
# what remains to do is to update all dataset, so they have there own copy
# of aggregated metadata and update their respective aggregate.json with
# info on what states we just aggregated from
# first, let's figure out what dataset need updating at all
# get adjencency info of the dataset tree spanning the base to all leaf dataset
# associated with the path arguments
ds_adj = {}
discover_dataset_trace_to_targets(ds.path, to_aggregate, [], ds_adj)
# TODO we need to work in the info about dataset that we only got from
# aggregated metadata, that had no trace on the file system in here!!
subtrees = _adj2subtrees(ds.path, ds_adj, to_aggregate)
# go over datasets in bottom-up fashion
for parentds_path in sorted(subtrees, reverse=True):
lgr.info('Update aggregate metadata in dataset at: %s',
parentds_path)
_update_ds_agginfo(ds.path, parentds_path, subtrees[parentds_path],
agginfo_db, to_save)
# update complete
yield get_status_dict(status='ok',
action='aggregate_metadata',
path=parentds_path,
type='dataset',
logger=lgr)
#
# save potential modifications to dataset global metadata
#
if not to_save:
return
lgr.info('Attempting to save %i files/datasets', len(to_save))
for res in Save.__call__(
path=to_save,
dataset=refds_path,
message='[DATALAD] dataset aggregate metadata update',
return_type='generator',
result_xfm=None,
result_filter=None,
on_failure='ignore'):
yield res
def __call__(path=None,
dataset=None,
recursive=False,
check=True,
save=True,
message=None,
if_dirty='save-before'):
res_kwargs = dict(action='remove', logger=lgr)
if not dataset and not path:
raise InsufficientArgumentsError(
"insufficient information for `remove`: requires at least a path or dataset"
)
refds_path = Interface.get_refds_path(dataset)
res_kwargs['refds'] = refds_path
if refds_path and not path and not GitRepo.is_valid_repo(refds_path):
# nothing here, nothing to remove
yield get_status_dict(path=refds_path,
status='notneeded',
**res_kwargs)
return
if refds_path and not path:
# act on the whole dataset if nothing else was specified
# TODO i think that would happen automatically in annotation?
path = refds_path
to_process = []
for ap in AnnotatePaths.__call__(
path=path,
dataset=refds_path,
recursive=recursive,
# we only ever want to discover immediate subdatasets, the rest
# will happen in `uninstall`
recursion_limit=1,
action='remove',
unavailable_path_status='',
nondataset_path_status='error',
return_type='generator',
on_failure='ignore'):
if ap.get('status', None):
# this is done
yield ap
continue
if ap.get('state', None) == 'absent' and \
ap.get('parentds', None) is None:
# nothing exists at location, and there is no parent to
# remove from
ap['status'] = 'notneeded'
ap['message'] = "path does not exist and is not in a dataset"
yield ap
continue
if ap.get('raw_input', False) and ap.get('type',
None) == 'dataset':
# make sure dataset sorting yields a dedicted entry for this one
ap['process_content'] = True
to_process.append(ap)
if not to_process:
# nothing left to do, potentially all errored before
return
if path_is_under([ap['path'] for ap in to_process]):
# behave like `rm` and refuse to remove where we are
raise ValueError(
"refusing to uninstall current or parent directory")
# now sort into datasets so we can process them one by one
content_by_ds, ds_props, completed, nondataset_paths = \
annotated2content_by_ds(
to_process,
refds_path=refds_path)
assert (not completed)
# iterate over all datasets, starting at the bottom
# to make the removal of dataset content known upstairs
to_save = []
# track which submodules we have removed in the process, to avoid
# failure in case we revisit them due to a subsequent path argument
subm_removed = []
for ds_path in sorted(content_by_ds, reverse=True):
ds = Dataset(ds_path)
paths = content_by_ds[ds_path]
to_reporemove = dict()
# PLAN any dataset that was not raw_input, uninstall (passing recursive flag)
# if dataset itself is in paths, skip any nondataset
# sort reverse so we get subdatasets first
for ap in sorted(paths, key=lambda x: x['path'], reverse=True):
if ap.get('type', None) == 'dataset':
# entire dataset needs to go, uninstall if present, pass recursive!
uninstall_failed = False
if ap['path'] == refds_path or \
(refds_path is None and ap.get('raw_input', False)):
# top-level handling, cannot use regular uninstall call, as
# it will refuse to uninstall a top-level dataset
# and rightfully so, it is really a remove in that case
# bypass all the safety by using low-level helper
for r in _uninstall_dataset(ds,
check=check,
has_super=False,
**res_kwargs):
if r['status'] in ('impossible', 'error'):
# we need to inspect if something went wrong, in order
# to prevent failure from removing a non-empty dir below,
# but at the same time allow for continued processing
uninstall_failed = True
r['refds'] = refds_path
yield r
# recheck that it wasn't removed during a previous iteration
elif ap.get('state',
None) != 'absent' and GitRepo.is_valid_repo(
ap['path']):
# anything that is not the top-level -> regular uninstall
# this is for subdatasets of the to-be-removed dataset
# we want to simply uninstall them in a regular manner
for r in Uninstall.__call__(
# use annotate path as input, but pass a copy because
# we cannot rely on it being unaltered by reannotation
# TODO maybe adjust annotate_path to do that
[ap.copy()],
dataset=refds_path,
recursive=recursive,
check=check,
if_dirty=if_dirty,
result_xfm=None,
result_filter=None,
on_failure='ignore'):
if r['status'] in ('impossible', 'error'):
# we need to inspect if something went wrong, in order
# to prevent failure from removing a non-empty dir below,
# but at the same time allow for continued processing
uninstall_failed = True
yield r
if not ap.get('raw_input', False):
# we only ever want to actually unregister subdatasets that
# were given explicitly
continue
if not uninstall_failed and \
not ap['path'] in subm_removed and \
refds_path and \
ap.get('parentds', None) and \
not (relpath(ap['path'], start=refds_path).startswith(pardir) or
ap['path'] == refds_path) and \
ap.get('registered_subds', False):
# strip from superdataset, but only if a dataset was given explcitly
# as in "remove from this dataset", but not when just a path was given
# as in "remove from the filesystem"
subds_relpath = relpath(ap['path'],
start=ap['parentds'])
# remove submodule reference
parentds = Dataset(ap['parentds'])
# play safe, will fail on dirty
parentds.repo.deinit_submodule(ap['path'])
# remove now empty submodule link
parentds.repo.remove(ap['path'])
# make a record that we removed this already, should it be
# revisited via another path argument, because do not reannotate
# the paths after every removal
subm_removed.append(ap['path'])
yield dict(ap, status='ok', **res_kwargs)
# need .gitmodules update in parent
to_save.append(
dict(path=opj(parentds.path, '.gitmodules'),
parents=parentds.path,
type='file'))
# and the removal itself needs to be committed
# inform `save` that it is OK that this path
# doesn't exist on the filesystem anymore
ap['unavailable_path_status'] = ''
ap['process_content'] = False
to_save.append(ap)
if not uninstall_failed and exists(ap['path']):
# could be an empty dir in case an already uninstalled subdataset
# got removed
rmdir(ap['path'])
else:
# anything that is not a dataset can simply be passed on
to_reporemove[ap['path']] = ap
# avoid unnecessary git calls when there is nothing to do
if to_reporemove:
if check and hasattr(ds.repo, 'drop'):
for r in _drop_files(ds, list(to_reporemove), check=True):
if r['status'] == 'error':
# if drop errored on that path, we can't remove it
to_reporemove.pop(r['path'], 'avoidKeyError')
yield r
if to_reporemove:
for r in ds.repo.remove(list(to_reporemove), r=True):
# these were removed, but we still need to save the
# removal
r_abs = opj(ds.path, r)
if r_abs in to_reporemove:
ap = to_reporemove[r_abs]
else:
ap = {
'path': r_abs,
'parentds': ds.path,
'refds': refds_path
}
ap['unavailable_path_status'] = ''
to_save.append(ap)
yield get_status_dict(status='ok',
path=r,
**res_kwargs)
if not to_save:
# nothing left to do, potentially all errored before
return
if not save:
lgr.debug('Not calling `save` as instructed')
return
for res in Save.__call__(
# TODO compose hand-selected annotated paths
path=to_save,
# we might have removed the reference dataset by now, recheck
dataset=refds_path if
(refds_path and GitRepo.is_valid_repo(refds_path)) else None,
message=message if message else '[DATALAD] removed content',
return_type='generator',
result_xfm=None,
result_filter=None,
on_failure='ignore'):
yield res
def __call__(path=None,
dataset=None,
add=None,
init=None,
remove=None,
reset=None,
define_key=None,
dataset_global=False,
recursive=False,
recursion_limit=None):
# bring metadataset setter args in shape first
untag, remove = _parse_argspec(remove)
purge, reset = _parse_argspec(reset)
tag_add, add = _parse_argspec(add)
tag_init, init = _parse_argspec(init)
define_key = dict(define_key) if define_key else None
# merge all potential sources of tag specifications
all_untag = remove.get('tag', []) + untag
if all_untag:
remove['tag'] = all_untag
all_addtag = add.get('tag', []) + tag_add
if all_addtag:
add['tag'] = all_addtag
all_inittag = init.get('tag', []) + tag_init
if all_inittag:
init['tag'] = all_inittag
lgr.debug("Will 'init' metadata items: %s", init)
lgr.debug("Will 'add' metadata items: %s", add)
lgr.debug("Will 'remove' metadata items: %s", remove)
lgr.debug("Will 'reset' metadata items: %s", reset)
lgr.debug("Will 'purge' metadata items: %s", purge)
refds_path = Interface.get_refds_path(dataset)
res_kwargs = dict(action='metadata', logger=lgr, refds=refds_path)
to_process = []
for ap in AnnotatePaths.__call__(dataset=refds_path,
path=path,
recursive=recursive,
recursion_limit=recursion_limit,
action='metadata',
unavailable_path_status='error',
nondataset_path_status='error',
force_subds_discovery=False,
return_type='generator',
on_failure='ignore'):
if ap.get('status', None):
# this is done
yield ap
continue
if ap.get('type', None) == 'dataset':
if ap.get('state', None) == 'absent':
# just discovered via recursion, but not relevant here
continue
if GitRepo.is_valid_repo(ap['path']):
ap['process_content'] = True
to_process.append(ap)
content_by_ds, ds_props, completed, nondataset_paths = \
annotated2content_by_ds(
to_process,
refds_path=refds_path,
path_only=False)
assert (not completed)
# iterate over all datasets, order doesn't matter
to_save = []
for ds_path in content_by_ds:
# ignore submodule entries
content = [
ap for ap in content_by_ds[ds_path]
if ap.get('type', None) != 'dataset' or ap['path'] == ds_path
]
if not content:
# nothing other than subdatasets were given or discovered in
# this dataset, ignore
continue
ds = Dataset(ds_path)
if dataset_global or define_key:
db_path = opj(ds.path, '.datalad', 'metadata', 'dataset.json')
db = {}
if exists(db_path):
db_fp = open(db_path)
# need to read manually, load() would puke on an empty file
db_content = db_fp.read()
# minimize time for collision
db_fp.close()
if db_content:
db = json.loads(db_content)
# TODO make manipulation order identical to what git-annex does
for k, v in init.items() if init else []:
if k not in db:
db[k] = v
for k in purge:
if k in db:
del db[k]
for k, v in reset.items():
db[k] = v
for k, v in add.items():
db[k] = sorted(unique(db.get(k, []) + v))
for k, v in remove.items():
existing_data = db.get(k, [])
if isinstance(existing_data, dict):
db[k] = {
dk: existing_data[dk]
for dk in set(existing_data).difference(v)
}
else:
db[k] = list(set(existing_data).difference(v))
# wipe out if empty
if not db[k]:
del db[k]
added_def = False
if define_key:
defs = db.get('definition', {})
for k, v in define_key.items():
if k in defs:
if not defs[k] == v:
yield get_status_dict(
status='error',
ds=ds,
message=
("conflicting definition for key '%s': '%s' != '%s'",
k, v, defs[k]),
**res_kwargs)
continue
else:
defs[k] = v
added_def = True
db['definition'] = defs
# store, if there is anything
if db:
if not exists(dirname(db_path)):
makedirs(dirname(db_path))
db_fp = open(db_path, 'w')
# produce relatively compact, but also diff-friendly format
json.dump(db,
db_fp,
indent=0,
separators=(',', ':\n'),
sort_keys=True)
# minimize time for collision
db_fp.close()
# use add not save to also cover case of a fresh file
ds.add(db_path, save=False)
to_save.append(
dict(path=db_path, parentds=ds.path, type='file'))
elif exists(db_path):
# no metadata left, kill file
ds.remove(db_path)
to_save.append(dict(path=ds.path, type='dataset'))
if added_def or init or add or remove or reset or purge:
# if anything happended or could have happended
yield get_status_dict(status='ok',
ds=ds,
metadata=db,
**res_kwargs)
elif not isinstance(ds.repo, AnnexRepo):
# report on all explicitly requested paths only
for ap in [c for c in content if ap.get('raw_input', False)]:
yield dict(
ap,
status='impossible',
message=(
'non-annex dataset %s has no file metadata support',
ds),
**res_kwargs)
continue
ds_paths = [p['path'] for p in content]
if not dataset_global:
if reset or purge or add or init or remove:
# file metadata manipulation
mod_paths = []
for mp in ds.repo.set_metadata(
ds_paths,
reset=reset,
add=add,
init=init,
remove=remove,
purge=purge,
# we always go recursive
# TODO is that a good thing? But how to otherwise distinuish
# this kind of recursive from the one across datasets in
# the API?
recursive=True):
if mp.get('success', False):
mod_paths.append(mp['file'])
else:
yield get_status_dict(
status='error',
message='setting metadata failed',
path=opj(ds.path, mp[0]),
type='file',
**res_kwargs)
# query the actually modified paths only
ds_paths = mod_paths
# and lastly, query -- even if we set before -- there could
# be side-effect from multiple set paths on an individual
# path, hence we need to query to get the final result
for file, meta in ds.repo.get_metadata(ds_paths):
r = get_status_dict(status='ok',
path=opj(ds.path, file),
type='file',
metadata=meta,
**res_kwargs)
yield r
# save potential modifications to dataset global metadata
if not to_save:
return
for res in Save.__call__(path=to_save,
dataset=refds_path,
message='[DATALAD] dataset metadata update',
return_type='generator',
result_xfm=None,
result_filter=None,
on_failure='ignore'):
yield res
def __call__(
path=None,
dataset=None,
recursive=False,
check=True,
save=True,
message=None,
if_dirty='save-before'):
res_kwargs = dict(action='remove', logger=lgr)
if not dataset and not path:
raise InsufficientArgumentsError(
"insufficient information for `remove`: requires at least a path or dataset")
refds_path = Interface.get_refds_path(dataset)
res_kwargs['refds'] = refds_path
if refds_path and not path and not GitRepo.is_valid_repo(refds_path):
# nothing here, nothing to remove
yield get_status_dict(path=refds_path, status='notneeded', **res_kwargs)
return
if refds_path and not path:
# act on the whole dataset if nothing else was specified
# TODO i think that would happen automatically in annotation?
path = refds_path
to_process = []
for ap in AnnotatePaths.__call__(
path=path,
dataset=refds_path,
recursive=recursive,
# we only ever want to discover immediate subdatasets, the rest
# will happen in `uninstall`
recursion_limit=1,
action='remove',
unavailable_path_status='',
nondataset_path_status='error',
return_type='generator',
on_failure='ignore'):
if ap.get('status', None):
# this is done
yield ap
continue
if ap.get('state', None) == 'absent' and \
ap.get('parentds', None) is None:
# nothing exists at location, and there is no parent to
# remove from
ap['status'] = 'notneeded'
ap['message'] = "path does not exist and is not in a dataset"
yield ap
continue
if ap.get('raw_input', False) and ap.get('type', None) == 'dataset':
# make sure dataset sorting yields a dedicted entry for this one
ap['process_content'] = True
to_process.append(ap)
if not to_process:
# nothing left to do, potentially all errored before
return
if path_is_under([ap['path'] for ap in to_process]):
# behave like `rm` and refuse to remove where we are
raise ValueError(
"refusing to uninstall current or parent directory")
# now sort into datasets so we can process them one by one
content_by_ds, ds_props, completed, nondataset_paths = \
annotated2content_by_ds(
to_process,
refds_path=refds_path)
assert(not completed)
# iterate over all datasets, starting at the bottom
# to make the removal of dataset content known upstairs
to_save = []
# track which submodules we have removed in the process, to avoid
# failure in case we revisit them due to a subsequent path argument
subm_removed = []
for ds_path in sorted(content_by_ds, reverse=True):
ds = Dataset(ds_path)
paths = content_by_ds[ds_path]
to_reporemove = dict()
# PLAN any dataset that was not raw_input, uninstall (passing recursive flag)
# if dataset itself is in paths, skip any nondataset
# sort reverse so we get subdatasets first
for ap in sorted(paths, key=lambda x: x['path'], reverse=True):
if ap.get('type', None) == 'dataset':
# entire dataset needs to go, uninstall if present, pass recursive!
uninstall_failed = False
if ap['path'] == refds_path or \
(refds_path is None and ap.get('raw_input', False)):
# top-level handling, cannot use regular uninstall call, as
# it will refuse to uninstall a top-level dataset
# and rightfully so, it is really a remove in that case
# bypass all the safety by using low-level helper
for r in _uninstall_dataset(ds, check=check, has_super=False,
**res_kwargs):
if r['status'] in ('impossible', 'error'):
# we need to inspect if something went wrong, in order
# to prevent failure from removing a non-empty dir below,
# but at the same time allow for continued processing
uninstall_failed = True
r['refds'] = refds_path
yield r
# recheck that it wasn't removed during a previous iteration
elif ap.get('state', None) != 'absent' and GitRepo.is_valid_repo(ap['path']):
# anything that is not the top-level -> regular uninstall
# this is for subdatasets of the to-be-removed dataset
# we want to simply uninstall them in a regular manner
for r in Uninstall.__call__(
# use annotate path as input, but pass a copy because
# we cannot rely on it being unaltered by reannotation
# TODO maybe adjust annotate_path to do that
[ap.copy()],
dataset=refds_path, recursive=recursive, check=check,
if_dirty=if_dirty, result_xfm=None, result_filter=None,
on_failure='ignore'):
if r['status'] in ('impossible', 'error'):
# we need to inspect if something went wrong, in order
# to prevent failure from removing a non-empty dir below,
# but at the same time allow for continued processing
uninstall_failed = True
yield r
if not ap.get('raw_input', False):
# we only ever want to actually unregister subdatasets that
# were given explicitly
continue
if not uninstall_failed and \
not ap['path'] in subm_removed and \
refds_path and \
ap.get('parentds', None) and \
not (relpath(ap['path'], start=refds_path).startswith(pardir) or
ap['path'] == refds_path) and \
ap.get('registered_subds', False):
# strip from superdataset, but only if a dataset was given explcitly
# as in "remove from this dataset", but not when just a path was given
# as in "remove from the filesystem"
subds_relpath = relpath(ap['path'], start=ap['parentds'])
# remove submodule reference
parentds = Dataset(ap['parentds'])
# play safe, will fail on dirty
parentds.repo.deinit_submodule(ap['path'])
# remove now empty submodule link
parentds.repo.remove(ap['path'])
# make a record that we removed this already, should it be
# revisited via another path argument, because do not reannotate
# the paths after every removal
subm_removed.append(ap['path'])
yield dict(ap, status='ok', **res_kwargs)
# need .gitmodules update in parent
to_save.append(dict(
path=opj(parentds.path, '.gitmodules'),
parents=parentds.path,
type='file'))
# and the removal itself needs to be committed
# inform `save` that it is OK that this path
# doesn't exist on the filesystem anymore
ap['unavailable_path_status'] = ''
ap['process_content'] = False
to_save.append(ap)
if not uninstall_failed and exists(ap['path']):
# could be an empty dir in case an already uninstalled subdataset
# got removed
rmdir(ap['path'])
else:
# anything that is not a dataset can simply be passed on
to_reporemove[ap['path']] = ap
# avoid unnecessary git calls when there is nothing to do
if to_reporemove:
if check and hasattr(ds.repo, 'drop'):
for r in _drop_files(ds, list(to_reporemove),
check=True):
if r['status'] == 'error':
# if drop errored on that path, we can't remove it
to_reporemove.pop(r['path'], 'avoidKeyError')
yield r
if to_reporemove:
for r in ds.repo.remove(list(to_reporemove), r=True):
# these were removed, but we still need to save the
# removal
r_abs = opj(ds.path, r)
if r_abs in to_reporemove:
ap = to_reporemove[r_abs]
else:
ap = {'path': r_abs,
'parentds': ds.path,
'refds': refds_path
}
ap['unavailable_path_status'] = ''
to_save.append(ap)
yield get_status_dict(
status='ok',
path=r,
**res_kwargs)
if not to_save:
# nothing left to do, potentially all errored before
return
if not save:
lgr.debug('Not calling `save` as instructed')
return
for res in Save.__call__(
# TODO compose hand-selected annotated paths
path=to_save,
# we might have removed the reference dataset by now, recheck
dataset=refds_path
if (refds_path and GitRepo.is_valid_repo(refds_path))
else None,
message=message if message else '[DATALAD] removed content',
return_type='generator',
result_xfm=None,
result_filter=None,
on_failure='ignore'):
yield res
def test_interface_prep():
# verify sanity if nothing was given, as it would look like from the
# cmdline
assert_equal(Save._prep(path=[], dataset=None), ({}, []))
def __call__(path=None,
source=None,
dataset=None,
to_git=False,
save=True,
recursive=False,
recursion_limit=None,
if_dirty='ignore',
git_opts=None,
annex_opts=None,
annex_add_opts=None,
jobs=None):
# parameter constraints:
if not path and not source:
raise InsufficientArgumentsError(
"insufficient information for "
"adding: requires at least a path "
"or a source.")
# When called from cmdline `path` and `source` will be a list even if
# there is only one item.
# Make sure we deal with the same when called via python API:
# always yields list; empty if None
path = assure_list(path)
source = assure_list(source)
# TODO: Q: are the list operations in the following 3 blocks (resolving
# paths, sources and datasets) guaranteed to be stable
# regarding order?
# resolve path(s):
# TODO: RF: resolve_path => datalad.utils => more general (repos => normalize paths)
resolved_paths = [resolve_path(p, dataset) for p in path]
# must come after resolve_path()!!
# resolve dataset:
dataset = require_dataset(dataset,
check_installed=True,
purpose='adding')
handle_dirty_dataset(dataset, if_dirty)
# resolve source(s):
resolved_sources = []
for s in source:
if not is_datalad_compat_ri(s):
raise ValueError("invalid source parameter: %s" % s)
resolved_sources.append(_get_git_url_from_source(s))
# find (sub-)datasets to add things to (and fail on invalid paths):
if recursive:
# 1. Find the (sub-)datasets containing the given path(s):
# Note, that `get_containing_subdataset` raises if `p` is
# outside `dataset`, but it returns `dataset`, if `p` is inside
# a subdataset not included by `recursion_limit`. In the latter
# case, the git calls will fail instead.
# We could check for this right here and fail early, but this
# would lead to the need to discover the entire hierarchy no
# matter if actually required.
resolved_datasets = [
dataset.get_containing_subdataset(
p, recursion_limit=recursion_limit) for p in resolved_paths
]
# 2. Find implicit subdatasets to call add on:
# If there are directories in resolved_paths (Note,
# that this includes '.' and '..'), check for subdatasets
# beneath them. These should be called recursively with '.'.
# Therefore add the subdatasets to resolved_datasets and
# corresponding '.' to resolved_paths, in order to generate the
# correct call.
for p in resolved_paths:
if isdir(p):
for subds_path in \
dataset.get_subdatasets(absolute=True, recursive=True,
recursion_limit=recursion_limit):
if subds_path.startswith(_with_sep(p)):
resolved_datasets.append(Dataset(subds_path))
resolved_paths.append(curdir)
else:
# if not recursive, try to add everything to dataset itself:
resolved_datasets = [dataset for i in range(len(resolved_paths))]
# we need a resolved dataset per path:
assert len(resolved_paths) == len(resolved_datasets)
# sort parameters for actual git/git-annex calls:
# (dataset, path, source)
from six.moves import zip_longest
param_tuples = list(
zip_longest(resolved_datasets, resolved_paths, resolved_sources))
# possible None-datasets in `param_tuples` were filled in by zip_longest
# and need to be replaced by `dataset`:
param_tuples = [(d if d is not None else dataset, p, s)
for d, p, s in param_tuples]
calls = {
d.path: { # list of paths to 'git-add':
'g_add': [],
# list of paths to 'git-annex-add':
'a_add': [],
# list of sources to 'git-annex-addurl':
'addurl_s': [],
# list of (path, source) to
# 'git-annex-addurl --file':
'addurl_f': []
}
for d in [i for i, p, s in param_tuples]
}
for ds, p, s in param_tuples:
# it should not happen, that `path` as well as `source` are None:
assert p or s
if not s:
# we have a path only
# Do not try to add to annex whenever there is no annex
if to_git or not isinstance(ds.repo, AnnexRepo):
calls[ds.path]['g_add'].append(p)
else:
calls[ds.path]['a_add'].append(p)
elif not p:
# we have a source only
if to_git:
raise NotImplementedError("Can't add a remote source "
"directly to git.")
calls[ds.path]['addurl_s'].append(s)
else:
# we have a path and a source
if to_git:
raise NotImplementedError("Can't add a remote source "
"directly to git.")
calls[ds.path]['addurl_f'].append((p, s))
# now do the actual add operations:
# TODO: implement git/git-annex/git-annex-add options
datasets_return_values = defaultdict(list)
for dspath in calls:
ds = Dataset(dspath)
return_values = datasets_return_values[dspath]
lgr.info("Processing dataset %s ..." % ds)
# check every (sub-)dataset for annex once, since we can't add or
# addurl anything, if there is no annex:
# TODO: Q: Alternatively, just call git-annex-init if there's no
# annex yet and we have an annex-add/annex-addurl request?
_is_annex = isinstance(ds.repo, AnnexRepo)
if calls[ds.path]['g_add']:
lgr.debug("Adding %s to git", calls[dspath]['g_add'])
added = ds.repo.add(calls[dspath]['g_add'],
git=True,
git_options=git_opts)
return_values.extend(added)
if calls[ds.path]['a_add']:
if _is_annex:
lgr.debug("Adding %s to annex", calls[dspath]['a_add'])
return_values.extend(
ds.repo.add(calls[dspath]['a_add'],
git=False,
jobs=jobs,
git_options=git_opts,
annex_options=annex_opts,
options=annex_add_opts))
else:
lgr.debug("{0} is no annex. Skip 'annex-add' for "
"files {1}".format(ds, calls[dspath]['a_add']))
return_values.extend([{
'file': f,
'success': False,
'note': "no annex at %s" % ds.path
} for f in calls[dspath]['a_add']])
# TODO: AnnexRepo.add_urls' return value doesn't contain the created
# file name but the url
if calls[ds.path]['addurl_s']:
if _is_annex:
lgr.debug("Adding urls %s to annex",
calls[dspath]['addurl_s'])
return_values.extend(
ds.repo.add_urls(
calls[ds.path]['addurl_s'],
options=annex_add_opts,
# TODO: extra parameter for addurl?
git_options=git_opts,
annex_options=annex_opts,
jobs=jobs,
))
else:
lgr.debug("{0} is no annex. Skip 'annex-addurl' for "
"files {1}".format(ds,
calls[dspath]['addurl_s']))
return_values.extend([{
'file': f,
'success': False,
'note': "no annex at %s" % ds.path
} for f in calls[dspath]['addurl_s']])
if calls[ds.path]['addurl_f']:
if _is_annex:
for f, u in calls[ds.path]['addurl_f']:
lgr.debug("Adding urls %s to files in annex",
calls[dspath]['addurl_f'])
return_values.append(
ds.repo.add_url_to_file(
f,
u,
options=annex_add_opts, # TODO: see above
git_options=git_opts,
annex_options=annex_opts,
batch=True))
else:
lgr.debug("{0} is no annex. Skip 'annex-addurl' for "
"files {1}".format(ds,
calls[dspath]['addurl_f']))
return_values.extend([{
'file': f,
'success': False,
'note': "no annex at %s" % ds.path
} for f in calls[dspath]['addurl_f']])
return_values = None # to avoid mis-use
# XXX or we could return entire datasets_return_values, could be useful
# that way. But then should be unified with the rest of commands, e.g.
# get etc
return_values_flat = []
for dspath, return_values in datasets_return_values.items():
if save and len(return_values):
# we got something added -> save
# everything we care about at this point should be staged already
Save.__call__(message='[DATALAD] added content',
dataset=ds,
auto_add_changes=False,
recursive=False)
# TODO: you feels that this is some common logic we already have somewhere
dsrelpath = relpath(dspath, dataset.path)
if dsrelpath != curdir:
# we need ot adjust 'file' entry in each record
for return_value in return_values:
if 'file' in return_value:
return_value['file'] = opj(dsrelpath,
return_value['file'])
return_values_flat.append(return_value)
else:
return_values_flat.extend(return_values)
return return_values_flat
def __call__(
path=None,
dataset=None,
remove_data=True,
remove_handles=False,
recursive=False,
remove_history=False,
check=True,
kill=False,
if_dirty='save-before'):
# upfront check prior any resolution attempt to avoid disaster
if path is None and dataset is None:
raise InsufficientArgumentsError(
"insufficient information for uninstallation (needs at "
"least a dataset or a path. To uninstall an entire dataset "
"it needs to be given explicitly.")
if remove_history and not remove_handles:
raise ValueError("`remove_history` flag, requires `remove_handles` flag")
if not remove_data and not remove_handles:
raise ValueError("instructed to neither drop data, nor remove handles: cannot perform")
path, dataset_path = get_normalized_path_arguments(
path, dataset, default=curdir)
results = []
if kill:
lgr.warning("Force-removing %d paths", len(path))
for p in path:
rmtree(p)
results.append(p)
return results
ds = require_dataset(
dataset, check_installed=True, purpose='uninstall')
# make sure we get to an expected state
handle_dirty_dataset(ds, if_dirty)
# sort paths into the respective datasets that contain them
# considering 1st-level subdatasets at most
# NOTE: little dance with two dicts is necessary, because ATM our
# Datasets are not hashable enough for PY3
whocares_paths = {}
whocares_ds = {}
pwd = getpwd()
for p in path:
if remove_handles:
# behave like `rm -r` and refuse to remove where we are
rpath = relpath(p, start=pwd)
if rpath == os.curdir \
or rpath == os.pardir \
or set(psplit(rpath)) == {os.pardir}:
raise ValueError(
"refusing to remove current or parent directory")
containerds = ds.get_containing_subdataset(p, recursion_limit=1)
if not recursive and containerds.path != ds.path:
raise ValueError(
"will not uninstall content in subdatasets without the recursive flag")
ps = whocares_paths.get(containerds.path, [])
ps.append(p)
whocares_paths[containerds.path] = ps
whocares_ds[containerds.path] = containerds
ds_gonealready = False
if ds.path in whocares_paths:
# start with the content of this dataset, as any somewhat
# total recursive removal here would have most impact
lgr.debug("Uninstall content in {}".format(ds))
res, ds_gonealready = _uninstall(
whocares_ds[ds.path],
whocares_paths[ds.path],
check=check,
remove_history=remove_history,
remove_data=remove_data,
remove_handles=remove_handles,
recursive=recursive)
results.extend(res)
if ds_gonealready:
rmtree(ds.path)
# the underlying repo is gone, the assert makes sure that the Dataset
# instance becomes aware of that
assert(not ds.is_installed())
return results
# otherwise deal with any other subdataset
for subdspath in whocares_paths:
subds = whocares_ds[subdspath]
subdsrelpath = relpath(subdspath, start=ds.path)
if subds == ds:
continue
res, subds_gone = _uninstall(
subds,
whocares_paths[subdspath],
check=check,
remove_history=remove_history,
remove_data=remove_data,
remove_handles=remove_handles,
recursive=recursive)
results.extend(res)
if subds_gone:
# clean divorce, if we lost the subds in the process
# find the submodule that matches the patch
# regular access goes by name, but we cannot trust
# our own consistency, yet
submodule = [sm for sm in ds.repo.repo.submodules
if sm.path == subdsrelpath][0]
submodule.remove()
elif remove_handles:
# we could have removed handles -> save
Save.__call__(
message='[DATALAD] uninstalled content',
dataset=subds,
auto_add_changes=False,
recursive=False)
# add this change to the parent, but don't save, will do in
# one go below
ds.repo.add(subdsrelpath, git=True)
if remove_handles:
# something of the original dataset is left at this point
# and all subdatasets have been saved already
# -> save changes
Save.__call__(
message='[DATALAD] uninstalled content',
dataset=ds,
auto_add_changes=False,
recursive=False)
return results
def test_interface_prep():
# verify sanity if nothing was given, as it would look like from the
# cmdline
assert_equal(Save._prep(path=[], dataset=None), ({}, []))
def __call__(
path=None,
dataset=None,
recursive=False,
recursion_limit=None,
update_mode='target',
incremental=False,
force_extraction=False,
save=True):
refds_path = Interface.get_refds_path(dataset)
# it really doesn't work without a dataset
ds = require_dataset(
dataset, check_installed=True, purpose='metadata aggregation')
path = assure_list(path)
if not path:
# then current/reference dataset is "aggregated"
# We should not add ds.path always since then --recursive would
# also recurse current even if paths are given
path.append(ds.path)
agginfo_db_location, agg_base_path = get_ds_aggregate_db_locations(ds)
agginfo_db = load_ds_aggregate_db(ds, abspath=True)
to_save = []
to_aggregate = set()
for ap in AnnotatePaths.__call__(
dataset=refds_path,
path=path,
recursive=recursive,
recursion_limit=recursion_limit,
action='aggregate_metadata',
# uninstalled subdatasets could be queried via aggregated metadata
# -> no 'error'
unavailable_path_status='',
nondataset_path_status='error',
return_type='generator',
on_failure='ignore'):
if ap.get('status', None):
# this is done
yield ap
continue
ap_type = ap.get('type', None)
ap_state = ap.get('state', None)
assert('parentds' in ap or ap_type == 'dataset')
if ap_type == 'dataset' and ap_state != 'absent':
# a present dataset, we can take directly from it
aggsrc = ap['path']
lgr.info('Aggregate metadata for dataset %s', aggsrc)
else:
# everything else needs to come from the parent
aggsrc = ap['parentds']
if ap_state == 'absent':
lgr.info(
'Attempt to use pre-aggregate metadata for absent %s from dataset at %s',
ap['path'],
aggsrc)
else:
lgr.info(
'Aggregate metadata for %s from dataset at %s',
ap['path'],
aggsrc)
to_aggregate.add(aggsrc)
if ap_state == 'absent':
# key thought: recursive is done by path annotation, hence
# once we hit an absent dataset, we are 100% certain that
# there is nothing to recurse into on the file system
# hence we only have to look into the aggregated metadata
# of the last available dataset in the dataset tree edge
#
# if there is nothing at this path, we need to look into the
# parentds and check if we know anything about this path
# if we do, we need to grab all the info and objects
# if not, we need to error
res = _get_dsinfo_from_aggmetadata(
aggsrc, ap['path'], recursive, agginfo_db)
if not isinstance(res, list):
yield get_status_dict(
status='impossible',
message=res,
action='aggregate_metadata',
path=ap['path'],
logger=lgr)
continue
# cue for aggregation
to_aggregate.update(res)
else:
# actually aggregate metadata for this dataset, immediately place
# generated objects into the aggregated or reference dataset,
# and put info into DB to get the distributed to all datasets
# that need to be updated
errored = _dump_extracted_metadata(
ds,
Dataset(aggsrc),
agginfo_db,
to_save,
force_extraction,
agg_base_path)
if errored:
yield get_status_dict(
status='error',
message='Metadata extraction failed (see previous error message, set datalad.runtime.raiseonerror=yes to fail immediately)',
action='aggregate_metadata',
path=aggsrc,
logger=lgr)
# at this point we have dumped all aggregated metadata into object files
# somewhere, we know what needs saving, but having saved anything, and
# we know about the states of all aggregated dataset in the DB
# what remains to do is to update all dataset, so they have there own copy
# of aggregated metadata and update their respective aggregate.json with
# info on what states we just aggregated from
# first, let's figure out what dataset need updating at all
# get adjencency info of the dataset tree spanning the base to all leaf dataset
# associated with the path arguments
if update_mode == 'all':
ds_adj = {}
discover_dataset_trace_to_targets(
ds.path, to_aggregate, [], ds_adj,
# we know that to_aggregate only lists datasets, existing and
# absent ones -- we want to aggregate all of them, either from
# just extracted metadata, or from previously aggregated metadata
# of the closest superdataset
includeds=to_aggregate)
# TODO we need to work in the info about dataset that we only got from
# aggregated metadata, that had no trace on the file system in here!!
subtrees = _adj2subtrees(ds.path, ds_adj, to_aggregate)
elif update_mode == 'target':
subtrees = {ds.path: list(agginfo_db.keys())}
else:
raise ValueError(
"unknown `update_mode` '%s' for metadata aggregation", update_mode)
# go over datasets in bottom-up fashion
for parentds_path in sorted(subtrees, reverse=True):
lgr.info('Update aggregate metadata in dataset at: %s', parentds_path)
_update_ds_agginfo(
ds.path,
parentds_path,
subtrees[parentds_path],
incremental,
agginfo_db,
to_save)
# update complete
res = get_status_dict(
status='ok',
action='aggregate_metadata',
path=parentds_path,
type='dataset',
logger=lgr)
res.update(agginfo_db.get(parentds_path, {}))
yield res
#
# save potential modifications to dataset global metadata
#
if not to_save:
return
lgr.info('Attempting to save %i files/datasets', len(to_save))
for res in Save.__call__(
path=to_save,
dataset=refds_path,
message='[DATALAD] Dataset aggregate metadata update',
return_type='generator',
result_xfm=None,
result_filter=None,
on_failure='ignore'):
yield res
def __call__(path=None,
force=False,
description=None,
dataset=None,
no_annex=False,
save=True,
annex_version=None,
annex_backend='MD5E',
native_metadata_type=None,
if_dirty='save-before',
shared_access=None,
git_opts=None,
annex_opts=None,
annex_init_opts=None):
# two major cases
# 1. we got a `dataset` -> we either want to create it (path is None),
# or another dataset in it (path is not None)
# 2. we got no dataset -> we want to create a fresh dataset at the
# desired location, either at `path` or PWD
# sanity check first
if git_opts:
lgr.warning(
"`git_opts` argument is presently ignored, please complain!")
if no_annex:
if description:
raise ValueError("Incompatible arguments: cannot specify "
"description for annex repo and declaring "
"no annex repo.")
if annex_opts:
raise ValueError("Incompatible arguments: cannot specify "
"options for annex and declaring no "
"annex repo.")
if annex_init_opts:
raise ValueError("Incompatible arguments: cannot specify "
"options for annex init and declaring no "
"annex repo.")
if not isinstance(force, bool):
raise ValueError(
"force should be bool, got %r. Did you mean to provide a 'path'?"
% force)
# straight from input arg, no messing around before this
if path is None:
if dataset is None:
# nothing given explicity, assume create fresh right here
path = getpwd()
else:
# no path, but dataset -> create that dataset
path = dataset.path
else:
# resolve the path against a potential dataset
path = resolve_path(path, ds=dataset)
# we know that we need to create a dataset at `path`
assert (path is not None)
if git_opts is None:
git_opts = {}
if shared_access:
# configure `git --shared` value
git_opts['shared'] = shared_access
# check for sane subdataset path
real_targetpath = with_pathsep(realpath(path)) # realpath OK
if dataset is not None:
# make sure we get to an expected state
if dataset.is_installed():
handle_dirty_dataset(dataset, if_dirty)
if not real_targetpath.startswith( # realpath OK
with_pathsep(realpath(dataset.path))): # realpath OK
raise ValueError("path {} outside {}".format(path, dataset))
# important to use the given Dataset object to avoid spurious ID
# changes with not-yet-materialized Datasets
tbds = dataset if dataset is not None and dataset.path == path else Dataset(
path)
# don't create in non-empty directory without `force`:
if isdir(tbds.path) and listdir(tbds.path) != [] and not force:
raise ValueError("Cannot create dataset in directory %s "
"(not empty). Use option 'force' in order to "
"ignore this and enforce creation." % tbds.path)
if no_annex:
lgr.info("Creating a new git repo at %s", tbds.path)
GitRepo(tbds.path, url=None, create=True, git_opts=git_opts)
else:
# always come with annex when created from scratch
lgr.info("Creating a new annex repo at %s", tbds.path)
AnnexRepo(tbds.path,
url=None,
create=True,
backend=annex_backend,
version=annex_version,
description=description,
git_opts=git_opts,
annex_opts=annex_opts,
annex_init_opts=annex_init_opts)
if native_metadata_type is not None:
if not isinstance(native_metadata_type, list):
native_metadata_type = [native_metadata_type]
for nt in native_metadata_type:
tbds.config.add('datalad.metadata.nativetype', nt)
# record an ID for this repo for the afterlife
# to be able to track siblings and children
id_var = 'datalad.dataset.id'
if id_var in tbds.config:
# make sure we reset this variable completely, in case of a re-create
tbds.config.unset(id_var, where='dataset')
tbds.config.add(id_var,
tbds.id if tbds.id is not None else
uuid.uuid1().urn.split(':')[-1],
where='dataset')
# save everthing
tbds.repo.add('.datalad', git=True)
if save:
Save.__call__(message='[DATALAD] new dataset',
dataset=tbds,
auto_add_changes=False,
recursive=False)
if dataset is not None and dataset.path != tbds.path:
# we created a dataset in another dataset
# -> make submodule
from datalad.distribution.utils import _install_subds_inplace
subdsrelpath = relpath(realpath(tbds.path),
realpath(dataset.path)) # realpath OK
_install_subds_inplace(ds=dataset,
path=tbds.path,
relativepath=subdsrelpath)
# this will have staged the changes in the superdataset already
if save:
Save.__call__(message='[DATALAD] added subdataset',
dataset=dataset,
auto_add_changes=False,
recursive=False)
return tbds
