def __call__(
path=None,
message=None,
dataset=None,
version_tag=None,
recursive=False,
recursion_limit=None,
updated=False,
message_file=None,
to_git=None,
):
if message and message_file:
raise ValueError(
"Both a message and message file were specified for save()")
path = assure_list(path)
if message_file:
with open(message_file) as mfh:
message = mfh.read()
# we want 'normal' to achieve the most compact argument list
# for git calls
# untracked_mode = 'no' if updated else 'normal'
# TODO however, Repo.add() would refuse to add any dotfiles
# in a directory that is itself untracked, hence the only
# choice is to go with potentially crazy long lists
# until https://github.com/datalad/datalad/issues/1454
# has a resolution
untracked_mode = 'no' if updated else 'all'
# there are three basic scenarios:
# 1. save modifications to any already tracked content
# 2. save any content (including removal of deleted content)
# to bring things to a clean state
# 3. like (2), but only operate on a given subset of content
# identified by paths
# - all three have to work in conjunction with --recursive
# - the difference between (1) and (2) should be no more
# that a switch from --untracked=no to --untracked=all
# in Repo.save()
# we do not support
# - simultaneous operations on multiple datasets from disjoint
# dataset hierarchies, hence a single reference dataset must be
# identifiable from the either
# - curdir or
# - the `dataset` argument.
# This avoids complex annotation loops and hierarchy tracking.
# - any modification upwards from the root dataset
ds = require_dataset(dataset, check_installed=True, purpose='saving')
# use status() to do all discovery and annotation of paths
paths_by_ds = {}
for s in Status()(
# ATTN: it is vital to pass the `dataset` argument as it,
# and not a dataset instance in order to maintain the path
# semantics between here and the status() call
dataset=dataset,
path=path,
untracked=untracked_mode,
recursive=recursive,
recursion_limit=recursion_limit,
result_renderer='disabled'):
# fish out status dict for this parent dataset
ds_status = paths_by_ds.get(s['parentds'], {})
# reassemble path status info as repo.status() would have made it
ds_status[ut.Path(s['path'])] = \
{k: v for k, v in iteritems(s)
if k not in (
'path', 'parentds', 'refds', 'status', 'action',
'logger')}
paths_by_ds[s['parentds']] = ds_status
lgr.debug('Determined %i datasets for saving from input arguments',
len(paths_by_ds))
# figure out what datasets to process, start with the ones containing
# the paths that were given as arguments
discovered_datasets = list(paths_by_ds.keys())
if dataset:
# if a reference dataset was given we want to save all the way up
# to it, so let's throw it into the mix
discovered_datasets.append(ds.path)
# sort the datasets into (potentially) disjoint hierarchies,
# or a single one, if a reference dataset was given
dataset_hierarchies = get_tree_roots(discovered_datasets)
for rootds, children in iteritems(dataset_hierarchies):
edges = {}
discover_dataset_trace_to_targets(rootds,
children, [],
edges,
includeds=children)
for superds, subdss in iteritems(edges):
superds_status = paths_by_ds.get(superds, {})
for subds in subdss:
# TODO actually start from an entry that may already
# exist in the status record
superds_status[ut.Path(subds)] = dict(
# shot from the hip, some status config
# to trigger this specific super/sub
# relation to be saved
state='untracked',
type='dataset')
paths_by_ds[superds] = superds_status
# TODO parallelize, whenever we have multiple subdataset of a single
# dataset they can all be processed simultaneously
# sort list of dataset to handle, starting with the ones deep down
for pdspath in sorted(paths_by_ds, reverse=True):
pds = Dataset(pdspath)
# pop status for this dataset, we are not coming back to it
pds_status = {
# for handing over to the low-level code, we recode any
# path relative to the real repo location, this avoid
# cumbersome symlink handling without context in the
# lower levels
pds.repo.pathobj / p.relative_to(pdspath): props
for p, props in iteritems(paths_by_ds.pop(pdspath))
}
start_commit = pds.repo.get_hexsha()
if not all(p['state'] == 'clean' for p in pds_status.values()):
for res in pds.repo.save_(
message=message,
# make sure to have the `path` arg be None, as we want
# to prevent and bypass any additional repo.status()
# calls
paths=None,
# prevent whining of GitRepo
git=True
if not hasattr(ds.repo, 'annexstatus') else to_git,
# we are supplying the full status already, do not
# detect anything else
untracked='no',
_status=pds_status):
# TODO remove stringification when datalad-core can handle
# path objects, or when PY3.6 is the lowest supported
# version
for k in ('path', 'refds'):
if k in res:
res[k] = str(
# recode path back to dataset path anchor
pds.pathobj /
res[k].relative_to(pds.repo.pathobj))
yield res
# report on the dataset itself
dsres = dict(
action='save',
type='dataset',
path=pds.path,
refds=ds.path,
status='ok'
if start_commit != pds.repo.get_hexsha() else 'notneeded',
logger=lgr,
)
if not version_tag:
yield dsres
continue
try:
pds.repo.tag(version_tag)
dsres.update(status='ok', version_tag=version_tag)
yield dsres
except CommandError as e:
if dsres['status'] == 'ok':
# first we yield the result for the actual save
yield dsres.copy()
# and now complain that tagging didn't work
dsres.update(status='error',
message=('cannot tag this version: %s',
e.stderr.strip()))
yield dsres
def __call__(message=None,
files=None,
dataset=None,
all_updated=True,
all_changes=None,
version_tag=None,
recursive=False,
recursion_limit=None,
super_datasets=False):
if all_changes is not None:
from datalad.support.exceptions import DeprecatedError
raise DeprecatedError(
new="all_updated option where fits and/or datalad add",
version="0.5.0",
msg="RF: all_changes option passed to the save")
if not dataset and not files:
# we got nothing at all -> save what is staged in the repo in "this" directory?
# we verify that there is an actual repo next
dataset = abspath(curdir)
refds_path = Interface.get_refds_path(dataset)
to_process = []
for ap in AnnotatePaths.__call__(
path=files,
dataset=refds_path,
recursive=recursive,
recursion_limit=recursion_limit,
action='save',
unavailable_path_status='impossible',
unavailable_path_msg="path does not exist: %s",
nondataset_path_status='impossible',
return_type='generator',
on_failure='ignore'):
# next check should not be done during annotation, as it is possibly expensive
# and not generally useful
if ap.get('status', None) == 'impossible' and \
ap.get('state', None) == 'absent' and \
ap.get('parentds', None):
# this is not here anymore, but it might actually have been a deleted
# component
if relpath(ap['path'], start=ap['parentds']) \
in Dataset(ap['parentds']).repo.get_deleted_files():
# ok, this is a staged deletion that we want to save
ap['status'] = ''
del ap['message']
if ap.get('status', None):
# this is done
yield ap
continue
# for things like: `ds.save()`
# or recursively discovered datasets
if ap['path'] == refds_path or \
(ap.get('type', None) == 'dataset' and
not ap.get('raw_input', False) and
not ap.get('state', None) == 'absent'):
ap['process_content'] = True
ap['process_updated_only'] = all_updated
to_process.append(ap)
if not to_process:
# nothing left to do, potentially all errored before
return
if super_datasets:
# search for the topmost superdatasets of any path
dss = [
Dataset(ap.get('parentds', ap['path'])) for ap in to_process
]
superdss = [ds.get_superdataset(topmost=True) for ds in dss]
superdss = get_tree_roots(
unique(ds.path for ds in dss + superdss if ds))
if dataset:
# need to adjust the reference to the new superds
# if we had one ref before, we should still have exactly one
assert len(superdss) <= 1
dataset = list(superdss.keys())[0]
refds_path = dataset
elif refds_path:
# there is a single superdataset
superdss = {
refds_path:
unique(
[ap['parentds'] for ap in to_process if 'parentds' in ap])
}
else:
# sort all datasets under their potential superdatasets
# start from the top to get all subdatasets down the line
# and collate them into as few superdatasets as possible
# this is quick, just string operations
superdss = get_tree_roots(
unique(
[ap['parentds'] for ap in to_process if 'parentds' in ap]))
# for each "superdataset" check the tree of subdatasets and make sure
# we gather all datasets between the super and any subdataset
# so we can save them all bottom-up in order to be able to properly
# save the superdataset
# if this is called from e.g. `add` this is actually not necessary,
# but in the general case we cannot avoid it
# TODO maybe introduce a switch?
discovered = {}
for superds_path in superdss:
target_subs = superdss[superds_path]
discover_dataset_trace_to_targets(
# from here
superds_path,
# to all
target_subs,
[],
discovered)
# create a new minimally annotated path for each discovered dataset
discovered_added = set()
for parentds in discovered:
for subds in discovered[parentds]:
to_process.append(
dict(path=subds, parentds=parentds, type='dataset'))
discovered_added.add(subds)
# make sure we have an entry for each dataset, including those
# tha are just parents
for parentds in discovered:
if parentds not in discovered_added:
to_process.append(
dict(
path=parentds,
type='dataset',
# make sure we save content of superds later on
process_content=True))
# now re-annotate all paths, this will be fast for already annotated ones
# and will amend the annotation for others, deduplication happens here too
annotated_paths = AnnotatePaths.__call__(
path=to_process,
dataset=dataset,
# never recursion, done already
recursive=False,
action='save',
unavailable_path_status='',
nondataset_path_status='impossible',
return_type='generator',
# if there is an error now, we made this mistake in here
on_failure='stop')
# now sort into datasets so we can process them one by one
content_by_ds, ds_props, completed, nondataset_paths = \
annotated2content_by_ds(
annotated_paths,
refds_path=refds_path,
path_only=False)
assert (not completed)
# iterate over all datasets, starting at the bottom
for dspath in sorted(content_by_ds.keys(), reverse=True):
ds = Dataset(dspath)
res = get_status_dict('save', ds=ds, logger=lgr)
if not ds.is_installed():
# TODO This is likely impossible now
res['status'] = 'impossible'
res['message'] = ('dataset %s is not installed', ds)
yield res
continue
saved_state = save_dataset(ds,
content_by_ds[dspath],
message=message,
version_tag=version_tag)
if saved_state:
res['status'] = 'ok'
else:
res['status'] = 'notneeded'
yield res
def __call__(path=None, message=None, dataset=None,
version_tag=None,
recursive=False, recursion_limit=None,
updated=False,
message_file=None,
to_git=None,
):
if message and message_file:
raise ValueError(
"Both a message and message file were specified for save()")
path = assure_list(path)
if message_file:
with open(message_file) as mfh:
message = mfh.read()
# we want 'normal' to achieve the most compact argument list
# for git calls
# untracked_mode = 'no' if updated else 'normal'
# TODO however, Repo.add() would refuse to add any dotfiles
# in a directory that is itself untracked, hence the only
# choice is to go with potentially crazy long lists
# until https://github.com/datalad/datalad/issues/1454
# has a resolution
untracked_mode = 'no' if updated else 'all'
# there are three basic scenarios:
# 1. save modifications to any already tracked content
# 2. save any content (including removal of deleted content)
# to bring things to a clean state
# 3. like (2), but only operate on a given subset of content
# identified by paths
# - all three have to work in conjunction with --recursive
# - the difference between (1) and (2) should be no more
# that a switch from --untracked=no to --untracked=all
# in Repo.save()
# we do not support
# - simultaneous operations on multiple datasets from disjoint
# dataset hierarchies, hence a single reference dataset must be
# identifiable from the either
# - curdir or
# - the `dataset` argument.
# This avoids complex annotation loops and hierarchy tracking.
# - any modification upwards from the root dataset
ds = require_dataset(dataset, check_installed=True, purpose='saving')
# use status() to do all discovery and annotation of paths
paths_by_ds = {}
for s in Status()(
# ATTN: it is vital to pass the `dataset` argument as it,
# and not a dataset instance in order to maintain the path
# semantics between here and the status() call
dataset=dataset,
path=path,
untracked=untracked_mode,
recursive=recursive,
recursion_limit=recursion_limit,
result_renderer='disabled'):
# fish out status dict for this parent dataset
ds_status = paths_by_ds.get(s['parentds'], {})
# reassemble path status info as repo.status() would have made it
ds_status[ut.Path(s['path'])] = \
{k: v for k, v in iteritems(s)
if k not in (
'path', 'parentds', 'refds', 'status', 'action',
'logger')}
paths_by_ds[s['parentds']] = ds_status
lgr.debug('Determined %i datasets for saving from input arguments',
len(paths_by_ds))
# figure out what datasets to process, start with the ones containing
# the paths that were given as arguments
discovered_datasets = list(paths_by_ds.keys())
if dataset:
# if a reference dataset was given we want to save all the way up
# to it, so let's throw it into the mix
discovered_datasets.append(ds.path)
# sort the datasets into (potentially) disjoint hierarchies,
# or a single one, if a reference dataset was given
dataset_hierarchies = get_tree_roots(discovered_datasets)
for rootds, children in iteritems(dataset_hierarchies):
edges = {}
discover_dataset_trace_to_targets(
rootds, children, [], edges, includeds=children)
for superds, subdss in iteritems(edges):
superds_status = paths_by_ds.get(superds, {})
for subds in subdss:
# TODO actually start from an entry that may already
# exist in the status record
superds_status[ut.Path(subds)] = dict(
# shot from the hip, some status config
# to trigger this specific super/sub
# relation to be saved
state='untracked',
type='dataset')
paths_by_ds[superds] = superds_status
# TODO parallelize, whenever we have multiple subdataset of a single
# dataset they can all be processed simultaneously
# sort list of dataset to handle, starting with the ones deep down
for pdspath in sorted(paths_by_ds, reverse=True):
pds = Dataset(pdspath)
# pop status for this dataset, we are not coming back to it
pds_status = {
# for handing over to the low-level code, we recode any
# path relative to the real repo location, this avoid
# cumbersome symlink handling without context in the
# lower levels
pds.repo.pathobj / p.relative_to(pdspath): props
for p, props in iteritems(paths_by_ds.pop(pdspath))}
start_commit = pds.repo.get_hexsha()
if not all(p['state'] == 'clean' for p in pds_status.values()):
for res in pds.repo.save_(
message=message,
# make sure to have the `path` arg be None, as we want
# to prevent and bypass any additional repo.status()
# calls
paths=None,
# prevent whining of GitRepo
git=True if not hasattr(ds.repo, 'annexstatus')
else to_git,
# we are supplying the full status already, do not
# detect anything else
untracked='no',
_status=pds_status):
# TODO remove stringification when datalad-core can handle
# path objects, or when PY3.6 is the lowest supported
# version
for k in ('path', 'refds'):
if k in res:
res[k] = text_type(
# recode path back to dataset path anchor
pds.pathobj / res[k].relative_to(
pds.repo.pathobj)
)
yield res
# report on the dataset itself
dsres = dict(
action='save',
type='dataset',
path=pds.path,
refds=ds.path,
status='ok'
if start_commit != pds.repo.get_hexsha()
else 'notneeded',
logger=lgr,
)
if not version_tag:
yield dsres
continue
try:
pds.repo.tag(version_tag)
dsres.update(
status='ok',
version_tag=version_tag)
yield dsres
except CommandError as e:
if dsres['status'] == 'ok':
# first we yield the result for the actual save
yield dsres.copy()
# and now complain that tagging didn't work
dsres.update(
status='error',
message=('cannot tag this version: %s', e.stderr.strip()))
yield dsres
def __call__(message=None, path=None, dataset=None,
all_updated=True, version_tag=None,
recursive=False, recursion_limit=None, super_datasets=False,
message_file=None
):
if not dataset and not path:
# we got nothing at all -> save what is staged in the repo in "this" directory?
# make sure we don't treat this as a user-provided '.' argument
path = [{'path': abspath(curdir), 'raw_input': False}]
refds_path = Interface.get_refds_path(dataset)
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_process = []
got_nothing = True
for ap in AnnotatePaths.__call__(
path=path,
dataset=refds_path,
recursive=recursive,
recursion_limit=recursion_limit,
action='save',
unavailable_path_status='impossible',
unavailable_path_msg="path does not exist: %s",
nondataset_path_status='impossible',
modified='HEAD' if not path and recursive else None,
return_type='generator',
on_failure='ignore'):
if ap.get('state', None) == 'untracked' and not ap.get('raw_input', False):
# this path was found untracked, but not explicitly given to save
# we will silently ignore this
continue
got_nothing = False
# next check should not be done during annotation, as it is possibly expensive
# and not generally useful
if ap.get('status', None) == 'impossible' and \
ap.get('state', None) == 'absent' and \
ap.get('parentds', None):
# this is not here anymore, but it might actually have been a deleted
# component
if relpath(ap['path'], start=ap['parentds']) \
in Dataset(ap['parentds']).repo.get_deleted_files():
# ok, this is a staged deletion that we want to save
ap['status'] = ''
del ap['message']
if ap.get('status', None):
# this is done
yield ap
continue
# for things like: `ds.save()`
# or recursively discovered datasets
if ap['path'] == refds_path or \
(ap.get('type', None) == 'dataset' and
not ap.get('raw_input', False) and
not ap.get('state', None) == 'absent'):
ap['process_content'] = True
ap['process_updated_only'] = all_updated
to_process.append(ap)
lgr.log(2, "save, to_process=%r", to_process)
if got_nothing and recursive and refds_path:
# 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(
'save',
status='notneeded',
path=refds_path,
type='dataset',
logger=lgr)
return
if not to_process:
# nothing left to do, potentially all errored before
return
if super_datasets:
# search for the topmost superdatasets of any path
dss = [Dataset(ap.get('parentds', ap['path'])) for ap in to_process]
superdss = [ds.get_superdataset(topmost=True)
for ds in dss]
superdss = get_tree_roots(
unique(ds.path for ds in dss + superdss if ds))
if dataset:
# need to adjust the reference to the new superds
# if we had one ref before, we should still have exactly one
assert len(superdss) <= 1
dataset = list(superdss.keys())[0]
refds_path = dataset
elif refds_path:
# there is a single superdataset
superdss = {
refds_path: unique([ap['parentds']
for ap in to_process if 'parentds' in ap])}
else:
# sort all datasets under their potential superdatasets
# start from the top to get all subdatasets down the line
# and collate them into as few superdatasets as possible
# this is quick, just string operations
superdss = get_tree_roots(
unique([ap['parentds'] for ap in to_process if 'parentds' in ap]))
# for each "superdataset" check the tree of subdatasets and make sure
# we gather all datasets between the super and any subdataset
# so we can save them all bottom-up in order to be able to properly
# save the superdataset
# if this is called from e.g. `add` this is actually not necessary,
# but in the general case we cannot avoid it
# TODO maybe introduce a switch?
discovered = {}
for superds_path in superdss:
target_subs = superdss[superds_path]
discover_dataset_trace_to_targets(
# from here
superds_path,
# to all
target_subs,
[],
discovered)
# create a new minimally annotated path for each discovered dataset
discovered_added = set()
for parentds in discovered:
for subds in discovered[parentds]:
to_process.append(dict(
path=subds,
parentds=parentds,
type='dataset'))
discovered_added.add(subds)
# make sure we have an entry for each dataset, including those
# tha are just parents
for parentds in discovered:
if parentds not in discovered_added:
to_process.append(dict(
path=parentds,
type='dataset',
# make sure we save content of superds later on
process_content=True,
# but not do nasty things, like adding untracked content
# just because we discovered this dataset
process_updated_only=True))
# now re-annotate all paths, this will be fast for already annotated ones
# and will amend the annotation for others, deduplication happens here too
annotated_paths = AnnotatePaths.__call__(
path=to_process,
dataset=dataset,
# never recursion, done already
recursive=False,
action='save',
unavailable_path_status='',
nondataset_path_status='impossible',
return_type='generator',
# if there is an error now, we made this mistake in here
on_failure='stop')
# now sort into datasets so we can process them one by one
content_by_ds, ds_props, completed, nondataset_paths = \
annotated2content_by_ds(
annotated_paths,
refds_path=refds_path)
assert(not completed)
# iterate over all datasets, starting at the bottom
for dspath in sorted(content_by_ds.keys(), reverse=True):
ds = Dataset(dspath)
res = get_status_dict('save', ds=ds, logger=lgr)
if not ds.is_installed():
# TODO This is likely impossible now
res['status'] = 'impossible'
res['message'] = ('dataset %s is not installed', ds)
yield res
continue
saved_state = save_dataset(
ds,
content_by_ds[dspath],
message=message)
res['status'] = 'ok' if saved_state else 'notneeded'
# MIH: let's tag even if there was nothing commit. I'd forget this
# option too often...
if version_tag:
try:
# TODO: check whether comment below is still true after
# removing the log swallowing:
# again cannot help but force-silence low-level code, because
# it screams like a made man instead of allowing top-level
# code an orderly error report
ds.repo.tag(version_tag)
# even if we haven't saved anything
res['status'] = 'ok'
yield res
except CommandError as e:
if saved_state:
# first we yield the result for the actual save
yield res
# and now complain that tagging didn't work
yield get_status_dict(
'save',
ds=ds,
logger=lgr,
status='error',
message=(
'cannot tag this version: %s',
e.stderr.strip()))
else:
yield res
def __call__(
path=None,
message=None,
dataset=None,
version_tag=None,
recursive=False,
recursion_limit=None,
updated=False,
message_file=None,
to_git=None,
jobs=None,
amend=False,
):
if message and message_file:
raise ValueError(
"Both a message and message file were specified for save()")
if amend and recursive:
raise ValueError("Cannot amend a commit recursively.")
path = ensure_list(path)
if message_file:
with open(message_file) as mfh:
message = mfh.read()
# we want 'normal' to achieve the most compact argument list
# for git calls
# untracked_mode = 'no' if updated else 'normal'
# TODO however, Repo.add() would refuse to add any dotfiles
# in a directory that is itself untracked, hence the only
# choice is to go with potentially crazy long lists
# until https://github.com/datalad/datalad/issues/1454
# has a resolution
untracked_mode = 'no' if updated else 'all'
# there are three basic scenarios:
# 1. save modifications to any already tracked content
# 2. save any content (including removal of deleted content)
# to bring things to a clean state
# 3. like (2), but only operate on a given subset of content
# identified by paths
# - all three have to work in conjunction with --recursive
# - the difference between (1) and (2) should be no more
# that a switch from --untracked=no to --untracked=all
# in Repo.save()
# we do not support
# - simultaneous operations on multiple datasets from disjoint
# dataset hierarchies, hence a single reference dataset must be
# identifiable from the either
# - curdir or
# - the `dataset` argument.
# This avoids complex annotation loops and hierarchy tracking.
# - any modification upwards from the root dataset
ds = require_dataset(dataset, check_installed=True, purpose='saving')
# use status() to do all discovery and annotation of paths
paths_by_ds = {}
for s in Status()(
# ATTN: it is vital to pass the `dataset` argument as it,
# and not a dataset instance in order to maintain the path
# semantics between here and the status() call
dataset=dataset,
path=path,
untracked=untracked_mode,
report_filetype=False,
recursive=recursive,
recursion_limit=recursion_limit,
on_failure='ignore',
# for save without recursion only commit matters
eval_subdataset_state='full' if recursive else 'commit',
result_renderer='disabled'):
if s['status'] == 'error':
# Downstream code can't do anything with these. Let the caller
# decide their fate.
yield s
continue
# fish out status dict for this parent dataset
ds_status = paths_by_ds.get(s['parentds'], {})
# reassemble path status info as repo.status() would have made it
ds_status[ut.Path(s['path'])] = \
{k: v for k, v in s.items()
if k not in (
'path', 'parentds', 'refds', 'status', 'action',
'logger')}
paths_by_ds[s['parentds']] = ds_status
lgr.debug('Determined %i datasets for saving from input arguments',
len(paths_by_ds))
# figure out what datasets to process, start with the ones containing
# the paths that were given as arguments
discovered_datasets = list(paths_by_ds.keys())
if dataset:
# if a reference dataset was given we want to save all the way up
# to it, so let's throw it into the mix
discovered_datasets.append(ds.path)
# sort the datasets into (potentially) disjoint hierarchies,
# or a single one, if a reference dataset was given
dataset_hierarchies = get_tree_roots(discovered_datasets)
for rootds, children in dataset_hierarchies.items():
edges = {}
discover_dataset_trace_to_targets(rootds,
children, [],
edges,
includeds=children)
for superds, subdss in edges.items():
superds_status = paths_by_ds.get(superds, {})
for subds in subdss:
subds_path = ut.Path(subds)
sub_status = superds_status.get(subds_path, {})
if not (sub_status.get("state") == "clean"
and sub_status.get("type") == "dataset"):
# TODO actually start from an entry that may already
# exist in the status record
superds_status[subds_path] = dict(
# shot from the hip, some status config
# to trigger this specific super/sub
# relation to be saved
state='untracked',
type='dataset')
paths_by_ds[superds] = superds_status
def save_ds(args, version_tag=None):
pdspath, paths = args
pds = Dataset(pdspath)
pds_repo = pds.repo
# pop status for this dataset, we are not coming back to it
pds_status = {
# for handing over to the low-level code, we recode any
# path relative to the real repo location, this avoid
# cumbersome symlink handling without context in the
# lower levels
pds_repo.pathobj / p.relative_to(pdspath): props
for p, props in paths.items()
}
start_commit = pds_repo.get_hexsha()
if not all(p['state'] == 'clean' for p in pds_status.values()) or \
(amend and message):
for res in pds_repo.save_(
message=message,
# make sure to have the `path` arg be None, as we want
# to prevent and bypass any additional repo.status()
# calls
paths=None,
# prevent whining of GitRepo
git=True
if not hasattr(ds.repo, 'annexstatus') else to_git,
# we are supplying the full status already, do not
# detect anything else
untracked='no',
_status=pds_status,
amend=amend):
# TODO remove stringification when datalad-core can handle
# path objects, or when PY3.6 is the lowest supported
# version
for k in ('path', 'refds'):
if k in res:
res[k] = str(
# recode path back to dataset path anchor
pds.pathobj /
res[k].relative_to(pds_repo.pathobj))
yield res
# report on the dataset itself
dsres = dict(
action='save',
type='dataset',
path=pds.path,
refds=ds.path,
status='ok'
if start_commit != pds_repo.get_hexsha() else 'notneeded',
logger=lgr,
)
if not version_tag:
yield dsres
return
try:
# method requires str
version_tag = str(version_tag)
pds_repo.tag(version_tag)
dsres.update(status='ok', version_tag=version_tag)
yield dsres
except CommandError as e:
if dsres['status'] == 'ok':
# first we yield the result for the actual save
# TODO: we will get duplicate dataset/save record obscuring
# progress reporting. yoh thought to decouple "tag" from "save"
# messages but was worrying that original authors would disagree
yield dsres.copy()
# and now complain that tagging didn't work
dsres.update(status='error',
message=('cannot tag this version: %s',
e.stderr.strip()))
yield dsres
if not paths_by_ds:
# Special case: empty repo. There's either an empty commit only or
# none at all. An empty one we can amend otherwise there's nothing
# to do.
if amend and ds.repo.get_hexsha():
yield from save_ds((ds.pathobj, dict()),
version_tag=version_tag)
else:
yield dict(action='save',
type='dataset',
path=ds.path,
refds=ds.path,
status='notneeded',
logger=lgr)
return
# TODO: in principle logging could be improved to go not by a dataset
# but by path(s) within subdatasets. That should provide a bit better ETA
# and more "dynamic" feedback than jumpy datasets count.
# See addurls where it is implemented that way by providing agg and another
# log_filter
yield from ProducerConsumerProgressLog(
sorted(paths_by_ds.items(), key=lambda v: v[0], reverse=True),
partial(save_ds, version_tag=version_tag),
safe_to_consume=no_subds_in_futures,
producer_future_key=lambda ds_items: ds_items[0],
jobs=jobs,
log_filter=_log_filter_save_dataset,
unit="datasets",
lgr=lgr,
)
def __call__(message=None,
path=None,
dataset=None,
all_updated=True,
version_tag=None,
recursive=False,
recursion_limit=None,
super_datasets=False,
message_file=None):
if not dataset and not path:
# we got nothing at all -> save what is staged in the repo in "this" directory?
# make sure we don't treat this as a user-provided '.' argument
path = [{'path': abspath(curdir), 'raw_input': False}]
refds_path = Interface.get_refds_path(dataset)
if message and message_file:
yield get_status_dict(
'save',
status='error',
path=refds_path,
message="Both a message and message file were specified",
logger=lgr)
return
if message_file:
with open(message_file) as mfh:
message = mfh.read()
to_process = []
got_nothing = True
for ap in AnnotatePaths.__call__(
path=path,
dataset=refds_path,
recursive=recursive,
recursion_limit=recursion_limit,
action='save',
unavailable_path_status='impossible',
unavailable_path_msg="path does not exist: %s",
nondataset_path_status='impossible',
modified='HEAD' if not path and recursive else None,
return_type='generator',
on_failure='ignore'):
if ap.get('state',
None) == 'untracked' and not ap.get('raw_input', False):
# this path was found untracked, but not explicitly given to save
# we will silently ignore this
continue
got_nothing = False
# next check should not be done during annotation, as it is possibly expensive
# and not generally useful
if ap.get('status', None) == 'impossible' and \
ap.get('state', None) == 'absent' and \
ap.get('parentds', None):
# this is not here anymore, but it might actually have been a deleted
# component
if relpath(ap['path'], start=ap['parentds']) \
in Dataset(ap['parentds']).repo.get_deleted_files():
# ok, this is a staged deletion that we want to save
ap['status'] = ''
del ap['message']
if ap.get('status', None):
# this is done
yield ap
continue
# for things like: `ds.save()`
# or recursively discovered datasets
if ap['path'] == refds_path or \
(ap.get('type', None) == 'dataset' and
not ap.get('raw_input', False) and
not ap.get('state', None) == 'absent'):
ap['process_content'] = True
ap['process_updated_only'] = all_updated
to_process.append(ap)
lgr.log(2, "save, to_process=%r", to_process)
if got_nothing and recursive and refds_path:
# 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('save',
status='notneeded',
path=refds_path,
type='dataset',
logger=lgr)
return
if not to_process:
# nothing left to do, potentially all errored before
return
if super_datasets:
# search for the topmost superdatasets of any path
dss = [
Dataset(ap.get('parentds', ap['path'])) for ap in to_process
]
superdss = [ds.get_superdataset(topmost=True) for ds in dss]
superdss = get_tree_roots(
unique(ds.path for ds in dss + superdss if ds))
if dataset:
# need to adjust the reference to the new superds
# if we had one ref before, we should still have exactly one
assert len(superdss) <= 1
dataset = list(superdss.keys())[0]
refds_path = dataset
elif refds_path:
# there is a single superdataset
superdss = {
refds_path:
unique(
[ap['parentds'] for ap in to_process if 'parentds' in ap])
}
else:
# sort all datasets under their potential superdatasets
# start from the top to get all subdatasets down the line
# and collate them into as few superdatasets as possible
# this is quick, just string operations
superdss = get_tree_roots(
unique(
[ap['parentds'] for ap in to_process if 'parentds' in ap]))
# for each "superdataset" check the tree of subdatasets and make sure
# we gather all datasets between the super and any subdataset
# so we can save them all bottom-up in order to be able to properly
# save the superdataset
# if this is called from e.g. `add` this is actually not necessary,
# but in the general case we cannot avoid it
# TODO maybe introduce a switch?
discovered = {}
for superds_path in superdss:
target_subs = superdss[superds_path]
discover_dataset_trace_to_targets(
# from here
superds_path,
# to all
target_subs,
[],
discovered)
# create a new minimally annotated path for each discovered dataset
discovered_added = set()
for parentds in discovered:
for subds in discovered[parentds]:
to_process.append(
dict(path=subds, parentds=parentds, type='dataset'))
discovered_added.add(subds)
# make sure we have an entry for each dataset, including those
# tha are just parents
for parentds in discovered:
if parentds not in discovered_added:
to_process.append(
dict(
path=parentds,
type='dataset',
# make sure we save content of superds later on
process_content=True,
# but not do nasty things, like adding untracked content
# just because we discovered this dataset
process_updated_only=True))
# now re-annotate all paths, this will be fast for already annotated ones
# and will amend the annotation for others, deduplication happens here too
annotated_paths = AnnotatePaths.__call__(
path=to_process,
dataset=dataset,
# never recursion, done already
recursive=False,
action='save',
unavailable_path_status='',
nondataset_path_status='impossible',
return_type='generator',
# if there is an error now, we made this mistake in here
on_failure='stop')
# now sort into datasets so we can process them one by one
content_by_ds, ds_props, completed, nondataset_paths = \
annotated2content_by_ds(
annotated_paths,
refds_path=refds_path)
assert (not completed)
# iterate over all datasets, starting at the bottom
for dspath in sorted(content_by_ds.keys(), reverse=True):
ds = Dataset(dspath)
res = get_status_dict('save', ds=ds, logger=lgr)
if not ds.is_installed():
# TODO This is likely impossible now
res['status'] = 'impossible'
res['message'] = ('dataset %s is not installed', ds)
yield res
continue
saved_state = save_dataset(ds,
content_by_ds[dspath],
message=message)
res['status'] = 'ok' if saved_state else 'notneeded'
# MIH: let's tag even if there was nothing commit. I'd forget this
# option too often...
if version_tag:
try:
# TODO: check whether comment below is still true after
# removing the log swallowing:
# again cannot help but force-silence low-level code, because
# it screams like a made man instead of allowing top-level
# code an orderly error report
ds.repo.tag(version_tag)
# even if we haven't saved anything
res['status'] = 'ok'
yield res
except CommandError as e:
if saved_state:
# first we yield the result for the actual save
yield res
# and now complain that tagging didn't work
yield get_status_dict(
'save',
ds=ds,
logger=lgr,
status='error',
message=('cannot tag this version: %s',
e.stderr.strip()))
else:
yield res