def audit_item_status(value, system):
if 'status' not in value:
return
level = STATUS_LEVEL.get(value['status'], 50)
if level == 0:
return
context = system['context']
request = system['request']
linked = set()
for schema_path in context.type_info.schema_links:
if schema_path in ['supercedes', 'step_run']:
continue
linked.update(simple_path_ids(value, schema_path))
for path in linked:
linked_value = request.embed(path + '@@object')
if 'status' not in linked_value:
continue
if linked_value['status'] == 'disabled':
continue
if ( # Special case: A revoked file can have a deleted replicate ticket #2938
'file' in value['@type'] and
value['status'] == 'revoked' and
'replicate' in linked_value['@type'] and
linked_value['status'] == 'deleted'
):
continue
linked_level = STATUS_LEVEL.get(linked_value['status'], 50)
if linked_level == 0:
detail = '{} {} has {} subobject {}'.format(
value['status'], value['@id'], linked_value['status'], linked_value['@id'])
yield AuditFailure('mismatched status', detail, level='ERROR')
elif linked_level < level:
detail = '{} {} has {} subobject {}'.format(
value['status'], value['@id'], linked_value['status'], linked_value['@id'])
yield AuditFailure('mismatched status', detail, level='DCC_ACTION')
def metadata_tsv(context, request):
param_list = parse_qs(request.matchdict['search_params'])
param_list['field'] = []
header = []
file_attributes = []
for prop in _tsv_mapping:
header.append(prop)
param_list['field'] = param_list['field'] + _tsv_mapping[prop]
if _tsv_mapping[prop][0].startswith('files'):
file_attributes = file_attributes + [_tsv_mapping[prop][0]]
param_list['limit'] = ['all']
path = '/search/?%s' % urlencode(param_list, True)
results = request.embed(path, as_user=True)
rows = []
for row in results['@graph']:
if row['files']:
exp_data_row = []
for column in header:
if not _tsv_mapping[column][0].startswith('files'):
temp = []
for c in _tsv_mapping[column]:
c_value = []
for value in simple_path_ids(row, c):
if str(value) not in c_value:
c_value.append(str(value))
if c == 'replicates.library.biosample.post_synchronization_time' and len(temp):
if len(c_value):
temp[0] = temp[0] + ' + ' + c_value[0]
elif len(temp):
if len(c_value):
temp = [x + ' ' + c_value[0] for x in temp]
else:
temp = c_value
exp_data_row.append(', '.join(list(set(temp))))
f_attributes = ['files.title', 'files.file_type',
'files.output_type']
for f in row['files']:
if 'files.file_type' in param_list:
if f['file_type'] not in param_list['files.file_type']:
continue
f['href'] = request.host_url + f['href']
f_row = []
for attr in f_attributes:
f_row.append(f[attr[6:]])
data_row = f_row + exp_data_row
internal_prop = True
for prop in file_attributes:
if prop in f_attributes:
continue
if prop == 'files.replicate.library':
if not internal_prop:
continue
internal_prop = False
libraries = []
for l in simple_path_ids(f, prop[6:]):
libraries.append(l)
if len(libraries):
library = request.embed(libraries[0])
data_row.append(library.get('fragmentation_method', ''))
data_row.append(library.get('size_range', ''))
if 'biosample' in library:
data_row.append(library['biosample'].get('age_display', ''))
else:
data_row.append('')
continue
else:
data_row = data_row + [''] * 3
continue
path = prop[6:]
temp = []
for value in simple_path_ids(f, path):
temp.append(str(value))
if prop == 'files.replicate.rbns_protein_concentration':
if 'replicate' in f and 'rbns_protein_concentration_units' in f['replicate']:
temp[0] = temp[0] + ' ' + f['replicate']['rbns_protein_concentration_units']
data_row.append(', '.join(list(set(temp))))
rows.append(data_row)
fout = io.StringIO()
writer = csv.writer(fout, delimiter='\t')
writer.writerow(header)
writer.writerows(rows)
return Response(
content_type='text/tsv',
body=fout.getvalue(),
content_disposition='attachment;filename="%s"' % 'metadata.tsv'
)
