def by_tool_input(self,
trans,
tool_id,
param_dump=None,
job_state='ok',
is_workflow_step=False):
"""Search for jobs producing same results using the 'inputs' part of a tool POST."""
user = trans.user
input_data = defaultdict(list)
input_ids = defaultdict(dict)
def populate_input_data_input_id(path, key, value):
"""Traverses expanded incoming using remap and collects input_ids and input_data."""
if key == 'id':
path_key = get_path_key(path[:-2])
current_case = param_dump
for p in path:
current_case = current_case[p]
src = current_case['src']
input_data[path_key].append({'src': src, 'id': value})
input_ids[src][value] = True
return key, value
return key, value
remap(param_dump, visit=populate_input_data_input_id)
return self.__search(tool_id=tool_id,
user=user,
input_data=input_data,
job_state=job_state,
param_dump=param_dump,
input_ids=input_ids,
is_workflow_step=is_workflow_step)
def summarize_job_outputs(job: model.Job, tool, params, security):
outputs = defaultdict(list)
output_labels = {}
possible_outputs = (
('hda', 'dataset_id', job.output_datasets),
('ldda', 'ldda_id', job.output_library_datasets),
('hdca', 'dataset_collection_id',
job.output_dataset_collection_instances),
)
for src, attribute, output_associations in possible_outputs:
for output_association in output_associations:
output_name = output_association.name
if output_name not in output_labels and tool:
tool_output = tool.output_collections if src == 'hdca' else tool.outputs
output_labels[output_name] = get_output_name(
tool=tool,
output=tool_output.get(output_name),
params=params)
label = output_labels.get(output_name)
outputs[output_name].append({
'label': label,
'value': {
'src':
src,
'id':
security.encode_id(getattr(output_association, attribute))
}
})
return outputs
def by_tool_input(self, trans, tool_id, tool_version, param=None, param_dump=None, job_state='ok'):
"""Search for jobs producing same results using the 'inputs' part of a tool POST."""
user = trans.user
input_data = defaultdict(list)
def populate_input_data_input_id(path, key, value):
"""Traverses expanded incoming using remap and collects input_ids and input_data."""
if key == 'id':
path_key = get_path_key(path[:-2])
current_case = param_dump
for p in path:
current_case = current_case[p]
src = current_case['src']
current_case = param
for i, p in enumerate(path):
if p == 'values' and i == len(path) - 2:
continue
if isinstance(current_case, (list, dict)):
current_case = current_case[p]
identifier = getattr(current_case, "element_identifier", None)
input_data[path_key].append({'src': src,
'id': value,
'identifier': identifier,
})
return key, "__id_wildcard__"
return key, value
wildcard_param_dump = remap(param_dump, visit=populate_input_data_input_id)
return self.__search(tool_id=tool_id,
tool_version=tool_version,
user=user,
input_data=input_data,
job_state=job_state,
param_dump=param_dump,
wildcard_param_dump=wildcard_param_dump)
def by_tool_input(self, trans, tool_id, tool_version, param=None, param_dump=None, job_state='ok'):
"""Search for jobs producing same results using the 'inputs' part of a tool POST."""
user = trans.user
input_data = defaultdict(list)
def populate_input_data_input_id(path, key, value):
"""Traverses expanded incoming using remap and collects input_ids and input_data."""
if key == 'id':
path_key = get_path_key(path[:-2])
current_case = param_dump
for p in path:
current_case = current_case[p]
src = current_case['src']
current_case = param
for i, p in enumerate(path):
if p == 'values' and i == len(path) - 2:
continue
if isinstance(current_case, (list, dict)):
current_case = current_case[p]
identifier = getattr(current_case, "element_identifier", None)
input_data[path_key].append({'src': src,
'id': value,
'identifier': identifier,
})
return key, "__id_wildcard__"
return key, value
wildcard_param_dump = remap(param_dump, visit=populate_input_data_input_id)
return self.__search(tool_id=tool_id,
tool_version=tool_version,
user=user,
input_data=input_data,
job_state=job_state,
param_dump=param_dump,
wildcard_param_dump=wildcard_param_dump)