def prep_template_graph_get_req(prep_id, user_id):
"""Returns graph of all artifacts created from the prep base artifact
Parameters
----------
prep_id : int
Prep template ID to get graph for
user_id : str
User making the request
Returns
-------
dict of lists of tuples
A dictionary containing the edge list representation of the graph,
and the node labels. Formatted as:
{'status': status,
'message': message,
'edge_list': [(0, 1), (0, 2)...],
'node_labels': [(0, 'label0'), (1, 'label1'), ...]}
Notes
-----
Nodes are identified by the corresponding Artifact ID.
"""
exists = _check_prep_template_exists(int(prep_id))
if exists['status'] != 'success':
return exists
prep = PrepTemplate(int(prep_id))
access_error = check_access(prep.study_id, user_id)
if access_error:
return access_error
# We should filter for only the public artifacts if the user
# doesn't have full access to the study
full_access = Study(prep.study_id).can_edit(User(user_id))
artifact = prep.artifact
if artifact is None:
return {'edges': [], 'nodes': [],
'status': 'success', 'message': ''}
G = artifact.descendants_with_jobs
nodes, edges, wf_id = get_network_nodes_edges(G, full_access)
# nodes returns [node_type, node_name, element_id]; here we are looking
# for the node_type == artifact, and check by the element/artifact_id if
# it's being deleted
artifacts_being_deleted = [a[2] for a in nodes if a[0] == 'artifact' and
Artifact(a[2]).being_deleted_by is not None]
return {'edges': edges,
'nodes': nodes,
'workflow': wf_id,
'status': 'success',
'artifacts_being_deleted': artifacts_being_deleted,
'message': ''}
def test_get_network_nodes_edges(self):
graph = Artifact(1).descendants_with_jobs
obs_nodes, obs_edges, obs_wf = get_network_nodes_edges(graph, True)
self.assertEqual(len(obs_nodes), 11)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'job']), 5)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'artifact']), 6)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'type']), 0)
self.assertEqual(len(obs_edges), 10)
self.assertIsNone(obs_wf)
# This graph only contains one node - check added to make sure that
# the graph gets extended accordingly
graph = Artifact(6).descendants_with_jobs
obs_nodes, obs_edges, obs_wf = get_network_nodes_edges(
graph, True, nodes=obs_nodes, edges=obs_edges)
self.assertEqual(len(obs_nodes), 12)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'job']), 5)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'artifact']), 7)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'type']), 0)
self.assertEqual(len(obs_edges), 10)
self.assertIsNone(obs_wf)
def test_get_network_nodes_edges(self):
graph = Artifact(1).descendants_with_jobs
obs_nodes, obs_edges, obs_wf = get_network_nodes_edges(graph, True)
self.assertEqual(len(obs_nodes), 11)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'job']), 5)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'artifact']), 6)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'type']), 0)
self.assertEqual(len(obs_edges), 10)
self.assertIsNone(obs_wf)
# This graph only contains one node - check added to make sure that
# the graph gets extended accordingly
graph = Artifact(6).descendants_with_jobs
obs_nodes, obs_edges, obs_wf = get_network_nodes_edges(
graph, True, nodes=obs_nodes, edges=obs_edges)
self.assertEqual(len(obs_nodes), 12)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'job']), 5)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'artifact']), 7)
self.assertEqual(len([x for x in obs_nodes if x[0] == 'type']), 0)
self.assertEqual(len(obs_edges), 10)
self.assertIsNone(obs_wf)
def prep_template_graph_get_req(prep_id, user_id):
"""Returns graph of all artifacts created from the prep base artifact
Parameters
----------
prep_id : int
Prep template ID to get graph for
user_id : str
User making the request
Returns
-------
dict of lists of tuples
A dictionary containing the edge list representation of the graph,
and the node labels. Formatted as:
{'status': status,
'message': message,
'edge_list': [(0, 1), (0, 2)...],
'node_labels': [(0, 'label0'), (1, 'label1'), ...]}
Notes
-----
Nodes are identified by the corresponding Artifact ID.
"""
exists = _check_prep_template_exists(int(prep_id))
if exists['status'] != 'success':
return exists
prep = PrepTemplate(int(prep_id))
access_error = check_access(prep.study_id, user_id)
if access_error:
return access_error
# We should filter for only the public artifacts if the user
# doesn't have full access to the study
full_access = Study(prep.study_id).can_edit(User(user_id))
artifact = prep.artifact
if artifact is None:
return {'edges': [], 'nodes': [],
'status': 'success', 'message': ''}
G = artifact.descendants_with_jobs
nodes, edges, wf_id = get_network_nodes_edges(G, full_access)
return {'edges': edges,
'nodes': nodes,
'workflow': wf_id,
'status': 'success',
'message': ''}
def analyisis_graph_handler_get_request(analysis_id, user):
"""Returns the graph information of the analysis
Parameters
----------
analysis_id : int
The analysis id
user : qiita_db.user.User
The user performing the request
Returns
-------
dict with the graph information
Raises
------
ValueError
If there is more than one workflow in a single analysis
"""
analysis = Analysis(analysis_id)
# Check if the user actually has access to the analysis
check_analysis_access(user, analysis)
# A user has full access to the analysis if it is one of its private
# analyses, the analysis has been shared with the user or the user is a
# superuser or admin
full_access = (analysis in (user.private_analyses | user.shared_analyses)
or user.level in {'superuser', 'admin'})
nodes = []
edges = []
wf_id = None
# Loop through all the initial artifacts of the analysis
for a in analysis.artifacts:
if a.processing_parameters is None:
g = a.descendants_with_jobs
nodes, edges, a_wf_id = get_network_nodes_edges(g,
full_access,
nodes=nodes,
edges=edges)
if wf_id is None:
wf_id = a_wf_id
elif a_wf_id is not None and wf_id != a_wf_id:
# This should never happen, but worth having a useful message
raise ValueError('More than one workflow in a single analysis')
return {'edges': edges, 'nodes': nodes, 'workflow': wf_id}
def analyisis_graph_handler_get_request(analysis_id, user):
"""Returns the graph information of the analysis
Parameters
----------
analysis_id : int
The analysis id
user : qiita_db.user.User
The user performing the request
Returns
-------
dict with the graph information
Raises
------
ValueError
If there is more than one workflow in a single analysis
"""
analysis = Analysis(analysis_id)
# Check if the user actually has access to the analysis
check_analysis_access(user, analysis)
# A user has full access to the analysis if it is one of its private
# analyses, the analysis has been shared with the user or the user is a
# superuser or admin
full_access = (analysis in (user.private_analyses | user.shared_analyses)
or user.level in {'superuser', 'admin'})
nodes = []
edges = []
wf_id = None
# Loop through all the initial artifacts of the analysis
for a in analysis.artifacts:
if a.processing_parameters is None:
g = a.descendants_with_jobs
nodes, edges, a_wf_id = get_network_nodes_edges(
g, full_access, nodes=nodes, edges=edges)
if wf_id is None:
wf_id = a_wf_id
elif a_wf_id is not None and wf_id != a_wf_id:
# This should never happen, but worth having a useful message
raise ValueError('More than one workflow in a single analysis')
return {'edges': edges, 'nodes': nodes, 'workflow': wf_id}
