def encode_channel(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'bit_depth': obj.bit_depth,
'layers': [encoder.default(ch) for ch in obj.layers],
}
def encode_mapobject_type(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'features': map(encoder.default, obj.features),
'layers': [encoder.default(layer) for layer in obj.layers]
}
def encode_mapobject_type(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'features': map(encoder.default, obj.features),
'layers': [encoder.default(layer) for layer in obj.layers]
}
def encode_experiment(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'description': obj.description,
'user': obj.user.name
}
def encode_channel(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'bit_depth': obj.bit_depth,
'layers': [encoder.default(ch) for ch in obj.layers],
}
def encode_experiment(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'description': obj.description,
'user': obj.user.name
}
def encode_well(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'description': obj.description,
'plate_name': obj.plate.name,
'dimensions': list(obj.dimensions)
}
def encode_well(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'description': obj.description,
'plate_name': obj.plate.name,
'dimensions': list(obj.dimensions)
}
def encode_plate(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'description': obj.description,
'acquisitions': map(encoder.default, obj.acquisitions),
'status': obj.status,
}
def encode_acquisition(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'description': obj.description,
'status': obj.status,
'plate_name': obj.plate.name
}
def encode_plate(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'description': obj.description,
'acquisitions': map(encoder.default, obj.acquisitions),
'status': obj.status,
}
def encode_acquisition(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'description': obj.description,
'status': obj.status,
'plate_name': obj.plate.name
}
def encode_segmentation_layer(obj, encoder):
return {
'id': encode_pk(obj.id),
'tpoint': obj.tpoint,
'zplane': obj.zplane,
'image_size': {
'width': obj.mapobject_type.experiment.pyramid_width,
'height': obj.mapobject_type.experiment.pyramid_height
}
}
def encode_segmentation_layer(obj, encoder):
return {
'id': encode_pk(obj.id),
'tpoint': obj.tpoint,
'zplane': obj.zplane,
'image_size': {
'width': obj.mapobject_type.experiment.pyramid_width,
'height': obj.mapobject_type.experiment.pyramid_height
}
}
def encode_tool_result(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'submission_id': obj.submission_id,
'tool_name': obj.tool_name,
'type': obj.type,
'attributes': obj.attributes,
'layers': [encoder.default(layer) for layer in obj.mapobject_type.layers],
'plots': map(encoder.default, obj.plots)
}
def encode_site(obj, encoder):
return {
'id': encode_pk(obj.id),
'y': obj.y,
'x': obj.x,
'height': obj.height,
'width': obj.width,
'well_name': obj.well.name,
'plate_name': obj.well.plate.name
# TODO: shifts ?
}
def encode_site(obj, encoder):
return {
'id': encode_pk(obj.id),
'y': obj.y,
'x': obj.x,
'height': obj.height,
'width': obj.width,
'well_name': obj.well.name,
'plate_name': obj.well.plate.name
# TODO: shifts ?
}
def encode_channel_layer(obj, encoder):
return {
'id': encode_pk(obj.id),
'max_zoom': obj.maxzoom_level_index,
'tpoint': obj.tpoint,
'zplane': obj.zplane,
'max_intensity': obj.max_intensity,
'min_intensity': obj.min_intensity,
'image_size': {
'width': obj.channel.experiment.pyramid_width,
'height': obj.channel.experiment.pyramid_height
}
}
def encode_channel_layer(obj, encoder):
return {
'id': encode_pk(obj.id),
'max_zoom': obj.maxzoom_level_index,
'tpoint': obj.tpoint,
'zplane': obj.zplane,
'max_intensity': obj.max_intensity,
'min_intensity': obj.min_intensity,
'image_size': {
'width': obj.channel.experiment.pyramid_width,
'height': obj.channel.experiment.pyramid_height
}
}
def get_tool_jobs(experiment_id):
"""
.. http:get:: /api/experiments/(string:experiment_id)/tools/jobs
Get the status of each :class:`ToolJob <tmlib.models.jobs.ToolJob>`
processing a tool request.
**Example response**:
.. sourcecode:: http
HTTP/1.1 200 OK
Content-Type: application/json
{
"data": [
{
"id": "dG1hcHM3NzYxOA==",
"name": "tool_Heatmap",
"submission_id": 4,
"submitted_at": "2017-04-01 10:42:10",
"state": "RUNNING",
"exitcode": null,
"memory": 1024,
"time": "1:21:33",
"cpu_time": "1:14:12"
},
...
]
}
:query submission_id: numeric ID of the submission for which the job status should be retrieved (optional)
:query tool_name: name of a tool for which job status should be retrieved (optional)
:query state: state jobs should have, e.g. RUNNING (optional)
:statuscode 400: malformed request
:statuscode 200: no error
"""
logger.info('get status of tool jobs for experiment %d', experiment_id)
submission_id = request.args.get('submission_id', type=int)
tool_name = request.args.get('tool_name')
state = request.args.get('state')
# TODO: batch_size, index - see workflow.get_jobs_status()
with tm.utils.MainSession() as session:
tool_jobs = session.query(
tm.Task.created_at, tm.Task.updated_at,
tm.Task.id, tm.Task.name, tm.Task.type, tm.Task.time,
tm.Task.cpu_time, tm.Task.memory,
tm.Task.state, tm.Task.submission_id, tm.Task.exitcode
).\
join(tm.Submission, tm.Task.submission_id == tm.Submission.id).\
filter(
tm.Submission.program == 'tool',
tm.Submission.experiment_id == experiment_id,
tm.Submission.user_id == current_identity.id
)
if state is not None:
logger.info('filter tool jobs for state "%s"', state)
tool_jobs = tool_jobs.filter(tm.Task.state == state)
if tool_name is not None:
logger.info('filter tool jobs for tool name "%s"', tool_name)
tool_jobs = tool_jobs.filter(tm.Task.name == 'tool_%s' % tool_name)
if submission_id is not None:
logger.info('filter tool jobs for submission %d', submission_id)
tool_jobs = tool_jobs.\
filter(tm.Task.submission_id == submission_id)
tool_jobs = tool_jobs.all()
tool_job_status = list()
for j in tool_jobs:
status = format_task_data(
j.name, j.type, j.created_at, j.updated_at, j.state, j.exitcode,
j.memory, j.time, j.cpu_time
)
status['id'] = encode_pk(j.id)
status['submission_id'] = j.submission_id
status['submitted_at'] = str(j.created_at)
tool_job_status.append(status)
return jsonify(data=tool_job_status)
def get_workflow_jobs(experiment_id):
"""
.. http:get:: /api/experiments/(string:experiment_id)/workflow/jobs
Query the status of jobs for a given
:class:`WorkflowStep <tmlib.workflow.workflow.WorkflowStep>`.
**Example response**:
.. sourcecode:: http
HTTP/1.1 200 OK
Content-Type: application/json
{
"data": [
{
"id": "dG1hcHM3NzYxOA==",
"name": "metaconfig_run_000001",
"state": "RUNNING",
"exitcode": 0,
"memory": 1024,
"time": "1:21:33"
"cpu_time": "1:14:12"
},
...
]
}
:query step_name: name of the workflow step for which jobs should be queried (required)
:query step_phase: name of the workflow step phase for which jobs should be queried (optional)
:query name: name of the job (optional)
:query index: the index of the first job queried (optional)
:query batch_size: the amount of job stati to return starting from ``index`` (optional)
:reqheader Authorization: JWT token issued by the server
:statuscode 400: malformed request
:statuscode 200: no error
.. note:: Parameters ``index`` and ``batch_size`` can only be used togethger.
Parameters ``name`` and ``step_phase`` are exclusive and cannot be
combined with ``index`` and ``batch_size``.
"""
step_name = request.args.get('step_name')
logger.info('get status of jobs for workflow step "%s" of experiment %d',
step_name, experiment_id)
step_phase = request.args.get('phase')
name = request.args.get('name')
index = request.args.get('index', type=int)
batch_size = request.args.get('batch_size', type=int)
if ((index is not None and batch_size is None)
or (index is None and batch_size is not None)):
raise MalformedRequestError(
'Either both or none of the following parameters must be specified: '
'"index", "batch_size"')
if index is not None and name is not None:
raise MalformedRequestError(
'Only one of the following parameters can be specified: '
'"name", "index"')
if batch_size is not None and name is not None:
raise MalformedRequestError(
'Only one of the following parameters can be specified: '
'"name", "batch_size"')
if step_phase is not None and name is not None:
raise MalformedRequestError(
'Only one of the following parameters can be specified: '
'"name", "step_phase"')
# If the index is negative don't send `batch_size` jobs.
# For example, if the index is -5 and the batch_size 50,
# send the first 45 jobs back.
if index is not None and batch_size is not None:
if index < 0 and batch_size is not None:
batch_size = batch_size + index
index = 0
if batch_size <= 0:
return jsonify(data=[])
submission_id = gc3pie.get_id_of_most_recent_submission(
experiment_id, 'workflow')
# TODO: Upon reload, the submission_id of tasks doesn't get updated.
# While this makes sense to track tasks belonging to the same collection
# it doesn't allow the differentiation of submissions (as the name implies).
with tm.utils.MainSession() as session:
step_task_id = session.query(tm.Task.id).\
filter(
tm.Task.submission_id == submission_id,
tm.Task.name == step_name,
tm.Task.is_collection
).\
one_or_none()
if step_task_id is None:
status = []
else:
phase_tasks = session.query(tm.Task.id, tm.Task.name).\
filter_by(parent_id=step_task_id).\
all()
if len(phase_tasks) == 0:
status = []
else:
task_ids = collections.defaultdict(list)
for phase_id, phase_name in phase_tasks:
if step_phase is not None:
if not phase_name.endswith(step_phase):
continue
subtasks = session.query(
tm.Task.id, tm.Task.is_collection, tm.Task.name
).\
filter_by(parent_id=phase_id).\
order_by(tm.Task.id).\
all()
if len(subtasks) == 0:
continue
else:
for st in subtasks:
if st.is_collection:
subsubtasks = session.query(
tm.Task.id, tm.Task.name
).\
filter_by(parent_id=st.id).\
order_by(tm.Task.id).\
all()
for sst in subsubtasks:
task_ids[sst.name].append(sst.id)
else:
task_ids[st.name].append(st.id)
task_ids = [v[0] for v in task_ids.values()]
if task_ids:
tasks = session.query(
tm.Task.id, tm.Task.name, tm.Task.type,
tm.Task.state, tm.Task.created_at,
tm.Task.updated_at, tm.Task.exitcode,
tm.Task.memory, tm.Task.time, tm.Task.cpu_time
).\
filter(tm.Task.id.in_(task_ids)).\
order_by(tm.Task.name)
if index is not None and batch_size is not None:
logger.debug('query status of %d jobs starting at %d',
batch_size, index)
tasks = tasks.limit(batch_size).offset(index)
if name is not None:
tasks = tasks.filter_by(name=name)
tasks = tasks.all()
status = []
for t in tasks:
s = format_task_data(t.name, t.type, t.created_at,
t.updated_at, t.state, t.exitcode,
t.memory, t.time, t.cpu_time)
s['id'] = encode_pk(t.id)
status.append(s)
else:
status = []
return jsonify(data=status)
def create_experiment():
"""
.. http:post:: /api/experiments
Create a new :class:`Experiment <tmlib.models.experiment.Experiment>`.
**Example request**:
.. sourcecode:: http
Content-Type: application/json
{
"name": "Experiment XY",
"description": "Optional description",
"workflow_type": "canonical",
"plate_format": "0",
"plate_acquisition_mode": "multiplexing",
"microscope_type": "cellvoyager"
}
**Example response**:
.. sourcecode:: http
HTTP/1.1 200 OK
Content-Type: application/json
{
"data": {
"id": "MQ==",
"name": "Experiment XY",
"description": "Optional description",
"user": "******"
}
}
:reqheader Authorization: JWT token issued by the server
:statuscode 200: no error
"""
data = request.get_json()
name = data.get('name')
workflow_type = data.get('workflow_type')
microscope_type = data.get('microscope_type')
plate_format = int(data.get('plate_format'))
plate_acquisition_mode = data.get('plate_acquisition_mode')
description = data.get('description', '')
logger.info('create experiment "%s"', name)
with tm.utils.MainSession() as session:
experiment_ref = tm.ExperimentReference(
name=name,
description=description,
user_id=current_identity.id,
root_directory=lib_cfg.storage_home
)
session.add(experiment_ref)
session.commit()
experiment_id = experiment_ref.id
experiment_location = experiment_ref.location
with tm.utils.ExperimentSession(experiment_id) as session:
experiment = tm.Experiment(
id=experiment_id,
location=experiment_location,
workflow_type=workflow_type,
microscope_type=microscope_type,
plate_format=plate_format,
plate_acquisition_mode=plate_acquisition_mode
)
session.add(experiment)
return jsonify({
'data': {
'id': encode_pk(experiment_id),
'name': name,
'description': description,
'user': current_identity.name
}
})
def get_workflow_jobs(experiment_id):
"""
.. http:get:: /api/experiments/(string:experiment_id)/workflow/jobs
Query the status of jobs for a given
:class:`WorkflowStep <tmlib.workflow.workflow.WorkflowStep>`.
**Example response**:
.. sourcecode:: http
HTTP/1.1 200 OK
Content-Type: application/json
{
"data": [
{
"id": "dG1hcHM3NzYxOA==",
"name": "metaconfig_run_000001",
"state": "RUNNING",
"exitcode": 0,
"memory": 1024,
"time": "1:21:33"
"cpu_time": "1:14:12"
},
...
]
}
:query step_name: name of the workflow step for which jobs should be queried (required)
:query step_phase: name of the workflow step phase for which jobs should be queried (optional)
:query name: name of the job (optional)
:query index: the index of the first job queried (optional)
:query batch_size: the amount of job stati to return starting from ``index`` (optional)
:reqheader Authorization: JWT token issued by the server
:statuscode 400: malformed request
:statuscode 200: no error
.. note:: Parameters ``index`` and ``batch_size`` can only be used togethger.
Parameters ``name`` and ``step_phase`` are exclusive and cannot be
combined with ``index`` and ``batch_size``.
"""
step_name = request.args.get('step_name')
logger.info(
'get status of jobs for workflow step "%s" of experiment %d',
step_name, experiment_id
)
step_phase = request.args.get('phase')
name = request.args.get('name')
index = request.args.get('index', type=int)
batch_size = request.args.get('batch_size', type=int)
if ((index is not None and batch_size is None) or
(index is None and batch_size is not None)):
raise MalformedRequestError(
'Either both or none of the following parameters must be specified: '
'"index", "batch_size"'
)
if index is not None and name is not None:
raise MalformedRequestError(
'Only one of the following parameters can be specified: '
'"name", "index"'
)
if batch_size is not None and name is not None:
raise MalformedRequestError(
'Only one of the following parameters can be specified: '
'"name", "batch_size"'
)
if step_phase is not None and name is not None:
raise MalformedRequestError(
'Only one of the following parameters can be specified: '
'"name", "step_phase"'
)
# If the index is negative don't send `batch_size` jobs.
# For example, if the index is -5 and the batch_size 50,
# send the first 45 jobs back.
if index is not None and batch_size is not None:
if index < 0 and batch_size is not None:
batch_size = batch_size + index
index = 0
if batch_size <= 0:
return jsonify(data=[])
submission_id = gc3pie.get_id_of_most_recent_submission(
experiment_id, 'workflow'
)
# TODO: Upon reload, the submission_id of tasks doesn't get updated.
# While this makes sense to track tasks belonging to the same collection
# it doesn't allow the differentiation of submissions (as the name implies).
with tm.utils.MainSession() as session:
step_task_id = session.query(tm.Task.id).\
filter(
tm.Task.submission_id == submission_id,
tm.Task.name == step_name,
tm.Task.is_collection
).\
one_or_none()
if step_task_id is None:
status = []
else:
phase_tasks = session.query(tm.Task.id, tm.Task.name).\
filter_by(parent_id=step_task_id).\
all()
if len(phase_tasks) == 0:
status = []
else:
task_ids = collections.defaultdict(list)
for phase_id, phase_name in phase_tasks:
if step_phase is not None:
if not phase_name.endswith(step_phase):
continue
subtasks = session.query(
tm.Task.id, tm.Task.is_collection, tm.Task.name
).\
filter_by(parent_id=phase_id).\
order_by(tm.Task.id).\
all()
if len(subtasks) == 0:
continue
else:
for st in subtasks:
if st.is_collection:
subsubtasks = session.query(
tm.Task.id, tm.Task.name
).\
filter_by(parent_id=st.id).\
order_by(tm.Task.id).\
all()
for sst in subsubtasks:
task_ids[sst.name].append(sst.id)
else:
task_ids[st.name].append(st.id)
task_ids = [v[0] for v in task_ids.values()]
if task_ids:
tasks = session.query(
tm.Task.id, tm.Task.name, tm.Task.type,
tm.Task.state, tm.Task.created_at,
tm.Task.updated_at, tm.Task.exitcode,
tm.Task.memory, tm.Task.time, tm.Task.cpu_time
).\
filter(tm.Task.id.in_(task_ids)).\
order_by(tm.Task.name)
if index is not None and batch_size is not None:
logger.debug(
'query status of %d jobs starting at %d',
batch_size, index
)
tasks = tasks.limit(batch_size).offset(index)
if name is not None:
tasks = tasks.filter_by(name=name)
tasks = tasks.all()
status = []
for t in tasks:
s = format_task_data(
t.name, t.type, t.created_at, t.updated_at,
t.state, t.exitcode, t.memory, t.time, t.cpu_time
)
s['id'] = encode_pk(t.id)
status.append(s)
else:
status = []
return jsonify(data=status)
def create_experiment():
"""
Create a new :class:`Experiment <tmlib.models.experiment.Experiment>`.
.. note::
The ``description`` parameter in this request is *not* the
"workflow description" YAML file: the latter is set to a default
value (depending on the ``workflow_type`` key) and can be later
changed with the ``update_workflow_description()``:func: API call; the
former is only used to set the ``description`` columnt in table
``experiment_references`` which is used when listing existing
experiments in the UI.
.. http:post:: /api/experiments
**Example request**:
.. sourcecode:: http
Content-Type: application/json
{
"name": "Experiment XY",
"description": "Optional description",
"workflow_type": "canonical",
"plate_format": "0",
"plate_acquisition_mode": "multiplexing",
"microscope_type": "cellvoyager"
}
**Example response**:
.. sourcecode:: http
HTTP/1.1 200 OK
Content-Type: application/json
{
"data": {
"id": "MQ==",
"name": "Experiment XY",
"description": "Optional description",
"user": "******"
}
}
:reqheader Authorization: JWT token issued by the server
:statuscode 200: no error
"""
data = request.get_json()
name = data.get('name')
workflow_type = data.get('workflow_type')
microscope_type = data.get('microscope_type')
plate_format = int(data.get('plate_format'))
plate_acquisition_mode = data.get('plate_acquisition_mode')
# WARNING: this description is just human-readable text,
# has no connection to the "workflow description" YAML file
description = data.get('description', '')
logger.info('create experiment "%s"', name)
with tm.utils.MainSession() as session:
experiment_ref = tm.ExperimentReference(
name=name,
description=description,
user_id=current_identity.id,
root_directory=lib_cfg.storage_home)
session.add(experiment_ref)
session.commit()
experiment_id = experiment_ref.id
experiment_location = experiment_ref.location
with tm.utils.ExperimentSession(experiment_id) as session:
experiment = tm.Experiment(
id=experiment_id,
location=experiment_location,
workflow_type=workflow_type,
microscope_type=microscope_type,
plate_format=plate_format,
plate_acquisition_mode=plate_acquisition_mode)
session.add(experiment)
session.commit()
return jsonify({
'data': {
'id': encode_pk(experiment_id),
'name': name,
'description': description,
'user': current_identity.name
}
})
def create_experiment():
"""
Create a new :class:`Experiment <tmlib.models.experiment.Experiment>`.
.. note::
The ``description`` parameter in this request is *not* the
"workflow description" YAML file: the latter is set to a default
value (depending on the ``workflow_type`` key) and can be later
changed with the ``update_workflow_description()``:func: API call; the
former is only used to set the ``description`` columnt in table
``experiment_references`` which is used when listing existing
experiments in the UI.
.. http:post:: /api/experiments
**Example request**:
.. sourcecode:: http
Content-Type: application/json
{
"name": "Experiment XY",
"description": "Optional description",
"workflow_type": "canonical",
"plate_format": "0",
"plate_acquisition_mode": "multiplexing",
"microscope_type": "cellvoyager"
}
**Example response**:
.. sourcecode:: http
HTTP/1.1 200 OK
Content-Type: application/json
{
"data": {
"id": "MQ==",
"name": "Experiment XY",
"description": "Optional description",
"user": "******"
}
}
:reqheader Authorization: JWT token issued by the server
:statuscode 200: no error
"""
data = request.get_json()
name = data.get('name')
workflow_type = data.get('workflow_type')
microscope_type = data.get('microscope_type')
plate_format = int(data.get('plate_format'))
plate_acquisition_mode = data.get('plate_acquisition_mode')
# WARNING: this description is just human-readable text,
# has no connection to the "workflow description" YAML file
description = data.get('description', '')
logger.info('create experiment "%s"', name)
with tm.utils.MainSession() as session:
experiment_ref = tm.ExperimentReference(
name=name,
description=description,
user_id=current_identity.id,
root_directory=lib_cfg.storage_home
)
session.add(experiment_ref)
session.commit()
experiment_id = experiment_ref.id
experiment_location = experiment_ref.location
with tm.utils.ExperimentSession(experiment_id) as session:
experiment = tm.Experiment(
id=experiment_id,
location=experiment_location,
workflow_type=workflow_type,
microscope_type=microscope_type,
plate_format=plate_format,
plate_acquisition_mode=plate_acquisition_mode
)
session.add(experiment)
session.commit()
return jsonify({
'data': {
'id': encode_pk(experiment_id),
'name': name,
'description': description,
'user': current_identity.name
}
})
def get_tool_jobs(experiment_id):
"""
.. http:get:: /api/experiments/(string:experiment_id)/tools/jobs
Get the status of each :class:`ToolJob <tmlib.models.jobs.ToolJob>`
processing a tool request.
**Example response**:
.. sourcecode:: http
HTTP/1.1 200 OK
Content-Type: application/json
{
"data": [
{
"id": "dG1hcHM3NzYxOA==",
"name": "tool_Heatmap",
"submission_id": 4,
"submitted_at": "2017-04-01 10:42:10",
"state": "RUNNING",
"exitcode": null,
"memory": 1024,
"time": "1:21:33",
"cpu_time": "1:14:12"
},
...
]
}
:query submission_id: numeric ID of the submission for which the job status should be retrieved (optional)
:query tool_name: name of a tool for which job status should be retrieved (optional)
:query state: state jobs should have, e.g. RUNNING (optional)
:statuscode 400: malformed request
:statuscode 200: no error
"""
logger.info('get status of tool jobs for experiment %d', experiment_id)
submission_id = request.args.get('submission_id', type=int)
tool_name = request.args.get('tool_name')
state = request.args.get('state')
# TODO: batch_size, index - see workflow.get_jobs_status()
with tm.utils.MainSession() as session:
tool_jobs = session.query(
tm.Task.created_at, tm.Task.updated_at,
tm.Task.id, tm.Task.name, tm.Task.type, tm.Task.time,
tm.Task.cpu_time, tm.Task.memory,
tm.Task.state, tm.Task.submission_id, tm.Task.exitcode
).\
join(tm.Submission, tm.Task.submission_id == tm.Submission.id).\
filter(
tm.Submission.program == 'tool',
tm.Submission.experiment_id == experiment_id,
tm.Submission.user_id == current_identity.id
)
if state is not None:
logger.info('filter tool jobs for state "%s"', state)
tool_jobs = tool_jobs.filter(tm.Task.state == state)
if tool_name is not None:
logger.info('filter tool jobs for tool name "%s"', tool_name)
tool_jobs = tool_jobs.filter(tm.Task.name == 'tool_%s' % tool_name)
if submission_id is not None:
logger.info('filter tool jobs for submission %d', submission_id)
tool_jobs = tool_jobs.\
filter(tm.Task.submission_id == submission_id)
tool_jobs = tool_jobs.all()
tool_job_status = list()
for j in tool_jobs:
status = format_task_data(j.name, j.type, j.created_at,
j.updated_at, j.state, j.exitcode,
j.memory, j.time, j.cpu_time)
status['id'] = encode_pk(j.id)
status['submission_id'] = j.submission_id
status['submitted_at'] = str(j.created_at)
tool_job_status.append(status)
return jsonify(data=tool_job_status)
def encode_cycle(obj, encoder):
return {
'id': encode_pk(obj.id),
'index': obj.index,
'tpoint': obj.tpoint
}
def encode_plot(obj, encoder):
return {
'id': encode_pk(obj.id),
'type': obj.type,
'attributes': obj.attributes
}
def encode_cycle(obj, encoder):
return {'id': encode_pk(obj.id), 'index': obj.index, 'tpoint': obj.tpoint}
def encode_microscope_metadata_file(obj, encoder):
return {'id': encode_pk(obj.id), 'name': obj.name, 'status': obj.status}
def encode_plot(obj, encoder):
return {
'id': encode_pk(obj.id),
'type': obj.type,
'attributes': obj.attributes
}
def encode_feature(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
}
def encode_feature(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
}
def encode_microscope_metadata_file(obj, encoder):
return {
'id': encode_pk(obj.id),
'name': obj.name,
'status': obj.status
}
