def test_get_grouped_profiled_requests(session, request_1, endpoint):
assert not get_grouped_profiled_requests(session, endpoint_id=endpoint.id)
add_stack_line(session,
request_id=request_1.id,
position=0,
indent=1,
duration=1,
code_line="code")
session.commit()
assert get_grouped_profiled_requests(session, endpoint_id=endpoint.id)
def test_get_grouped_profiled_requests(self):
with session_scope() as db_session:
self.assertEqual(
get_grouped_profiled_requests(db_session,
endpoint_id=ENDPOINT_ID), [])
add_stack_line(db_session,
request_id=ENDPOINT_ID,
position=0,
indent=1,
duration=1,
code_line="code")
self.assertNotEqual(
get_grouped_profiled_requests(db_session,
endpoint_id=ENDPOINT_ID), [])
def get_grouped_profiler(db_session, endpoint_id):
"""
:param db_session: session for the database
:param endpoint_id: endpoint to filter on
:return:
"""
requests = get_grouped_profiled_requests(db_session, endpoint_id)
db_session.expunge_all()
histogram = defaultdict(list) # path -> [list of values]
path_hash = PathHash()
for r in requests:
for index, stack_line in enumerate(r.stack_lines):
key = path_hash.get_stacklines_path(r.stack_lines, index)
histogram[key].append(stack_line.duration)
table = []
for key, duration_list in sorted(histogram.items(),
key=lambda row: row[0]):
table.append({
'indent': path_hash.get_indent(key) - 1,
'code': path_hash.get_code(key),
'hits': len(duration_list),
'duration': sum(duration_list),
'std': numpy.std(duration_list),
'total_hits': len(requests),
})
return table
def grouped_profiler(endpoint_id):
with session_scope() as db_session:
details = get_endpoint_details(db_session, endpoint_id)
requests = get_grouped_profiled_requests(db_session, endpoint_id)
db_session.expunge_all()
total_duration = sum([r.duration for r in requests])
histogram = defaultdict(list) # path -> [list of values]
path_hash = PathHash()
for r in requests:
for index, stack_line in enumerate(r.stack_lines):
key = path_hash.get_stacklines_path(r.stack_lines, index)
histogram[key].append(stack_line.duration)
table = []
for key, duration_list in sorted(histogram.items(),
key=lambda row: row[0]):
table.append(
GroupedStackLine(indent=path_hash.get_indent(key) - 1,
code=path_hash.get_code(key),
values=duration_list,
total_sum=total_duration,
total_hits=len(requests)))
for index, item in enumerate(table):
table[index].compute_body(index, table)
sunburst = json.dumps(table_to_json(table))
return render_template('fmd_dashboard/profiler_grouped.html',
details=details,
table=table,
sunburst=sunburst,
title='Grouped Profiler results for {}'.format(
details['endpoint']))
def get_grouped_profiler(session,
endpoint_id,
version=None,
previous_results=[],
changes=[]):
"""
:param session: session for the database
:param endpoint_id: endpoint to filter on
:return:
"""
requests = get_grouped_profiled_requests(session, endpoint_id, version)
session.expunge_all()
histogram = defaultdict(list) # path -> [list of values]
path_hash = PathHash()
for r in requests:
for index, stack_line in enumerate(r.stack_lines):
key = path_hash.get_stacklines_path(r.stack_lines, index)
histogram[key].append(stack_line.duration)
table = []
for key, duration_list in sorted(histogram.items(),
key=lambda row: row[0]):
previous = next((x for x in previous_results if x['id'] == key), None)
hits = len(duration_list)
duration = sum(duration_list)
avg_duration = duration / hits
std = numpy.std(duration_list)
total_hits = len(requests)
prev_hits = previous['hits'] if previous is not None else 0
prev_duration = previous['duration'] if previous is not None else 0
prev_avg_duration = previous[
'avg_duration'] if previous is not None else 0
was_changed = path_hash.get_code(key) in changes
duration_change = (
avg_duration - prev_avg_duration
) / prev_avg_duration if prev_avg_duration is not 0 else avg_duration
regression = bool(was_changed
and (avg_duration - prev_avg_duration) > std)
table.append({
'id': key,
'indent': path_hash.get_indent(key) - 1,
'code': path_hash.get_code(key),
'hits': hits,
'duration': duration,
'avg_duration': avg_duration,
'std': std,
'total_hits': total_hits,
'previous_hits': prev_hits,
'previous_duration': prev_duration,
'previous_avg_duration': prev_avg_duration,
'was_changed': was_changed,
'duration_change': duration_change,
'regression': regression,
})
return table
