def test_calendar_time_sum(self):
task = setup_task_history(self)
df = work_time_df([task.project])
# Duplicate the amount of work completed by creating a ficitonal
# second set of tasks. The calendar times are the same, so the
# project shouldn't have double the calendar time.
duplicate = df.copy(deep=True)
duplicate['task_id'] = duplicate.task_id + 1
df = concat([df, duplicate])
header = ['calendar_time']
# Test grouping by project ID
expected = DataFrame(
[(timedelta(hours=3, minutes=13))],
columns=header)
returned = calendar_time_sum(df, ['project_id'])
assert_frame_equal(returned[header], expected)
# Test grouping by task ID
expected = DataFrame(
[(timedelta(hours=3, minutes=13),),
(timedelta(hours=3, minutes=13),)],
columns=header)
returned = calendar_time_sum(df, ['project_id', 'task_id'])
assert_frame_equal(returned[header], expected)
def test_work_time_df(self):
task = setup_task_history(self)
returned = work_time_df([task.project])
self.assertEquals(returned.project_id.nunique(), 1)
self.assertEquals(returned.task_id.nunique(), 1)
header = ['assignment_level', 'worker', 'iteration', 'start_datetime',
'end_datetime', 'calendar_time', 'work_time']
expected = DataFrame(
[(1, 'test_user_5', 0, parse('2015-10-12T01:00:00+00:00'), parse('2015-10-12T02:00:00+00:00'), timedelta(hours=1), timedelta(seconds=0)), # noqa
(1, 'test_user_5', 1, parse('2015-10-12T02:00:00+00:00'), parse('2015-10-12T02:02:00+00:00'), timedelta(minutes=2), timedelta(seconds=35)), # noqa
(2, 'test_user_6', 0, parse('2015-10-12T02:02:00+00:00'), parse('2015-10-12T03:00:00+00:00'), timedelta(minutes=58), timedelta(seconds=0)), # noqa
(2, 'test_user_6', 1, parse('2015-10-12T03:00:00+00:00'), parse('2015-10-12T03:01:00+00:00'), timedelta(minutes=1), timedelta(seconds=36)), # noqa
(1, 'test_user_5', 2, parse('2015-10-12T03:01:00+00:00'), parse('2015-10-12T03:05:00+00:00'), timedelta(minutes=4), timedelta(seconds=37)), # noqa
(2, 'test_user_6', 2, parse('2015-10-12T03:05:00+00:00'), parse('2015-10-12T03:07:00+00:00'), timedelta(minutes=2), timedelta(seconds=38)), # noqa
(3, 'test_user_7', 0, parse('2015-10-12T03:07:00+00:00'), parse('2015-10-12T04:00:00+00:00'), timedelta(minutes=53), timedelta(seconds=0)), # noqa
(3, 'test_user_7', 1, parse('2015-10-12T04:00:00+00:00'), parse('2015-10-12T04:02:00+00:00'), timedelta(minutes=2), timedelta(seconds=36)), # noqa
(2, 'test_user_6', 3, parse('2015-10-12T04:02:00+00:00'), parse('2015-10-12T04:03:00+00:00'), timedelta(minutes=1), timedelta(seconds=35)), # noqa
(3, 'test_user_7', 2, parse('2015-10-12T04:03:00+00:00'), parse('2015-10-12T04:13:00+00:00'), timedelta(minutes=10), timedelta(seconds=38)), # noqa
],
columns=header)
expected['start_datetime'] = (
expected['start_datetime'].astype('datetime64[ns]'))
expected['end_datetime'] = (
expected['end_datetime'].astype('datetime64[ns]'))
assert_frame_equal(returned[header], expected)
def test_calendar_time_sum(self):
task = setup_task_history(self)
df = work_time_df([task.project])
# Duplicate the amount of work completed by creating a ficitonal
# second set of tasks. The calendar times are the same, so the
# project shouldn't have double the calendar time.
duplicate = df.copy(deep=True)
duplicate['task_id'] = duplicate.task_id + 1
df = concat([df, duplicate])
header = ['calendar_time']
# Test grouping by project ID
expected = DataFrame([(timedelta(hours=3, minutes=13))],
columns=header)
returned = calendar_time_sum(df, ['project_id'])
assert_frame_equal(returned[header], expected)
# Test grouping by task ID
expected = DataFrame([(timedelta(hours=3, minutes=13), ),
(timedelta(hours=3, minutes=13), )],
columns=header)
returned = calendar_time_sum(df, ['project_id', 'task_id'])
assert_frame_equal(returned[header], expected)
def test_work_time_sum(self):
task = setup_task_history(self)
df = work_time_df([task.project])
header = ['work_time']
expected = DataFrame([(timedelta(minutes=4, seconds=15))],
columns=header)
returned = work_time_sum(df, ['project_id'])
assert_frame_equal(returned[header], expected)
def test_work_time_sum(self):
task = setup_task_history(self)
df = work_time_df([task.project])
header = ['work_time']
expected = DataFrame(
[(timedelta(minutes=4, seconds=15))],
columns=header)
returned = work_time_sum(df, ['project_id'])
assert_frame_equal(returned[header], expected)
def test_work_time_df(self):
task = setup_task_history(self)
returned = work_time_df([task.project])
self.assertEquals(returned.project_id.nunique(), 1)
self.assertEquals(returned.task_id.nunique(), 1)
header = [
'assignment_level', 'worker', 'iteration', 'start_datetime',
'end_datetime', 'calendar_time', 'work_time'
]
expected = DataFrame(
[
(1, 'test_user_5', 0, parse('2015-10-12T01:00:00+00:00'),
parse('2015-10-12T02:00:00+00:00'), timedelta(hours=1),
timedelta(seconds=0)), # noqa
(1, 'test_user_5', 1, parse('2015-10-12T02:00:00+00:00'),
parse('2015-10-12T02:02:00+00:00'), timedelta(minutes=2),
timedelta(seconds=35)), # noqa
(2, 'test_user_6', 0, parse('2015-10-12T02:02:00+00:00'),
parse('2015-10-12T03:00:00+00:00'), timedelta(minutes=58),
timedelta(seconds=0)), # noqa
(2, 'test_user_6', 1, parse('2015-10-12T03:00:00+00:00'),
parse('2015-10-12T03:01:00+00:00'), timedelta(minutes=1),
timedelta(seconds=36)), # noqa
(1, 'test_user_5', 2, parse('2015-10-12T03:01:00+00:00'),
parse('2015-10-12T03:05:00+00:00'), timedelta(minutes=4),
timedelta(seconds=37)), # noqa
(2, 'test_user_6', 2, parse('2015-10-12T03:05:00+00:00'),
parse('2015-10-12T03:07:00+00:00'), timedelta(minutes=2),
timedelta(seconds=38)), # noqa
(3, 'test_user_7', 0, parse('2015-10-12T03:07:00+00:00'),
parse('2015-10-12T04:00:00+00:00'), timedelta(minutes=53),
timedelta(seconds=0)), # noqa
(3, 'test_user_7', 1, parse('2015-10-12T04:00:00+00:00'),
parse('2015-10-12T04:02:00+00:00'), timedelta(minutes=2),
timedelta(seconds=36)), # noqa
(2, 'test_user_6', 3, parse('2015-10-12T04:02:00+00:00'),
parse('2015-10-12T04:03:00+00:00'), timedelta(minutes=1),
timedelta(seconds=35)), # noqa
(3, 'test_user_7', 2, parse('2015-10-12T04:03:00+00:00'),
parse('2015-10-12T04:13:00+00:00'), timedelta(minutes=10),
timedelta(seconds=38)), # noqa
],
columns=header)
expected['start_datetime'] = (
expected['start_datetime'].astype('datetime64[ns]'))
expected['end_datetime'] = (
expected['end_datetime'].astype('datetime64[ns]'))
assert_frame_equal(returned[header], expected)
def main(options):
print(work_time_df(Project.objects.filter(id=1)))
def main(options):
print(work_time_df(Project.objects.filter(id=1)))
def project_management_information(project_id):
project = Project.objects.get(id=project_id)
df = work_time_df([project], human_only=False, complete_tasks_only=False)
project_information = get_project_information(project.id)
project_information['project']['status'] = dict(
Project.STATUS_CHOICES).get(project.status, None)
project_information['project']['admin_url'] = urljoin(
settings.ORCHESTRA_URL,
urlresolvers.reverse('admin:orchestra_project_change',
args=(project_id, )))
for slug, task in project_information['tasks'].items():
task['admin_url'] = urljoin(
settings.ORCHESTRA_URL,
urlresolvers.reverse('admin:orchestra_task_change',
args=(task['id'], )))
for assignment in task['assignments']:
assignment['admin_url'] = urljoin(
settings.ORCHESTRA_URL,
urlresolvers.reverse('admin:orchestra_taskassignment_change',
args=(assignment['id'], )))
iterations = df[(df.worker == assignment['worker']['username'])
& (df.task_id == task['id'])]
iterations = iterations[['start_datetime', 'end_datetime']]
assignment['iterations'] = []
for idx, info in iterations.T.items():
iteration = info.to_dict()
assignment['iterations'].append(iteration)
if assignment['status'] == 'Processing':
last_iteration_end = assignment['start_datetime']
last_assignment = last_snapshotted_assignment(task['id'])
if last_assignment and len(assignment['iterations']) > 1:
last_iteration_end = (
last_assignment.snapshots['snapshots'][-1]['datetime'])
assignment['iterations'].append({
'start_datetime': last_iteration_end,
'end_datetime': timezone.now()
})
if task['status'] in ('Awaiting Processing', 'Pending Review'):
last_assignment_end = task['start_datetime']
last_assignment = last_snapshotted_assignment(task['id'])
if last_assignment:
last_assignment_end = (
last_assignment.snapshots['snapshots'][-1]['datetime'])
task['assignments'].append({
'iterations': [{
'start_datetime': last_assignment_end,
'end_datetime': timezone.now()
}],
'snapshots':
empty_snapshots(),
'start_datetime':
last_assignment_end,
'status':
'Processing',
'task':
task['id'],
'worker': {
'id': None,
'username': None
},
})
return project_information
