def generate_series():
session = api.get_session()
test_starts = api.get_test_run_series(session)
session.close()
ts = pd.Series(test_starts).resample('D', how='sum')
daily_count = utils.filter_dates(ts)
mean = pd.rolling_mean(daily_count, 10)
rolling_std = pd.rolling_std(daily_count, 10)
plt.figure()
title = CONF.title or 'Number of tests run'
plt.title(title)
plt.ylabel('Number of tests')
plt.plot(daily_count.index, daily_count, 'k', label='Daily Test Count')
plt.plot(mean.index, mean, 'b', label='Avg. Daily Test Count')
upper_std_dev = mean + 2 * rolling_std
lower_std_dev = mean - 2 * rolling_std
# Set negative numbers to 0
lower_std_dev[lower_std_dev < 0] = 0
plt.fill_between(rolling_std.index,
lower_std_dev,
upper_std_dev,
color='b',
alpha=0.2,
label='std dev')
plt.legend()
plt.savefig(CONF.output)
def test_get_test_run_series_with_meta(self):
timestamp_a = datetime.datetime.utcnow()
timestamp_b = timestamp_a + datetime.timedelta(minutes=2)
run_a = api.create_run(passes=5, run_at=timestamp_a)
api.create_run(fails=2, run_at=timestamp_b)
api.add_run_metadata({'not_a_key': 'not_a_value'}, run_a.id)
result = api.get_test_run_series(key='not_a_key', value='not_a_value')
self.assertEqual(1, len(result.keys()))
self.assertIn(timestamp_a.replace(microsecond=0),
[x.replace(microsecond=0) for x in list(result.keys())])
self.assertNotIn(
timestamp_b.replace(microsecond=0),
[x.replace(microsecond=0) for x in list(result.keys())])
self.assertEqual(5, result[list(result.keys())[0]])
def generate_series():
if CONF.start_date:
start_date = datetime.datetime.strptime(CONF.start_date, '%Y-%m-%d')
else:
start_date = None
if CONF.stop_date:
stop_date = datetime.datetime.strptime(CONF.stop_date, '%Y-%m-%d')
else:
stop_date = None
session = api.get_session()
test_starts = api.get_test_run_series(start_date=start_date,
stop_date=stop_date,
session=session,
key=CONF.command.dcmd_key,
value=CONF.command.dcmd_value)
session.close()
ts = pd.Series(test_starts)
daily_count = ts.resample('D').sum().fillna(value=0)
mean = daily_count.rolling(window=10, center=False).mean()
rolling_std = daily_count.rolling(window=10, center=False).std()
plt.figure()
title = CONF.title or 'Number of Tests run Daily'
plt.title(title)
plt.ylabel('Number of tests')
fig, ax = plt.subplots(1)
fig.autofmt_xdate()
plt.title(title)
plt.ylabel('Number of tests')
xfmt = dates.DateFormatter("%b %d %Y")
ax.xaxis_date()
ax.xaxis.set_major_formatter(xfmt)
plt.plot(daily_count.index[10:],
daily_count[10:],
'k',
label='Daily Test Count')
plt.plot(mean.index[10:], mean[10:], 'b', label='Avg. Daily Test Count')
upper_std_dev = mean + 2 * rolling_std
lower_std_dev = mean - 2 * rolling_std
# Set negative numbers to 0
lower_std_dev[lower_std_dev < 0] = 0
plt.fill_between(rolling_std.index[10:],
lower_std_dev[10:],
upper_std_dev[10:],
color='b',
alpha=0.2,
label='Std Dev')
plt.legend()
plt.savefig(CONF.output, dpi=900)
def test_get_test_run_series_with_meta(self):
timestamp_a = datetime.datetime.utcnow()
timestamp_b = timestamp_a + datetime.timedelta(minutes=2)
run_a = api.create_run(passes=5, run_at=timestamp_a)
api.create_run(fails=2, run_at=timestamp_b)
api.add_run_metadata({'not_a_key': 'not_a_value'}, run_a.id)
result = api.get_test_run_series(key='not_a_key',
value='not_a_value')
self.assertEqual(1, len(result.keys()))
self.assertIn(timestamp_a.replace(microsecond=0),
[x.replace(microsecond=0) for x in list(result.keys())])
self.assertNotIn(timestamp_b.replace(microsecond=0),
[x.replace(microsecond=0) for x in list(
result.keys())])
self.assertEqual(5, result[list(result.keys())[0]])
def test_get_test_run_series(self):
timestamp_a = datetime.datetime.utcnow()
timestamp_b = timestamp_a + datetime.timedelta(minutes=2)
api.create_run(passes=5, run_at=timestamp_a)
api.create_run(fails=2, run_at=timestamp_b)
result = api.get_test_run_series(key=None, value=None)
self.assertEqual(2, len(result.keys()))
self.assertIn(timestamp_a.replace(microsecond=0),
[x.replace(microsecond=0) for x in list(result.keys())])
self.assertIn(timestamp_b.replace(microsecond=0),
[x.replace(microsecond=0) for x in list(result.keys())])
for timestamp in result:
if timestamp.replace(microsecond=0) == timestamp_a.replace(
microsecond=0):
self.assertEqual(5, result[timestamp])
else:
self.assertEqual(2, result[timestamp])
def test_get_test_run_series(self):
timestamp_a = datetime.datetime.utcnow()
timestamp_b = timestamp_a + datetime.timedelta(minutes=2)
api.create_run(passes=5, run_at=timestamp_a)
api.create_run(fails=2, run_at=timestamp_b)
result = api.get_test_run_series(key=None, value=None)
self.assertEqual(2, len(result.keys()))
self.assertIn(timestamp_a.replace(microsecond=0),
[x.replace(microsecond=0) for x in list(result.keys())])
self.assertIn(timestamp_b.replace(microsecond=0),
[x.replace(microsecond=0) for x in list(result.keys())])
for timestamp in result:
if timestamp.replace(
microsecond=0) == timestamp_a.replace(microsecond=0):
self.assertEqual(5, result[timestamp])
else:
self.assertEqual(2, result[timestamp])
def generate_series():
if CONF.start_date:
start_date = datetime.datetime.strptime(CONF.start_date, '%Y-%m-%d')
else:
start_date = None
if CONF.stop_date:
stop_date = datetime.datetime.strptime(CONF.stop_date, '%Y-%m-%d')
else:
stop_date = None
session = api.get_session()
test_starts = api.get_test_run_series(start_date=start_date,
stop_date=stop_date,
session=session,
key=CONF.command.dcmd_key,
value=CONF.command.dcmd_value)
session.close()
ts = pd.Series(test_starts)
daily_count = ts.resample('D').sum().fillna(value=0)
mean = daily_count.rolling(window=10, center=False).mean()
rolling_std = daily_count.rolling(window=10, center=False).std()
plt.figure()
title = CONF.title or 'Number of Tests run Daily'
plt.title(title)
plt.ylabel('Number of tests')
fig, ax = plt.subplots(1)
fig.autofmt_xdate()
plt.title(title)
plt.ylabel('Number of tests')
xfmt = dates.DateFormatter("%b %d %Y")
ax.xaxis_date()
ax.xaxis.set_major_formatter(xfmt)
plt.plot(daily_count.index[10:], daily_count[10:], 'k',
label='Daily Test Count')
plt.plot(mean.index[10:], mean[10:], 'b', label='Avg. Daily Test Count')
upper_std_dev = mean + 2 * rolling_std
lower_std_dev = mean - 2 * rolling_std
# Set negative numbers to 0
lower_std_dev[lower_std_dev < 0] = 0
plt.fill_between(rolling_std.index[10:], lower_std_dev[10:],
upper_std_dev[10:],
color='b', alpha=0.2, label='Std Dev')
plt.legend()
plt.savefig(CONF.output, dpi=CONF.dpi)
def generate_series():
session = api.get_session()
test_starts = api.get_test_run_series(session)
session.close()
ts = pd.Series(test_starts).resample('D', how='sum')
daily_count = utils.filter_dates(ts)
mean = pd.rolling_mean(daily_count, 10)
rolling_std = pd.rolling_std(daily_count, 10)
plt.figure()
title = CONF.title or 'Number of tests run'
plt.title(title)
plt.ylabel('Number of tests')
plt.plot(daily_count.index, daily_count, 'k', label='Daily Test Count')
plt.plot(mean.index, mean, 'b', label='Avg. Daily Test Count')
upper_std_dev = mean + 2 * rolling_std
lower_std_dev = mean - 2 * rolling_std
# Set negative numbers to 0
lower_std_dev[lower_std_dev < 0] = 0
plt.fill_between(rolling_std.index, lower_std_dev, upper_std_dev,
color='b', alpha=0.2, label='std dev')
plt.legend()
plt.savefig(CONF.output)