def _render_latest_data(self):
"""Render the latest data with sparkline for each timeseries."""
date = tslib.date_from_utc_ts(self._computation.last_logical_ts)
print('\033[K\rAt {date} (@{resolution}, Δ: {lag}):'.format(
date=white(self._render_date(date), bold=True),
resolution=tslib.render_delta(self._computation.resolution)
if self._computation.resolution else '-',
lag=tslib.render_delta_from_now(date)))
if not len(self._sparks):
print('(no data)')
return 2
for tsid, spark in self._sparks.items():
metadata = self._computation.get_metadata(tsid)
print(u'\033[K\r{repr:<60}: [{spark:10s}] '.format(
repr=utils.timeseries_repr(metadata) or '',
spark=self._render_spark_line(spark)),
end='')
value = spark[-1]
if type(value) == int:
print('\033[;1m{0:>10d}\033[;0m'.format(value))
elif type(value) == float:
print('\033[;1m{0:>10.2f}\033[;0m'.format(value))
else:
print('{:>10s}'.format('-'))
return len(self._sparks) + 1
def _render_latest_data(self):
"""Render the latest data with sparkline for each timeseries."""
date = tslib.date_from_utc_ts(self._computation.last_logical_ts)
print('\033[K\rAt {date} (@{resolution}, Δ: {lag}):'.format(
date=white(self._render_date(date), bold=True),
resolution=tslib.render_delta(self._computation.resolution)
if self._computation.resolution else '-',
lag=tslib.render_delta_from_now(date)))
if not len(self._sparks):
print('(no data)')
return 2
for tsid, spark in self._sparks.items():
metadata = self._computation.get_metadata(tsid)
print(u'\033[K\r{repr:<60}: [{spark:10s}] '
.format(repr=utils.timeseries_repr(metadata) or '',
spark=self._render_spark_line(spark)),
end='')
value = spark[-1]
if type(value) == int:
print('\033[;1m{0:>10d}\033[;0m'.format(value))
elif type(value) == float:
print('\033[;1m{0:>10.2f}\033[;0m'.format(value))
else:
print('{:>10s}'.format('-'))
return len(self._sparks) + 1
def _render_latest_events(self):
"""Render the latest events emitted by the computation.
TODO(mpetazzoni): render custom events/alert events differently and
support alert event schema v3.
"""
print('\nEvents:')
def maybe_json(v):
if isinstance(v, six.string_types):
return json.loads(v)
return v
for event in self._events:
ets = self._computation.get_metadata(event.tsid)
contexts = json.loads(ets.get('sf_detectInputContexts', '{}'))
values = maybe_json(event.properties.get('inputs', '{}'))
values = ' | '.join([
u'{name} ({key}): {value}'.format(
name=white(contexts[k].get('identifier', k)),
key=','.join([
u'{0}:{1}'.format(dim_name, dim_value)
for dim_name, dim_value in v.get('key', {}).items()
]),
value=v['value']) for k, v in values.items()
])
date = tslib.date_from_utc_ts(event.timestamp_ms)
is_now = event.properties['is']
print(u' {mark} {date} [{incident}]: {values}'.format(
mark=green(u'✓') if is_now == 'ok' else red(u'✗'),
date=white(self._render_date(date), bold=True),
incident=event.properties['incidentId'],
values=values))
return 2 + len(self._events)
def _render_latest_events(self):
"""Render the latest events emitted by the computation.
TODO(mpetazzoni): render custom events/alert events differently and
support alert event schema v3.
"""
print('\nEvents:')
def maybe_json(v):
if isinstance(v, six.string_types):
return json.loads(v)
return v
for event in self._events:
ets = self._computation.get_metadata(event.tsid)
contexts = json.loads(ets.get('sf_detectInputContexts', '{}'))
values = maybe_json(event.properties.get('inputs', '{}'))
values = ' | '.join([
u'{name} ({key}): {value}'.format(
name=white(contexts[k].get('identifier', k)),
key=','.join([u'{0}:{1}'.format(dim_name, dim_value)
for dim_name, dim_value
in v.get('key', {}).items()]),
value=v['value'])
for k, v in values.items()])
date = tslib.date_from_utc_ts(event.timestamp_ms)
is_now = event.properties['is']
print(u' {mark} {date} [{incident}]: {values}'
.format(mark=green(u'✓') if is_now == 'ok' else red(u'✗'),
date=white(self._render_date(date), bold=True),
incident=event.properties['incidentId'],
values=values))
return 2 + len(self._events)