def get(self):
datak = memcache.get('metrics')
if datak is None:
tdata = []
measurements = Measurement.query()
for m in measurements:
mdict = m.to_dict()
mdict['timestamp'] = datetime.strftime(mdict['timestamp'], "%Y-%m-%d %H:%M:%S")
if mdict['updated']:
mdict['updated'] = datetime.strftime(mdict['updated'], "%Y-%m-%d %H:%M:%S")
tdata.append(mdict)
datak = self._to_blobstore(tdata)
self.response.headers['Content-Type'] = 'application/zip'
stamp = str(int(time.mktime(memcache.get('updated').timetuple())))
self.send_blob(datak, save_as='metrics-{}.zip'.format(stamp))
def get(self):
# Generate lower bound for timestamp
lower_bound = datetime.now() + timedelta(days=-7)
dosables = Dosable.query(Dosable.timestamp > lower_bound).fetch()
measurements = (Measurement.query(Measurement.timestamp > lower_bound)
.fetch())
parallel_switches = (ParallelSwitch
.query(ParallelSwitch.timestamp > lower_bound).fetch())
# Sort data in each category by type
for data_group in [dosables, measurements, parallel_switches]:
data_group.sort(key=lambda d: d.type)
ret = {
category: {type: [instance.to_json() for instance in instances]
for type, instances
in itertools.groupby(data_group, key=lambda x: x.type)}
for category, data_group in [('dosables', dosables),
('measurements', measurements),
('parallel_switches', parallel_switches)]
}
self.out_json(ret)
def _get_count(self):
query = Measurement.query()
return query.count()
def _get_earliest(self):
query = Measurement.query()
return query.order(Measurement.timestamp).get().timestamp
