def async_usage_data(device_id, unit, channel, start_seconds, end_seconds):
"""
Return data from start_seconds to end_seconds from influxdb.
Used for asynchronous energy usage display of many points (up to millions).
"""
dbcon = InfluxDBClient(INFLUXDB_HOST, INFLUXDB_PORT, INFLUXDB_USER,
INFLUXDB_PASSWORD, INFLUXDB_DATABASE)
# Set the time frame to the past year if start/end not specified
if start_seconds == '0' and end_seconds == '0':
# Get how many points there are in the past year
query_str = query_string(unit,
device_id,
channel=channel,
value='COUNT')
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
count_points = raw_data['series'][0]['values'][0][1]
# Get the timestamp of the first point in the past year
query_str = query_string(unit, device_id, channel=channel, limit=1)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
first_point = raw_data['series'][0]['values'][0][0]
end = datetime.datetime.utcnow()
end_str = end.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
# Set the time frame to the past start epoch to now
elif start_seconds != '0' and end_seconds == '0':
start = datetime.datetime.utcfromtimestamp(float(start_seconds))
start_str = start.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
end = datetime.datetime.utcnow()
end_str = end.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
query_str = query_string(unit,
device_id,
channel=channel,
value='COUNT',
start_str=start_str,
end_str=end_str)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
count_points = raw_data['series'][0]['values'][0][1]
# Get the timestamp of the first point in the past year
query_str = query_string(unit,
device_id,
channel=channel,
start_str=start_str,
end_str=end_str,
limit=1)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
first_point = raw_data['series'][0]['values'][0][0]
else:
start = datetime.datetime.utcfromtimestamp(float(start_seconds))
start_str = start.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
end = datetime.datetime.utcfromtimestamp(float(end_seconds))
end_str = end.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
query_str = query_string(unit,
device_id,
channel=channel,
value='COUNT',
start_str=start_str,
end_str=end_str)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
count_points = raw_data['series'][0]['values'][0][1]
# Get the timestamp of the first point in the past year
query_str = query_string(unit,
device_id,
channel=channel,
start_str=start_str,
end_str=end_str,
limit=1)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
first_point = raw_data['series'][0]['values'][0][0]
start = datetime.datetime.strptime(
influx_time_str_to_milliseconds(first_point), '%Y-%m-%dT%H:%M:%S.%f')
start_str = start.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
logger.debug('Count = {}'.format(count_points))
logger.debug('Start = {}'.format(start))
logger.debug('End = {}'.format(end))
# How many seconds between the start and end period
time_difference_seconds = (end - start).total_seconds()
logger.debug('Difference seconds = {}'.format(time_difference_seconds))
# If there are more than 700 points in the time frame, we need to group
# data points into 700 groups with points averaged in each group.
if count_points > 700:
# Average period between input reads
seconds_per_point = time_difference_seconds / count_points
logger.debug('Seconds per point = {}'.format(seconds_per_point))
# How many seconds to group data points in
group_seconds = int(time_difference_seconds / 700)
logger.debug('Group seconds = {}'.format(group_seconds))
try:
query_str = query_string(unit,
device_id,
channel=channel,
value='MEAN',
start_str=start_str,
end_str=end_str,
group_sec=group_seconds)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
return jsonify(raw_data['series'][0]['values'])
except Exception as e:
logger.error("URL for 'async_data' raised and error: "
"{err}".format(err=e))
return '', 204
else:
try:
query_str = query_string(unit,
device_id,
channel=channel,
start_str=start_str,
end_str=end_str)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
return jsonify(raw_data['series'][0]['values'])
except Exception as e:
logger.error("URL for 'async_usage' raised and error: "
"{err}".format(err=e))
return '', 204
def async_data(device_id, device_type, measurement_id, start_seconds,
end_seconds):
"""
Return data from start_seconds to end_seconds from influxdb.
Used for asynchronous graph display of many points (up to millions).
"""
if device_type == 'tag':
notes_list = []
tag = NoteTags.query.filter(NoteTags.unique_id == device_id).first()
start = datetime.datetime.utcfromtimestamp(float(start_seconds))
if end_seconds == '0':
end = datetime.datetime.utcnow()
else:
end = datetime.datetime.utcfromtimestamp(float(end_seconds))
notes = Notes.query.filter(
and_(Notes.date_time >= start, Notes.date_time <= end)).all()
for each_note in notes:
if tag.unique_id in each_note.tags.split(','):
notes_list.append([
each_note.date_time.strftime(
"%Y-%m-%dT%H:%M:%S.000000000Z"), each_note.name,
each_note.note
])
if notes_list:
return jsonify(notes_list)
else:
return '', 204
dbcon = InfluxDBClient(INFLUXDB_HOST, INFLUXDB_PORT, INFLUXDB_USER,
INFLUXDB_PASSWORD, INFLUXDB_DATABASE)
if device_type in ['input', 'math', 'output', 'pid']:
measure = DeviceMeasurements.query.filter(
DeviceMeasurements.unique_id == measurement_id).first()
else:
measure = None
if not measure:
return "Could not find measurement"
if measure:
conversion = Conversion.query.filter(
Conversion.unique_id == measure.conversion_id).first()
else:
conversion = None
channel, unit, measurement = return_measurement_info(measure, conversion)
# Set the time frame to the past year if start/end not specified
if start_seconds == '0' and end_seconds == '0':
# Get how many points there are in the past year
query_str = query_string(unit,
device_id,
measure=measurement,
channel=channel,
value='COUNT')
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
count_points = raw_data['series'][0]['values'][0][1]
# Get the timestamp of the first point in the past year
query_str = query_string(unit,
device_id,
measure=measurement,
channel=channel,
limit=1)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
first_point = raw_data['series'][0]['values'][0][0]
end = datetime.datetime.utcnow()
end_str = end.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
# Set the time frame to the past start epoch to now
elif start_seconds != '0' and end_seconds == '0':
start = datetime.datetime.utcfromtimestamp(float(start_seconds))
start_str = start.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
end = datetime.datetime.utcnow()
end_str = end.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
query_str = query_string(unit,
device_id,
measure=measurement,
channel=channel,
value='COUNT',
start_str=start_str,
end_str=end_str)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
count_points = raw_data['series'][0]['values'][0][1]
# Get the timestamp of the first point in the past year
query_str = query_string(unit,
device_id,
measure=measurement,
channel=channel,
start_str=start_str,
end_str=end_str,
limit=1)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
first_point = raw_data['series'][0]['values'][0][0]
else:
start = datetime.datetime.utcfromtimestamp(float(start_seconds))
start_str = start.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
end = datetime.datetime.utcfromtimestamp(float(end_seconds))
end_str = end.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
query_str = query_string(unit,
device_id,
measure=measurement,
channel=channel,
value='COUNT',
start_str=start_str,
end_str=end_str)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
count_points = raw_data['series'][0]['values'][0][1]
# Get the timestamp of the first point in the past year
query_str = query_string(unit,
device_id,
measure=measurement,
channel=channel,
start_str=start_str,
end_str=end_str,
limit=1)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
first_point = raw_data['series'][0]['values'][0][0]
start = datetime.datetime.strptime(
influx_time_str_to_milliseconds(first_point), '%Y-%m-%dT%H:%M:%S.%f')
start_str = start.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
logger.debug('Count = {}'.format(count_points))
logger.debug('Start = {}'.format(start))
logger.debug('End = {}'.format(end))
# How many seconds between the start and end period
time_difference_seconds = (end - start).total_seconds()
logger.debug('Difference seconds = {}'.format(time_difference_seconds))
# If there are more than 700 points in the time frame, we need to group
# data points into 700 groups with points averaged in each group.
if count_points > 700:
# Average period between input reads
seconds_per_point = time_difference_seconds / count_points
logger.debug('Seconds per point = {}'.format(seconds_per_point))
# How many seconds to group data points in
group_seconds = int(time_difference_seconds / 700)
logger.debug('Group seconds = {}'.format(group_seconds))
try:
query_str = query_string(unit,
device_id,
measure=measurement,
channel=channel,
value='MEAN',
start_str=start_str,
end_str=end_str,
group_sec=group_seconds)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
return jsonify(raw_data['series'][0]['values'])
except Exception as e:
logger.error("URL for 'async_data' raised and error: "
"{err}".format(err=e))
return '', 204
else:
try:
query_str = query_string(unit,
device_id,
measure=measurement,
channel=channel,
start_str=start_str,
end_str=end_str)
if query_str == 1:
return '', 204
raw_data = dbcon.query(query_str).raw
return jsonify(raw_data['series'][0]['values'])
except Exception as e:
logger.error("URL for 'async_data' raised and error: "
"{err}".format(err=e))
return '', 204
