def get_steps_by_date(start_date, end_date, db: Session = Depends(get_db)):
local_start_datetime = utilities.localize_datetime_for_display(
utilities.localize_datetime_to_utc_for_storage(
utilities.get_datetime_obj_from_string(start_date)))
local_end_datetime = utilities.localize_datetime_for_display(
utilities.localize_datetime_to_utc_for_storage(
utilities.get_datetime_obj_from_string(end_date)))
return steps.format_steps_for_display(local_start_datetime,
local_end_datetime, db)
def parse_stress_data_from_monitor_file(fit_file):
records = []
for row in fit_file.get_messages('stress_level'):
record = {}
for field in row:
if field.name == 'stress_level_value':
record['stress_level'] = field.value
if field.name == 'stress_level_time':
record['timestamp_utc'] = localize_datetime_to_utc_for_storage(
field.value)
records.append(record)
return records
def parse_heart_metabolic_rate_from_monitor_file(fit_file):
records = []
for row in fit_file.get_messages('monitoring_info'):
record = {}
for field in row:
if field.name == 'resting_metabolic_rate':
record[field.name] = field.value
if field.name in TIME_FIELDS:
record[
f'{field.name}_utc'] = localize_datetime_to_utc_for_storage(
field.value)
records.append(record)
return records
def get_activity_record_data(fit_file):
records = []
for row in fit_file.get_messages('record'):
record = {}
for field in row:
if field.name in RECORD_FIELDS:
record[field.name] = field.value
if field.name in RECORD_FIELDS_TIME:
record[
f'{field.name}_utc'] = localize_datetime_to_utc_for_storage(
field.value)
if field.name in RECORD_FIELDS_GPS:
record[f'{field.name}_sem'] = field.value
record[f'{field.name}_deg'] = convert_semicircles_to_degrees(
field.value)
records.append(record)
return records
def _get_activity_session_data(fit_file):
session_data = [row for row in fit_file.get_messages('session')][0]
formatted_session_data = {
'start_time_utc':
localize_datetime_to_utc_for_storage(
session_data.get('start_time').value),
'total_elapsed_time':
session_data.get('total_elapsed_time').value,
'total_timer_time':
session_data.get('total_timer_time').value,
'total_distance':
session_data.get('total_distance').value,
'total_strides':
session_data.get('total_strides').value
if session_data.get('total_strides') else None,
'total_cycles':
session_data.get('total_cycles').value
if session_data.get('total_cycles') else None,
'total_calories':
session_data.get('total_calories').value,
'enhanced_avg_speed':
session_data.get('enhanced_avg_speed').value,
'avg_speed':
session_data.get('avg_speed').value,
'enhanced_max_speed':
session_data.get('enhanced_max_speed').value,
'max_speed':
session_data.get('max_speed').value,
'avg_power':
session_data.get('avg_power').value,
'max_power':
session_data.get('max_power').value,
'total_ascent':
session_data.get('total_ascent').value,
'total_descent':
session_data.get('total_descent').value,
}
# GPS data is only present when GPS is enabled and relevant to the activity
if session_data.get('start_position_lat').value and session_data.get(
'start_position_long').value:
formatted_session_data.update(
_get_activity_session_gps_data(session_data))
return formatted_session_data
def parse_heart_rate_data_from_monitor_file(fit_file):
most_recent_timestamp_ant_epoch = None
records = []
for row in fit_file.get_messages('monitoring'):
record = {}
for field in row:
if field.name == 'heart_rate':
record[field.name] = field.value
if field.name in TIME_FIELDS:
record[
f'{field.name}_utc'] = localize_datetime_to_utc_for_storage(
field.value)
most_recent_timestamp_ant_epoch = field.raw_value
if field.name in TIME_16_FIELDS:
timestamp = bitswap_ant_timestamp_to_unix_timestamp(
most_recent_timestamp_ant_epoch, field.raw_value)
record['timestamp_utc'] = timestamp
# throw out the rows without heart rate data
if record.get('heart_rate'):
records.append(record)
return records
def parse_step_data_from_monitor_file(fit_file):
"""
There is no consistency across ANT files about how many times the step data will be written per file or per day.
The value is not consistently located in a single column or associated with a single key.
If multiple ANT files are created in a single day (for example if activities are started and stopped), the step data
for the day will be spread across multiple monitor files.
Step data values are not cumulative; they state the number of steps taken until that point in time.
Example:
2020-01-01 00:00:00 1 step
2020-01-01 00:00:10 7 steps
2020-01-01 00:00:20 23 steps
2020-01-01 00:00:30 47 steps
The simplest way to get the accurate step count for the day is to grab every record until no more records are found,
and to keep only the largest one found. The last value found in a file is not guaranteed to be the largest.
If multiple files exist for a single day, comparison must be done across the files associated with that day to
ensure that the value taken is the largest.
"""
record = {}
timestamp_utc = None
for row in fit_file.get_messages('monitoring'):
for field in row:
if field.name in TIME_FIELDS:
timestamp_utc = localize_datetime_to_utc_for_storage(
field.value)
if not record.get('timestamp_utc'):
record['timestamp_utc'] = timestamp_utc
if field.name in ['steps']:
# step data is a mess to parse. the largest value is the correct value.
if field.value > record.get(field.name, 0):
record[field.name] = field.value
if timestamp_utc:
record['timestamp_utc'] = timestamp_utc
timestamp_utc = None
return record