def from_API(self, access_token, start_dt, end_dt):
available_datasources = query_data_sources(access_token)
datasets = defaultdict(lambda: {})
data_types_synced = set()
data_sources_synced = set()
for data_type_name, data_stream_id in available_datasources:
if data_type_name not in GOOGLEFIT_SYNCED_DATATYPES:
continue
monthly_dataset = {}
for i, dt in enumerate(rrule(DAILY, dtstart=start_dt,
until=end_dt)):
print("Getting {} for {}".format(data_stream_id,
start_of_day(dt)))
res = query_data_stream(access_token, data_stream_id,
start_of_day(dt), end_of_day(dt))
res = remove_empty_buckets(res)
monthly_dataset[dt.strftime("%Y-%m-%d")] = res
datasets[data_type_name][data_stream_id] = monthly_dataset
data_types_synced.add(data_type_name)
data_sources_synced.add((data_type_name, data_stream_id))
metadata = {
'month': start_dt.strftime("%Y-%m"),
'last_dt': end_dt.strftime("%Y-%m-%d %H:%M:%S"),
'data_source_pairs': list(data_sources_synced),
'data_types': list(data_types_synced)
}
return GoogleFitData(datasets, metadata)
def find_first_date_with_data(access_token, end_dt):
start_dt = find_first_month_with_data(access_token, end_dt)
for i, dt in enumerate(rrule(DAILY, dtstart=start_dt, until=end_dt)):
res = query_data_stream(access_token,
'com.google.active_minutes',
start_of_day(dt),
end_of_day(dt),
bucketing=12 * HOURLY,
aggregate_name="dataTypeName")
is_empty = is_empty_aggregate_result(res)
if is_empty:
print("No data for {}, will look at later dates".format(dt))
else:
return start_of_day(dt)
return None
def generate_monthly_ranges(first_date, last_date):
first_month_date = first_date
while (True):
last_month_date = end_of_month(first_month_date)
if last_month_date >= last_date:
yield first_month_date, last_date
return
yield first_month_date, last_month_date
# get the first date for the next month
first_month_date = start_of_day(last_month_date + timedelta(days=1))
def get_last_synced_data(oh_access_token, gf_access_token, current_date):
download_url = get_latest_googlefit_file_url(oh_access_token)
if download_url:
existing_data_json = download_to_json(download_url)
last_monthly_gf_data = GoogleFitData.from_json(existing_data_json)
start_date = start_of_day(
last_monthly_gf_data.last_dt
) # start of day to account for partial data in the last day
else:
last_monthly_gf_data = None
start_date = find_first_date_with_data(gf_access_token, current_date)
return last_monthly_gf_data, start_date
def find_first_month_with_data(access_token, end_dt):
start_dt = GOOGLEFIT_DEFAULT_START_DATE
for i, dt in enumerate(rrule(MONTHLY, dtstart=start_dt, until=end_dt)):
res = query_data_stream(access_token,
'com.google.active_minutes',
start_of_day(dt),
end_of_day(dt + timedelta(days=32)),
bucketing=12 * HOURLY,
aggregate_name="dataTypeName")
is_empty = is_empty_aggregate_result(res)
if is_empty:
print("No data for {}, will look at later dates".format(dt))
continue
else:
return start_of_month(dt)
return None