def test_adding_data(self):
fb = FitbitCache('test_user')
date = datetime.date.today()
i = 0
for k, v in test_data[0].items():
fb.add_item(date, k, v)
i += 1
self.assertEqual(len(fb), 1)
self.assertTrue(date in fb)
self.assertEqual(len(fb[date]), i)
def test_adding_data(self):
fb = FitbitCache('test_user')
date = datetime.date.today()
i = 0
for k, v in test_data[0].items():
fb.add_item(date, k, v)
i += 1
self.assertEqual(len(fb), 1)
self.assertTrue(date in fb)
self.assertEqual(len(fb[date]), i)
def create_test_user():
""" write a few days to a test_user.json file """
fb = FitbitCache('test_user')
date = datetime.date(2017, 1, 1)
days_added = 0
items_added = 0
for td in test_data:
days_added += 1
for k, v in td.items():
fb.add_item(date, k, v)
items_added += 1
date += datetime.timedelta(days=1)
fb.write()
return 'test_user'
for key, row in df.iterrows():
date = row.start.date() # convert from pandas timestamp to date
if date in cache:
# round values to the precision we want
row.steps = int(round(row.steps, 0))
row.distance = round(row.distance, 2)
row.flights = int(round(row.flights, 0))
# do basic validation before adding values in
if row.steps > 1000:
if cache[date].get('steps_aw', 0) > row.steps:
print('warning:{}: steps_aw is {} but db has {}'.format(date, row.steps,
cache[date]['steps_aw']))
elif not cache[date].get('steps_aw'):
cache.add_item(date, 'steps_aw', row.steps, 0)
print('{}: steps_aw={}'.format(date, row.steps))
if row.steps > 1.0:
if cache[date].get('dist_aw', 0) > row.steps:
print('warning:{}: dist_aw is {} but db has {}'.format(date, row.distance,
cache[date]['dist_aw']))
elif not cache[date].get('dist_aw'):
cache.add_item(date, 'dist_aw', row.distance)
print('{}: dist_aw={}'.format(date, row.distance))
if row.flights > 1:
if cache[date].get('floors_aw', 0) > row.steps:
print('warning:{}: floors_aw is {} but db has {}'.format(date, row.flights,
cache[date]['floors_aw']))
elif not cache[date].get('floors_aw'):
cache.add_item(date, 'floors_aw', row.flights)
print('{}: floors_aw={}'.format(date, row.flights))
for key, row in df.iterrows():
date = row.start.date() # convert from pandas timestamp to date
if date in cache:
# round values to the precision we want
row.steps = int(round(row.steps, 0))
row.distance = round(row.distance, 2)
row.flights = int(round(row.flights, 0))
# do basic validation before adding values in
if row.steps > 1000:
if cache[date].get('steps_aw', 0) > row.steps:
print('warning:{}: steps_aw is {} but db has {}'.format(
date, row.steps, cache[date]['steps_aw']))
elif not cache[date].get('steps_aw'):
cache.add_item(date, 'steps_aw', row.steps, 0)
print('{}: steps_aw={}'.format(date, row.steps))
if row.steps > 1.0:
if cache[date].get('dist_aw', 0) > row.steps:
print('warning:{}: dist_aw is {} but db has {}'.format(
date, row.distance, cache[date]['dist_aw']))
elif not cache[date].get('dist_aw'):
cache.add_item(date, 'dist_aw', row.distance)
print('{}: dist_aw={}'.format(date, row.distance))
if row.flights > 1:
if cache[date].get('floors_aw', 0) > row.steps:
print('warning:{}: floors_aw is {} but db has {}'.format(
date, row.flights, cache[date]['floors_aw']))
elif not cache[date].get('floors_aw'):
cache.add_item(date, 'floors_aw', row.flights)
print('{}: floors_aw={}'.format(date, row.flights))