def create_dummy_subtheme(self) -> SubTheme:
"""
Create SubTheme
:return: SubTheme
"""
subtheme = SubTheme.get_by_name('_TEST_SUB_THEME_')
if not subtheme:
subtheme = SubTheme(self.theme.id, '_TEST_SUB_THEME_')
subtheme.save()
subtheme.commit()
subtheme = SubTheme.get_by_name('_TEST_SUB_THEME_')
return subtheme
def create_sub_theme(theme: Theme, name: str = 'Airquality') -> None:
"""
Create a SubTheme
:param theme: Parent Theme
:param name: SubThemes name
:raises ValueError: If the new SubTheme is not persisted to the dB
"""
sub_theme = SubTheme.get_by_name(name)
if not sub_theme:
sub_theme = SubTheme(theme.id, name)
sub_theme.save()
sub_theme.commit()
if not sub_theme:
logger.critical('ValueError raised while creating SubTheme')
raise ValueError
def post(self) -> (dict, HTTPStatus):
"""
Get dummy data from CSV. Store dummy data in database
:param file_name: File name to extract data from.
:return: A Status Report detailing the dB Entries created and an HTTP
Status code 200 on success otherwise, a JSON error message is returned
with the appropriate HTTPStatus code
"""
args = self.reqparser.parse_args()
# Get size of tables before import
self.loc_stats["before"] = db.session.query(func.count(
LocationData.id)).scalar()
self.tracker_stats["before"] = db.session.query(func.count(
Tracker.id)).scalar()
# Fetch Data from CSV
try:
df = pd.read_csv(args['file_name'])
except IOError as ioe:
logger.error("Unable to parse CSV data to dataframe",
ioe.with_traceback(ioe.__traceback__))
return dict(error="Unable to parse CSV data to dataframe",
trackback=ioe.with_traceback(
ioe.__traceback__)), HTTPStatus.BAD_REQUEST
moving_theme = Theme.get_by_name("Moving_Sensors")
if moving_theme:
moving_sensor_theme_id = moving_theme.id
else:
moving_sensor_theme = Theme("Moving_Sensors")
moving_sensor_theme.save()
moving_sensor_theme.commit()
moving_sensor_theme_id = moving_sensor_theme.id
moving_subtheme = SubTheme.get_by_name("Moving_Airquality")
if moving_subtheme:
moving_sensor_subtheme_id = moving_subtheme.id
else:
moving_sensor_subtheme = SubTheme(moving_sensor_theme_id,
"Moving_Airquality")
moving_sensor_subtheme.save()
moving_sensor_subtheme.commit()
moving_sensor_subtheme_id = moving_sensor_subtheme.id
# Trackers must be unique, Fetch trackers and make dB entries for
# each unique tracker
unique_tracker_ids = df["tracker"].unique()
for tracker_id in unique_tracker_ids:
self.t_ids[self.create_trackers(str(tracker_id),
moving_sensor_subtheme_id)] = 0
# Define Location data Pandas DataFrame Column names
loc_df = df[[
'tracker', 'datetime', 'latitude', 'longitude', 'speed', 'heading',
'elevation', 'charger', 'battery', 'signalquality', 'satcnt'
]]
# Drop all entries that are incomplete have NaN or None/ Null values
loc_df = loc_df.dropna()
# Store Location Data in the dB
for index, row in loc_df.iterrows():
self.add_location_data(row['tracker'], row['datetime'],
row['latitude'], row['longitude'],
row['speed'], row['heading'],
row['elevation'], row['charger'],
row['battery'], row['signalquality'],
row['satcnt'])
self.loc_stats["after"] = db.session.query(func.count(
LocationData.id)).scalar()
self.tracker_stats["after"] = db.session.query(func.count(
Tracker.id)).scalar()
return self.status_report(), 200
