def init_state(terms=None, tilds=None, timestamp=None):
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
date = models.get_current_date(tilds)
return {
'terms' : terms or '',
'terms_v' : terms or '',
'tilds' : tilds or '',
'tilds_v' : tilds or '',
'timestamp' : tools.to_timestamp(date) or timestamp or '',
'timestamp_v' : tools.to_verbose(d=date) or tools.to_verbose(t=timestamp) or ''
}
def get_json(self, tilds):
context = { }
try:
date = models.get_current_date(tilds)
context = {
'tilds' : tilds,
'timestamp' : tools.to_timestamp(date) or '',
'timestamp_v' : tools.to_verbose(d=date) or ''
}
except Exception as e:
context['error'] = str(e)
finally:
tools.json_response(self, context)
def extract_app_usage_data(userId, filepath):
# Format : App name / Date / Time / Duration
data = tools.get_dataframe(filepath)
new_data = {'User_ID': [], 'Time': [], 'App Name': [], 'Duration': []}
# For each data line
for i in range(data.shape[0]):
# Create a dict with formatted values
doc = {
'User_ID': userId,
'Time': tools.to_timestamp(data['Date'][i], data['Time'][i]),
'App Name': tools.appname_process(data['App name'][i]),
'Duration': tools.time_in_seconds(data['Duration'][i])
}
# If the data needs to be stored, addition to the dict new_data
if doc['Duration'] != 0 and doc['App Name'] not in tools.app_to_remove():
for k in new_data:
new_data[k].append(doc[k])
# Create a df with new data and return it
return pd.DataFrame(new_data)
