def run(enrich_data_params, update_dataset_params):
enrich_out_dir = enrich_data_params["enrich_out_dir"]
enrich_out_archive_dir = enrich_data_params["enrich_out_archive_dir"]
update_in_dir = update_dataset_params["update_in_dir"]
update_in_archive_dir = update_dataset_params["update_in_archive_dir"]
dataset_file = update_dataset_params["dataset_file"]
# copy correlate data out to enrich in
# move correlate out to correlate out archive
FileUtil.copy_and_move_files(enrich_out_dir, update_in_dir,
enrich_out_archive_dir, "*.csv")
print("\nLoading Data to be added to Dataset from Filesystem...")
df_update = FileUtil.get_df_from_csv_dir(update_in_dir, "*.csv")
print("Complete. Count: " + str(df_update.shape[0]))
# get header
header = ','.join(df_update.columns) + '\n'
# print(header)
# add header if file does not exist
if not FileUtil.file_exists(dataset_file):
FileUtil.write_to_file(dataset_file, header)
# append to file
FileUtil.add_df_to_csv_file(df_update, dataset_file)
# move enrich in to enrich in archive
FileUtil.move_files(update_in_dir, update_in_archive_dir, "*.csv")
def run(debug, env, username, password, correlate_data_params,
enrich_data_params):
correlate_out_dir = correlate_data_params["correlate_out_dir"]
correlate_out_archive_dir = correlate_data_params[
"correlate_out_archive_dir"]
enrich_in_dir = enrich_data_params["enrich_in_dir"]
enrich_in_archive_dir = enrich_data_params["enrich_in_archive_dir"]
enrich_out_dir = enrich_data_params["enrich_out_dir"]
# copy correlate data out to enrich in
# move correlate out to correlate out archive
FileUtil.copy_and_move_files(correlate_out_dir, enrich_in_dir,
correlate_out_archive_dir, "*.csv")
wj_api = WorkjamAPI(debug, env, username, password)
# now in milliseconds
now_timestamp = TimeUtil.get_current_milli_time()
enrich_filename = 'Enrich_' + str(now_timestamp) + ".csv"
print("\nLoading Data to be enriched from Filesystem...")
df_enrich = FileUtil.get_df_from_csv_dir(enrich_in_dir, "*.csv")
print("Complete. Count: " + str(df_enrich.shape[0]))
# write header to the file
response_user_header = wj_api.get_user_details(True, '', '')
response_event_header = wj_api.get_event_details(True, '', '', '')
FileUtil.write_to_file(
enrich_out_dir + enrich_filename,
'loggedin_user,company_id,query_datetime,apply_datetime,number_of_open_shifts,location_id,event_id,'
+ response_user_header + ',' + response_event_header +
',applied\n')
print("\nEnriching User and Event info...")
num_records_written_to_file = 0
for index, row in df_enrich.iterrows():
loggedinuser = row['loggedinuser']
companyid = row['companyid']
query_datetime = row['query_datetime']
apply_datetime = row['apply_datetime']
numberofopenshifts = row['numberofopenshifts']
locationid = row['locationid']
eventid = row['eventid']
applied = row['applied']
try:
# Get Info for the Event in context
response_event_csv = wj_api.get_event_details(
False, companyid, locationid, eventid)
# Get Info for the User in context
response_user_csv = wj_api.get_user_details(
False, companyid, loggedinuser)
# # write enriche data to out dir with timestamp
FileUtil.append_to_file(
enrich_out_dir + enrich_filename,
str(loggedinuser) + ',' + str(companyid) + ',' +
str(query_datetime) + ',' + str(apply_datetime) + ',' +
str(numberofopenshifts) + ',' + str(locationid) + ',' +
str(eventid) + ',' + response_user_csv + ',' +
response_event_csv + ',' + str(applied) + '\n')
num_records_written_to_file += 1
except Exception as e:
print(e)
print("Complete. Found: {} Written: {}\n".format(
str(df_enrich.shape[0]), num_records_written_to_file))
# move enrich in to enrich in archive
FileUtil.move_files(enrich_in_dir, enrich_in_archive_dir, "*.csv")
def run(debug, get_data_params, correlate_data_params):
sumologic_out_dir = get_data_params["sumologic_out_dir"]
sumologic_out_archive_dir = get_data_params["sumologic_out_archive_dir"]
correlate_in_current_cycle_dir = correlate_data_params["correlate_in_current_cycle_dir"]
correlate_in_previous_cycle_dir = correlate_data_params["correlate_in_previous_cycle_dir"]
correlate_in_archive_dir = correlate_data_params["correlate_in_archive_dir"]
correlate_out_dir = correlate_data_params["correlate_out_dir"]
# copy sumologic out to correlate in current cycle
# move sumologic out to sumologic out archive
FileUtil.copy_and_move_files(sumologic_out_dir,
correlate_in_current_cycle_dir,
sumologic_out_archive_dir, "*.csv")
# now in milliseconds
now_timestamp = TimeUtil.get_current_milli_time()
correlate_filename = 'Correlate_'+str(now_timestamp)+".csv"
print("\nLoading Open Shift Requests from Filesystem...")
# correlate apply with requests in current and previoud cycle
df_requests = FileUtil.get_df_from_csv_dirs(correlate_in_current_cycle_dir,
correlate_in_previous_cycle_dir,
"Requests*")
print("Complete. Count: " + str(df_requests.shape[0]))
if(debug):
for index, row in df_requests.iterrows():
print(row)
print("\nLoading Apply to Open Shifts from Filesystem...")
df_apply = FileUtil.get_df_from_csv_dir(correlate_in_current_cycle_dir,
"Apply*")
print("Complete. Count: " + str(df_apply.shape[0]))
print("\nCorrelating Apply Open Shifts with Open Shifts Requests... ")
fields = ['loggedinuser', 'companyid',
'query_datetime', 'apply_datetime', 'numberofopenshifts',
'locationid', 'eventid', 'applied']
CorrelateData.add_header(correlate_out_dir+correlate_filename, fields)
for index, row in df_apply.iterrows():
apply_datetime = row['datetime']
loggedinuser = row['loggedinuser']
companyid = row['companyid']
locationid = row['locationid']
eventid = row['eventid']
df_filtered = df_requests.loc[
(df_requests['loggedinuser'] == loggedinuser) &
(df_requests['companyid'] == companyid) &
(df_requests['datetime'] < apply_datetime) &
(df_requests['eventandlocationids'].str.contains(str(eventid)+","+str(locationid)))
].drop_duplicates().sort_values(by=['datetime'], ascending=False).head(1)
if df_filtered.shape[0] > 0:
# lets first get rid of ', ' and replace it with '|' and then split
# Example text: (3714cb1e-4839-4d8c-818e-9d01c655cd86,328038), (d87a2bb7-05e0-465e-8b6c-aa18d89a9c9f,328038), (e7bee5c5-8f4e-457f-95e7-b1ec82e8ab21,328038), (f04d14c1-68c3-4dda-8698-3d95eb3a4b9d,328038)
events_and_locations = df_filtered.iloc[0]['eventandlocationids'].replace(', ','|').split('|')
for event_location in events_and_locations:
# lets get rid of paranthesis and split text by ','
# Example text: (3714cb1e-4839-4d8c-818e-9d01c655cd86,328038)
eventid_in_request, locationid_in_request = event_location.replace('(','').replace(')','').split(',')
applied = False
if str(eventid) == str(eventid_in_request) and str(locationid) == str(locationid_in_request):
applied = True
row = {'loggedinuser': loggedinuser,
'companyid': companyid,
'query_datetime': df_filtered.iloc[0]['datetime'],
'apply_datetime': apply_datetime,
'numberofopenshifts': df_filtered.iloc[0]['numberofopenshifts'],
'locationid': locationid_in_request,
'eventid': eventid_in_request,
'applied': applied}
CorrelateData.add_row(correlate_out_dir+correlate_filename, fields, row)
print("Complete. Results written to: {} \n".format(correlate_out_dir+correlate_filename))
# move correlate in previous cycle to correlate in archive
FileUtil.move_files(correlate_in_previous_cycle_dir,
correlate_in_archive_dir, "*.csv")
# move correlate in current cycle (Apply) to
# correlate in archive cycle
FileUtil.move_files(correlate_in_current_cycle_dir,
correlate_in_archive_dir, "Apply*")
# move correlate in current cycle (Requests) to
# correlate in previous cycle
FileUtil.move_files(correlate_in_current_cycle_dir,
correlate_in_previous_cycle_dir, "Requests*")
