def run(batch_id, source_file_name, output_file_name, source_service_resources, delta=timedelta(days=14)): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) data_gen.add_formula_column('Start', lambda cv: "" if cv['Start'] == "" else (dateutil.parser.parse(cv['Start']) + timedelta(days=delta.days - 1)).replace(tzinfo=None)) data_gen.add_formula_column('End', lambda cv: "" if cv['End'] == "" else (dateutil.parser.parse(cv['End']) + timedelta(days=delta.days - 1)).replace(tzinfo=None)) service_resources = data_gen.load_dataset("ServiceResources", source_service_resources, ['Id', 'External_ID__c']).dict('Id', 'External_ID__c') data_gen.add_map_column('Resource.External_Id__c', 'ResourceId', service_resources) data_gen.apply_transformations() data_gen.add_copy_column('CreatedDate__c', 'Start') data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'Resource.External_Id__c', 'CreatedDate__c', 'Start', 'End', 'Type', #'State', #'Country', #'City' ])
def run(batch_id, source_file_name, output_file_name, source_service_resources, source_service_appointments): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) service_resources = data_gen.load_dataset("ServiceResources", source_service_resources, ['Id', 'External_ID__c']).dict( 'Id', 'External_ID__c') data_gen.add_map_column('ServiceResource.External_Id__c', 'ServiceResourceId', service_resources) service_appointments = data_gen.load_dataset( "ServiceAppointments", source_service_appointments, ['Id', 'External_ID__c']).dict('Id', 'External_ID__c') data_gen.add_map_column('ServiceAppointment.External_Id__c', 'ServiceAppointmentId', service_appointments) data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'ServiceResource.External_Id__c', 'ServiceAppointment.External_Id__c', 'ActualTravelTime', 'EstimatedTravelTime' ])
def run(batch_id, source_file_name, output_file_name, source_operating_hours, reference_datetime=today_datetime): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) data_gen.add_constant_column('CreatedDate__c', reference_datetime.isoformat(sep=' ')) operating_hours = data_gen.load_dataset("OperatingHours", source_operating_hours, ['Id', 'External_ID__c']).dict( 'Id', 'External_ID__c') data_gen.add_map_column('OperatingHours.External_Id__c', 'OperatingHoursId', operating_hours) data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'OperatingHours.External_Id__c', 'StartTime', 'EndTime' ])
def run(batch_id, source_file_name, output_file_name, source_accounts): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) accounts = data_gen.load_dataset("Accounts", source_accounts, ['Id', 'External_ID__c']).dict('Id', 'External_ID__c') data_gen.add_map_column('Account.External_Id__c', 'AccountId', accounts) data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'Account.External_Id__c', 'Subject' ])
def updateCreatedDate(source_file_name, output_file_name, source_service_appointments, reference_datetime=today_datetime): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) service_appointments = data_gen.load_dataset( "ServiceAppointments", source_service_appointments, ['External_ID__c']).dict('External_ID__c', 'External_ID__c') service_appointments[None] = 'None' data_gen.add_map_column('ServiceAppointment.External_Id__c', 'ServiceAppointment.External_Id__c', service_appointments) data_gen.apply_transformations() data_gen.filter(lambda cv: cv['ServiceAppointment.External_Id__c']. startswith('ServiceAppointment')) data_gen.apply_transformations() service_appointment_dates = data_gen.load_dataset( "ServiceAppointmentDates", source_service_appointments, ['External_ID__c', 'CreatedDate__c']).dict('External_ID__c', 'CreatedDate__c') service_appointment_dates[None] = reference_datetime + timedelta(days=-1) data_gen.add_map_column('CreatedDate__c', 'ServiceAppointment.External_Id__c', service_appointment_dates) data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'ServiceResource.External_Id__c', 'ServiceAppointment.External_Id__c', 'CreatedDate__c', 'ActualTravelTime', 'EstimatedTravelTime' ])
def run(batch_id, source_file_name, output_file_name, source_products): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) products = data_gen.load_dataset("Products", source_products, ['Id', 'External_ID__c']).dict( 'Id', 'External_ID__c') data_gen.add_map_column('Product2.External_Id__c', 'Product2Id', products) data_gen.add_constant_column('Pricebook2.Name', 'Standard Price Book') data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_Id__c', 'Product2.External_Id__c', 'IsActive', 'Pricebook2.Name', 'UnitPrice' ])
def run(batch_id, source_file_name, output_file_name, source_pricebook, source_work_orders): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) pricebook = data_gen.load_dataset("Pricebook", source_pricebook, ['Id', 'External_Id__c']).dict('Id', 'External_Id__c') data_gen.add_map_column('PricebookEntry.External_Id__c', 'PricebookEntryId', pricebook) work_orders = data_gen.load_dataset("WorkOrders", source_work_orders, ['Id', 'External_ID__c']).dict('Id', 'External_ID__c') data_gen.add_map_column('WorkOrder.External_Id__c', 'WorkOrderId', work_orders) data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'PricebookEntry.External_Id__c', 'WorkOrder.External_Id__c', 'QuantityConsumed' ])
def run(batch_id, source_file_name, output_file_name, source_operating_hours): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) operating_hours = data_gen.load_dataset("OperatingHours", source_operating_hours, ['Id', 'External_ID__c']).dict('Id', 'External_ID__c') data_gen.add_map_column('OperatingHours.External_Id__c', 'OperatingHoursId', operating_hours) data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'Name', 'OperatingHours.External_Id__c', 'State', 'IsActive', 'Country', 'City' ])
def update(source_file_name, output_file_name, source_work_orders): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) service_appointments = data_gen.load_dataset("WorkOrders", source_work_orders, ['External_ID__c']).dict('External_ID__c', 'External_ID__c') service_appointments[None] = 'None' data_gen.add_map_column('WorkOrder.External_Id__c', 'WorkOrder.External_Id__c', service_appointments) data_gen.apply_transformations() data_gen.filter(lambda cv: cv['WorkOrder.External_Id__c'].startswith('WO.')) data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'PricebookEntry.External_Id__c', 'WorkOrder.External_Id__c', 'QuantityConsumed' ])
def run(batch_id, source_file_name, output_file_name, source_cases, source_accounts, source_work_types, source_service_appointments, reference_datetime=today_datetime): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) cases = data_gen.load_dataset("Cases", source_cases, ['Id', 'External_ID__c']).dict('Id', 'External_ID__c') data_gen.add_map_column('Case.External_Id__c', 'CaseId', cases) accounts = data_gen.load_dataset("Accounts", source_accounts, ['Id', 'External_ID__c']).dict('Id', 'External_ID__c') data_gen.add_map_column('Account.External_Id__c', 'AccountId', accounts) work_types = data_gen.load_dataset("WorkTypes", source_work_types, ['Id', 'External_ID__c']).dict('Id', 'External_ID__c') data_gen.add_map_column('WorkType.External_Id__c', 'WorkTypeId', work_types) data_gen.add_constant_column('Pricebook2.Name', 'Standard Price Book') service_appointment_dates = data_gen.load_dataset("ServiceAppointmentDates", source_service_appointments, ['WorkOrder.External_Id__c', 'CreatedDate__c']).dict('WorkOrder.External_Id__c', 'CreatedDate__c') service_appointment_dates[None] = reference_datetime + timedelta(days=-1) data_gen.add_map_column('CreatedDate__c', 'External_ID__c', service_appointment_dates) data_gen.apply_transformations() data_gen.filter(lambda cv: cv['WorkType.External_Id__c'].startswith('WT.')) data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'CreatedDate__c', 'Status', 'Pricebook2.Name', 'Priority', 'Case.External_Id__c', 'Account.External_Id__c', 'WorkType.External_Id__c' ])
def run(batch_id, source_file_name, output_file_name, accounts_file_name, contacts_file_name): data_gen = DataGenerator() # load source file source_columns = [ 'External_Id__c', 'AccountExternalId__c', 'Owner.External_Id__c', 'LeadSource', 'CloseDate', 'CreatedDate__c' ] data_gen.load_source_file(source_file_name, source_columns) # load accounts as dataset account_columns = [ 'External_Id__c', 'Name', 'BillingState', 'Industry' ] account_dataset = data_gen.load_dataset('accounts', accounts_file_name, account_columns) accounts_by_id = account_dataset.group_by('External_Id__c') # load contacts as dataset contact_columns = [ 'External_Id__c', 'FirstName', 'LastName' ] contact_dataset = data_gen.load_dataset('contacts', contacts_file_name, contact_columns) contacts_by_id = contact_dataset.group_by('External_Id__c') # helper method to get account data def get_account_data(column_values, account_column_name): return accounts_by_id.get(column_values['ConvertedAccount.External_Id__c'])[0].get(account_column_name) # helper method to get contact data def get_contact_data(column_values, contact_column_name): return contacts_by_id.get(column_values['ConvertedContact.External_Id__c'])[0].get(contact_column_name) # rename columns data_gen.rename_column('External_Id__c', 'ConvertedOpportunity.External_Id__c') data_gen.rename_column('AccountExternalId__c', 'ConvertedAccount.External_Id__c') data_gen.rename_column('CloseDate', 'ConvertedDate__c') # generate converted lead at a random ratio data_gen.duplicate_rows(duplication_factor=lambda: choice([0, 1], p=[.75, .25])) # generate id data_gen.add_formula_column('External_Id__c', formula=lambda: 'W_Lead.' + str(data_gen.current_row + 1)) # generate create date def create_date_formula(column_values): oppty_create_date = dateutil.parser.parse(column_values['CreatedDate__c']) return oppty_create_date - timedelta(days=randint(0, 45)) data_gen.add_formula_column('CreatedDate__c', create_date_formula) # generate status data_gen.add_formula_column('Status', formula=lead.lead_status) # generate status data_gen.add_map_column('IsConverted', 'Status', { 'Qualified - Convert': 'true', None: 'false' }) # generate opportunity data_gen.add_map_column('ConvertedOpportunity.External_Id__c', 'Status', { 'Qualified - Convert': lambda cv: cv['ConvertedOpportunity.External_Id__c'], None: '' }) # generate account data_gen.add_map_column('ConvertedAccount.External_Id__c', 'Status', { 'Qualified - Convert': lambda cv: cv['ConvertedAccount.External_Id__c'], None: '' }) # generate contact data_gen.add_map_column('ConvertedContact.External_Id__c', 'Status', { 'Qualified - Convert': lambda cv: cv['ConvertedAccount.External_Id__c'].replace('W_Account', 'W_Contact'), None: '' }) # generate converted date data_gen.add_map_column('ConvertedDate__c', 'Status', { 'Qualified - Convert': lambda cv: cv['ConvertedDate__c'], None: '' }) # generate name data_gen.add_map_column('FirstName', 'Status', { 'Qualified - Convert': lambda cv: get_contact_data(cv, 'FirstName'), None: lambda: fake.first_name() }) data_gen.add_map_column('LastName', 'Status', { 'Qualified - Convert': lambda cv: get_contact_data(cv, 'LastName'), None: lambda: fake.last_name() }) # generate company data_gen.add_map_column('Company', 'Status', { 'Qualified - Convert': lambda cv: get_account_data(cv, 'Name'), None: 'Not Applicable' }) # generate industry data_gen.add_map_column('Industry', 'Status', { 'Qualified - Convert': lambda cv: get_account_data(cv, 'Industry'), None: '' }) # generate state data_gen.add_map_column('State', 'Status', { 'Qualified - Convert': lambda cv: get_account_data(cv, 'BillingState'), None: '' }) # generate is unread by owner data_gen.add_map_column('IsUnreadByOwner', 'Status', { 'Qualified - Convert': 'false', None: lead.lead_is_unread_by_owner }) # generate rating data_gen.add_formula_column('Rating', formula=lead.lead_rating) # add a UUID for each row that is created in this batch data_gen.add_constant_column('analyticsdemo_batch_id__c', batch_id) # apply transformations and write file data_gen.apply_transformations() data_gen.write(output_file_name)
def run(batch_id, source_file_name, output_file_name, reference_datetime=today): data_gen = DataGenerator() # load source file source_columns = [ 'External_Id__c', 'Owner.External_Id__c', 'CreatedDate__c', 'ClosedDate__c', 'Origin' ] data_gen.load_source_file(source_file_name, source_columns) data_gen.rename_column('External_Id__c', 'Case.External_Id__c') data_gen.rename_column('ClosedDate__c', 'EndTime__c') data_gen.duplicate_rows(duplication_factor=lambda: choice( [1, 2, 3, 4, 5], p=[.65, .15, .10, .05, .05])) data_gen.add_formula_column( 'External_Id__c', lambda: 'W_LiveChatTranscript.' + str(data_gen.current_row + 1)) data_gen.add_formula_column('Abandoned__c', lambda: randint(1, 300)) data_gen.add_formula_column('AverageResponseTimeOperator__c', lambda: randint(1, 180)) data_gen.add_formula_column('AverageResponseTimeVisitor__c', lambda: randint(1, 180)) data_gen.add_formula_column('Body__c', formula=fake.body) data_gen.add_formula_column('Browser__c', formula=fake.browser) data_gen.add_constant_column('BrowserLanguage__c', 'en_US') data_gen.add_formula_column('ChatDuration__c', lambda: randint(1, 600)) data_gen.add_formula_column('ChatKey__c', formula=fake.md5) data_gen.add_formula_column('IpAddress__c', formula=fake.ipv4) data_gen.add_formula_column('LiveChatButton.DeveloperName', ['Public_Website_Chat_Button']) data_gen.add_formula_column('Location__c', formula=fake.city) data_gen.add_formula_column('MaxResponseTimeOperator__c', lambda: randint(1, 120)) data_gen.add_formula_column('MaxResponseTimeVisitor__c', lambda: randint(1, 240)) data_gen.add_formula_column('Name__c', lambda: str(data_gen.current_row + 1).zfill(8)) data_gen.add_formula_column('OperatorMessageCount__c', lambda: randint(1, 100)) data_gen.add_formula_column( 'Platform__c', ['MacOSX', 'iOS', 'Android', 'Windows', 'Unix']) referrer = [ "https://na17.salesforce.com/setup/forcecomHomepage.apexp?setupid=ForceCom&retURL=%2Fui%2Fsupport%2Fservicedesk%2FServiceDeskPage", "https://na13.salesforce.com/home/home.jsp", "https://sdodemo-main.force.com/partners/servlet/servlet.Integration?lid=01ra0000001VlbA&ic=1", "https://sitestudio.na17.force.com/?exitURL=%2F_ui%2Fnetworks%2Fsetup%2FSetupNetworksPage%2Fd", "https://mail.google.com/mail/u/0/", "https://sdodemo-main.force.com/customers/servlet/servlet.Integration?lid=01ra0000001VlbP&ic=1", "https://sdodemo-main.force.com/consumers/servlet/servlet.Integration?lid=01ro0000000EN78&ic=1", "https://na17.salesforce.com/servlet/servlet.su?oid=00D300000007EfQ&retURL=%2F0033000000PuxU2&sunetworkuserid=005a000000AuCha&sunetworkid=0DBo0000000Gn4h", "https://sdodemo-main.force.com/customers/servlet/servlet.Integration?ic=1&lid=01ra0000001VlbP" ] data_gen.add_formula_column('ReferrerUri__c', referrer) def create_date_formula(column_values): case_create_date = dateutil.parser.parse( column_values['CreatedDate__c']) case_close_date = dateutil.parser.parse(column_values['EndTime__c']) create_date = fake.date_time_between_dates(case_create_date, case_close_date) if create_date > reference_datetime: create_date = reference_datetime return create_date.isoformat(sep=' ') data_gen.add_formula_column('CreatedDate__c', create_date_formula) def start_time_formula(column_values): create_date = dateutil.parser.parse(column_values['CreatedDate__c']) start_time = create_date + timedelta(seconds=randint(1, 300)) return start_time.isoformat(sep=' ') data_gen.add_formula_column('StartTime__c', start_time_formula) def end_time_formula(column_values): create_date = dateutil.parser.parse(column_values['StartTime__c']) end_time = create_date + timedelta(seconds=randint(1, 600)) return end_time.isoformat(sep=' ') data_gen.add_formula_column('EndTime__c', end_time_formula) data_gen.add_copy_column('RequestTime__c', 'CreatedDate__c') data_gen.add_formula_column( 'Status__c', lambda: choice(['Missed', 'Completed'], p=[.20, .80])) data_gen.add_map_column('EndedBy__c', 'Status__c', { 'Completed': ['Visitor', 'Agent'], None: 'Visitor' }) data_gen.add_constant_column('SupervisorTranscriptBody__c', '') data_gen.add_constant_column('ScreenResolution__c', '') data_gen.add_formula_column('UserAgent__c', formula=fake.user_agent) data_gen.add_formula_column('VisitorMessageCount__c', lambda: randint(1, 50)) data_gen.add_formula_column('WaitTime__c', lambda: randint(1, 120)) def last_referenced_date_formula(column_values): create_date = dateutil.parser.parse(column_values['CreatedDate__c']) last_referenced_date = create_date + timedelta(seconds=randint(1, 300)) return last_referenced_date.isoformat(sep=' ') data_gen.add_formula_column('LastReferencedDate__c', last_referenced_date_formula) data_gen.add_copy_column('LastViewedDate__c', 'LastReferencedDate__c') # add a UUID for each row that is created in this batch data_gen.add_constant_column('analyticsdemo_batch_id__c', batch_id) def filter_func(column_values): return column_values['Origin'] == 'Chat' data_gen.filter(filter_function=filter_func) # apply transformations and write file data_gen.apply_transformations() data_gen.sort_by('StartTime__c') output_columns = [ 'External_Id__c', 'Abandoned__c', 'AverageResponseTimeOperator__c', 'MaxResponseTimeOperator__c', 'OperatorMessageCount__c', 'Body__c', 'Browser__c', 'BrowserLanguage__c', 'Case.External_Id__c', 'ChatDuration__c', 'ChatKey__c', 'CreatedDate__c', 'StartTime__c', 'EndTime__c', 'EndedBy__c', 'LastReferencedDate__c', 'LastViewedDate__c', 'LiveChatButton.DeveloperName', 'Location__c', 'Owner.External_Id__c', 'Platform__c', 'ReferrerUri__c', 'ScreenResolution__c', 'RequestTime__c', 'Status__c', 'SupervisorTranscriptBody__c', 'UserAgent__c', 'AverageResponseTimeVisitor__c', 'IpAddress__c', 'MaxResponseTimeVisitor__c', 'VisitorMessageCount__c', 'WaitTime__c', 'analyticsdemo_batch_id__c' ] data_gen.write(output_file_name, output_columns)
def run(source_file_name, output_file_name): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) # find mean and std of profit profits = [] for row in data_gen.rows: column_values = data_gen.row_to_column_values(row) profits.append(float(column_values['Profit'])) profit_mean = mean(profits) profit_std = std(profits) # filter out profits more than 2 std out. def filter_func(column_values): profit = float(column_values['Profit']) z_score = abs((profit - profit_mean) / profit_std) return z_score <= 2 data_gen.filter(filter_function=filter_func) store_tier_map = { 'New York 4': "Tier 1", 'New York 3': "Tier 1", 'New York 2': "Tier 1", 'New York 1': "Tier 1", 'Chicago 3': "Tier 1", 'Chicago 2': "Tier 2", 'Chicago 1': "Tier 2", 'Boston 2': "Tier 2", 'Boston 1': "Tier 3" } data_gen.add_map_column('Tier', 'Store', store_tier_map) month_channel_map = { 'January': 'Chat', 'February': 'Chat', 'March': 'Chat', 'April': 'Chat', 'May': 'Chat', 'June': 'Email', 'July': 'Email', 'August': 'Facebook', 'September': 'Phone', 'October': 'Phone', 'November': 'Website', 'December': 'Website' } data_gen.add_map_column('Origin', 'Month', month_channel_map) discount_support_map = { '0': 'Free', '0.05': 'Free', '0.15': 'Basic', '0.1': 'Silver', '0.2': 'Platinum' } data_gen.add_map_column('Type_of_Support__c', 'Discount', discount_support_map) camp_reason_map = { "Bundled": "Documentation", "Buy More & Save": "Unknown Failure", "Competitor Focus": "Feature Question", "Door Buster": "Hardware Question", "Friends & Family": "Late Delivery", "Local": "Software Question", "Paper Circular": "General Question", "Regional": "Item Damaged", "Social": "Item Damaged" } data_gen.add_map_column('Reason', 'Marketing Campaign', camp_reason_map) city_priority_map = { "Boston": "Low", "Chicago": "Medium", "New York": "High" } data_gen.add_map_column('Priority', 'City', city_priority_map) comp_sla_map = { "High": "Violation", "Normal": "Compliant", "Low": "Compliant" } data_gen.add_map_column('SLA', 'Competition', comp_sla_map) data_gen.add_constant_column('Status', 'Closed') sla_first_contact_close_map = { 'Compliant': lambda: choice(['true', 'false'], p=[.9, .1]), 'Violation': lambda: choice(['true', 'false'], p=[.7, .3]) } data_gen.add_map_column('First_Contact_Close__c', 'SLA', sla_first_contact_close_map) sla_time_open_map = { 'Compliant': lambda: choice([12, 24, 36, 48], p=[.50, .20, .20, .10]), 'Violation': lambda: choice([60, 72, 84, 96, 108, 120], p=[.60, .20, .10, .05, .03, .02]) } data_gen.add_map_column('Time_Open__c', 'SLA', sla_time_open_map) def region_formula(column_values): average_age = float(column_values['Average Age']) if average_age < 40: return 'West CSR' elif average_age >= 40.0 and average_age < 50: return 'Central CSR' else: return 'East CSR' data_gen.add_formula_column('Team__c', region_formula) def user_formula(column_values): average_age = float(column_values['Average Age']) if average_age < 40: return 'W_Services_User.' + str(choice([1, 2, 3, 4, 5])) elif average_age >= 40.0 and average_age < 50: return 'W_Services_User.' + str(choice([6, 7, 8, 9, 10, 11])) else: return 'W_Services_User.' + str(choice([12, 13, 14, 15, 16, 17])) data_gen.add_formula_column('Owner.External_Id__c', user_formula) # generate offer voucher - give vouchers to customers that were unhappy with Video Games or Cables to boost CSAT def offer_voucher_formula(column_values): csat = float(column_values['Profit Linear']) item = column_values['Item'] if item in ['Video Games', 'Cables']: return choice(['true', 'false'], p=[csat/100, (100 - csat) / 100]) else: return 'false' data_gen.add_formula_column('Offer_Voucher__c', offer_voucher_formula) def send_field_service_formula(column_values): csat = float(column_values['Profit Linear']) item = column_values['Item'] if csat >= 80.0 and item == 'Tablet': return 'true' else: return choice(['true', 'false'], p=[.25, .75]) data_gen.add_formula_column('Send_FieldService__c', send_field_service_formula) data_gen.add_map_column('IsEscalated', 'Tier', {'Tier 1': 'true', None: 'false'}) # generate close date offset # random offset covering the last 14 months data_gen.add_formula_column('close_date_offset', lambda: randint(1, 30 * 14)) # generate account id - generate a long tail distribution - cubic function +- randint # helper dataset used for account selection data_gen.add_dataset('current_account', {'account_id': 0, 'account_count': 0}) # generate a distribution of account ids def account_id_formula(column_values): current_account = data_gen.datasets['current_account'] account_id = current_account['account_id'] account_count = current_account['account_count'] if account_count > 0: # continue with the current account_id if there are still any to take # but first decrement account count account_count += -1 current_account['account_count'] = account_count else: # use new account id account_id += 1 account_count = int(round(lognormal(1))) + randint(1, 7) # update account dataset for next iteration account_count += -1 current_account['account_count'] = account_count current_account['account_id'] = account_id return 'W_Services_Account.' + str(account_id) data_gen.add_formula_column('Account.External_Id__c', account_id_formula) def csat_formula(column_values): # first normalize csat between 30-90 csat = float(column_values['Profit Linear']) new_delta = 70 csat = (new_delta * csat / 100) + 30 channel = column_values['Origin'] is_escalated = column_values['IsEscalated'] send_field_service = column_values['Send_FieldService__c'] offer_voucher = column_values['Offer_Voucher__c'] if is_escalated == 'true': if channel == 'Phone': csat = csat - 2 else: csat = csat + 2 if send_field_service == 'true': if channel == 'Phone': csat = csat - 2 else: csat = csat + 4 if offer_voucher == 'true': if channel == 'Phone': csat = csat - 2 else: csat = csat + 4 return csat data_gen.add_formula_column('CSAT__c', formula=csat_formula) data_gen.add_map_column('Outlier', 'Outlier', value_map={ 'TRUE': 'true', None: 'false' }) data_gen.apply_transformations() data_gen.add_map_column('Time_Open__c', 'First_Contact_Close__c', value_map={ 'true': 0, None: lambda cv: cv['Time_Open__c'] }) data_gen.apply_transformations() rename_map = { 'Item': 'Product_Family_KB__c' } data_gen.rename_columns(rename_map) output_columns = [ 'Origin', 'Store', 'Tier', 'Product_Family_KB__c', 'Priority', 'Average Age', 'Percent Male', 'SLA', 'Daily Revenue', 'Reason', 'Reg Price', 'Type_of_Support__c', 'Price', 'Quantity', 'Cost', 'Profit', 'CSAT__c', 'Profit Log', 'Outlier', 'Status', 'First_Contact_Close__c', 'Time_Open__c', 'Team__c', 'Owner.External_Id__c', 'close_date_offset', 'Account.External_Id__c', 'Offer_Voucher__c', 'Send_FieldService__c', 'IsEscalated' ] data_gen.write(output_file_name, output_columns)
def run(batch_id, source_file_name, output_file_name, source_accounts, source_service_resources, source_service_territories, source_work_orders, reference_datetime=today): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) data_gen.add_formula_column( 'EarliestStartTime', lambda cv: dateutil.parser.parse(cv['EarliestStartTime'])) data_gen.apply_transformations() data_gen.sort_by('EarliestStartTime', reverse=True) # shift dates to be 2 weeks prior to the reference date delta = reference_datetime.date() - data_gen.row_to_column_values( data_gen.rows[0])['EarliestStartTime'].date() data_gen.add_formula_column( 'EarliestStartTime', lambda cv: (cv['EarliestStartTime'] + timedelta( days=delta.days - 1)).replace(tzinfo=None)) data_gen.add_formula_column( 'ActualStartTime', lambda cv: "" if cv['ActualStartTime'] == "" else (dateutil.parser.parse(cv['ActualStartTime']) + timedelta( days=delta.days - 1)).replace(tzinfo=None)) data_gen.add_formula_column( 'ActualEndTime', lambda cv: "" if cv['ActualEndTime'] == "" else (dateutil.parser.parse(cv['ActualEndTime']) + timedelta( days=delta.days - 1)).replace(tzinfo=None)) data_gen.add_formula_column( 'ArrivalWindowStartTime', lambda cv: "" if cv['ArrivalWindowStartTime'] == "" else (dateutil.parser.parse(cv['ArrivalWindowStartTime']) + timedelta( days=delta.days - 1)).replace(tzinfo=None)) data_gen.add_formula_column( 'ArrivalWindowEndTime', lambda cv: "" if cv['ArrivalWindowEndTime'] == "" else (dateutil.parser.parse(cv['ArrivalWindowEndTime']) + timedelta( days=delta.days - 1)).replace(tzinfo=None)) data_gen.add_formula_column( 'DueDate', lambda cv: "" if cv['DueDate'] == "" else (dateutil.parser.parse(cv[ 'DueDate']) + timedelta(days=delta.days - 1)).replace(tzinfo=None)) data_gen.apply_transformations() data_gen.add_copy_column('CreatedDate__c', 'EarliestStartTime') accounts = data_gen.load_dataset("Accounts", source_accounts, ['Id', 'External_ID__c']).dict( 'Id', 'External_ID__c') data_gen.add_map_column('Account.External_Id__c', 'AccountId', accounts) service_resources = data_gen.load_dataset("ServiceResources", source_service_resources, ['Id', 'External_ID__c']).dict( 'Id', 'External_ID__c') data_gen.add_map_column('ServiceResource.External_Id__c', 'FSLDemoTools_Service_Resource__c', service_resources) service_territories = data_gen.load_dataset("ServiceTerritories", source_service_territories, ['Id', 'External_ID__c']).dict( 'Id', 'External_ID__c') data_gen.add_map_column('ServiceTerritory.External_Id__c', 'ServiceTerritoryId', service_territories) work_orders = data_gen.load_dataset("WorkOrders", source_work_orders, ['Id', 'External_ID__c']).dict( 'Id', 'External_ID__c') data_gen.add_map_column('WorkOrder.External_Id__c', 'ParentRecordId', work_orders) data_gen.apply_transformations() data_gen.filter( lambda cv: cv['WorkOrder.External_Id__c'].startswith('WO.')) data_gen.apply_transformations() data_gen.write( output_file_name, columns=[ 'External_ID__c', 'CreatedDate__c', 'ServiceResource.External_Id__c', 'ServiceTerritory.External_Id__c', 'WorkOrder.External_Id__c', 'ActualStartTime', 'ArrivalWindowStartTime', 'ActualDuration', 'EarliestStartTime', 'Duration', 'DurationType', 'Status', 'DueDate', 'ActualEndTime', 'ArrivalWindowEndTime' ]) return delta
def run(batch_id, source_file_name, output_file_name, reference_datetime=today): data_gen = DataGenerator() # load source file source_columns = [ 'External_Id__c', 'Owner.External_Id__c', 'CreatedDate__c', 'LastActivityDate__c', 'Team__c' ] data_gen.load_source_file(source_file_name, source_columns) data_gen.rename_column('External_Id__c', 'Case.External_Id__c') data_gen.rename_column('LastActivityDate__c', 'ActivityDate') data_gen.rename_column('Team__c', 'CallObject') # generate a random number of tasks per case data_gen.duplicate_rows(duplication_factor=lambda: randint(0, 3)) data_gen.add_formula_column('External_Id__c', formula=lambda: 'W_Services_Task.' + str(data_gen.current_row + 1)) data_gen.add_formula_column('TaskSubtype', formula=task.task_subtype) data_gen.add_formula_column('CallDurationInSeconds', formula=task.task_call_duration) data_gen.add_formula_column('CallDisposition', formula=task.task_call_disposition) data_gen.add_formula_column('CallType', formula=task.task_call_type) data_gen.add_formula_column('Status', formula=task.task_status) data_gen.add_formula_column('Priority', formula=task.task_priority) def create_date_formula(column_values): case_create_date = dateutil.parser.parse(column_values['CreatedDate__c']) case_close_date = datetime.combine(dateutil.parser.parse(column_values['ActivityDate']), case_create_date.time()) create_date = fake.date_time_between_dates(case_create_date, case_close_date) if create_date > reference_datetime: create_date = reference_datetime return create_date.isoformat(sep=' ') data_gen.add_formula_column('CreatedDate__c', create_date_formula) data_gen.add_copy_column('LastModifiedDate__c', 'CreatedDate__c') def activity_date_formula(column_values): create_date = dateutil.parser.parse(column_values['CreatedDate__c']).date() return (create_date + timedelta(days=randint(0, 14))).isoformat() data_gen.add_formula_column('ActivityDate', activity_date_formula) data_gen.add_formula_column('Subject', formula=task.task_subject_simple) data_gen.add_map_column('Type', 'Subject', value_map={ 'Call': lambda: choice(['Call', 'Meeting'], p=[.70, .30]), 'Send Letter': 'Email', 'Send Quote': 'Email', None: lambda: choice(['Meeting', 'Prep', 'Other'], p=[.50, .25, .25]) }) # add a UUID for each row that is created in this batch data_gen.add_constant_column('analyticsdemo_batch_id__c', batch_id) # apply transformations and write data_gen.apply_transformations() output_columns = [ 'External_Id__c', 'Owner.External_Id__c', 'Case.External_Id__c', 'CreatedDate__c', 'LastModifiedDate__c', 'ActivityDate', 'Subject', 'Type', 'TaskSubtype', 'CallDurationInSeconds', 'CallDisposition', 'CallType', 'CallObject', 'Status', 'Priority', 'analyticsdemo_batch_id__c' ] data_gen.write(output_file_name, output_columns)
def run(source_file_name, output_file_name): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) rename_map = { 'Supplies Group': 'Product2Family__c', 'Region': 'Region__c', 'Route To Market': 'LeadSource', 'Elapsed Days In Sales Stage': 'TimeToClose__c', 'Sales Stage Change Count': 'SalesStageCount__c', 'Opportunity Amount USD': 'Amount', 'Deal Size Category': 'DealSizeCategory__c' } data_gen.rename_columns(rename_map) # multiple time to close by 2 data_gen.add_formula_column('TimeToClose__c', lambda cv: int(cv['TimeToClose__c']) * 2) # map existing columns to new columns data_gen.add_map_column('Competitor__c', 'Competitor Type', definitions.competitor_type) data_gen.add_map_column('Product2Name__c', 'Supplies Subgroup', definitions.supplies_subgroup_map) data_gen.add_map_column('AccountAnnualRevenue__c', 'Client Size By Revenue', definitions.client_size_rev) data_gen.add_map_column('AccountNumberOfEmployees__c', 'Client Size By Employee Count', definitions.client_size_employees) data_gen.add_map_column('AccountBookings__c', 'Revenue From Client Past Two Years', definitions.client_past_revenue) data_gen.add_map_column('IsWon', 'Opportunity Result', definitions.isWon) # generate external id data_gen.add_formula_column( 'External_Id__c', formula=lambda: 'W_Opportunity.' + str(data_gen.current_row + 1)) data_gen.add_formula_column( 'Exec_Meeting__c', lambda: choice(['true', 'false'], p=[.35, .65])) data_gen.add_formula_column( 'Interactive_Demo__c', lambda: choice(['true', 'false'], p=[.30, .70])) def ttc_formula(column_values): ttc = int(column_values['TimeToClose__c']) exec_meeting = column_values['Exec_Meeting__c'] competitor_type = column_values['Competitor Type'] demo = column_values['Interactive_Demo__c'] rev = column_values['AccountAnnualRevenue__c'] if ttc == 0: return 0 if exec_meeting == 'true': if competitor_type == 'None': ttc = ttc + 4 else: ttc = ttc - 6 if demo == 'true': if rev == 'T100': ttc = ttc + 6 else: ttc = ttc - 5 if ttc < 0: return 0 return ttc data_gen.add_formula_column('TimeToClose__c', formula=ttc_formula) data_gen.add_constant_column('IsClosed', 'true') data_gen.add_formula_column( 'RecordType.DeveloperName', formula=lambda: choice(['SimpleOpportunity', 'ChannelPartner'], p=[.70, .30])) # generate opportunity type types = [ 'Add-On Business', 'Existing Business', 'New Business', 'New Business / Add-on' ] data_gen.add_formula_column( 'Type', formula=lambda: choice(types, p=[0.1, 0.3, 0.5, 0.1])) # generate a close date year and quarter data_gen.add_formula_column('close_date_year', formula=lambda: choice(list(range(0, 30)))) data_gen.add_formula_column( 'close_date_quarter', formula=lambda: choice([1, 2, 3, 4], p=[0.21, 0.24, 0.22, 0.33])) # generate a close date offset from the year and quarter def offset_formula(column_values): day = int(round(chisquare(9) * 5)) offset = 365 * (column_values['close_date_year']) + 91 * ( column_values['close_date_quarter'] - 1) + day return offset data_gen.add_formula_column('close_date_offset__c', offset_formula) # generate a close date def close_date_formula(column_values): last_day = date(date.today().year, 12, 31) offset = column_values['close_date_offset__c'] # last day of current year - offset close_date = last_day - timedelta(days=int(offset)) return str(close_date) data_gen.add_formula_column('CloseDate', close_date_formula) # generate a create date def create_date_formula(column_values): close_date = dateutil.parser.parse(column_values['CloseDate']) offset = column_values['TimeToClose__c'] create_date = close_date - timedelta(days=int(offset)) return create_date.isoformat(sep=' ') data_gen.add_formula_column('CreatedDate__c', create_date_formula) # generate last activity date def last_activity_date_formula(column_values): create_date = dateutil.parser.parse(column_values['CreatedDate__c']) close_date = dateutil.parser.parse(column_values['CloseDate']) if close_date > today_datetime: close_date = today_datetime if create_date > today_datetime: create_date = today_datetime return fake.date_time_between_dates(create_date, close_date).date() data_gen.add_formula_column('LastActivityDate__c', formula=last_activity_date_formula) # generate StageName, ForecastCategory, and Probability data_gen.add_map_column('StageName', 'Opportunity Result', value_map={ 'Won': 'Closed Won', None: 'Closed Lost' }) data_gen.add_map_column('ForecastCategory', 'Opportunity Result', value_map={ 'Won': 'Closed', None: 'Omitted' }) data_gen.add_map_column('ForecastCategoryName', 'Opportunity Result', value_map={ 'Won': 'Closed', None: 'Omitted' }) data_gen.add_map_column('Probability', 'Opportunity Result', value_map={ 'Won': '100', None: '0' }) # randomly pick an owner from the same region region_territory_map = { 'Pacific': lambda: 'W_Sales_User.' + str(choice([1, 2, 3, 4, 5, 6])), "Northwest": lambda: 'W_Sales_User.' + str(choice([1, 2, 3, 4, 5, 6])), "Midwest": lambda: 'W_Sales_User.' + str(choice([7, 8, 9, 10, 11])), "Southwest": lambda: 'W_Sales_User.' + str(choice([7, 8, 9, 10, 11])), "Mid-Atlantic": lambda: 'W_Sales_User.' + str(choice([7, 8, 9, 10, 11])), "Northeast": lambda: 'W_Sales_User.' + str(choice([12, 13, 14, 15, 16, 17])), "Southeast": lambda: 'W_Sales_User.' + str(choice([12, 13, 14, 15, 16, 17])) } data_gen.add_map_column('Owner.External_Id__c', 'Region__c', region_territory_map) # build out helper column for account selection def account_cat_formula(column_values): x1 = column_values['Client Size By Revenue'] x2 = column_values['Client Size By Employee Count'] x3 = column_values['Revenue From Client Past Two Years'] return str(x1) + '.' + str(x2) + '.' + str(x3) data_gen.add_formula_column('account_cat', account_cat_formula) # apply pending transformations now so we can sort by account_cat data_gen.apply_transformations() data_gen.sort_by('account_cat') # helper dataset used for account selection data_gen.add_dataset('account_segment', { 'account_id': 0, 'account_count': 0, 'current_account_cat': None }) # generate a distribution of account ids def account_id_formula(column_values): account_segment = data_gen.datasets['account_segment'] account_id = account_segment['account_id'] account_count = account_segment['account_count'] current_account_cat = account_segment['current_account_cat'] if column_values[ 'account_cat'] == current_account_cat and account_count > 0: # continue with the current account_id if there are still any to take # but first decrement account count account_count += -1 account_segment['account_count'] = account_count return account_id else: # use new account id account_id += 1 # generate a random number of opportunties to associate to an account account_count = int(round(lognormal(1))) + randint(1, 7) current_account_cat = column_values['account_cat'] # update account segment dataset for next iteration account_count += -1 account_segment['account_id'] = account_id account_segment['account_count'] = account_count account_segment['current_account_cat'] = current_account_cat return account_id data_gen.add_formula_column('AccountId__c', account_id_formula) # generate account id string data_gen.add_formula_column( 'AccountExternalId__c', formula=lambda cv: 'W_Account.' + str(cv['AccountId__c'])) # generate account name string account_names = {} def account_name_formula(column_values): account_id = column_values['AccountId__c'] if account_id in account_names: return account_names[account_id] else: account_name = account.account_name() account_names[account_id] = account_name return account_name data_gen.add_formula_column('AccountName__c', formula=account_name_formula) # generate name def name_formula(column_values): account_name = column_values['AccountName__c'] amount = column_values['Amount'] product_2_name = column_values['Product2Name__c'] return account_name + ' ' + str(data_gen.current_row % 256) data_gen.add_formula_column('Name', name_formula) # apply remaining transformations data_gen.apply_transformations() # sort by account id data_gen.sort_by('AccountId__c') columns_to_write = [ 'External_Id__c', 'Product2Name__c', 'Product2Family__c', 'Region__c', 'LeadSource', 'TimeToClose__c', 'SalesStageCount__c', 'Amount', 'AccountAnnualRevenue__c', 'AccountNumberOfEmployees__c', 'AccountBookings__c', 'Competitor__c', 'DealSizeCategory__c', 'AccountExternalId__c', 'AccountName__c', 'close_date_year', 'close_date_quarter', 'close_date_offset__c', 'Exec_Meeting__c', 'Interactive_Demo__c', 'IsWon', 'IsClosed', 'Owner.External_Id__c', 'Name', 'Type', 'StageName', 'ForecastCategory', 'ForecastCategoryName', 'Probability', 'RecordType.DeveloperName' ] data_gen.write(output_file_name, columns_to_write)
def run(batch_id, source_file_name, output_file_name, manager_output_file_name): data_gen = DataGenerator() # load source file source_columns = ['Owner.External_Id__c', 'Team__c'] data_gen.load_source_file(source_file_name, source_columns) data_gen.unique() # rename columns data_gen.rename_column('Owner.External_Id__c', 'External_Id__c') data_gen.rename_column('Team__c', 'UserRole.Name') # add 3 manager users west_manager = ['W_User.M.' + str(len(data_gen.rows) + 1), 'West CSM'] east_manager = ['W_User.M.' + str(len(data_gen.rows) + 2), 'East CSM'] central_manager = ['W_User.M.' + str(len(data_gen.rows) + 3), 'Central CSM'] ## managers from Sales ## # west_manager = ['RVP West', 'W_Sales_User.M.' + str(len(data_gen.rows) + 1)] # east_manager = ['RVP East', 'W_Sales_User.M.' + str(len(data_gen.rows) + 2)] # central_manager = ['RVP Central', 'W_Sales_User.M.' + str(len(data_gen.rows) + 3)] ######################## data_gen.rows.append(west_manager) data_gen.rows.append(east_manager) data_gen.rows.append(central_manager) # generate company name data_gen.add_formula_column('CompanyName', formula=fake.company) # generate fake first and last name def first_name_formula(column_values): id = int(column_values['External_Id__c'].split('.')[-1]) return fake.first_name_female() if id < 13 else fake.first_name_male() data_gen.add_formula_column('FirstName', formula=first_name_formula) data_gen.add_formula_column('LastName', formula=fake.last_name) # generate data based on fake first and last name data_gen.add_formula_column('Name', lambda cv: cv['FirstName'] + ' ' + cv['LastName']) # generate data based on fake first and last name def alias_formula(column_values): alias = (column_values['FirstName'][0] + column_values['LastName']).lower() trimmed_alias = alias[:8] if len(alias) > 8 else alias return trimmed_alias data_gen.add_formula_column('Alias', formula=alias_formula) data_gen.add_formula_column('Username', lambda cv: cv['Alias'] + '@demo.user') data_gen.add_formula_column('CommunityNickname', lambda cv: cv['Alias'] + str(randint(100, 999))) data_gen.add_formula_column('Email', lambda cv: cv['Alias'] + '@webmail.com') data_gen.add_formula_column('Phone', formula=fake.phone_number) titles = ['Customer Service Representative', 'Senior Customer Service Representative'] data_gen.add_formula_column('Title', lambda: choice(titles, p=[.70, .30])) # generate constant values data_gen.add_constant_column('IsActive', 'false') data_gen.add_constant_column('TimeZoneSidKey', 'America/Los_Angeles') data_gen.add_constant_column('Profile.Name', 'Standard User') # from oppty> data_gen.add_constant_column('Profile.Name', 'Standard User') data_gen.add_constant_column('LocaleSidKey', 'en_US') data_gen.add_constant_column('LanguageLocaleKey', 'en_US') data_gen.add_constant_column('EmailEncodingKey', 'ISO-8859-1') data_gen.add_constant_column('ForecastEnabled', 'true') # this comes from Sales data_gen.add_constant_column('UserPermissionsAvantgoUser', 'false') data_gen.add_constant_column('UserPermissionsCallCenterAutoLogin', 'false') data_gen.add_constant_column('UserPermissionsChatterAnswersUser', 'false') data_gen.add_constant_column('UserPermissionsInteractionUser', 'false') data_gen.add_constant_column('UserPermissionsJigsawProspectingUser', 'false') data_gen.add_constant_column('UserPermissionsKnowledgeUser', 'false') data_gen.add_constant_column('UserPermissionsLiveAgentUser', 'false') data_gen.add_constant_column('UserPermissionsMarketingUser', 'false') data_gen.add_constant_column('UserPermissionsMobileUser', 'false') data_gen.add_constant_column('UserPermissionsOfflineUser', 'false') data_gen.add_constant_column('UserPermissionsSFContentUser', 'false') data_gen.add_constant_column('UserPermissionsSiteforceContributorUser', 'false') data_gen.add_constant_column('UserPermissionsSiteforcePublisherUser', 'false') data_gen.add_constant_column('UserPermissionsSupportUser', 'false') data_gen.add_constant_column('UserPermissionsWorkDotComUserFeature', 'false') data_gen.add_constant_column('UserPreferencesActivityRemindersPopup', 'false') data_gen.add_constant_column('UserPreferencesApexPagesDeveloperMode', 'false') data_gen.add_constant_column('UserPreferencesCacheDiagnostics', 'false') data_gen.add_constant_column('UserPreferencesContentEmailAsAndWhen', 'false') data_gen.add_constant_column('UserPreferencesContentNoEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableAllFeedsEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableBookmarkEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableChangeCommentEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableEndorsementEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableFeedbackEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableFileShareNotificationsForApi', 'false') data_gen.add_constant_column('UserPreferencesDisableFollowersEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableLaterCommentEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableLikeEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableMentionsPostEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableMessageEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableProfilePostEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableRewardEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableSharePostEmail', 'false') data_gen.add_constant_column('UserPreferencesDisableWorkEmail', 'false') data_gen.add_constant_column('UserPreferencesDisCommentAfterLikeEmail', 'false') data_gen.add_constant_column('UserPreferencesDisMentionsCommentEmail', 'false') data_gen.add_constant_column('UserPreferencesDisProfPostCommentEmail', 'false') data_gen.add_constant_column('UserPreferencesEnableAutoSubForFeeds', 'false') data_gen.add_constant_column('UserPreferencesEventRemindersCheckboxDefault', 'false') data_gen.add_constant_column('UserPreferencesHideBiggerPhotoCallout', 'false') data_gen.add_constant_column('UserPreferencesHideChatterOnboardingSplash', 'false') data_gen.add_constant_column('UserPreferencesHideCSNDesktopTask', 'false') data_gen.add_constant_column('UserPreferencesHideCSNGetChatterMobileTask', 'false') data_gen.add_constant_column('UserPreferencesHideEndUserOnboardingAssistantModal', 'false') data_gen.add_constant_column('UserPreferencesHideLightningMigrationModal', 'false') data_gen.add_constant_column('UserPreferencesHideS1BrowserUI', 'false') data_gen.add_constant_column('UserPreferencesHideSecondChatterOnboardingSplash', 'false') data_gen.add_constant_column('UserPreferencesHideSfxWelcomeMat', 'false') data_gen.add_constant_column('UserPreferencesJigsawListUser', 'false') data_gen.add_constant_column('UserPreferencesLightningExperiencePreferred', 'false') data_gen.add_constant_column('UserPreferencesPathAssistantCollapsed', 'false') data_gen.add_constant_column('UserPreferencesPreviewLightning', 'false') data_gen.add_constant_column('UserPreferencesReminderSoundOff', 'false') data_gen.add_constant_column('UserPreferencesShowCityToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowCityToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowCountryToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowCountryToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowEmailToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowEmailToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowFaxToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowFaxToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowManagerToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowManagerToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowMobilePhoneToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowMobilePhoneToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowPostalCodeToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowPostalCodeToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowProfilePicToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowStateToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowStateToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowStreetAddressToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowStreetAddressToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowTitleToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowTitleToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesShowWorkPhoneToExternalUsers', 'false') data_gen.add_constant_column('UserPreferencesShowWorkPhoneToGuestUsers', 'false') data_gen.add_constant_column('UserPreferencesSortFeedByComment', 'false') data_gen.add_constant_column('UserPreferencesTaskRemindersCheckboxDefault', 'false') data_gen.add_constant_column('EmailPreferencesAutoBcc', 'false') data_gen.add_constant_column('EmailPreferencesAutoBccStayInTouch', 'false') data_gen.add_constant_column('EmailPreferencesStayInTouchReminder', 'false') data_gen.add_constant_column('UserPreferencesGlobalNavBarWTShown', 'false') data_gen.add_constant_column('UserPreferencesGlobalNavGridMenuWTShown', 'false') data_gen.add_constant_column('UserPreferencesCreateLEXAppsWTShown', 'false') # add a UUID for each row that is created in this batch data_gen.add_constant_column('analyticsdemo_batch_id__c', batch_id) # apply transformations and write file data_gen.apply_transformations() data_gen.write(output_file_name) # create manager file data_gen.filter(lambda cv: 'CSM' not in cv['UserRole.Name']) manager_map = { 'West CSR': west_manager[0], 'East CSR': east_manager[0], 'Central CSR': central_manager[0] } ### this is the manager file section in Sales> ### # # create manager file # data_gen.filter(lambda cv: 'RVP' not in cv['UserRole.Name']) # manager_map = { # 'West Sales': west_manager[1], # 'East Sales': east_manager[1], # 'Central Sales': central_manager[1], # } ################################################## data_gen.add_map_column('Manager.External_Id__c', 'UserRole.Name', manager_map) data_gen.apply_transformations() data_gen.write(manager_output_file_name, ['External_Id__c', 'Manager.External_Id__c'])
def run(batch_id, source_file_name, output_file_name, source_profiles): data_gen = DataGenerator() # load source file data_gen.load_source_file(source_file_name) accounts = data_gen.load_dataset("Profiles", source_profiles, ['Id', 'Name']).dict('Id', 'Name') data_gen.add_map_column('Profile.Name', 'ProfileId', accounts) data_gen.apply_transformations() data_gen.write(output_file_name, columns=[ 'External_ID__c', 'FirstName', 'LastName', 'Alias', 'Email', 'TimeZoneSidKey', 'Profile.Name', 'LocaleSidKey', 'LanguageLocaleKey', 'EmailEncodingKey', 'UserPermissionsAvantgoUser', 'UserPermissionsCallCenterAutoLogin', #'UserPermissionsChatterAnswersUser', 'UserPermissionsInteractionUser', #'UserPermissionsJigsawProspectingUser', 'UserPermissionsKnowledgeUser', 'UserPermissionsLiveAgentUser', 'UserPermissionsMarketingUser', 'UserPermissionsMobileUser', 'UserPermissionsOfflineUser', 'UserPermissionsSFContentUser', 'UserPermissionsSiteforceContributorUser', 'UserPermissionsSiteforcePublisherUser', 'UserPermissionsSupportUser', 'UserPermissionsWorkDotComUserFeature', 'UserPreferencesActivityRemindersPopup', 'UserPreferencesApexPagesDeveloperMode', 'UserPreferencesCacheDiagnostics', 'UserPreferencesContentEmailAsAndWhen', 'UserPreferencesContentNoEmail', 'UserPreferencesDisableAllFeedsEmail', 'UserPreferencesDisableBookmarkEmail', 'UserPreferencesDisableChangeCommentEmail', 'UserPreferencesDisableEndorsementEmail', 'UserPreferencesDisableFeedbackEmail', 'UserPreferencesDisableFileShareNotificationsForApi', 'UserPreferencesDisableFollowersEmail', 'UserPreferencesDisableLaterCommentEmail', 'UserPreferencesDisableLikeEmail', 'UserPreferencesDisableMentionsPostEmail', 'UserPreferencesDisableMessageEmail', 'UserPreferencesDisableProfilePostEmail', 'UserPreferencesDisableRewardEmail', 'UserPreferencesDisableSharePostEmail', 'UserPreferencesDisableWorkEmail', 'UserPreferencesDisCommentAfterLikeEmail', 'UserPreferencesDisMentionsCommentEmail', 'UserPreferencesDisProfPostCommentEmail', 'UserPreferencesEnableAutoSubForFeeds', 'UserPreferencesEventRemindersCheckboxDefault', 'UserPreferencesHideBiggerPhotoCallout', 'UserPreferencesHideChatterOnboardingSplash', 'UserPreferencesHideCSNDesktopTask', 'UserPreferencesHideCSNGetChatterMobileTask', 'UserPreferencesHideEndUserOnboardingAssistantModal', 'UserPreferencesHideLightningMigrationModal', 'UserPreferencesHideS1BrowserUI', 'UserPreferencesHideSecondChatterOnboardingSplash', 'UserPreferencesHideSfxWelcomeMat', #'UserPreferencesJigsawListUser', 'UserPreferencesLightningExperiencePreferred', 'UserPreferencesPathAssistantCollapsed', 'UserPreferencesPreviewLightning', 'UserPreferencesReminderSoundOff', 'UserPreferencesShowCityToExternalUsers', 'UserPreferencesShowCityToGuestUsers', 'UserPreferencesShowCountryToExternalUsers', 'UserPreferencesShowCountryToGuestUsers', 'UserPreferencesShowEmailToExternalUsers', 'UserPreferencesShowEmailToGuestUsers', 'UserPreferencesShowFaxToExternalUsers', 'UserPreferencesShowFaxToGuestUsers', 'UserPreferencesShowManagerToExternalUsers', 'UserPreferencesShowManagerToGuestUsers', 'UserPreferencesShowMobilePhoneToExternalUsers', 'UserPreferencesShowMobilePhoneToGuestUsers', 'UserPreferencesShowPostalCodeToExternalUsers', 'UserPreferencesShowPostalCodeToGuestUsers', 'UserPreferencesShowProfilePicToGuestUsers', 'UserPreferencesShowStateToExternalUsers', 'UserPreferencesShowStateToGuestUsers', 'UserPreferencesShowStreetAddressToExternalUsers', 'UserPreferencesShowStreetAddressToGuestUsers', 'UserPreferencesShowTitleToExternalUsers', 'UserPreferencesShowTitleToGuestUsers', 'UserPreferencesShowWorkPhoneToExternalUsers', 'UserPreferencesShowWorkPhoneToGuestUsers', 'UserPreferencesSortFeedByComment', 'UserPreferencesTaskRemindersCheckboxDefault', 'EmailPreferencesAutoBcc', 'EmailPreferencesAutoBccStayInTouch', 'EmailPreferencesStayInTouchReminder', 'UserPreferencesGlobalNavBarWTShown', 'UserPreferencesGlobalNavGridMenuWTShown', 'UserPreferencesCreateLEXAppsWTShown' ])