savestate before github
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Rene Kaßeböhmer
1
prepared_steps/19_create_contractlineitems/command.txt
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prepared_steps/19_create_contractlineitems/command.txt
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sf sfdmu run --sourceusername csvfile --targetusername rene.kasseboehmer@vaillant.de.devrene
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prepared_steps/19_create_contractlineitems/export.json
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prepared_steps/19_create_contractlineitems/export.json
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{
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"allOrNone": true,
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"excludeIdsFromCSVFiles": true,
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"objects": [
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{
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"query": "SELECT Id, PKey__c FROM ServiceContract WHERE TemplateId__c != null AND Pricebook2.Country__c = 'NL'",
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"operation": "Readonly",
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"externalId": "PKey__c",
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"master": false
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},{
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"query": "SELECT Id, PKey__c FROM Asset WHERE Location.ParentLocation.VisitorAddress.CountryCode = 'NL'",
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"operation": "Readonly",
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"externalId": "PKey__c",
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"master": false
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},{
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"query": "SELECT Id, ServiceContractId, AssetId FROM ContractLineItem",
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"operation": "Insert",
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"externalId": "Id",
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"master": true,
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"useSourceCSVFile": true
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}
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]
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}
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import pandas as pd
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import argparse
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from sys import path
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path.append('../..')
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from utils import bulk_insert_records
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from datetime import datetime, timedelta
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# Find last maintenance/order date for each ServiceContractId
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def get_last_maintenance_date(service_contract_id):
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# Try to find in LastMaintenanceInformation
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lm_rows = df_lm[df_lm['Order__r.Contract__c'] == service_contract_id]
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if not lm_rows.empty:
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# Use the most recent Order__r.Closed__c
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return lm_rows['Order__r.Closed__c'].max()
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# If not found, try LastOrderInformation
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lo_rows = df_lo[df_lo['Contract__c'] == service_contract_id]
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if not lo_rows.empty:
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return lo_rows['Closed__c'].max()
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return None
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='Insert MaintenancePlan records via Bulk API')
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parser.add_argument('--context', type=str, required=True,
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help='Salesforce org context (e.g., "qa2", "prod")')
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parser.add_argument('--csv', type=str, default='MaintenancePlan.csv',
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help='CSV file to process (default: MaintenancePlan.csv)')
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args = parser.parse_args()
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#read_df_sc = pd.read_csv('../16_insert_servicecontract/successful_records.csv', header=0, keep_default_na=False, dtype=str)
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read_df_mp = pd.read_csv('./MaintenancePlan_beforetransform.csv', header=0, keep_default_na=False, dtype=str)
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#"sf__Id","sf__Created",PKey__c,BillingCountryCode,Term,EndDate,StartDate,AccountId,Service_Recipient__c,IoT_Registration_Status__c,Name,Pricebook2Id,TemplateId__c
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#reindex_columns_sc = ['sf__Id','sf__Created','PKey__c', 'BillingCountryCode', 'Term', 'EndDate', 'StartDate', 'AccountId', 'Service_Recipient__c', 'IoT_Registration_Status__c', 'Name', 'Pricebook2Id', 'TemplateId__c']
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#ServiceContract.PKey__c,StartDate,EndDate,AccountId,MaintenanceWindowEndDays,MaintenanceWindowStartDays,GenerationTimeframe,Frequency,GenerationTimeframeType,WorkTypeId
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reindex_columns_mp = ['ServiceContract.PKey__c', 'StartDate', 'EndDate', 'AccountId', 'MaintenanceWindowEndDays', 'MaintenanceWindowStartDays', 'GenerationTimeframe', 'Frequency', 'GenerationTimeframeType', 'WorkTypeId']
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reindex_columns_lastmaintenance = []
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# Reindex the columns to match the desired format
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#df_sc = read_df_sc.reindex(reindex_columns_sc, axis=1)
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df_mp = read_df_mp.reindex(reindex_columns_mp, axis=1)
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# Only load 'sf__Id' and 'PKey__c' from the ServiceContract CSV
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df_sc = pd.read_csv('../16_insert_servicecontract/successful_records.csv', usecols=['sf__Id', 'PKey__c'])
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# Load LastMaintenanceInformation and LastOrderInformation CSVs for NextSuggestedMaintenanceDate calculation
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df_lm = pd.read_csv('../1_extract_data/results/LastMaintenanceInformation.csv', usecols=['Id', 'Order__r.Closed__c', 'Order__r.Contract__c'])
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df_lo = pd.read_csv('../1_extract_data/results/LastOrderInformation.csv', usecols=['Id', 'Closed__c', 'Contract__c'])
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#
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# Merge df_mp with df_sc including Id based on PKey__c
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merged_df_mp = pd.merge(df_mp,
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df_sc[['sf__Id', 'PKey__c']],
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left_on='ServiceContract.PKey__c',
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right_on='PKey__c',
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how='left')
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# Rename only 'old_name' to 'new_name'
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merged_df_mp = merged_df_mp.rename(columns={'sf__Id': 'ServiceContractId'})
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merged_df_mp = merged_df_mp.drop('ServiceContract.PKey__c', axis=1)
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merged_df_mp = merged_df_mp.drop('PKey__c', axis=1)
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def get_next_suggested_maintenance_date(service_contract_id):
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# Try to find in LastMaintenanceInformation
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lm_rows = df_lm[df_lm['Order__r.Contract__c'] == service_contract_id]
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if not lm_rows.empty:
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last_date = lm_rows['Order__r.Closed__c'].max()
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else:
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# If not found, try LastOrderInformation
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lo_rows = df_lo[df_lo['Contract__c'] == service_contract_id]
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if not lo_rows.empty:
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last_date = lo_rows['Closed__c'].max()
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else:
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last_date = None
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if pd.notnull(last_date):
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try:
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dt = pd.to_datetime(last_date)
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next_date = dt + pd.DateOffset(years=1)
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return next_date.strftime('%Y-%m-%d')
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except Exception:
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pass
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# If no date found or parsing fails, use today
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next_date = datetime.today()
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return next_date.strftime('%Y-%m-%d')
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merged_df_mp['NextSuggestedMaintenanceDate'] = merged_df_mp['ServiceContractId'].apply(get_next_suggested_maintenance_date)
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# Set DoesAutoGenerateWorkOrders to True only if a date was found (not defaulted to today)
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def does_auto_generate_work_orders(service_contract_id):
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# Try to find in LastMaintenanceInformation
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lm_rows = df_lm[df_lm['Order__r.Contract__c'] == service_contract_id]
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if not lm_rows.empty:
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last_date = lm_rows['Order__r.Closed__c'].max()
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else:
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# If not found, try LastOrderInformation
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lo_rows = df_lo[df_lo['Contract__c'] == service_contract_id]
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if not lo_rows.empty:
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last_date = lo_rows['Closed__c'].max()
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else:
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last_date = None
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return pd.notnull(last_date)
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merged_df_mp['DoesAutoGenerateWorkOrders'] = merged_df_mp['ServiceContractId'].apply(does_auto_generate_work_orders)
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#transform values into int
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merged_df_mp['MaintenanceWindowEndDays'] = pd.to_numeric(merged_df_mp['MaintenanceWindowEndDays'], errors='coerce').fillna(0).astype(int)
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merged_df_mp['MaintenanceWindowStartDays'] = pd.to_numeric(merged_df_mp['MaintenanceWindowStartDays'], errors='coerce').fillna(0).astype(int)
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merged_df_mp['GenerationTimeframe'] = pd.to_numeric(merged_df_mp['GenerationTimeframe'], errors='coerce').fillna(0).astype(int)
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merged_df_mp['Frequency'] = pd.to_numeric(merged_df_mp['Frequency'], errors='coerce').fillna(0).astype(int)
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#safe csv
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merged_df_mp.to_csv('./MaintenancePlan.csv', index=False)
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bulk_insert_records(args.context, 'MaintenancePlan', args.csv)
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