asset warranty saves
This commit is contained in:
Rene Kaßeböhmer
@ -4,7 +4,7 @@ read_df_sc = pd.read_csv('../15_insert_servicecontract/ServiceCOntract_beforetra
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read_df_pb2 = pd.read_csv('../12_insert_pricebook2_and_pricebookentries/target/Pricebook2_insert_target.csv', header=0, keep_default_na=False, dtype=str)
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read_df_sct = pd.read_csv('../13_insert_servicecontracttemplates_dummies/target/ServiceContract_insert_target.csv', header=0, keep_default_na=False, dtype=str)
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reindex_columns_sc = ['PKey__c','TemplateId__r.PKey__c','Status','BillingCountryCode','Term','EndDate','StartDate','AccountId','Service_Recipient__c','IoT_Registration_Status__c','Pricebook2.Name','Name']
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reindex_columns_sc = ['PKey__c', 'Name', 'TemplateId__r.PKey__c','Status','BillingCountryCode','Term','EndDate','StartDate','AccountId','Service_Recipient__c','IoT_Registration_Status__c','Pricebook2.Name','Name']
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reindex_columns_pb2 = ['Brand__c','Business_Type__c','Country__c','Errors','Id','IsActive','Name']
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reindex_columns_sct = ['BillingCountryCode','Errors','Id','IsTemplate__c','Name','PKey__c','Pricebook2Id','Term']
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@ -26,43 +26,73 @@ def animate():
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time.sleep(0.1)
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sys.stdout.write('\rDone! ')
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# ...existing code for animate() function...
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def extract_data(object_id, query, output_path='output', context='qa2'):
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def extract_data(object_id, query, output_path='output', context='qa2', use_rest=False):
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"""
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Extract data using Bulk API and save as CSV
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Extract data using either REST or Bulk API and save as CSV
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Args:
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object_id (str): Salesforce object ID
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output_path (str): Path to save the output file (default 'output')
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context (str): Context name for credentials (e.g., 'qa2', 'prod')
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query (str): SOQL query
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output_path (str): Path to save the output file
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context (str): Context name for credentials
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use_rest (bool): Whether to use REST API instead of Bulk API
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"""
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global done
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done = False
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t = None
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try:
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global done
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done = False
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# Get Salesforce connection using the new module
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# Get Salesforce connection
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sf = get_sf_connection(context)
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# Start animation thread
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t = threading.Thread(target=animate)
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t.start()
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results = sf.bulk2.__getattr__(object_id).query_all(
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query
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)
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print(f'Extracting: {object_id}')
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for i, data in enumerate(results):
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with open(f"results/{object_id}.csv", "w", encoding="utf-8") as bos:
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bos.write(data)
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# Choose API method based on use_rest flag
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if use_rest:
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# Use REST API query
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results = sf.query(query)
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records = results['records']
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# Handle pagination if needed
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while not results['done']:
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results = sf.query_more(results['nextRecordsUrl'], identifier_is_url=True)
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records.extend(results['records'])
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# Convert records to CSV format
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if records:
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df = pd.DataFrame(records)
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df = df.drop('attributes', axis=1) # Remove Salesforce metadata
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output_file = f"results/{object_id}.csv"
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os.makedirs('results', exist_ok=True)
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df.to_csv(output_file, index=False)
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else:
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# Use Bulk API query
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results = sf.bulk2.__getattr__(object_id).query(
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query, max_records=2000000
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)
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# Write results to file
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output_file = f"results/{object_id}.csv"
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os.makedirs('results', exist_ok=True)
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for data in results:
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with open(output_file, "w", encoding="utf-8") as bos:
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bos.write(data)
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time.sleep(10)
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done = True
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t.do_run = False
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return output_file
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except Exception as e:
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done = True
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t.do_run = False
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raise ValueError(f'Error extracting data: {str(e)}')
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finally:
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# Clean up thread and animation state
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done = True
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if t and t.is_alive():
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t.join(timeout=1)
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if __name__ == '__main__':
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import argparse
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@ -92,23 +122,19 @@ if __name__ == '__main__':
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for query_def in queries:
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sobject = query_def['sobject']
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query_str = query_def['query'].replace('{country}', args.country)
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use_rest = query_def.get('useREST', False) # Default to False if not specified
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# Skip if --sobjects is provided and current sobject isn't in the list
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if selected_sobjects and sobject not in selected_sobjects:
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print(f'Skipping {sobject} as it is not specified in --sobjects')
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continue
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try:
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print(f'\nRunning query for {sobject}:')
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output_file = extract_data(
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object_id=sobject,
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query=query_str,
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output_path=args.output_path,
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context=args.context
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)
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print(f'File saved at: {output_file}')
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except Exception as e:
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print(f'Error running query for {sobject}: {str(e)}')
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# Optionally, you can choose to skip failed queries or exit here
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if not selected_sobjects or sobject in selected_sobjects:
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try:
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output_file = extract_data(
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object_id=sobject,
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query=query_str,
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output_path=args.output_path,
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context=args.context,
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use_rest=use_rest
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)
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print(f'Successfully extracted {sobject} to {output_file}')
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except Exception as e:
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print(f'Error extracting {sobject}: {str(e)}')
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print('\nExtraction complete.')
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@ -5,7 +5,7 @@
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"query": "SELECT Id, City__c, Country__c, GeoY__c, GeoX__c, PostalCode__c, Street__c, Extension__c, HouseNo__c, FlatNo__c, Floor__c FROM SCInstalledBaseLocation__c WHERE Country__c = '{country}' limit 3"
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},{
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"sobject": "SCInstalledBase__c",
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"query": "SELECT Id, Name, CommissioningDate__c,InstallationDate__c,ProductEnergy__c, ProductUnitClass__c,ArticleNo__c,SerialNo__c, SerialNoException__c, ProductUnitType__c, InstalledBaseLocation__c FROM SCInstalledBase__c WHERE Country__c = '{country}' limit 3"
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"query": "SELECT Id, Name, CommissioningDate__c,InstallationDate__c,ProductEnergy__c, ProductUnitClass__c,ArticleNo__c,SerialNo__c, SerialNoException__c, ProductUnitType__c, InstalledBaseLocation__c, WarrantyDuration__c, GuaranteeStandard__c, GuaranteeExtended__c FROM SCInstalledBase__c WHERE Country__c = '{country}' limit 3"
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},{
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"sobject": "Asset",
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"query": "SELECT Id, Serialnumber FROM Asset WHERE Location.ParentLocation.Name LIKE '%{country}'"
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@ -39,6 +39,10 @@
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},{
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"sobject": "SCContract__c",
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"query": "SELECT id, name, Template__c, status__c, Brand__r.Name, Country__c, Runtime__c, EndDate__c, StartDate__c, Account__c, AccountOwner__c, IoT_Registration_Status__c FROM SCContract__c WHERE Template__c != null AND EndDate__c >= TODAY AND Country__c = '{country}' limit 3"
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},{
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"sobject": "WarrantyTerm",
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"useREST": true,
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"query": "SELECT Id, WarrantyTermName, WarrantyDuration, WarrantyType, pricebook2.country__c FROM WarrantyTerm WHERE Pricebook2Id = null OR pricebook2.Country__c = '{country}'"
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}
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]
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}
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@ -40,10 +40,11 @@ read_df_address_iot = pd.read_csv('../1_extract_data/results/Address.csv', heade
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read_df_location_iot = pd.read_csv('../1_extract_data/results/ParentLocation.csv', header=0, keep_default_na=False, dtype=str)
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read_df_servicecontracttemplates = pd.read_csv('../1_extract_data/results/ContractTemplates.csv', header=0, keep_default_na=False, dtype=str)
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read_df_servicecontracts = pd.read_csv('../1_extract_data/results/SCContract__c.csv', header=0, keep_default_na=False, dtype=str)
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read_df_warrantyterm = pd.read_csv('../1_extract_data/results/WarrantyTerm.csv', header=0, keep_default_na=False, dtype=str)
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# Columns for reindexing
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reindex_columns = ['Id','City__c','Country__c','GeoY__c','GeoX__c','PostalCode__c','Street__c','Extension__c','HouseNo__c','FlatNo__c','Floor__c']
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reindex_columns_ib = ['Id','Name','CommissioningDate__c','InstallationDate__c','ProductEnergy__c','ProductUnitClass__c','ArticleNo__c','SerialNo__c','SerialNoException__c','ProductUnitType__c','InstalledBaseLocation__c']
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reindex_columns_ib = ['Id', 'Name', 'CommissioningDate__c', 'InstallationDate__c', 'ProductEnergy__c', 'ProductUnitClass__c', 'ArticleNo__c', 'SerialNo__c', 'SerialNoException__c', 'ProductUnitType__c', 'InstalledBaseLocation__c', 'WarrantyDuration__c', 'GuaranteeStandard__c', 'GuaranteeExtended__c']
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reindex_columns_product2 = ['Id','Main_Product_Group__c','Family','MaterialType__c','Name','Product_Code__c','ProductCode','EAN_Product_Code__c']
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reindex_columns_ibr = ['Id', 'InstalledBaseLocation__c', 'Role__c', 'ValidFrom__c', 'ValidTo__c', 'Account__c']
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reindex_columns_pricelist = ['Id', 'Name', 'Brand__r.Name', 'Country__c']
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@ -53,6 +54,7 @@ reindex_columns_address_iot = ['Id', 'Country', 'CountryCode', 'Street', 'City',
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reindex_columns_location_iot = ['Id', 'Name']
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reindex_columns_servicecontracttemplates = ['Id', 'Name', 'TemplateName__c', 'Status__c', 'Brand__r.Name', 'Country__c', 'Runtime__c']
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reindex_columns_servicecontracts = ['Id', 'Name', 'Template__c', 'Status__c', 'Brand__r.Name', 'Country__c', 'Runtime__c', 'EndDate__c', 'StartDate__c', 'Account__c', 'AccountOwner__c', 'IoT_Registration_Status__c']
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reindex_columns_warrantyterm = ['Id', 'WarrantyTermName', 'WarrantyDuration', 'WarrantyType', 'Pricebook2']
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# Reindex the columns to match the desired format
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df = read_df.reindex(reindex_columns, axis=1)
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@ -66,6 +68,7 @@ df_address_iot = read_df_address_iot.reindex(reindex_columns_address_iot, axis=1
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df_location_iot = read_df_location_iot.reindex(reindex_columns_location_iot, axis=1)
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df_servicecontracttemplates = read_df_servicecontracttemplates.reindex(reindex_columns_servicecontracttemplates, axis=1)
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df_servicecontract = read_df_servicecontracts.reindex(reindex_columns_servicecontracts, axis=1)
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df_warrantyterm = read_df_warrantyterm.reindex(reindex_columns_warrantyterm, axis=1)
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##--------------------------------------------------------------------------##
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## Update for IoT Addresses and Locations
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@ -112,30 +115,6 @@ df['PKey__c'] = (
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df['Country__c'].astype(str)
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)
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# Merge df_ib with df including additional columns
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merged_df_ib = pd.merge(df_ib,
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df[['Id', 'PKey__c', 'Extension__c', 'FlatNo__c', 'Floor__c']],
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left_on='InstalledBaseLocation__c',
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right_on='Id',
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how='left')
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print(merged_df_ib.columns)
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# If there are missing values (no match found), you can fill them with a placeholder
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#merged_df_ib['PKey__c'].fillna('Not Found', inplace=True)
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#merged_df_ib = merged_df_ib['PKey__c'].fillna('Not Found')
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merged_df_ib['PKey__c'] = (
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merged_df_ib['PKey__c'].astype(str) + ';' +
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merged_df_ib['Extension__c'].astype(str) + ';' +
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merged_df_ib['FlatNo__c'].astype(str) + ';' +
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merged_df_ib['Floor__c'].astype(str)
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)
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merged_df_ib = merged_df_ib.drop('Extension__c', axis=1)
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merged_df_ib = merged_df_ib.drop('FlatNo__c', axis=1)
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merged_df_ib = merged_df_ib.drop('Floor__c', axis=1)
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## 1. Address.csv
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# Columns needed for Address table based on the input CSV structure
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address_columns = ['City__c', 'Country__c',
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@ -224,6 +203,84 @@ child_df['IsInventoryLocation'] = 'false'
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child_df['IsMobile'] = 'false'
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child_df['LocationType'] = 'Site'
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##--------------------------------------------------------------------------##
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## Asset, AssociatedLocation, Asset Warranty
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##--------------------------------------------------------------------------##
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# Merge df_ib with df including additional columns
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merged_df_ib = pd.merge(df_ib,
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df[['Id', 'PKey__c', 'Extension__c', 'FlatNo__c', 'Floor__c']],
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left_on='InstalledBaseLocation__c',
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right_on='Id',
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how='left')
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print(merged_df_ib.columns)
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#Fetching data for standard warranty
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df_assetwarranty_standard = df_ib[['Id', 'InstallationDate__c', 'GuaranteeStandard__c']]
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# Filter df_warrantyterm to get only standard warranty type rows
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standard_warranty = df_warrantyterm[df_warrantyterm['WarrantyType'] == 'Standard']
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# Add the warranty term ID to df_assetwarranty_standard
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df_assetwarranty_standard['WarrantyTermId'] = standard_warranty['Id'].iloc[0]
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print(df_assetwarranty_standard)
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# Rename columns for asset warranty
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df_assetwarranty_standard.columns = ['Asset.PKey__c', 'StartDate', 'EndDate', 'WarrantyTerm.Id']
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#Fetching data for extended warranty where GuaranteeExtended__c is filled and different from GuaranteeStandard__c
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df_assetwarranty_extended = df_ib[
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(df_ib['GuaranteeExtended__c'].notna()) &
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(df_ib['GuaranteeExtended__c'] != df_ib['GuaranteeStandard__c'])
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][['Id', 'GuaranteeExtended__c', 'WarrantyDuration__c']]
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if(not df_assetwarranty_extended.empty):
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# Calculate start date for extended warranty based on warranty duration
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df_assetwarranty_extended['StartDate'] = pd.to_datetime(df_assetwarranty_extended['GuaranteeExtended__c']) - pd.to_timedelta(df_assetwarranty_extended['WarrantyDuration__c'].astype(float) * 30, unit='D')
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# Filter df_warrantyterm to get only extended warranty type rows
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# Filter for extended warranty and matching warranty duration
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extended_warranty = df_warrantyterm[(df_warrantyterm['WarrantyType'] == 'Extended') &
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(df_warrantyterm['WarrantyDuration'] == df_assetwarranty_extended['WarrantyDuration__c'].iloc[0])]
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# If multiple or no warranty terms found, set WarrantyTermId to empty
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if len(extended_warranty) != 1:
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df_assetwarranty_extended['WarrantyTermId'] = ''
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else:
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df_assetwarranty_extended['WarrantyTermId'] = extended_warranty['Id'].iloc[0]
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df_assetwarranty_extended = df_assetwarranty_extended.drop('WarrantyDuration__c', axis=1)
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print(df_assetwarranty_extended)
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# Rename columns for asset warranty
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df_assetwarranty_extended.columns = ['Asset.PKey__c', 'StartDate', 'EndDate', 'WarrantyTerm.Id']
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# Add them to a merged df for saving purposes
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df_assetwarranty_save = pd.concat(df_assetwarranty_standard, df_assetwarranty_extended)
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else:
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df_assetwarranty_save = df_assetwarranty_standard
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merged_df_ib = merged_df_ib.drop('GuaranteeStandard__c', axis=1)
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merged_df_ib = merged_df_ib.drop('GuaranteeExtended__c', axis=1)
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merged_df_ib = merged_df_ib.drop('WarrantyDuration__c', axis=1)
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# If there are missing values (no match found), you can fill them with a placeholder
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#merged_df_ib['PKey__c'].fillna('Not Found', inplace=True)
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#merged_df_ib = merged_df_ib['PKey__c'].fillna('Not Found')
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merged_df_ib['PKey__c'] = (
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merged_df_ib['PKey__c'].astype(str) + ';' +
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merged_df_ib['Extension__c'].astype(str) + ';' +
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merged_df_ib['FlatNo__c'].astype(str) + ';' +
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merged_df_ib['Floor__c'].astype(str)
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)
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merged_df_ib = merged_df_ib.drop('Extension__c', axis=1)
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merged_df_ib = merged_df_ib.drop('FlatNo__c', axis=1)
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merged_df_ib = merged_df_ib.drop('Floor__c', axis=1)
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## 4. Assets.csv
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#ArticleNo__c,CommissioningDate__c,Id,InstallationDate__c,InstalledBaseLocation__c,InstalledBaseLocation__r.Extension__c,InstalledBaseLocation__r.FlatNo__c,InstalledBaseLocation__r.Floor__c,InstalledBaseLocation__r.Id,Name,ProductEnergy__c,ProductUnitClass__c,ProductUnitType__c,SerialNo__c,SerialNoException__c
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@ -468,13 +525,12 @@ df_servicecontract['Pricebook2.Name'] = (
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"SERVICE"
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)
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df_servicecontract = df_servicecontract.drop('Name', axis=1)
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df_servicecontract = df_servicecontract.drop('Brand__r.Name', axis=1)
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df_servicecontract.columns = ['PKey__c', 'TemplateId__r.PKey__c', 'Status', 'BillingCountryCode', 'Term', 'EndDate', 'StartDate', 'AccountId', 'Service_Recipient__c', 'IoT_Registration_Status__c', 'Pricebook2.Name']
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df_servicecontract.columns = ['PKey__c', 'Name', 'TemplateId__r.PKey__c', 'Status', 'BillingCountryCode', 'Term', 'EndDate', 'StartDate', 'AccountId', 'Service_Recipient__c', 'IoT_Registration_Status__c', 'Pricebook2.Name']
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df_servicecontract['IoT_Registration_Status__c'] = df_servicecontract['IoT_Registration_Status__c'].replace('', 'Open')
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df_servicecontract['Name'] = df_servicecontract['PKey__c']
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#df_servicecontract['Name'] = df_servicecontract['PKey__c']
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df_servicecontract['TemplateCountry__c'] = df_servicecontract['BillingCountryCode']
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#df_servicecontract = df_servicecontract.drop('TemplateId__r.PKey__c', axis=1)
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@ -498,6 +554,7 @@ df_pricelistitem.to_csv('../12_insert_pricebook2_and_pricebookentries/PricebookE
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merged_df_location_iot.to_csv('../3_update_address_and_location_data_for_migration/Location.csv', index=False)
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df_servicecontracttemplates.to_csv('../13_insert_servicecontracttemplates_dummies/ServiceContract.csv', index=False)
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df_servicecontract.to_csv('../15_insert_servicecontract/ServiceContract_beforetransform.csv', index=False)
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df_assetwarranty_save.to_csv('../8_upsert_assets/AssetWarranty.csv', index=False)
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## end mapping
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print('Data has been successfully transformed and saved to CSV files.')
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