asset warranty saves

This commit is contained in:
Rene Kaßeböhmer
2025-05-16 12:13:54 +02:00
parent d4f944dca4
commit d5742d7d30
7 changed files with 204 additions and 104 deletions

View File

@ -40,10 +40,11 @@ read_df_address_iot = pd.read_csv('../1_extract_data/results/Address.csv', heade
read_df_location_iot = pd.read_csv('../1_extract_data/results/ParentLocation.csv', header=0, keep_default_na=False, dtype=str)
read_df_servicecontracttemplates = pd.read_csv('../1_extract_data/results/ContractTemplates.csv', header=0, keep_default_na=False, dtype=str)
read_df_servicecontracts = pd.read_csv('../1_extract_data/results/SCContract__c.csv', header=0, keep_default_na=False, dtype=str)
read_df_warrantyterm = pd.read_csv('../1_extract_data/results/WarrantyTerm.csv', header=0, keep_default_na=False, dtype=str)
# Columns for reindexing
reindex_columns = ['Id','City__c','Country__c','GeoY__c','GeoX__c','PostalCode__c','Street__c','Extension__c','HouseNo__c','FlatNo__c','Floor__c']
reindex_columns_ib = ['Id','Name','CommissioningDate__c','InstallationDate__c','ProductEnergy__c','ProductUnitClass__c','ArticleNo__c','SerialNo__c','SerialNoException__c','ProductUnitType__c','InstalledBaseLocation__c']
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']
reindex_columns_product2 = ['Id','Main_Product_Group__c','Family','MaterialType__c','Name','Product_Code__c','ProductCode','EAN_Product_Code__c']
reindex_columns_ibr = ['Id', 'InstalledBaseLocation__c', 'Role__c', 'ValidFrom__c', 'ValidTo__c', 'Account__c']
reindex_columns_pricelist = ['Id', 'Name', 'Brand__r.Name', 'Country__c']
@ -53,6 +54,7 @@ reindex_columns_address_iot = ['Id', 'Country', 'CountryCode', 'Street', 'City',
reindex_columns_location_iot = ['Id', 'Name']
reindex_columns_servicecontracttemplates = ['Id', 'Name', 'TemplateName__c', 'Status__c', 'Brand__r.Name', 'Country__c', 'Runtime__c']
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']
reindex_columns_warrantyterm = ['Id', 'WarrantyTermName', 'WarrantyDuration', 'WarrantyType', 'Pricebook2']
# Reindex the columns to match the desired format
df = read_df.reindex(reindex_columns, axis=1)
@ -66,6 +68,7 @@ df_address_iot = read_df_address_iot.reindex(reindex_columns_address_iot, axis=1
df_location_iot = read_df_location_iot.reindex(reindex_columns_location_iot, axis=1)
df_servicecontracttemplates = read_df_servicecontracttemplates.reindex(reindex_columns_servicecontracttemplates, axis=1)
df_servicecontract = read_df_servicecontracts.reindex(reindex_columns_servicecontracts, axis=1)
df_warrantyterm = read_df_warrantyterm.reindex(reindex_columns_warrantyterm, axis=1)
##--------------------------------------------------------------------------##
## Update for IoT Addresses and Locations
@ -112,30 +115,6 @@ df['PKey__c'] = (
df['Country__c'].astype(str)
)
# Merge df_ib with df including additional columns
merged_df_ib = pd.merge(df_ib,
df[['Id', 'PKey__c', 'Extension__c', 'FlatNo__c', 'Floor__c']],
left_on='InstalledBaseLocation__c',
right_on='Id',
how='left')
print(merged_df_ib.columns)
# If there are missing values (no match found), you can fill them with a placeholder
#merged_df_ib['PKey__c'].fillna('Not Found', inplace=True)
#merged_df_ib = merged_df_ib['PKey__c'].fillna('Not Found')
merged_df_ib['PKey__c'] = (
merged_df_ib['PKey__c'].astype(str) + ';' +
merged_df_ib['Extension__c'].astype(str) + ';' +
merged_df_ib['FlatNo__c'].astype(str) + ';' +
merged_df_ib['Floor__c'].astype(str)
)
merged_df_ib = merged_df_ib.drop('Extension__c', axis=1)
merged_df_ib = merged_df_ib.drop('FlatNo__c', axis=1)
merged_df_ib = merged_df_ib.drop('Floor__c', axis=1)
## 1. Address.csv
# Columns needed for Address table based on the input CSV structure
address_columns = ['City__c', 'Country__c',
@ -224,6 +203,84 @@ child_df['IsInventoryLocation'] = 'false'
child_df['IsMobile'] = 'false'
child_df['LocationType'] = 'Site'
##--------------------------------------------------------------------------##
## Asset, AssociatedLocation, Asset Warranty
##--------------------------------------------------------------------------##
# Merge df_ib with df including additional columns
merged_df_ib = pd.merge(df_ib,
df[['Id', 'PKey__c', 'Extension__c', 'FlatNo__c', 'Floor__c']],
left_on='InstalledBaseLocation__c',
right_on='Id',
how='left')
print(merged_df_ib.columns)
#Fetching data for standard warranty
df_assetwarranty_standard = df_ib[['Id', 'InstallationDate__c', 'GuaranteeStandard__c']]
# Filter df_warrantyterm to get only standard warranty type rows
standard_warranty = df_warrantyterm[df_warrantyterm['WarrantyType'] == 'Standard']
# Add the warranty term ID to df_assetwarranty_standard
df_assetwarranty_standard['WarrantyTermId'] = standard_warranty['Id'].iloc[0]
print(df_assetwarranty_standard)
# Rename columns for asset warranty
df_assetwarranty_standard.columns = ['Asset.PKey__c', 'StartDate', 'EndDate', 'WarrantyTerm.Id']
#Fetching data for extended warranty where GuaranteeExtended__c is filled and different from GuaranteeStandard__c
df_assetwarranty_extended = df_ib[
(df_ib['GuaranteeExtended__c'].notna()) &
(df_ib['GuaranteeExtended__c'] != df_ib['GuaranteeStandard__c'])
][['Id', 'GuaranteeExtended__c', 'WarrantyDuration__c']]
if(not df_assetwarranty_extended.empty):
# Calculate start date for extended warranty based on warranty duration
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')
# Filter df_warrantyterm to get only extended warranty type rows
# Filter for extended warranty and matching warranty duration
extended_warranty = df_warrantyterm[(df_warrantyterm['WarrantyType'] == 'Extended') &
(df_warrantyterm['WarrantyDuration'] == df_assetwarranty_extended['WarrantyDuration__c'].iloc[0])]
# If multiple or no warranty terms found, set WarrantyTermId to empty
if len(extended_warranty) != 1:
df_assetwarranty_extended['WarrantyTermId'] = ''
else:
df_assetwarranty_extended['WarrantyTermId'] = extended_warranty['Id'].iloc[0]
df_assetwarranty_extended = df_assetwarranty_extended.drop('WarrantyDuration__c', axis=1)
print(df_assetwarranty_extended)
# Rename columns for asset warranty
df_assetwarranty_extended.columns = ['Asset.PKey__c', 'StartDate', 'EndDate', 'WarrantyTerm.Id']
# Add them to a merged df for saving purposes
df_assetwarranty_save = pd.concat(df_assetwarranty_standard, df_assetwarranty_extended)
else:
df_assetwarranty_save = df_assetwarranty_standard
merged_df_ib = merged_df_ib.drop('GuaranteeStandard__c', axis=1)
merged_df_ib = merged_df_ib.drop('GuaranteeExtended__c', axis=1)
merged_df_ib = merged_df_ib.drop('WarrantyDuration__c', axis=1)
# If there are missing values (no match found), you can fill them with a placeholder
#merged_df_ib['PKey__c'].fillna('Not Found', inplace=True)
#merged_df_ib = merged_df_ib['PKey__c'].fillna('Not Found')
merged_df_ib['PKey__c'] = (
merged_df_ib['PKey__c'].astype(str) + ';' +
merged_df_ib['Extension__c'].astype(str) + ';' +
merged_df_ib['FlatNo__c'].astype(str) + ';' +
merged_df_ib['Floor__c'].astype(str)
)
merged_df_ib = merged_df_ib.drop('Extension__c', axis=1)
merged_df_ib = merged_df_ib.drop('FlatNo__c', axis=1)
merged_df_ib = merged_df_ib.drop('Floor__c', axis=1)
## 4. Assets.csv
#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
@ -468,13 +525,12 @@ df_servicecontract['Pricebook2.Name'] = (
"SERVICE"
)
df_servicecontract = df_servicecontract.drop('Name', axis=1)
df_servicecontract = df_servicecontract.drop('Brand__r.Name', axis=1)
df_servicecontract.columns = ['PKey__c', 'TemplateId__r.PKey__c', 'Status', 'BillingCountryCode', 'Term', 'EndDate', 'StartDate', 'AccountId', 'Service_Recipient__c', 'IoT_Registration_Status__c', 'Pricebook2.Name']
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']
df_servicecontract['IoT_Registration_Status__c'] = df_servicecontract['IoT_Registration_Status__c'].replace('', 'Open')
df_servicecontract['Name'] = df_servicecontract['PKey__c']
#df_servicecontract['Name'] = df_servicecontract['PKey__c']
df_servicecontract['TemplateCountry__c'] = df_servicecontract['BillingCountryCode']
#df_servicecontract = df_servicecontract.drop('TemplateId__r.PKey__c', axis=1)
@ -498,6 +554,7 @@ df_pricelistitem.to_csv('../12_insert_pricebook2_and_pricebookentries/PricebookE
merged_df_location_iot.to_csv('../3_update_address_and_location_data_for_migration/Location.csv', index=False)
df_servicecontracttemplates.to_csv('../13_insert_servicecontracttemplates_dummies/ServiceContract.csv', index=False)
df_servicecontract.to_csv('../15_insert_servicecontract/ServiceContract_beforetransform.csv', index=False)
df_assetwarranty_save.to_csv('../8_upsert_assets/AssetWarranty.csv', index=False)
## end mapping
print('Data has been successfully transformed and saved to CSV files.')