IB import nearly finished

This commit is contained in:
Rene Kaßeböhmer
2025-04-02 15:31:44 +02:00
parent 6bc3fd1a00
commit 5b5a2769c8
3 changed files with 30 additions and 43 deletions

View File

@ -5,8 +5,8 @@ country_mapping = {
} }
# Read the input CSV file, assuming the second row is the header # Read the input CSV file, assuming the second row is the header
read_df = pd.read_csv('../1/SCInstalledBaseLocation__c.csv', header=0, keep_default_na=False) read_df = pd.read_csv('../1/SCInstalledBaseLocation__c.csv', header=0, keep_default_na=False, dtype=str)
read_df_ib = pd.read_csv('../1/SCInstalledBase__c.csv', header=0, keep_default_na=False) read_df_ib = pd.read_csv('../1/SCInstalledBase__c.csv', header=0, keep_default_na=False, dtype=str)
for row in read_df.to_dict('records'): for row in read_df.to_dict('records'):
try: try:
# Your processing logic here # Your processing logic here
@ -45,14 +45,20 @@ merged_df_ib = pd.merge(df_ib,
right_on='Id', right_on='Id',
how='left') how='left')
# Handle missing values by setting them to None
merged_df_ib['Extension__c'] = merged_df_ib['Extension__c'].fillna('')
merged_df_ib['FlatNo__c'] = merged_df_ib['FlatNo__c'].fillna('')
merged_df_ib['Floor__c'] = merged_df_ib['Floor__c'].fillna('')
# If there are missing values (no match found), you can fill them with a placeholder # 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['PKey__c'].fillna('Not Found', inplace=True)
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 ## 1. Address.csv
# Columns needed for Address table based on the input CSV structure # Columns needed for Address table based on the input CSV structure
address_columns = ['City__c', 'Country__c', address_columns = ['City__c', 'Country__c',
@ -114,9 +120,17 @@ child_df['Name'] = (
# Replace any row where 'Floor__c', 'FlatNo__c', and 'Extension__c' are all empty with "HOME" # Replace any row where 'Floor__c', 'FlatNo__c', and 'Extension__c' are all empty with "HOME"
child_df.replace({'Name': {'--': 'HOME'}}, inplace=True) child_df.replace({'Name': {'--': 'HOME'}}, inplace=True)
# Create the 'ExternalReference' column for Asset assignment
child_df['ExternalReference'] = (
child_df['PKey__c'].astype(str) + ';' +
child_df['Extension__c'].astype(str) + ';' +
child_df['FlatNo__c'].astype(str) + ';' +
child_df['Floor__c'].astype(str)
)
# Rename columns to match the desired format # Rename columns to match the desired format
child_df.columns = ['Extension__c', 'Flat__c', 'Floor__c', 'City', 'Country', child_df.columns = ['Extension__c', 'Flat__c', 'Floor__c', 'City', 'Country',
'PostalCode', 'Street', 'PKey__c', 'Name'] 'PostalCode', 'Street', 'PKey__c', 'Name', 'ExternalReference']
child_df = child_df.drop_duplicates(subset=['Extension__c', 'Flat__c', 'Floor__c','City', 'Country', 'PostalCode', 'Street'], keep='first') child_df = child_df.drop_duplicates(subset=['Extension__c', 'Flat__c', 'Floor__c','City', 'Country', 'PostalCode', 'Street'], keep='first')
@ -137,7 +151,7 @@ merged_df_ib = merged_df_ib.drop('InstalledBaseLocation__c', axis=1)
merged_df_ib = merged_df_ib.drop('InstalledBaseLocation__r.Id', axis=1) merged_df_ib = merged_df_ib.drop('InstalledBaseLocation__r.Id', axis=1)
merged_df_ib = merged_df_ib.drop('Id_y', axis=1) merged_df_ib = merged_df_ib.drop('Id_y', axis=1)
print(merged_df_ib.columns) print(merged_df_ib.columns)
merged_df_ib.columns = ['Product2.EAN_Product_Code__c', 'FSL_1st_Ignition_Date__c', 'Id', 'InstallDate', 'Name', 'Kind_of_Energy__c', 'Kind_of_Installation__c', 'Main_Product_Group__c', 'SerialNumber', 'Serialnumber_Exception__c', 'Location.PKey__c', 'Location.Extension__c', 'Location.Flat__c', 'Location.Floor__c',] merged_df_ib.columns = ['Product2.EAN_Product_Code__c', 'FSL_1st_Ignition_Date__c', 'Id', 'InstallDate', 'Name', 'Kind_of_Energy__c', 'Kind_of_Installation__c', 'Main_Product_Group__c', 'SerialNumber', 'Serialnumber_Exception__c', 'Location.ExternalReference']
# Write each DataFrame to a separate CSV file # Write each DataFrame to a separate CSV file
address_df.to_csv('../3/Address.csv', index=False) address_df.to_csv('../3/Address.csv', index=False)

View File

@ -1 +1 @@
sf sfdmu run --sourceusername rene.kasseboehmer@vaillant.de.devrene --targetusername rene.kasseboehmer@vaillant.de.devrene sf sfdmu run --sourceusername csvfile --targetusername rene.kasseboehmer@vaillant.de.devrene

View File

@ -3,43 +3,16 @@
"excludeIdsFromCSVFiles": true, "excludeIdsFromCSVFiles": true,
"objects": [ "objects": [
{ {
"query": "SELECT Id, Extension__c,Flat__c,Floor__c,Name,PKey__c FROM Location WHERE ParentLocationId != null AND ParentLocation.VisitorAddress.CountryCode = 'NL'", "query": "SELECT ExternalReference FROM Location WHERE ExternalReference != null AND ParentLocation.VisitorAddress.CountryCode = 'NL'",
"operation": "Readonly", "operation": "Readonly",
"externalId": "PKey__c;Extension__c;Flat__c;Floor__c", "externalId": "ExternalReference"
"master": false
},{ },{
"query": "SELECT Id, EAN_Product_Code__c FROM Product2 WHERE EAN_Product_Code__c != null", "query": "SELECT EAN_Product_Code__c FROM Product2 WHERE EAN_Product_Code__c != null",
"operation": "Readonly", "operation": "Readonly",
"externalId": "EAN_Product_Code__c", "externalId": "EAN_Product_Code__c"
"master": false
},{ },{
"query": "SELECT Product2Id,FSL_1st_Ignition_Date__c,Id,InstallDate,Name,Kind_of_Energy__c,Kind_of_Installation__c,Main_Product_Group__c,SerialNumber,Serialnumber_Exception__c,LocationId FROM Asset", "query": "SELECT Product2Id,Id,InstallDate,Name,Kind_of_Energy__c,Kind_of_Installation__c,Main_Product_Group__c,SerialNumber,Serialnumber_Exception__c,LocationId FROM Asset",
"operation": "Insert", "operation": "Insert"
"useSourceCSVFile": true,
"beforeUpdateAddons": [
{
"module": "core:RecordsTransform",
"description": "Updates ParentLocationId with source Address.ParentId based on Pkey__c",
"args": {
"fields": [
{
"alias": "sourceLocationIdFromPkeyExtensionFlatFloor",
"sourceObject": "Location",
"sourceField": "Id",
"lookupExpression": "source.PKey__c == target.Location.PKey__c && source.Extension__c == target.Location.Extension__c && source.Flat__c == target.Location.Flat__c && source.Floor__c == target.Location.Floor__c",
"lookupSource": "source"
}
],
"transformations": [
{
"targetObject": "Asset",
"targetField": "LocationId",
"formula": "formula.sourceLocationIdFromPkeyExtensionFlatFloor"
}
]
}
}
]
} }
] ]
} }