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# ... for _, row in filtered_df.iterrows(): eprm_table_name = row['eprm_table_name'] eprm_join_cols_entity = row['eprm_join_cols_entity'] eprm_join_cols_reim = row['eprm_join_cols_reim'] eprm_table_alias = row['eprm_table_alias'] # Split the strings by ',' to get individual column assignments columns_entity = eprm_join_cols_entity.split(',') if eprm_join_cols_entity else [] columns_reim = eprm_join_cols_reim.split(',') if eprm_join_cols_reim else [] # Compare the lengths of the column assignments if len(columns_entity) != len(columns_reim): # If entity columns are fewer, append missing columns to the end of columns_reim if len(columns_entity) < len(columns_reim): columns_entity += columns_reim[len(columns_entity):] # If entity columns are more, append missing columns to the end of columns_entity else: columns_reim += columns_entity[len(columns_reim):] # Construct the modified assignment string assignment_string = '' for col_entity, col_reim in zip(columns_entity, columns_reim): # Extract the column name after '=' col_name_entity = col_entity.split('=')[0].strip() col_name_reim = col_reim.split('=')[0].strip() # Append the modified assignment to the string assignment_string += f"{col_reim.replace(col_name_reim, eprm_table_alias + '.' + col_name_entity)}, " # Remove the trailing comma and whitespace assignment_string = assignment_string.rstrip(', ') assignment_string = assignment_string.replace("AND", ",") eprm_join_reim = assignment_string # ...
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