refactor: remove commented code

server/workers/orcid/src/orcid_service.py

@@ -345,50 +345,6 @@ def get_unversioned_doi(doi_str):
 
         return base_metadata
 
-    def _explode_merged_dois(self, base_metadata: pd.DataFrame) -> pd.DataFrame:
-        """
-        Explode merged_dois field to create separate rows for each DOI variant.
-
-        If base_metadata contains a 'merged_dois' field with multiple DOIs separated by '; ',
-        this function creates separate rows for each DOI, allowing matching with ORCID metadata
-        by any of those DOIs.
-
-        Parameters:
-        - base_metadata: DataFrame with BASE metadata, potentially containing 'merged_dois' field
-
-        Returns:
-        - DataFrame with exploded rows where each row has a single DOI in the 'doi' column
-        """
-        # Process merged_dois: explode to create separate rows for each DOI variant
-        # This allows us to match BASE records with multiple DOIs to ORCID records by any of those DOIs
-        if 'merged_dois' in base_metadata.columns:
-            # Split merged_dois by "; " and create a list of DOIs for each row
-            # If merged_dois is empty/NaN, create empty list; otherwise split and process each DOI
-            base_metadata['merged_dois_list'] = base_metadata['merged_dois'].apply(
-                lambda x: [remove_doi_prefix(doi.strip()) for doi in str(x).split('; ') if doi.strip()] 
-                if pd.notna(x) and str(x).strip() else []
-            )
-
-            # Use explode to create separate rows for each DOI in merged_dois_list
-            # Rows with empty lists will remain as single rows
-            base_metadata = base_metadata.explode('merged_dois_list', ignore_index=True)
-
-            # For rows where merged_dois_list is not empty, use it as the DOI
-            # For rows where merged_dois_list is empty/NaN, use the regular doi column
-            mask_has_merged_doi = pd.notna(base_metadata['merged_dois_list']) & (base_metadata['merged_dois_list'] != '')
-            base_metadata.loc[mask_has_merged_doi, 'doi'] = base_metadata.loc[mask_has_merged_doi, 'merged_dois_list']
-
-            # Process regular doi column for rows without merged_dois
-            base_metadata.loc[~mask_has_merged_doi, 'doi'] = base_metadata.loc[~mask_has_merged_doi, 'doi'].apply(remove_doi_prefix)
-
-            # Drop temporary column
-            base_metadata = base_metadata.drop(columns=['merged_dois_list'])
-        else:
-            # No merged_dois column, process regular doi column
-            base_metadata.loc[:, 'doi'] = base_metadata['doi'].apply(remove_doi_prefix)
-
-        return base_metadata
-
     def enrich_metadata_with_base(self, params: Dict[str, str], metadata: pd.DataFrame) -> pd.DataFrame:
         self.logger.debug(f"Enriching metadata with base for ORCID {params.get('orcid')}")
 
@@ -437,7 +393,6 @@ def enrich_metadata_with_base(self, params: Dict[str, str], metadata: pd.DataFra
 
         base_metadata = base_metadata.reindex(columns=required_fields)
 
-        #base_metadata = self._explode_merged_dois(base_metadata)
         base_metadata['merged_dois'] = base_metadata['merged_dois'].apply(lambda x: x[0] if isinstance(x, list) and len(x) > 0 else x)
         base_metadata['merged_dois'] = base_metadata['merged_dois'].apply(lambda x: x.split(';') if isinstance(x, str) else [])
         base_metadata['merged_dois'] = base_metadata['merged_dois'].apply(lambda x: [x.strip() for x in x] if isinstance(x, list) else x)