feat!: generalize script by removing organizational metadata

Remove Phase class, organizational metadata blocks, and unused project fields. Update configuration
to use 'default_grants' and simplify PI usage to fallback corresponding author determination only.

BREAKING CHANGES: - Remove 'phase' and 'project' fields from configuration - Use 'default_grants'
instead of 'default_grant' - Generate only standard Dataverse citation metadata

tests/test_metadata_processor.py

@@ -1,7 +1,8 @@
 import json
 import os
+from unittest.mock import MagicMock
+
 import pytest
-from unittest.mock import MagicMock, patch
 
 from doi2dataset import MetadataProcessor
 
@@ -27,36 +28,35 @@ def test_build_metadata_basic_fields(metadata_processor, openalex_data, monkeypa
     """Test that _build_metadata correctly extracts basic metadata fields"""
     # Mock the console to avoid print errors
     metadata_processor.console = MagicMock()
-    
+
     # Mock the Abstract related methods and objects to avoid console errors
     abstract_mock = MagicMock()
     abstract_mock.text = "This is a sample abstract"
     abstract_mock.source = "openalex"
     monkeypatch.setattr("doi2dataset.AbstractProcessor.get_abstract", lambda *args, **kwargs: abstract_mock)
-    
+
     # Mock the _fetch_data method to return our test data
     metadata_processor._fetch_data = MagicMock(return_value=openalex_data)
-    
+
     # Mock methods that might cause issues in isolation
     metadata_processor._build_description = MagicMock(return_value="Test description")
     metadata_processor._get_involved_pis = MagicMock(return_value=[])
-    metadata_processor._build_organization_metadata = MagicMock(return_value={})
-    
+
     # Call the method we're testing
     metadata = metadata_processor._build_metadata(openalex_data)
 
     # Verify the basic metadata fields were extracted correctly
     assert metadata is not None
     assert 'datasetVersion' in metadata
-    
+
     # Examine the fields inside datasetVersion.metadataBlocks
     assert 'metadataBlocks' in metadata['datasetVersion']
     citation = metadata['datasetVersion']['metadataBlocks'].get('citation', {})
-    
+
     # Check fields in citation section
     assert 'fields' in citation
     fields = citation['fields']
-    
+
     # Check for basic metadata fields in a more flexible way
     field_names = [field.get('typeName') for field in fields]
     assert 'title' in field_names
@@ -68,44 +68,43 @@ def test_build_metadata_authors(metadata_processor, openalex_data, monkeypatch):
     """Test that _build_metadata correctly processes author information"""
     # Mock the console to avoid print errors
     metadata_processor.console = MagicMock()
-    
+
     # Mock the Abstract related methods and objects to avoid console errors
     abstract_mock = MagicMock()
     abstract_mock.text = "This is a sample abstract"
     abstract_mock.source = "openalex"
     monkeypatch.setattr("doi2dataset.AbstractProcessor.get_abstract", lambda *args, **kwargs: abstract_mock)
-    
+
     # Mock the _fetch_data method to return our test data
     metadata_processor._fetch_data = MagicMock(return_value=openalex_data)
-    
+
     # Mock methods that might cause issues in isolation
     metadata_processor._build_description = MagicMock(return_value="Test description")
     metadata_processor._get_involved_pis = MagicMock(return_value=[])
-    metadata_processor._build_organization_metadata = MagicMock(return_value={})
-    
+
     # Call the method we're testing
     metadata = metadata_processor._build_metadata(openalex_data)
 
     # Examine the fields inside datasetVersion.metadataBlocks
     assert 'metadataBlocks' in metadata['datasetVersion']
     citation = metadata['datasetVersion']['metadataBlocks'].get('citation', {})
-    
+
     # Check fields in citation section
     assert 'fields' in citation
     fields = citation['fields']
-    
+
     # Check for author and datasetContact fields
     field_names = [field.get('typeName') for field in fields]
     assert 'author' in field_names
     assert 'datasetContact' in field_names
-    
+
     # Verify these are compound fields with actual entries
     for field in fields:
         if field.get('typeName') == 'author':
             assert 'value' in field
             assert isinstance(field['value'], list)
             assert len(field['value']) > 0
-        
+
         if field.get('typeName') == 'datasetContact':
             assert 'value' in field
             assert isinstance(field['value'], list)
@@ -117,46 +116,45 @@ def test_build_metadata_keywords_and_topics(metadata_processor, openalex_data, m
     """Test that _build_metadata correctly extracts keywords and topics"""
     # Mock the console to avoid print errors
     metadata_processor.console = MagicMock()
-    
+
     # Mock the Abstract related methods and objects to avoid console errors
     abstract_mock = MagicMock()
     abstract_mock.text = "This is a sample abstract"
     abstract_mock.source = "openalex"
     monkeypatch.setattr("doi2dataset.AbstractProcessor.get_abstract", lambda *args, **kwargs: abstract_mock)
-    
+
     # Mock the _fetch_data method to return our test data
     metadata_processor._fetch_data = MagicMock(return_value=openalex_data)
-    
+
     # Mock methods that might cause issues in isolation
     metadata_processor._build_description = MagicMock(return_value="Test description")
     metadata_processor._get_involved_pis = MagicMock(return_value=[])
-    metadata_processor._build_organization_metadata = MagicMock(return_value={})
-    
+
     # Call the method we're testing
     metadata = metadata_processor._build_metadata(openalex_data)
-        
+
     # Examine the fields inside datasetVersion.metadataBlocks
     assert 'metadataBlocks' in metadata['datasetVersion']
     citation = metadata['datasetVersion']['metadataBlocks'].get('citation', {})
-    
+
     # Check fields in citation section
     assert 'fields' in citation
     fields = citation['fields']
-    
+
     # Check for keyword and subject fields
     field_names = [field.get('typeName') for field in fields]
-    
+
     # If keywords exist, verify structure
     if 'keyword' in field_names:
         for field in fields:
             if field.get('typeName') == 'keyword':
                 assert 'value' in field
                 assert isinstance(field['value'], list)
-    
+
     # Check for subject field which should definitely exist
     assert 'subject' in field_names
     for field in fields:
         if field.get('typeName') == 'subject':
             assert 'value' in field
             assert isinstance(field['value'], list)
-            assert len(field['value']) > 0
+            assert len(field['value']) > 0