fixed missing publications and qualified_predicate bug, added knowled…

…ge level and agent type

parsers/monarchkg/src/loadMonarchKG.py

@@ -5,7 +5,7 @@
 
 from Common.loader_interface import SourceDataLoader
 from Common.kgxmodel import kgxedge
-from Common.biolink_constants import PUBLICATIONS
+from Common.biolink_constants import *
 from Common.utils import GetData
 
 
@@ -18,7 +18,7 @@ class MonarchKGLoader(SourceDataLoader):
 
     source_id: str = 'MonarchKG'
     provenance_id: str = 'infores:monarchinitiative'
-    parsing_version: str = '1.0'
+    parsing_version: str = '1.1'
 
     def __init__(self, test_mode: bool = False, source_data_dir: str = None):
         """
@@ -89,12 +89,13 @@ def parse_data(self) -> dict:
             with tar_files.extractfile(self.monarch_edge_file_archive_path) as edges_file:
                 for line in edges_file:
                     monarch_edge = orjson.loads(line)
-                    subject_id = monarch_edge['subject']
-                    object_id = monarch_edge['object']
-                    predicate = monarch_edge['predicate']
+                    # normally we wouldn't use constants to read FROM a source,
+                    # but in this case monarch kg is biolink compliant, so they should be the same
+                    subject_id = monarch_edge[SUBJECT_ID]
+                    object_id = monarch_edge[OBJECT_ID]
+                    predicate = monarch_edge[PREDICATE]
                     if not (subject_id and object_id and predicate):
                         skipped_bad_record_counter += 1
-                        print(line)
                         continue
 
                     if predicate not in self.desired_predicates:
@@ -103,26 +104,32 @@ def parse_data(self) -> dict:
 
                     # get the knowledge sources, map them to something else if needed,
                     # then check if edge should be ignored due to the knowledge source
-                    primary_knowledge_source = self.knowledge_source_mapping.get(monarch_edge['primary_knowledge_source'],
-                                                                                 monarch_edge['primary_knowledge_source'])
-                    aggregator_knowledge_sources = [self.knowledge_source_mapping.get(ks, ks) for ks in monarch_edge['aggregator_knowledge_source']]
+                    primary_knowledge_source = self.knowledge_source_mapping.get(monarch_edge[PRIMARY_KNOWLEDGE_SOURCE],
+                                                                                 monarch_edge[PRIMARY_KNOWLEDGE_SOURCE])
+                    aggregator_knowledge_sources = [self.knowledge_source_mapping.get(ks, ks) for ks in monarch_edge[AGGREGATOR_KNOWLEDGE_SOURCES]]
                     if primary_knowledge_source in self.knowledge_source_ignore_list or \
                             any([ks in self.knowledge_source_ignore_list for ks in aggregator_knowledge_sources]):
                         skipped_ignore_knowledge_source += 1
                         continue
 
-                    edge_properties = {}
-                    if monarch_edge['publications']:
-                        edge_properties[PUBLICATIONS] = monarch_edge['publications']
+                    edge_properties = {
+                        KNOWLEDGE_LEVEL: monarch_edge[KNOWLEDGE_LEVEL] if KNOWLEDGE_LEVEL in monarch_edge else NOT_PROVIDED,
+                        AGENT_TYPE: monarch_edge[AGENT_TYPE] if AGENT_TYPE in monarch_edge else NOT_PROVIDED
+                    }
+                    if monarch_edge[PUBLICATIONS]:
+                        edge_properties[PUBLICATIONS] = monarch_edge[PUBLICATIONS]
                     for edge_attribute in monarch_edge:
                         if '_qualifier' in edge_attribute and monarch_edge[edge_attribute]:
                             edge_properties[edge_attribute] = monarch_edge[edge_attribute]
+                        elif edge_attribute == QUALIFIED_PREDICATE and monarch_edge[QUALIFIED_PREDICATE]:
+                            edge_properties[QUALIFIED_PREDICATE] = monarch_edge[QUALIFIED_PREDICATE]
                     output_edge = kgxedge(
                         subject_id=subject_id,
                         predicate=predicate,
                         object_id=object_id,
                         primary_knowledge_source=primary_knowledge_source,
-                        aggregator_knowledge_sources=aggregator_knowledge_sources
+                        aggregator_knowledge_sources=aggregator_knowledge_sources,
+                        edgeprops=edge_properties
                     )
                     self.output_file_writer.write_node(object_id)
                     self.output_file_writer.write_node(subject_id)