async def upload_mappings(file: UploadFile = File(...)):
if file.content_type == 'text/tab-separated-values':
df = pd.read_csv(file.file, sep='\t', comment='#').fillna('')
msd = from_dataframe(df, NAMESPACES, {})
# Importer(neo4j_graph()).import_mapping_set(msd.mapping_set, NAMESPACES)
Importer(neo4j_graph()).import_mapping_set(msd.mapping_set)
return {
"filename": file.filename,
'mappings': len(msd.mapping_set.mappings)
}
else:
raise HTTPException(
status_code=404,
detail=f"content type not supported: {file.content_type}")
def import_all():
"""Import data from all nodes / data sources"""
Importer(neo4j_graph()).import_ncit()
Importer(neo4j_graph()).import_node_attributes(
PdcImporter.read_data_dictionary())
Importer(neo4j_graph()).import_node_attributes(
GdcImporter.read_data_dictionary())
Importer(neo4j_graph()).import_harmonized_attributes(
CrdcHImporter.read_harmonized_attributes())
Importer(neo4j_graph()).import_ncit_mapping(
GdcImporter.read_ncit_mappings(), 'GDC')
Importer(neo4j_graph()).import_ncit_mapping(
GdcImporter.read_ncit_mappings(), 'PDC')
"""CCDH Concept References: classes and endpoints"""
from fastapi import Request
from ccdh.api.cache import cache
from starlette.responses import StreamingResponse
from tccm_api.routers import concept_reference
from ccdh.api.routers.mappings import generate_sssom_tsv
from ccdh.api.routers.models import MappingSet
from ccdh.config import neo4j_graph
from ccdh.db.mdr_graph import MdrGraph
# TODO: Architecturally, why is 'concept_reference' in TCCM-API when so much else
# ...is in CCDH terminology service? What is the logic behind what is and isn't
# ...in TCCM? - joeflack4 2021/10/27
router = concept_reference.router
mdr_graph = MdrGraph(neo4j_graph())
@router.get(
'/{curie}/mappings',
description=
'An SSSOM TSV file depending on request headers, otherwise a list of mappings',
response_model=MappingSet)
@cache()
def get_concept_reference_mappings(curie: str, request: Request):
"""Get concept reference mappings"""
mapping_set = mdr_graph.find_mappings_of_concept_reference(curie)
if request.headers['accept'] == 'text/tab-separated-values+sssom':
return StreamingResponse(generate_sssom_tsv(
MappingSet.parse_obj(mapping_set.__dict__)),
media_type='text/tab-separated-values+sssom')
class_values = standard_class_dict.values() # dict_values
harmonized_attributes = {}
for cls in class_values:
for attribute in cls.get('attributes', {}).values():
key = f'{model_name}.{cls["name"]}.{attribute["name"]}'
harmonized_attribute = {
'system': model_name,
'entity': cls["name"],
'attribute': attribute["name"],
'definition': attribute["description"],
'node_attributes': []
}
for mapping in mapping_types:
if mapping in attribute:
for m in attribute[mapping]:
# TODO: Shouldn't exact_mapping be nested within node_attributes or
# ...node_attributes/mappings?= instead? (updated here and in
# ...Importer.read_harmonized_attribute()
harmonized_attribute['node_attributes'].append(m)
harmonized_attributes[key] = harmonized_attribute
logger.info("Parsed the content in the CCDH Model YAML")
return harmonized_attributes
if __name__ == '__main__':
from ccdh.importers.importer import Importer
Importer(neo4j_graph()).import_harmonized_attributes(
CrdcHImporter.read_harmonized_attributes())
print(
f'GDC data dictionary saved to \n{jsonfile}\nand linked to \n{GDC_JSON_FILE}'
)
@staticmethod
def read_ncit_mappings():
"""Read mappings from NCIT"""
gdc_ncit_map = {}
gdc_ncit_file = GDC_MAPING_DIR / 'current.csv'
with open(gdc_ncit_file, 'r') as csvfile:
reader = csv.reader(csvfile)
next(reader)
for row in reader:
target_code = row[3]
if target_code not in gdc_ncit_map:
gdc_ncit_map[target_code] = {}
gdc_ncit_map[target_code][row[4]] = row
return gdc_ncit_map
if __name__ == '__main__':
# A. If just need update dictionary
GdcImporter.update_data_dictionary()
# B. If need debug importer
from ccdh.importers.importer import Importer
# Importer(neo4j_graph()).import_node_attributes(GdcImporter.read_data_dictionary())
Importer(neo4j_graph()).import_ncit_mapping(
GdcImporter.read_ncit_mappings(), 'GDC')
Importer(neo4j_graph()).import_ncit_mapping(
GdcImporter.read_ncit_mappings(), 'PDC')