def mongo_writer(client, pipeline, job, batch, pipeline_config: config.PipelineConfig, val, doc, type):
db = client[util.mongo_db]
obj = {
"pipeline_type": type,
"pipeline_id": pipeline,
"job_id": job,
"batch": batch,
"owner": pipeline_config.owner,
"sentence": val.sentence,
"report_type": doc["report_type"],
"nlpql_feature": pipeline_config.name,
"inserted_date": datetime.datetime.now(),
"report_id": doc["report_id"],
"subject": doc["subject"],
"report_date": doc["report_date"],
"section": "",
"concept_code": pipeline_config.concept_code,
"term": val.text,
"text": val.text,
"start": val.start,
"end": val.end,
"label": val.label,
"description": val.description,
"phenotype_final": False
}
inserted = config.insert_pipeline_results(pipeline_config, db, obj)
return inserted
def mongo_writer(client, pipeline, job, batch, pipeline_config, term, doc,
type):
db = client[util.mongo_db]
obj = {
"pipeline_type": type,
"pipeline_id": pipeline,
"job_id": job,
"batch": batch,
"owner": pipeline_config.owner,
"sentence": term.sentence,
"report_type": doc["report_type"],
"nlpql_feature": pipeline_config.name,
"inserted_date": datetime.datetime.now(),
"report_id": doc["report_id"],
"subject": doc["subject"],
"report_date": doc["report_date"],
"section": term.section,
"term": term.term,
"start": term.start,
"end": term.end,
"concept_code": pipeline_config.concept_code,
"negation": term.negex,
"temporality": term.temporality,
"experiencer": term.experiencer,
"phenotype_final": False
}
inserted = config.insert_pipeline_results(pipeline_config, db, obj)
return inserted
def mongo_writer(client, pipeline, job, batch, pipeline_config, val, doc, p_type):
db = client[util.mongo_db]
obj = {
"pipeline_type": p_type,
"pipeline_id": pipeline,
"job_id": job,
"batch": batch,
"owner": pipeline_config.owner,
"sentence": val.sentence,
"report_type": doc["report_type"],
"nlpql_feature": pipeline_config.name,
"inserted_date": datetime.datetime.now(),
"report_id": doc["report_id"],
"subject": doc["subject"],
"report_date": doc["report_date"],
"section": "",
"concept_code": pipeline_config.concept_code,
"term": val.text,
"text": val.text,
"lemma": val.lemma,
"pos": val.pos,
"tag": val.tag,
"dep": val.dep,
"shape": val.shape,
"is_alpha": val.is_alpha,
"is_stop": val.is_stop,
"description": val.description,
"phenotype_final": False
}
inserted = config.insert_pipeline_results(pipeline_config, db, obj)
return inserted
def pipeline_mongo_writer(client,
pipeline_id,
pipeline_type,
job,
batch,
p_config: pipeline_config.PipelineConfig,
doc,
data_fields: dict,
prefix: str = '',
phenotype_final: bool = False):
db = client[util.mongo_db]
if not data_fields:
print('must have additional data fields')
return None
if not p_config:
print('must have pipeline config')
return None
data_fields["pipeline_type"] = pipeline_type
data_fields["pipeline_id"] = pipeline_id
data_fields["job_id"] = job
data_fields["batch"] = batch
data_fields["owner"] = p_config.owner
data_fields["nlpql_feature"] = (prefix + p_config.name)
data_fields["inserted_date"] = datetime.datetime.now()
data_fields["concept_code"] = p_config.concept_code
data_fields["concept_code_system"] = p_config.concept_code_system
data_fields["phenotype_final"] = (phenotype_final or p_config.final)
if doc:
data_fields["report_id"] = doc[util.solr_report_id_field]
data_fields["subject"] = doc[util.solr_subject_field]
data_fields["report_date"] = doc[util.solr_report_date_field]
data_fields["report_type"] = doc[util.solr_report_type_field]
data_fields["source"] = doc[util.solr_source_field]
data_fields["solr_id"] = doc[util.solr_id_field]
else:
for df in doc_fields:
if df not in data_fields:
data_fields[df] = ''
inserted = config.insert_pipeline_results(p_config, db, data_fields)
return inserted
def mongo_writer(client, pipeline, job, batch,
pipeline_config: config.PipelineConfig, meas: Measurement,
doc, type):
db = client[util.mongo_db]
value = meas['X']
obj = {
"pipeline_type": type,
"pipeline_id": pipeline,
"job_id": job,
"batch": batch,
"owner": pipeline_config.owner,
"sentence": meas.sentence,
"report_type": doc["report_type"],
"nlpql_feature": pipeline_config.name,
"inserted_date": datetime.datetime.now(),
"report_id": doc["report_id"],
"subject": doc["subject"],
"report_date": doc["report_date"],
"section": "",
"concept_code": pipeline_config.concept_code,
"text": meas.text,
"start": meas.start,
"value": value,
"end": meas.end,
"term": meas.subject,
"dimension_X": meas.X,
"dimension_Y": meas.Y,
"dimension_Z": meas.Z,
"units": meas.units,
"location": meas.location,
"condition": meas.condition,
"value1": meas.value1,
"value2": meas.value2,
"temporality": meas.temporality,
"phenotype_final": False
}
inserted = config.insert_pipeline_results(pipeline_config, db, obj)
return inserted
def pipeline_mongo_writer(client, pipeline_id, pipeline_type, job, batch,
p_config: pipeline_config.PipelineConfig, doc,
data_fields: dict):
db = client[util.mongo_db]
data_fields["pipeline_type"] = pipeline_type
data_fields["pipeline_id"] = pipeline_id
data_fields["job_id"] = job
data_fields["batch"] = batch
data_fields["owner"] = p_config.owner
data_fields["nlpql_feature"] = p_config.name
data_fields["inserted_date"] = datetime.datetime.now()
data_fields["report_id"] = doc[util.solr_report_id_field]
data_fields["subject"] = doc[util.solr_subject_field]
data_fields["report_date"] = doc[util.solr_report_date_field]
data_fields["concept_code"] = p_config.concept_code
data_fields["phenotype_final"] = False
inserted = config.insert_pipeline_results(p_config, db, data_fields)
return inserted
def pipeline_mongo_writer(client,
pipeline_id,
pipeline_type,
job,
batch,
p_config: pipeline_config.PipelineConfig,
doc,
data_fields: dict,
prefix: str = '',
phenotype_final: bool = False):
db = client[util.mongo_db]
if not data_fields:
log('must have additional data fields', ERROR)
return None
if not p_config:
log('must have pipeline config', ERROR)
return None
# log('writing results...', DEBUG)
data_fields["pipeline_type"] = pipeline_type
data_fields["pipeline_id"] = int(pipeline_id)
data_fields["job_id"] = int(job)
data_fields["batch"] = batch
data_fields["owner"] = p_config.owner
data_fields["nlpql_feature"] = (prefix + p_config.name)
data_fields["inserted_date"] = datetime.datetime.now()
data_fields["concept_code"] = p_config.concept_code
data_fields["concept_code_system"] = p_config.concept_code_system
data_fields["phenotype_final"] = (phenotype_final or p_config.final)
data_fields["display_name"] = p_config.display_name
if doc:
data_fields["report_id"] = doc[util.solr_report_id_field]
data_fields["subject"] = doc[util.solr_subject_field]
data_fields["report_date"] = doc[util.solr_report_date_field]
data_fields["report_type"] = doc[util.solr_report_type_field]
data_fields["source"] = doc[util.solr_source_field]
data_fields["solr_id"] = doc[util.solr_id_field]
else:
for df in doc_fields:
if df not in data_fields:
data_fields[df] = ''
highlight_fields = [
'term', 'text', 'value', 'units', 'word', 'highlight', 'highlights'
]
if "result_display" not in data_fields:
s = data_fields.get('start')
e = data_fields.get('end')
if not s:
s = 0
if not e:
e = 0
highlights = []
for h in highlight_fields:
txt = data_fields.get(h, '')
if len(txt) > 0:
highlights.append(txt)
break
data_fields["result_display"] = {
"date": data_fields.get('report_date'),
"result_content": data_fields.get('sentence'),
"highlights": highlights,
"sentence": data_fields.get('sentence'),
'start': [s],
'end': [e]
}
else:
display = data_fields.get('result_display')
highlights = display.get("highlights", list())
if len(highlights) == 0:
highlights = []
for h in highlight_fields:
txt = data_fields.get(h, '')
if len(txt) > 0:
highlights.append(txt)
break
data_fields['result_display']['highlights'] = highlights
inserted = config.insert_pipeline_results(p_config, db, data_fields)
log(
'(job={}; pipeline={}) inserted into mongodb {}'.format(
job, pipeline_id, repr(inserted.inserted_id)), DEBUG)
return inserted
def pipeline_mongo_writer(client,
pipeline_id,
pipeline_type,
job,
batch,
p_config: pipeline_config.PipelineConfig,
doc,
data_fields: dict,
prefix: str = '',
phenotype_final: bool = False):
db = client[util.mongo_db]
if not data_fields:
print('must have additional data fields')
return None
if not p_config:
print('must have pipeline config')
return None
data_fields["pipeline_type"] = pipeline_type
data_fields["pipeline_id"] = pipeline_id
data_fields["job_id"] = job
data_fields["batch"] = batch
data_fields["owner"] = p_config.owner
data_fields["nlpql_feature"] = (prefix + p_config.name)
data_fields["inserted_date"] = datetime.datetime.now()
data_fields["concept_code"] = p_config.concept_code
data_fields["concept_code_system"] = p_config.concept_code_system
data_fields["phenotype_final"] = (phenotype_final or p_config.final)
data_fields["display_name"] = p_config.display_name
if doc:
data_fields["report_id"] = doc[util.solr_report_id_field]
data_fields["subject"] = doc[util.solr_subject_field]
data_fields["report_date"] = doc[util.solr_report_date_field]
data_fields["report_type"] = doc[util.solr_report_type_field]
data_fields["source"] = doc[util.solr_source_field]
data_fields["solr_id"] = doc[util.solr_id_field]
else:
for df in doc_fields:
if df not in data_fields:
data_fields[df] = ''
if "result_display" not in data_fields:
s = data_fields.get('start')
e = data_fields.get('end')
if not s:
s = 0
if not e:
e = 0
highlights = []
txt = data_fields.get('text')
if txt:
highlights = [txt]
data_fields["result_display"] = {
"date": data_fields.get('report_date'),
"result_content": data_fields.get('sentence'),
"highlights": highlights,
"sentence": data_fields.get('sentence'),
'start': [s],
'end': [e]
}
inserted = config.insert_pipeline_results(p_config, db, data_fields)
return inserted
