def getqid():
print(request.form.get("buttom"))
pprint.pprint(request.form)
if request.form.get("button") == "PMID":
qid = wdi_helpers.PublicationHelper(request.form.get("refid"), id_type="pmid",source="europepmc").get_or_create(login)
elif request.form.get("button") == "DOI":
qid = wdi_helpers.PublicationHelper(request.form.get("refid"), id_type="doi", source="crossref").get_or_create(login)
return render_template("resolve.html", wdid=qid)
def create_reference(source_str, evidence_level, login):
"""
Reference is:
curator: Cancer Biomarkers database
retrieved: date
stated in: links to pmid items
no reference URL
"""
reference = [
wdi_core.WDItemID(ITEMS['Cancer Biomarkers database'],
PROPS['curator'],
is_reference=True)
]
t = strftime("+%Y-%m-%dT00:00:00Z", gmtime())
reference.append(
wdi_core.WDTime(t, prop_nr=PROPS['retrieved'], is_reference=True))
for source in source_str.split(";"):
if source.startswith("PMID:"):
qid, _, success = wdi_helpers.PublicationHelper(
source.replace("PMID:", ""),
id_type="pmid",
source="europepmc").get_or_create(login)
if success:
reference.append(
wdi_core.WDItemID(qid,
PROPS['stated in'],
is_reference=True))
elif source in source_map:
reference.append(
wdi_core.WDItemID(source_map[source],
PROPS['stated in'],
is_reference=True))
else:
print("unknown source: {}".format(source))
return reference
def create_articles(pmids: Set[str],
login: object,
write: bool = True) -> Dict[str, str]:
"""
Given a list of pmids, make article items for each
:param pmids: list of pmids
:param login: wdi_core login instance
:param write: actually perform write
:return: map pmid -> wdid
"""
pmid_map = dict()
for pmid in pmids:
p = wdi_helpers.PublicationHelper(pmid.replace("PMID:", ""),
id_type="pmid",
source="europepmc")
if write:
try:
pmid_wdid, _, success = p.get_or_create(login)
if success:
pmid_map[pmid] = pmid_wdid
except Exception as e:
print("Error creating article pmid: {}, error: {}".format(
pmid, e))
continue
else:
pmid_map[pmid] = 'Q1'
return pmid_map
def run(self):
wd_genes = defaultdict(list)
wd_diseases = defaultdict(list)
gdrs = list(self.gwas_catalog.data)
print("Get or create references")
pmids = set([x.pmid for x in gdrs])
print("Need {} pmids".format(len(pmids)))
self.pmid_qid_map = get_values("P698", pmids)
print("Found {} pmids".format(len(self.pmid_qid_map)))
for pmid in pmids - set(self.pmid_qid_map.keys()):
qid, _, success = wdi_helpers.PublicationHelper(
pmid.replace("PMID:", ""), id_type="pmid",
source="europepmc").get_or_create(self.login)
if success:
self.pmid_qid_map[pmid] = qid
print("Building relationships & references")
for gdr in tqdm(gdrs):
try:
# Retrieve Wikidata ID for this disease phenotype
doid_wdid = self.doid_wdid_map["DOID:{}".format(gdr.doid)]
except KeyError as e:
msg = "Missing DOID Disease WD Item; skipping {}".format(
gdr.doid)
print(msg)
wdi_core.WDItemEngine.log(
"ERROR",
wdi_helpers.format_msg(gdr.doid,
PROPS['Disease Ontology ID'], None,
msg, type(e)))
continue
try:
# Retrieve Wikidata ID for this gene
gene_wdid = self.gene_wdid_map[gdr.ncbi]
except KeyError as e:
msg = "Missing NCBI Gene WD Item; skipping {}".format(gdr.ncbi)
print(msg)
wdi_core.WDItemEngine.log(
"ERROR",
wdi_helpers.format_msg(gdr.ncbi, PROPS['Entrez Gene ID'],
None, msg, type(e)))
continue
try:
items = self.process_relationship(gene_wdid, doid_wdid, gdr)
except Exception as e:
print(e)
wdi_core.WDItemEngine.log(
"ERROR",
wdi_helpers.format_msg(gdr.ncbi, PROPS['Entrez Gene ID'],
None, str(e), type(e)))
continue
gdr.gene_wditem = items['gene_item']
gdr.disease_wditem = items['disease_item']
# Aggregating data to reduce wikidata updates
wd_genes[gene_wdid].append(gdr)
wd_diseases[doid_wdid].append(gdr)
print("Begin creating Wikidata Gene items with new relationships")
# Create Wikidata items for genes
for wdid, gdrs in tqdm(wd_genes.items()):
# Attach updated disease information to gene
try:
gene_wd_item = wdi_core.WDItemEngine(
wd_item_id=wdid,
data=[gdr.disease_wditem for gdr in gdrs],
domain="genes",
append_value=[PROPS["genetic association"]],
fast_run=self.fast_run,
fast_run_base_filter=self.fast_run_base_gene_filter,
fast_run_use_refs=True,
ref_handler=update_retrieved_if_new,
global_ref_mode="CUSTOM",
core_props=core_props)
wd_item = {
'item': gene_wd_item,
'record_id': gdrs[0].ncbi,
'record_prop': PROPS['Entrez Gene ID']
}
self.write_item(wd_item)
except Exception as e:
msg = "Problem Creating Gene WDItem; skipping {}".format(
gdr.ncbi)
wdi_core.WDItemEngine.log(
"ERROR",
wdi_helpers.format_msg(gdr.ncbi, PROPS['Entrez Gene ID'],
wdid, msg, type(e)))
print("Begin creating Wikidata Disease items with new relationships")
for wdid, gdrs in tqdm(wd_diseases.items()):
# Attach updated gene information to disease
try:
disease_wd_item = wdi_core.WDItemEngine(
wd_item_id=wdid,
data=[gdr.gene_wditem for gdr in gdrs],
domain="diseases",
append_value=[PROPS["genetic association"]],
fast_run=self.fast_run,
fast_run_base_filter=self.fast_run_base_disease_filter,
fast_run_use_refs=True,
ref_handler=update_retrieved_if_new,
global_ref_mode="CUSTOM",
core_props=core_props)
wd_item = {
'item': disease_wd_item,
'record_id': "DOID:{}".format(gdrs[0].doid),
'record_prop': PROPS['Disease Ontology ID']
}
self.write_item(wd_item)
except Exception as e:
msg = "Problem Creating Disease WDItem; skipping {}".format(
gdr.doid)
wdi_core.WDItemEngine.log(
"ERROR",
wdi_helpers.format_msg(gdr.doid,
PROPS['Disease Ontology ID'], wdid,
msg, type(e)))
from src.local import WDUSER, WDPASS
from wikidataintegrator import wdi_core, wdi_login, wdi_helpers
from tqdm import tqdm
from src.utils import *
folder_for_errors = sys.argv[1]
assert (folder_for_errors
), "You need to pass the folder for errors used by prepare_files.py"
doi_file = folder_for_errors + "/references_absent_in_wikidata.txt"
with open(doi_file, "r") as f:
references = f.readlines()
references_still_absent = []
login_instance = wdi_login.WDLogin(user=WDUSER, pwd=WDPASS)
for reference in tqdm(references):
doi = reference.replace("DOI=", "").replace("\n", "")
tqdm.write(f"Adding article with DOI = {doi}")
print(doi)
wdi_publication_helper = wdi_helpers.PublicationHelper(ext_id=doi,
id_type="doi",
source="crossref")
wdi_result = wdi_publication_helper.get_or_create(login_instance)
print(wdi_result)
if wdi_result[0] == None:
print("Not added to Wikidata.")
references_still_absent.append(reference.strip())
write_list(doi_file, references_still_absent)
def run_one(pathway_id, retrieved, fast_run, write, login, temp):
print(pathway_id)
pathway_reference = create_reference(pathway_id, retrieved)
prep = dict()
prep = get_PathwayElements(pathway=pathway_id,
datatype="Metabolite",
temp=temp,
prep=prep)
prep = get_PathwayElements(pathway=pathway_id,
datatype="GeneProduct",
temp=temp,
prep=prep)
# P703 = found in taxon, Q15978631 = "H**o sapiens"
prep["P703"] = [
wdi_core.WDItemID(value="Q15978631",
prop_nr='P703',
references=[copy.deepcopy(pathway_reference)])
]
query = """
PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
PREFIX gpml: <http://vocabularies.wikipathways.org/gpml#>
PREFIX dcterms: <http://purl.org/dc/terms/>
SELECT DISTINCT ?pathway ?pwId ?pwLabel ?description
WHERE {
VALUES ?pwId {"""
query += "\"" + pathway_id + "\"^^xsd:string}"
query += """
?pathway a wp:Pathway ;
dc:title ?pwLabel ;
dcterms:description ?description ;
dcterms:identifier ?pwId ;
<http://vocabularies.wikipathways.org/wp#isAbout> ?details ;
wp:organismName "H**o sapiens"^^xsd:string .
}"""
qres3 = temp.query(query)
for row in qres3:
#pathway_iri = str(row[0])
pw_id = str(row[1])
pw_label = str(row[2])
description = str(row[3])
## clean up descriptions
description = re.sub(r'https?:\/\/.*[\s\r\n]', '', description)
description = description.replace('\n', ' ').replace(
'\r', ' ').replace('\'\'\'',
'').replace('\'\'',
'').replace('[',
'').replace(']', '')
description = description.replace(
'Proteins on this pathway have targeted assays available via the Portal',
'')
description = (description[:246] +
'...') if len(description) > 246 else description
description = 'biological pathway in human' if len(
description) < 20 else description
# P31 = instance of
prep["P31"] = [
wdi_core.WDItemID(value="Q4915012",
prop_nr="P31",
references=[copy.deepcopy(pathway_reference)])
]
prep["P1476"] = [
wdi_core.WDMonolingualText(
value=pw_label,
prop_nr="P1476",
references=[copy.deepcopy(pathway_reference)])
]
# P2410 = WikiPathways ID
prep["P2410"] = [
wdi_core.WDString(pathway_id,
prop_nr='P2410',
references=[copy.deepcopy(pathway_reference)])
]
# P2888 = exact match
prep["P2888"] = [
wdi_core.WDUrl("http://identifiers.org/wikipathways/" + pw_id,
prop_nr='P2888',
references=[copy.deepcopy(pathway_reference)])
]
query = """
PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
PREFIX dcterms: <http://purl.org/dc/terms/>
select ?pubmed
WHERE {
?pubmed a wp:PublicationReference ;
dcterms:isPartOf <"""
query += str(row[0])
query += """> .}
"""
qres4 = temp.query(query)
p = re.compile('^[0-9]+$')
for pubmed_result in qres4:
pmid = str(pubmed_result[0]).replace(
"http://identifiers.org/pubmed/", "")
print(pmid)
m = p.match(pmid)
if not m:
pmid_qid, _, _ = wdi_helpers.PublicationHelper(
pmid, id_type="doi",
source="crossref").get_or_create(login if write else None)
else:
pmid_qid, _, _ = wdi_helpers.PublicationHelper(
pmid.replace("PMID:", ""),
id_type="pmid",
source="europepmc").get_or_create(login if write else None)
if pmid_qid is None:
return panic(pathway_id, "not found: {}".format(pmid), "pmid")
else:
if 'P2860' not in prep.keys():
prep["P2860"] = []
print(pmid_qid)
prep['P2860'].append(
wdi_core.WDItemID(
value=str(pmid_qid),
prop_nr='P2860',
references=[copy.deepcopy(pathway_reference)]))
author_query = """
PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
SELECT ?author ?authorName ?authorHomepage ?authorQIRI
WHERE {
<http://identifiers.org/wikipathways/""" + pathway_id + """> dc:creator ?author .
?author a foaf:Person ;
foaf:name ?authorName ;
foaf:homepage ?authorHomepage .
OPTIONAL { ?author owl:sameAs ?authorQIRI . }
}
"""
author_query_res = temp.query(author_query)
prep["P2093"] = []
prep["P50"] = []
for row in author_query_res:
author_name = str(row[1])
print("author_name")
print(author_name)
author_homepage = str(row[2])
print("author_homepage")
print(author_homepage)
# P2093 = author name string
author_url_qualifier = wdi_core.WDString(value=author_homepage,
prop_nr="P2699",
is_qualifier=True)
prep["P2093"].append(
wdi_core.WDString(
author_name,
prop_nr='P2093',
qualifiers=[copy.deepcopy(author_url_qualifier)],
references=[copy.deepcopy(pathway_reference)]))
if row[3] != None: # only if row[3] exists (authorQIRI)
author_iri = str(row[0])
author_name = str(row[1])
print("author_name")
print(author_name)
author_qiri = str(row[3])
if ("https://www.wikidata.org/wiki/" in author_qiri):
author_qid = author_qiri.replace(
"https://www.wikidata.org/wiki/", "")
if ("http://www.wikidata.org/entity/" in author_qiri):
author_qid = author_qiri.replace(
"http://www.wikidata.org/entity/", "")
print("author_qid")
print(author_qid)
# P50 = author
prep["P50"].append(
wdi_core.WDItemID(
author_qid,
prop_nr='P50',
references=[copy.deepcopy(pathway_reference)]))
disease_ontology_query = """
PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
PREFIX dcterms: <http://purl.org/dc/terms/>
SELECT ?diseaseOntologyTerm
WHERE {
?pathwayRDF wp:diseaseOntologyTag ?diseaseOntologyTerm ;
foaf:page ?pathway ;
dcterms:identifier \"""" + pathway_id + """\"^^xsd:string .
}
"""
disease_ontology_query_res = temp.query(disease_ontology_query)
prep["P1050"] = []
for row in disease_ontology_query_res:
disease_ontology_iri = str(row[0])
doid = disease_ontology_iri.replace(
"http://purl.obolibrary.org/obo/DOID_", "DOID:")
print("doid")
print(doid)
# P1050 = medical condition
if doid_qid.get(doid) != None: #skip if qid is missing
prep["P1050"].append(
wdi_core.WDItemID(
doid_qid[doid],
prop_nr='P1050',
references=[copy.deepcopy(pathway_reference)]))
pw_ontology_query = """
PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
PREFIX dcterms: <http://purl.org/dc/terms/>
SELECT ?pwOntologyTerm
WHERE {
?pathwayRDF wp:pathwayOntologyTag ?pwOntologyTerm ;
foaf:page ?pathway ;
dcterms:identifier \"""" + pathway_id + """\"^^xsd:string .
}
"""
pw_ontology_query_res = temp.query(pw_ontology_query)
prep["P921"] = []
for row in pw_ontology_query_res:
pw_ontology_iri = str(row[0])
poid = pw_ontology_iri.replace(
"http://purl.obolibrary.org/obo/PW_", "PW:")
print("poid")
print(poid)
# P921 = main subject
if poid_qid.get(poid) != None: #skip if qid is missing
prep["P921"].append(
wdi_core.WDItemID(
poid_qid[poid],
prop_nr='P921',
references=[copy.deepcopy(pathway_reference)]))
#TODO: Propose Cell Type Ontology ID as new property, add release item, associate terms with WD items.
#cell_type_ontology_query = """
# PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
# PREFIX dcterms: <http://purl.org/dc/terms/>
# SELECT ?cellTypeOntologyTerm
# WHERE {
# ?pathwayRDF wp:cellTypeOntologyTag ?cellTypeOntologyTerm ;
# foaf:page ?pathway ;
# dcterms:identifier \"""" + pathway_id + """\"^^xsd:string .
# }
# """
#cell_type_ontology_query_res = temp.query(cell_type_ontology_query)
#prep["P927"] = []
#for row in cell_type_ontology_query_res:
# cell_type_ontology_iri = str(row[0])
# ctoid = cell_type_ontology_iri.replace("http://purl.obolibrary.org/obo/CL_", "CL:")
# print("ctoid")
# print(ctoid)
# P927 = anatomical location
# prep["P927"].append(wdi_core.WDItem(qid[ctoid], prop_nr='P927', references=[copy.deepcopy(pathway_reference)]))
data2add = []
for key in prep.keys():
for statement in prep[key]:
data2add.append(statement)
print(statement.prop_nr, statement.value)
wdPage = wdi_core.WDItemEngine(
data=data2add,
fast_run=fast_run,
fast_run_base_filter=fast_run_base_filter,
fast_run_use_refs=True,
ref_handler=update_retrieved_if_new_multiple_refs,
core_props=core_props)
wdPage.set_label(pw_label, lang="en")
wdPage.set_description(description, lang="en")
try_write(wdPage,
record_id=pathway_id,
record_prop=PROPS['Wikipathways ID'],
edit_summary="Updated a Wikipathways pathway",
login=login,
write=write)
def make_statements_from_evidence(variant_id, evidence_item, login, write):
ss = []
## determination method and rating qualifiers
ev_quals = [
wdi_core.WDItemID(value=EVIDENCE_LEVEL[str(
evidence_item["evidence_level"])],
prop_nr=PROPS['determination method'],
is_qualifier=True),
wdi_core.WDItemID(value=TRUST_RATING[str(evidence_item["rating"])],
prop_nr=PROPS['rating'],
is_qualifier=True)
]
## Disease
if not evidence_item["disease"]["doid"]:
panic(variant_id, "", "no disease")
return []
doid = "DOID:" + evidence_item["disease"]["doid"]
if doid not in DO_QID_MAP:
panic(variant_id, doid, "disease")
return []
disease = DO_QID_MAP[doid]
## Drugs
drug_qids = []
for drug in evidence_item["drugs"]:
drug_label = drug['name'].lower()
if drug_label not in DRUGLABEL_QID_MAP:
panic(variant_id, drug_label, "drug")
return []
drug_qids.append(DRUGLABEL_QID_MAP[drug_label])
dit = evidence_item['drug_interaction_type']
if dit == "Combination":
# make this a drug therapy combination item instead!!
drug_qids = [
DrugCombo(drug_qids).get_or_create(login if write else None)
]
elif dit == "Substitutes":
# see "Drug Interaction Type" in https://civicdb.org/help/evidence/overview
# we're going to add a statement for each drug
pass
elif dit == "Sequential":
# we have no wikidata way of specying this for now
panic(variant_id, "drug_interaction_type: {}".format(dit), "drug")
return []
elif dit:
panic(variant_id, "drug_interaction_type: {}".format(dit), "drug")
return []
## Reference
pmid = evidence_item["source"]["pubmed_id"]
pmid_qid, _, _ = wdi_helpers.PublicationHelper(
pmid.replace("PMID:", ""), id_type="pmid",
source="europepmc").get_or_create(login if write else None)
if not pmid_qid:
panic(variant_id, "not found: {}".format(pmid), "pmid")
return []
refStatedIn = wdi_core.WDItemID(value=pmid_qid,
prop_nr=PROPS['stated in'],
is_reference=True)
timeStringNow = retrieved.strftime("+%Y-%m-%dT00:00:00Z")
refRetrieved = wdi_core.WDTime(timeStringNow,
prop_nr=PROPS['retrieved'],
is_reference=True)
url = "https://civic.genome.wustl.edu/links/evidence/" + str(
evidence_item['id'])
refReferenceURL = wdi_core.WDUrl(url,
prop_nr=PROPS['reference URL'],
is_reference=True)
refCurator = wdi_core.WDItemID(value=ITEMS['CIViC database'],
prop_nr=PROPS['curator'],
is_reference=True)
evidence_reference = [
refCurator, refRetrieved, refReferenceURL, refStatedIn
]
## "disputed by" qualifer that can be added onto the qualifiers
refDisputedBy = wdi_core.WDItemID(value=pmid_qid,
prop_nr=PROPS['statement disputed by'],
is_qualifier=True)
# positive/negative therapeutic predictor
if evidence_item["evidence_type"] == "Predictive":
if evidence_item["clinical_significance"] == "Sensitivity/Response":
prop = PROPS['positive therapeutic predictor']
elif evidence_item["clinical_significance"] == "Resistance":
prop = PROPS['negative therapeutic predictor']
else:
return []
ev_quals.append(
wdi_core.WDItemID(disease,
PROPS['medical condition treated'],
is_qualifier=True))
if evidence_item["evidence_direction"] == "Does Not Support":
ev_quals.append(refDisputedBy)
for drug_qid in drug_qids:
ss.append(
wdi_core.WDItemID(drug_qid,
prop,
references=[evidence_reference],
qualifiers=ev_quals))
# positive/negative Diagnostic predictor
if evidence_item["evidence_type"] == "Diagnostic":
if evidence_item["clinical_significance"] == "Positive":
prop = PROPS['positive diagnostic predictor']
elif evidence_item["clinical_significance"] == "Negative":
prop = PROPS['negative diagnostic predictor']
else:
return []
if evidence_item["evidence_direction"] == "Does Not Support":
ev_quals.append(refDisputedBy)
ss.append(
wdi_core.WDItemID(disease,
prop,
references=[evidence_reference],
qualifiers=ev_quals))
# positive/negative Prognostic predictor
if evidence_item["evidence_type"] == "Prognostic":
if evidence_item["clinical_significance"] in {
"Better Outcome", "Good Outcome"
}:
prop = PROPS['positive prognostic predictor']
elif evidence_item["clinical_significance"] == "Poor Outcome":
prop = PROPS['negative prognostic predictor']
else:
return []
if evidence_item["evidence_direction"] == "Does Not Support":
ev_quals.append(refDisputedBy)
ss.append(
wdi_core.WDItemID(disease,
prop,
references=[evidence_reference],
qualifiers=ev_quals))
return ss
def run_one(pathway_id, retrieved, fast_run, write, login, temp):
print(pathway_id)
pathway_reference = create_reference(pathway_id, retrieved)
prep = dict()
prep = get_PathwayElements(pathway=pathway_id,
datatype="Metabolite",
temp=temp,
prep=prep)
prep = get_PathwayElements(pathway=pathway_id,
datatype="GeneProduct",
temp=temp,
prep=prep)
# P703 = found in taxon, Q15978631 = "H**o sapiens"
prep["P703"] = [
wdi_core.WDItemID(value="Q15978631",
prop_nr='P703',
references=[copy.deepcopy(pathway_reference)])
]
query = """
PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
PREFIX gpml: <http://vocabularies.wikipathways.org/gpml#>
PREFIX dcterms: <http://purl.org/dc/terms/>
SELECT DISTINCT ?pathway ?pwId ?pwLabel
WHERE {
VALUES ?pwId {"""
query += "\"" + pathway_id + "\"^^xsd:string}"
query += """
?pathway a wp:Pathway ;
dc:title ?pwLabel ;
dcterms:identifier ?pwId ;
<http://vocabularies.wikipathways.org/wp#isAbout> ?details ;
wp:organismName "H**o sapiens"^^xsd:string .
}"""
# print(query)
qres3 = temp.query(query)
for row in qres3:
print(row[1])
print(str(row[2]))
# P31 = instance of
prep["P31"] = [
wdi_core.WDItemID(value="Q4915012",
prop_nr="P31",
references=[copy.deepcopy(pathway_reference)])
]
# P2410 = WikiPathways ID
prep["P2410"] = [
wdi_core.WDString(pathway_id,
prop_nr='P2410',
references=[copy.deepcopy(pathway_reference)])
]
# P2888 = exact match
prep["P2888"] = [
wdi_core.WDUrl("http://identifiers.org/wikipathways/" +
str(row[1]),
prop_nr='P2888',
references=[copy.deepcopy(pathway_reference)])
]
query = """
PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
PREFIX dcterms: <http://purl.org/dc/terms/>
select ?pubmed
WHERE {
?pubmed a wp:PublicationReference ;
dcterms:isPartOf <"""
query += str(row[0])
query += """> .}
"""
qres4 = temp.query(query)
print(query)
for pubmed_result in qres4:
pprint.pprint(pubmed_result)
pmid = str(pubmed_result[0]).replace(
"http://identifiers.org/pubmed/", "")
print(pmid)
pmid_qid, _, _ = wdi_helpers.PublicationHelper(
pmid.replace("PMID:", ""), id_type="pmid",
source="europepmc").get_or_create(login if write else None)
if pmid_qid is None:
return panic(pathway_id, "not found: {}".format(pmid), "pmid")
else:
print(pmid_qid)
if 'P2860' not in prep.keys():
prep["P2860"] = []
prep['P2860'].append(
wdi_core.WDItemID(
value=str(pmid_qid),
prop_nr='P2860',
references=[copy.deepcopy(pathway_reference)]))
data2add = []
for key in prep.keys():
for statement in prep[key]:
data2add.append(statement)
print(statement.prop_nr, statement.value)
pprint.pprint(data2add)
wdPage = wdi_core.WDItemEngine(
data=data2add,
domain="pathways",
fast_run=fast_run,
item_name=row.pwLabel,
fast_run_base_filter=fast_run_base_filter,
fast_run_use_refs=True,
ref_handler=update_retrieved_if_new_multiple_refs,
core_props=core_props)
wdPage.set_label(str(row[2]), lang="en")
wdPage.set_description("biological pathway in human", lang="en")
try_write(wdPage,
record_id=pathway_id,
record_prop=PROPS['Wikipathways ID'],
edit_summary="Updated a Wikipathways pathway",
login=login,
write=write)