def do_annotation(s, f, q):
# This will probably stay hardcoded
TEI_data = "http://shelleygodwinarchive.org/tei/"
libraries = ["ox/", "bl/"]
format = "jsonld"
hl_simple_pre = '_#_'
hl_simple_post = '_#_'
annotations = []
# Create a UUID for this iteration
uid = str(uuid.uuid4())
# get solr fields from request
fields = f.split(",")
fqs = []
if len(fields) > 0:
fqs = fields[1:]
fqs = [f + ":" + q for f in fqs]
# send query, filter by fields (AND only at the moment), return highlights on text field.
# text field is the only one that keeps all the text with all the whitespace
# so all the positions are extracted from there.
#
# hl_fragsize=0 is important to calculate correct positions that SC will understand.
response = s.raw_query(q=fields[0] + ":" + q,
fl='shelfmark,id',
fq=fqs,
wt='json',
start=0,
rows=9999,
hl='true',
hl_fl="text",
hl_fragsize='0',
hl_simple_pre=hl_simple_pre,
hl_simple_post=hl_simple_post)
r = json.loads(response)
# Find all the highlights and make them into OA annotations
for i, TEI_id in enumerate(r["highlighting"]):
hl = r["highlighting"][TEI_id]["text"][0]
for library in libraries:
annotations += annotator.oa_annotations(
hl, TEI_id, TEI_data + library, uid + ":-" + str(i),
hl_simple_pre, hl_simple_post, format)
# prepare a headless JSON
final = {}
if format == "jsonld":
final["@context"] = "http://mith.um.edu/sc/context.json"
final["@graph"] = []
for anno in annotations:
if format == "jsonld":
final["@graph"].append(anno)
else:
for a in anno:
final[a] = anno[a]
return jsonify(final)
def do_annotation(s, f, q):
# This will probably stay hardcoded
TEI_data = "http://shelleygodwinarchive.org/tei/"
libraries = ["ox/", "bl/"]
format = "jsonld"
hl_simple_pre = '_#_'
hl_simple_post = '_#_'
annotations = []
# Create a UUID for this iteration
uid = str(uuid.uuid4())
# get solr fields from request
fields = f.split(",")
fqs = []
if len(fields) > 0:
fqs = fields[1:]
fqs = [f+":"+q for f in fqs]
# send query, filter by fields (AND only at the moment), return highlights on text field.
# text field is the only one that keeps all the text with all the whitespace
# so all the positions are extracted from there.
#
# hl_fragsize=0 is important to calculate correct positions that SC will understand.
response = s.raw_query(q=fields[0]+":"+q,
fl='shelfmark,id',
fq=fqs,
wt='json',
start=0,
rows=9999,
hl='true',
hl_fl="text",
hl_fragsize='0',
hl_simple_pre=hl_simple_pre,
hl_simple_post=hl_simple_post)
r = json.loads(response)
# Find all the highlights and make them into OA annotations
for i, TEI_id in enumerate(r["highlighting"]):
hl = r["highlighting"][TEI_id]["text"][0]
for library in libraries:
annotations += annotator.oa_annotations(hl, TEI_id, TEI_data + library, uid+":-"+str(i), hl_simple_pre, hl_simple_post, format)
# prepare a headless JSON
final = {}
if format == "jsonld":
final["@context"] = "http://mith.um.edu/sc/context.json"
final["@graph"] = []
for anno in annotations:
if format == "jsonld":
final["@graph"].append(anno)
else:
for a in anno:
final[a] = anno[a]
return jsonify(final)