# %%
import json
import csv
# IMPORT MASTER FILE
with open('.dat/man_draft.json', 'r') as in_file:
data = json.load(in_file)
with open('entities_in.csv', 'r') as csv_in_1:
reader = csv.DictReader(csv_in_1)
ent_csv_in = [row for row in reader]
with open('relations_in.csv', 'r') as csv_in_2:
reader = csv.DictReader(csv_in_2)
rel_csv_in = [row for row in reader]
# %%
# Consistency check
entity_rels = {ent for rel in data['Relazioni'] for ent in [rel['Entità 1'], rel['Entità 2']]}
entities = set(data['Entità'].keys())
entities.add('#any') # For compatibility
if not entity_rels.issubset(entities):
print(entity_rels.difference(entities))
# %%
# USE A DIRTY SHORTCUT: paste entity/relation info on a precompiled rdf template file.
# Load template
with open('template_2.rdf', 'r') as in_file:
raw_rdf = in_file.read()
# Defined rdf snippets; info will replace placeholder tags (in uppercase between '#')
entity_template = '''
#LABEL#
#PARENT#
'''
subclass_string = " #PARENT#\n"
class_defined_string = ' \n'
object_property_template = '''
#LABEL#
'''
object_property_inverse_template = '''
#LABEL#
'''
object_defined_string = ' \n'
datatype_property_template = '''
#LABEL#
'''
datatype_defined_string = ' \n'
# Define a normalization function for rdf labels for easier portability
def label_to_name(label):
return label.replace(' ', '_').replace('à', 'a').replace('è', 'e').replace('é', 'e').replace('ì', 'i').replace('ò', 'o').replace('ù', 'u')
# Generic ('propietary') datatypes to std. xsd datatypes mapping
datatype_xsd = {
"#string": 'string',
'#uri': '#uri',
'#number': 'decimal',
'#date': 'date',
'#coordinates': '#coordinates'
}
# %%
# Map entity info to dedicated lists
entities_rdf_list = []
entities_csv = []
datatype_properties_rdf_list = []
same_as = list(data['Same_as'].keys())
for label, ent in data['Entità'].items():
entity_name = label_to_name(label)
entity_rdf = entity_template.replace('#LABEL#', label).replace('#NAME#', entity_name)
# Try to find entity in extra csv, see if there is CIDOC info and if so, map it
entity_in_csv = next((ent for ent in ent_csv_in if ent['ENTITÀ']==label), None)
cidoc_class = None
if entity_in_csv is not None:
cidoc_class = entity_in_csv.get('CIDOC-LINK')
if cidoc_class is not None and cidoc_class!='':
entity_rdf = entity_rdf.replace('#URI#', cidoc_class)
else:
entity_rdf = entity_rdf.replace(class_defined_string, '')
# Subclasses
if 'Sottoclasse di' in ent.keys():
parent = ent['Sottoclasse di']
data['Relazioni'].append({"Entità 1": label,
"Entità 2": parent,
"Etichetta": "is_subclass_of", "Inversa": "is_superclass_of"})
entity_rdf = entity_rdf.replace('#PARENT#', label_to_name(parent))
else:
entity_rdf = entity_rdf.replace(subclass_string, '')
entities_rdf_list.append(entity_rdf)
#
if label in same_as:
entities_csv.append( [label, "", ', '.join(data['Same_as'][label])] )
else:
entities_csv.append([label, "", ""])
for datatype_label, datatype_val in ent.items():
if not isinstance(datatype_val, str) or not datatype_val.startswith('#'):
continue
entities_csv.append(["", datatype_label, ""])
datatype_name = label_to_name(datatype_label)
datatype_rdf = datatype_property_template.replace('#LABEL#', datatype_label).replace('#NAME#', datatype_name).replace('#DOMAIN#', entity_name)
# Try to find entity in extra csv, see if there is CIDOC info and if so, map it
datatype_in_csv = next((ent for ent in ent_csv_in if ent['ATTRIBUTO (LITERAL)']==datatype_label), None)
cidoc_class = None
if datatype_in_csv is not None:
cidoc_class = datatype_in_csv.get('CIDOC-LINK')
if cidoc_class is not None and cidoc_class!='':
datatype_rdf = datatype_rdf.replace('#URI#', cidoc_class)
else:
datatype_rdf = datatype_rdf.replace(datatype_defined_string, '')
datatype_properties_rdf_list.append(datatype_rdf)
# Map relation info to dedicated lists
relations_rdf_list = []
relations_csv = []
for rel in data['Relazioni']:
label = rel['Etichetta']
inverse_label = rel['Inversa']
domain = label_to_name(rel['Entità 1'])
range1 = label_to_name(rel['Entità 2'])
relations_csv.append([rel['Entità 1'], rel['Entità 2'], rel['Etichetta'], rel['Inversa']])
name = domain + '_' + label_to_name(label) + '_' + range1
inverse_name = range1 + '_' + label_to_name(inverse_label) + '_' + domain
# Try to find entity in extra csv, see if there is CIDOC info and if so, map it
relation_in_csv = next((rel_csv for rel_csv in rel_csv_in if (rel_csv['ENTITÀ 1']==rel['Entità 1'] and rel_csv['ENTITÀ 2']==rel['Entità 2']) ), None)
cidoc_class = None
#
relation_rdf = object_property_template.replace('#NAME#', name).replace('#LABEL#', label).replace('#DOMAIN#', domain).replace('#RANGE#', range1)
#
if relation_in_csv is not None:
cidoc_class = relation_in_csv.get('CIDOC-LINK')
if cidoc_class is not None and cidoc_class!='':
relation_rdf = relation_rdf.replace('#URI#', cidoc_class)
else:
relation_rdf = relation_rdf.replace(object_defined_string, '')
#
relation_inverse_rdf = object_property_inverse_template.replace('#NAME#', inverse_name).replace('#LABEL#', inverse_label).replace('#DOMAIN#', range1).replace('#RANGE#', domain).replace('#INV#', name)
#
if cidoc_class is not None and cidoc_class!='':
relation_inverse_rdf = relation_inverse_rdf.replace('#URI#', cidoc_class)
else:
relation_inverse_rdf = relation_inverse_rdf.replace('', '')
#
relation_full_rdf = relation_rdf + '\n\n\n' + relation_inverse_rdf
relations_rdf_list.append(relation_full_rdf)
# Write info to template and export it to output file
with open('draft.rdf', 'w') as out_file:
to_out = raw_rdf.replace(entity_template, '\n\n\n'.join(entities_rdf_list)).replace(datatype_property_template, '\n\n\n'.join(datatype_properties_rdf_list)).replace(object_property_inverse_template, '\n\n\n'.join(relations_rdf_list))
out_file.write(to_out)
# %%
# Write info to two csv files (one for Entities, one for Relations) for extra human readability
with open('entities.csv', 'w') as out_csv:
writer = csv.writer(out_csv)
writer.writerow(['ENTITÀ', 'ATTRIBUTO (LITERAL)', 'SAME AS'])
writer.writerows(entities_csv)
with open('relations.csv', 'w') as out_csv:
writer = csv.writer(out_csv)
writer.writerow(['ENTITÀ 1', 'ENTITÀ 2', 'NOME RELAZIONE', 'NOME RELAZIONE INVERSA'])
writer.writerows(relations_csv)
# %%
print(raw_rdf)
# %%
entity_template in raw_rdf
# %%
entity_template
# %%