Create dictionary from values extracted through regex-CodePudding

I have a sparql query (qres1) that fetches strings from concepts of an RDF file (eg. below), on which I am applying regex to get two values. I would like to store these values as key-value pair in dictionary.

eg. (rdflib.term.Literal('skin sarcoma', lang='en'), rdflib.term.URIRef('http://purl.obolibrary.org/obo/DOID_2687'))

pattern_doid = '.*\/(DOID.*)'
pattern_label = '.*\(\'(.*)\',.*'
doid = []
label = []
dict = {}

for line in qres1:
    doid = re.findall(pattern_doid, str(line[0]), re.MULTILINE)
    label = re.findall(pattern_label, str(line[1]), re.MULTILINE)

   #create dictionary with doid as key and prefLabel as value
    dict[doid[0]] = label[0]

This gives me the following error. IndexError: list index out of range

How can I create such dictionary. Any help is highly appreciated.

CodePudding user response：

I've tweaked the regex but generally it seems okay.

>>> import re
>>> re.findall(r'.*\/(DOID_\d ).*', "rdflib.term.URIRef('http://purl.obolibrary.org/obo/DOID_2687'))", re.MULTILINE)
['DOID_2687']
>>> re.findall(r'.*\(\'(.*)\'\).*', "rdflib.term.URIRef('http://purl.obolibrary.org/obo/DOID_2687'))", re.MULTILINE)
['http://purl.obolibrary.org/obo/DOID_2687']

You will get an indexing error if the string doesn't have a 'doid' or 'label'.

e.g.

>>> re.findall(r'.*\(\'(.*)\'\).*', "rdflib.term.URIRef'))", re.MULTILINE)[0]
Traceback (most recent call last):
  File "<pyshell#3>", line 1, in <module>
    re.findall(r'.*\(\'(.*)\'\).*', "rdflib.term.URIRef'))", re.MULTILINE)[0]
IndexError: list index out of range

CodePudding user response：

You could use zip to pair up the keys and values so that if any of them is missing, you won't get an error:

myDictionary.update(zip(doid[:1],label))

BTW dict is a type name in Python, you should not use it as a variable name.

You might also want to check the order of the lines (line[0],line[1]) vs the patterns (doid,label) you are searching for. Seems to me that the 'DOID_' part is at line[1] based on your example data)