def parse(oboFile, typedefs):
"""
Parses an OBO (ontology file) creating a correspoinding Ontology
object composed of Term objects that relate to the terms found in the
ontology file.
"""
ontology = Ontology()
## Use groupby to group the lines of our file into chunks of text, some
## stanzas, some typedefs, and other metadata to be processed
with open(oboFile) as f:
for (key, group) in groupby(f, is_data):
if key:
header = group.next().rstrip('\n')
if header.find('[Typedef]') != -1:
dataDict = get_data_as_dict(group)
ontology.add_typedef(dataDict['name'])
elif header.find('[Term]') != -1:
dataDict = get_data_as_dict(group, typedefs)
ontology.add_term(build_term(dataDict))
else:
# We are dealing with ontology metadata that should be
# captured in our ontology object.
ontology.metadata.append(header)
ontology.metadata.extend([x.strip() for x in group])
return ontology
def parse(oboFile, typedefs):
"""
Parses an OBO (ontology file) creating a correspoinding Ontology
object composed of Term objects that relate to the terms found in the
ontology file.
"""
ontology = Ontology()
## Use groupby to group the lines of our file into chunks of text, some
## stanzas, some typedefs, and other metadata to be processed
with open(oboFile) as f:
for (key, group) in groupby(f, is_data):
if key:
header = group.next().rstrip('\n')
if header.find('[Typedef]') != -1:
dataDict = get_data_as_dict(group)
ontology.add_typedef(dataDict['name'])
elif header.find('[Term]') != -1:
dataDict = get_data_as_dict(group, typedefs)
ontology.add_term(build_term(dataDict))
else:
# We are dealing with ontology metadata that should be
# captured in our ontology object.
ontology.metadata.append(header)
ontology.metadata.extend([x.strip() for x in group])
return ontology
