def __contains__(self, term):
# Check if the term is in the dictionary.
# If the term is not in the dictionary, check the classifiers.
term = self._normalize(term)
if dict.__contains__(self, term):
return True
for classifier in self.classifiers:
if classifier.parents(term) \
or classifier.children(term):
return True
return False
def test_lazydict(self):
# Assert lazy dictionary only has data after one of its methods is called.
class V(text.lazydict):
def load(self):
dict.__setitem__(self, "a", 1)
v = V()
self.assertTrue(dict.__len__(v) == 0)
self.assertTrue(dict.__contains__(v, "a") is False)
self.assertTrue(len(v), 1)
self.assertTrue(v["a"] == 1)
print("pattern.text.lazydict")
def __contains__(self, term):
# Check if the term is in the dictionary.
# If the term is not in the dictionary, check the classifiers.
term = self._normalize(term)
if dict.__contains__(self, term):
return True
for classifier in self.classifiers:
if classifier.parents(term) \
or classifier.children(term):
return True
return False
def test_lazydict(self):
# Assert lazy dictionary only has data after one of its methods is called.
class V(text.lazydict):
def load(self):
dict.__setitem__(self, "a", 1)
v = V()
self.assertTrue(dict.__len__(v) == 0)
self.assertTrue(dict.__contains__(v, "a") is False)
self.assertTrue(len(v), 1)
self.assertTrue(v["a"] == 1)
print("pattern.text.lazydict")
def dfs(term, recursive=False, visited={}, **kwargs):
if term in visited: # Break on cyclic relations.
return []
visited[term], a = True, []
if dict.__contains__(self, term):
a = list(self[term][1].keys())
for classifier in self.classifiers:
a.extend(classifier.children(term, **kwargs) or [])
if recursive:
for w in a:
a += dfs(w, recursive, visited, **kwargs)
return a
def dfs(term, recursive=False, visited={}, **kwargs):
if term in visited: # Break on cyclic relations.
return []
visited[term], a = True, []
if dict.__contains__(self, term):
a = list(self[term][1].keys())
for classifier in self.classifiers:
a.extend(classifier.children(term, **kwargs) or [])
if recursive:
for w in a:
a += dfs(w, recursive, visited, **kwargs)
return a
def classify(self, term, **kwargs):
""" Returns the (most recently added) semantic type for the given term ("many" => "quantity").
If the term is not in the dictionary, try Taxonomy.classifiers.
"""
term = self._normalize(term)
if dict.__contains__(self, term):
return list(self[term][0].keys())[-1]
# If the term is not in the dictionary, check the classifiers.
# Returns the first term in the list returned by a classifier.
for classifier in self.classifiers:
# **kwargs are useful if the classifier requests extra information,
# for example the part-of-speech tag.
v = classifier.parents(term, **kwargs)
if v:
return v[0]
def classify(self, term, **kwargs):
""" Returns the (most recently added) semantic type for the given term ("many" => "quantity").
If the term is not in the dictionary, try Taxonomy.classifiers.
"""
term = self._normalize(term)
if dict.__contains__(self, term):
return list(self[term][0].keys())[-1]
# If the term is not in the dictionary, check the classifiers.
# Returns the first term in the list returned by a classifier.
for classifier in self.classifiers:
# **kwargs are useful if the classifier requests extra information,
# for example the part-of-speech tag.
v = classifier.parents(term, **kwargs)
if v:
return v[0]
def __contains__(self, k):
try:
return hasattr(self, k) or dict.__contains__(self, k)
except:
return False
def remove(self, term):
if dict.__contains__(self, term):
for w in self.parents(term):
self[w][1].pop(term)
dict.pop(self, term)
def remove(self, term):
if dict.__contains__(self, term):
for w in self.parents(term):
self[w][1].pop(term)
dict.pop(self, term)