def test_unpickle():
fd, path = mkstemp()
# Pickle an object to this temporary file.
obj = {'a': 1}
with os.fdopen(fd, 'wb') as file:
pickle.dump(obj, file)
# Check it's unpickled well.
unpickled_obj = unpickle(path)
assert obj == unpickled_obj
assert obj is not unpickled_obj
# The unpickling is cached.
assert unpickled_obj is unpickle(path)
# Clean up.
os.remove(path)
def _frequency(cls, word=None):
"""frequency"""
frequency = unpickle(settings.FREQUENCY)
if word is None:
return frequency.keys()
return frequency.get(word, np.nan)
def _clustering(cls, word=None):
"""clustering"""
clustering = unpickle(settings.CLUSTERING)
if word is None:
return clustering.keys()
return clustering.get(word, np.nan)
def _betweenness(cls, word=None):
"""betweenness"""
betweenness = unpickle(settings.BETWEENNESS)
if word is None:
return betweenness.keys()
return betweenness.get(word, np.nan)
def _pagerank(cls, word=None):
"""pagerank"""
pagerank = unpickle(settings.PAGERANK)
if word is None:
return pagerank.keys()
return pagerank.get(word, np.nan)
def _degree(cls, word=None):
"""degree"""
degree = unpickle(settings.DEGREE)
if word is None:
return degree.keys()
return degree.get(word, np.nan)
def _letters_count(cls, word=None):
"""#letters"""
if word is None:
return unpickle(settings.TOKENS)
return len(word)
