spaCy/spacy/tests/doc/test_pickle_doc.py

58 lines
1.5 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
from spacy.language import Language
from spacy.compat import pickle, unicode_
def test_pickle_single_doc():
nlp = Language()
doc = nlp("pickle roundtrip")
data = pickle.dumps(doc, 1)
doc2 = pickle.loads(data)
assert doc2.text == "pickle roundtrip"
def test_list_of_docs_pickles_efficiently():
nlp = Language()
for i in range(10000):
_ = nlp.vocab[unicode_(i)] # noqa: F841
one_pickled = pickle.dumps(nlp("0"), -1)
docs = list(nlp.pipe(unicode_(i) for i in range(100)))
many_pickled = pickle.dumps(docs, -1)
assert len(many_pickled) < (len(one_pickled) * 2)
many_unpickled = pickle.loads(many_pickled)
assert many_unpickled[0].text == "0"
assert many_unpickled[-1].text == "99"
assert len(many_unpickled) == 100
def test_user_data_from_disk():
nlp = Language()
doc = nlp("Hello")
doc.user_data[(0, 1)] = False
b = doc.to_bytes()
doc2 = doc.__class__(doc.vocab).from_bytes(b)
assert doc2.user_data[(0, 1)] is False
def test_user_data_unpickles():
nlp = Language()
doc = nlp("Hello")
doc.user_data[(0, 1)] = False
b = pickle.dumps(doc)
doc2 = pickle.loads(b)
assert doc2.user_data[(0, 1)] is False
def test_hooks_unpickle():
def inner_func(d1, d2):
return "hello!"
nlp = Language()
doc = nlp("Hello")
doc.user_hooks["similarity"] = inner_func
b = pickle.dumps(doc)
doc2 = pickle.loads(b)
assert doc2.similarity(None) == "hello!"