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Reformat pickle tests
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# coding: utf-8
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from __future__ import unicode_literals
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from __future__ import unicode_literals
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import io
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import pytest
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import pytest
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import dill as pickle
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import dill as pickle
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from ..strings import StringStore
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from ..vocab import Vocab
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from ..vocab import Vocab
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from ..attrs import NORM
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from ..attrs import NORM
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def test_pickle_string_store():
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@pytest.mark.parametrize('text1,text2', [('hello', 'bye')])
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sstore = StringStore()
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def test_pickle_string_store(stringstore, text1, text2):
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hello = sstore['hello']
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store1 = stringstore[text1]
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bye = sstore['bye']
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store2 = stringstore[text2]
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bdata = pickle.dumps(sstore, protocol=-1)
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data = pickle.dumps(stringstore, protocol=-1)
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unpickled = pickle.loads(bdata)
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unpickled = pickle.loads(data)
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assert unpickled['hello'] == hello
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assert unpickled[text1] == store1
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assert unpickled['bye'] == bye
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assert unpickled[text2] == store2
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assert len(sstore) == len(unpickled)
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assert len(stringstore) == len(unpickled)
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@pytest.mark.xfail
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@pytest.mark.xfail
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def test_pickle_vocab():
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@pytest.mark.parametrize('text1,text2', [('dog', 'cat')])
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def test_pickle_vocab(text1, text2):
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vocab = Vocab(lex_attr_getters={int(NORM): lambda string: string[:-1]})
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vocab = Vocab(lex_attr_getters={int(NORM): lambda string: string[:-1]})
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dog = vocab[u'dog']
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lex1 = vocab[text1]
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cat = vocab[u'cat']
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lex2 = vocab[text2]
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assert dog.norm_ == 'do'
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assert lex1.norm_ == text1[:-1]
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assert cat.norm_ == 'ca'
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assert lex2.norm_ == text2[:-1]
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data = pickle.dumps(vocab)
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bdata = pickle.dumps(vocab)
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unpickled = pickle.loads(data)
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unpickled = pickle.loads(bdata)
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assert unpickled[text1].orth == lex1.orth
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assert unpickled[text2].orth == lex2.orth
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assert unpickled[u'dog'].orth == dog.orth
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assert unpickled[text1].norm == lex1.norm
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assert unpickled[u'cat'].orth == cat.orth
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assert unpickled[text2].norm == lex2.norm
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assert unpickled[u'dog'].norm == dog.norm
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assert unpickled[text1].norm != unpickled[text2].norm
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assert unpickled[u'cat'].norm == cat.norm
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dog_ = unpickled[u'dog']
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cat_ = unpickled[u'cat']
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assert dog_.norm != cat_.norm
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