spaCy/spacy/tests/test_pickles.py

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# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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import numpy
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import srsly
💫 Refactor test suite (#2568) ## Description Related issues: #2379 (should be fixed by separating model tests) * **total execution time down from > 300 seconds to under 60 seconds** 🎉 * removed all model-specific tests that could only really be run manually anyway – those will now live in a separate test suite in the [`spacy-models`](https://github.com/explosion/spacy-models) repository and are already integrated into our new model training infrastructure * changed all relative imports to absolute imports to prepare for moving the test suite from `/spacy/tests` to `/tests` (it'll now always test against the installed version) * merged old regression tests into collections, e.g. `test_issue1001-1500.py` (about 90% of the regression tests are very short anyways) * tidied up and rewrote existing tests wherever possible ### Todo - [ ] move tests to `/tests` and adjust CI commands accordingly - [x] move model test suite from internal repo to `spacy-models` - [x] ~~investigate why `pipeline/test_textcat.py` is flakey~~ - [x] review old regression tests (leftover files) and see if they can be merged, simplified or deleted - [ ] update documentation on how to run tests ### Types of change enhancement, tests ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [ ] My changes don't require a change to the documentation, or if they do, I've added all required information.
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from spacy.strings import StringStore
from spacy.vocab import Vocab
from spacy.attrs import NORM
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@pytest.mark.parametrize("text1,text2", [("hello", "bye")])
💫 Refactor test suite (#2568) ## Description Related issues: #2379 (should be fixed by separating model tests) * **total execution time down from > 300 seconds to under 60 seconds** 🎉 * removed all model-specific tests that could only really be run manually anyway – those will now live in a separate test suite in the [`spacy-models`](https://github.com/explosion/spacy-models) repository and are already integrated into our new model training infrastructure * changed all relative imports to absolute imports to prepare for moving the test suite from `/spacy/tests` to `/tests` (it'll now always test against the installed version) * merged old regression tests into collections, e.g. `test_issue1001-1500.py` (about 90% of the regression tests are very short anyways) * tidied up and rewrote existing tests wherever possible ### Todo - [ ] move tests to `/tests` and adjust CI commands accordingly - [x] move model test suite from internal repo to `spacy-models` - [x] ~~investigate why `pipeline/test_textcat.py` is flakey~~ - [x] review old regression tests (leftover files) and see if they can be merged, simplified or deleted - [ ] update documentation on how to run tests ### Types of change enhancement, tests ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [ ] My changes don't require a change to the documentation, or if they do, I've added all required information.
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def test_pickle_string_store(text1, text2):
stringstore = StringStore()
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store1 = stringstore[text1]
store2 = stringstore[text2]
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data = srsly.pickle_dumps(stringstore, protocol=-1)
unpickled = srsly.pickle_loads(data)
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assert unpickled[text1] == store1
assert unpickled[text2] == store2
assert len(stringstore) == len(unpickled)
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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]})
vocab.set_vector("dog", numpy.ones((5,), dtype="f"))
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lex1 = vocab[text1]
lex2 = vocab[text2]
assert lex1.norm_ == text1[:-1]
assert lex2.norm_ == text2[:-1]
data = pickle.dumps(vocab)
unpickled = pickle.loads(data)
assert unpickled[text1].orth == lex1.orth
assert unpickled[text2].orth == lex2.orth
assert unpickled[text1].norm == lex1.norm
assert unpickled[text2].norm == lex2.norm
assert unpickled[text1].norm != unpickled[text2].norm
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assert unpickled.vectors is not None
assert list(vocab["dog"].vector) == [1.0, 1.0, 1.0, 1.0, 1.0]