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## 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.
24 lines
659 B
Python
24 lines
659 B
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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@pytest.mark.parametrize('text,lemma', [
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("aprox.", "aproximadamente"),
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("esq.", "esquina"),
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("pág.", "página"),
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("p.ej.", "por ejemplo")])
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def test_es_tokenizer_handles_abbr(es_tokenizer, text, lemma):
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tokens = es_tokenizer(text)
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assert len(tokens) == 1
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assert tokens[0].lemma_ == lemma
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def test_es_tokenizer_handles_exc_in_text(es_tokenizer):
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text = "Mariano Rajoy ha corrido aprox. medio kilómetro"
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tokens = es_tokenizer(text)
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assert len(tokens) == 7
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assert tokens[4].text == "aprox."
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assert tokens[4].lemma_ == "aproximadamente"
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