spaCy/spacy/tests/lang/ja/test_lemmatization.py

import pytest


@pytest.mark.parametrize(
    "word,lemma",
    [
        ("新しく", "新しい"),
        ("赤く", "赤い"),
        ("すごく", "すごい"),
        ("いただきました", "いただく"),
        ("なった", "なる"),
    ],
)
def test_ja_lemmatizer_assigns(ja_tokenizer, word, lemma):
    test_lemma = ja_tokenizer(word)[0].lemma_
    assert test_lemma == lemma


@pytest.mark.parametrize(
    "word,norm",
    [
        ("SUMMER", "サマー"),
        ("食べ物", "食べ物"),
        ("綜合", "総合"),
        ("コンピュータ", "コンピューター"),
    ],
)
def test_ja_lemmatizer_norm(ja_tokenizer, word, norm):
    test_norm = ja_tokenizer(word)[0].norm_
    assert test_norm == norm
💫 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. 2018-07-25 00:38:44 +03:00			`import pytest`


💫 Tidy up and auto-format tests (#2967) * Auto-format tests with black * Add flake8 config * Tidy up and remove unused imports * Fix redefinitions of test functions * Replace orths_and_spaces with words and spaces * Fix compatibility with pytest 4.0 * xfail test for now Test was previously overwritten by following test due to naming conflict, so failure wasn't reported * Unfail passing test * Only use fixture via arguments Fixes pytest 4.0 compatibility 2018-11-27 03:09:36 +03:00			`@pytest.mark.parametrize(`
			`"word,lemma",`
Update requirements, fixing windows crashes (#13727) * Re-enable pretraining test * Require thinc 8.3.4 * Reformat * Re-enable test 2025-01-13 18:39:46 +03:00			`[`
			`("新しく", "新しい"),`
			`("赤く", "赤い"),`
			`("すごく", "すごい"),`
			`("いただきました", "いただく"),`
			`("なった", "なる"),`
			`],`
💫 Tidy up and auto-format tests (#2967) * Auto-format tests with black * Add flake8 config * Tidy up and remove unused imports * Fix redefinitions of test functions * Replace orths_and_spaces with words and spaces * Fix compatibility with pytest 4.0 * xfail test for now Test was previously overwritten by following test due to naming conflict, so failure wasn't reported * Unfail passing test * Only use fixture via arguments Fixes pytest 4.0 compatibility 2018-11-27 03:09:36 +03:00			`)`
💫 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. 2018-07-25 00:38:44 +03:00			`def test_ja_lemmatizer_assigns(ja_tokenizer, word, lemma):`
			`test_lemma = ja_tokenizer(word)[0].lemma_`
			`assert test_lemma == lemma`
Moving Japanese tokenizer extra info to Token.morph (#8977) * Use morph for extra Japanese tokenizer info Previously Japanese tokenizer info that didn't correspond to Token fields was put in user data. Since spaCy core should avoid touching user data, this moves most information to the Token.morph attribute. It also adds the normalized form, which wasn't exposed before. The subtokens, which are a list of full tokens, are still added to user data, except with the default tokenizer granualarity. With the default tokenizer settings the subtokens are all None, so in this case the user data is simply not set. * Update tests Also adds a new test for norm data. * Update docs * Add Japanese morphologizer factory Set the default to `extend=True` so that the morphologizer does not clobber the values set by the tokenizer. * Use the norm_ field for normalized forms Before this commit, normalized forms were put in the "norm" field in the morph attributes. I am not sure why I did that instead of using the token morph, I think I just forgot about it. * Skip test if sudachipy is not installed * Fix import Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> 2021-10-01 20:19:26 +03:00

			`@pytest.mark.parametrize(`
			`"word,norm",`
			`[`
			`("SUMMER", "サマー"),`
			`("食べ物", "食べ物"),`
			`("綜合", "総合"),`
			`("コンピュータ", "コンピューター"),`
			`],`
			`)`
			`def test_ja_lemmatizer_norm(ja_tokenizer, word, norm):`
			`test_norm = ja_tokenizer(word)[0].norm_`
			`assert test_norm == norm`