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357be2614e
* Fuzz tokenizer.explain: draft for fuzzy tests. * Fuzz tokenizer.explain: xignoring tokenizer.explain() tests. Removed deadline modification. Removed LANGUAGES_WITHOUT_TOKENIZERS. * Fuzz tokenizer.explain: changed tokenizer initialization to avoid failus in Azure runs. * Fuzz tokenizer.explain: type hint for tokenizer in test. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
129 lines
4.7 KiB
Python
129 lines
4.7 KiB
Python
import re
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import string
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import hypothesis
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import hypothesis.strategies
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import pytest
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import spacy
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from spacy.tokenizer import Tokenizer
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from spacy.util import get_lang_class
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# Only include languages with no external dependencies
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# "is" seems to confuse importlib, so we're also excluding it for now
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# excluded: ja, ru, th, uk, vi, zh, is
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LANGUAGES = [
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pytest.param("fr", marks=pytest.mark.slow()),
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pytest.param("af", marks=pytest.mark.slow()),
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pytest.param("ar", marks=pytest.mark.slow()),
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pytest.param("bg", marks=pytest.mark.slow()),
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"bn",
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pytest.param("ca", marks=pytest.mark.slow()),
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pytest.param("cs", marks=pytest.mark.slow()),
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pytest.param("da", marks=pytest.mark.slow()),
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pytest.param("de", marks=pytest.mark.slow()),
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"el",
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"en",
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pytest.param("es", marks=pytest.mark.slow()),
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pytest.param("et", marks=pytest.mark.slow()),
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pytest.param("fa", marks=pytest.mark.slow()),
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pytest.param("fi", marks=pytest.mark.slow()),
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"fr",
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pytest.param("ga", marks=pytest.mark.slow()),
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pytest.param("he", marks=pytest.mark.slow()),
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pytest.param("hi", marks=pytest.mark.slow()),
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pytest.param("hr", marks=pytest.mark.slow()),
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"hu",
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pytest.param("id", marks=pytest.mark.slow()),
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pytest.param("it", marks=pytest.mark.slow()),
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pytest.param("kn", marks=pytest.mark.slow()),
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pytest.param("lb", marks=pytest.mark.slow()),
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pytest.param("lt", marks=pytest.mark.slow()),
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pytest.param("lv", marks=pytest.mark.slow()),
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pytest.param("nb", marks=pytest.mark.slow()),
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pytest.param("nl", marks=pytest.mark.slow()),
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"pl",
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pytest.param("pt", marks=pytest.mark.slow()),
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pytest.param("ro", marks=pytest.mark.slow()),
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pytest.param("si", marks=pytest.mark.slow()),
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pytest.param("sk", marks=pytest.mark.slow()),
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pytest.param("sl", marks=pytest.mark.slow()),
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pytest.param("sq", marks=pytest.mark.slow()),
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pytest.param("sr", marks=pytest.mark.slow()),
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pytest.param("sv", marks=pytest.mark.slow()),
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pytest.param("ta", marks=pytest.mark.slow()),
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pytest.param("te", marks=pytest.mark.slow()),
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pytest.param("tl", marks=pytest.mark.slow()),
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pytest.param("tr", marks=pytest.mark.slow()),
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pytest.param("tt", marks=pytest.mark.slow()),
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pytest.param("ur", marks=pytest.mark.slow()),
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]
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@pytest.mark.parametrize("lang", LANGUAGES)
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def test_tokenizer_explain(lang):
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tokenizer = get_lang_class(lang)().tokenizer
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examples = pytest.importorskip(f"spacy.lang.{lang}.examples")
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for sentence in examples.sentences:
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tokens = [t.text for t in tokenizer(sentence) if not t.is_space]
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debug_tokens = [t[1] for t in tokenizer.explain(sentence)]
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assert tokens == debug_tokens
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def test_tokenizer_explain_special_matcher(en_vocab):
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suffix_re = re.compile(r"[\.]$")
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infix_re = re.compile(r"[/]")
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rules = {"a.": [{"ORTH": "a."}]}
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tokenizer = Tokenizer(
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en_vocab,
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rules=rules,
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suffix_search=suffix_re.search,
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infix_finditer=infix_re.finditer,
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)
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tokens = [t.text for t in tokenizer("a/a.")]
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explain_tokens = [t[1] for t in tokenizer.explain("a/a.")]
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assert tokens == explain_tokens
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@hypothesis.strategies.composite
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def sentence_strategy(draw: hypothesis.strategies.DrawFn, max_n_words: int = 4) -> str:
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"""
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Composite strategy for fuzzily generating sentence with varying interpunctation.
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draw (hypothesis.strategies.DrawFn): Protocol for drawing function allowing to fuzzily pick from hypothesis'
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strategies.
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max_n_words (int): Max. number of words in generated sentence.
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RETURNS (str): Fuzzily generated sentence.
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"""
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punctuation_and_space_regex = "|".join(
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[*[re.escape(p) for p in string.punctuation], r"\s"]
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)
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sentence = [
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[
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draw(hypothesis.strategies.text(min_size=1)),
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draw(hypothesis.strategies.from_regex(punctuation_and_space_regex)),
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]
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for _ in range(
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draw(hypothesis.strategies.integers(min_value=2, max_value=max_n_words))
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)
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]
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return " ".join([token for token_pair in sentence for token in token_pair])
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@pytest.mark.xfail
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@pytest.mark.parametrize("lang", LANGUAGES)
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@hypothesis.given(sentence=sentence_strategy())
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def test_tokenizer_explain_fuzzy(lang: str, sentence: str) -> None:
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"""
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Tests whether output of tokenizer.explain() matches tokenizer output. Input generated by hypothesis.
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lang (str): Language to test.
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text (str): Fuzzily generated sentence to tokenize.
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"""
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tokenizer: Tokenizer = spacy.blank(lang).tokenizer
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tokens = [t.text for t in tokenizer(sentence) if not t.is_space]
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debug_tokens = [t[1] for t in tokenizer.explain(sentence)]
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assert tokens == debug_tokens, f"{tokens}, {debug_tokens}, {sentence}"
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