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eddeb36c96
<!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## 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. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
178 lines
5.3 KiB
Python
178 lines
5.3 KiB
Python
# encoding: utf8
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from __future__ import unicode_literals, print_function
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from ...language import Language
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from ...attrs import LANG
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from ...tokens import Doc, Token
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from ...tokenizer import Tokenizer
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from ... import util
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from .tag_map import TAG_MAP
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import re
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from collections import namedtuple
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ShortUnitWord = namedtuple("ShortUnitWord", ["surface", "lemma", "pos"])
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def try_mecab_import():
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"""Mecab is required for Japanese support, so check for it.
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It it's not available blow up and explain how to fix it."""
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try:
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import MeCab
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# XXX Is this the right place for this?
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Token.set_extension("mecab_tag", default=None)
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return MeCab
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except ImportError:
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raise ImportError(
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"Japanese support requires MeCab: "
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"https://github.com/SamuraiT/mecab-python3"
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)
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def resolve_pos(token):
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"""If necessary, add a field to the POS tag for UD mapping.
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Under Universal Dependencies, sometimes the same Unidic POS tag can
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be mapped differently depending on the literal token or its context
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in the sentence. This function adds information to the POS tag to
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resolve ambiguous mappings.
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"""
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# NOTE: This is a first take. The rules here are crude approximations.
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# For many of these, full dependencies are needed to properly resolve
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# PoS mappings.
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if token.pos == "連体詞,*,*,*":
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if re.match("^[こそあど此其彼]の", token.surface):
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return token.pos + ",DET"
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if re.match("^[こそあど此其彼]", token.surface):
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return token.pos + ",PRON"
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else:
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return token.pos + ",ADJ"
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return token.pos
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def detailed_tokens(tokenizer, text):
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"""Format Mecab output into a nice data structure, based on Janome."""
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tokenizer.parse(text)
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node = tokenizer.parseToNode(text)
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node = node.next # first node is beginning of sentence and empty, skip it
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words = []
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while node.posid != 0:
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surface = node.surface
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base = surface # a default value. Updated if available later.
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parts = node.feature.split(",")
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pos = ",".join(parts[0:4])
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if len(parts) > 7:
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# this information is only available for words in the tokenizer dictionary
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base = parts[7]
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words.append(ShortUnitWord(surface, base, pos))
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node = node.next
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return words
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class JapaneseTokenizer(object):
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def __init__(self, cls, nlp=None):
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self.vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp)
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MeCab = try_mecab_import()
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self.tokenizer = MeCab.Tagger()
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def __call__(self, text):
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dtokens = detailed_tokens(self.tokenizer, text)
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words = [x.surface for x in dtokens]
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doc = Doc(self.vocab, words=words, spaces=[False] * len(words))
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for token, dtoken in zip(doc, dtokens):
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token._.mecab_tag = dtoken.pos
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token.tag_ = resolve_pos(dtoken)
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token.lemma_ = dtoken.lemma
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return doc
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# add dummy methods for to_bytes, from_bytes, to_disk and from_disk to
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# allow serialization (see #1557)
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def to_bytes(self, **exclude):
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return b""
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def from_bytes(self, bytes_data, **exclude):
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return self
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def to_disk(self, path, **exclude):
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return None
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def from_disk(self, path, **exclude):
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return self
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class JapaneseCharacterSegmenter(object):
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def __init__(self, vocab):
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self.vocab = vocab
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self._presegmenter = self._make_presegmenter(self.vocab)
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def _make_presegmenter(self, vocab):
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rules = Japanese.Defaults.tokenizer_exceptions
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token_match = Japanese.Defaults.token_match
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prefix_search = (
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util.compile_prefix_regex(Japanese.Defaults.prefixes).search
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if Japanese.Defaults.prefixes
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else None
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)
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suffix_search = (
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util.compile_suffix_regex(Japanese.Defaults.suffixes).search
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if Japanese.Defaults.suffixes
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else None
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)
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infix_finditer = (
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util.compile_infix_regex(Japanese.Defaults.infixes).finditer
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if Japanese.Defaults.infixes
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else None
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)
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return Tokenizer(
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vocab,
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rules=rules,
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prefix_search=prefix_search,
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suffix_search=suffix_search,
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infix_finditer=infix_finditer,
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token_match=token_match,
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)
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def __call__(self, text):
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words = []
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spaces = []
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doc = self._presegmenter(text)
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for token in doc:
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words.extend(list(token.text))
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spaces.extend([False] * len(token.text))
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spaces[-1] = bool(token.whitespace_)
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return Doc(self.vocab, words=words, spaces=spaces)
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class JapaneseDefaults(Language.Defaults):
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lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
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lex_attr_getters[LANG] = lambda text: "ja"
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tag_map = TAG_MAP
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use_janome = True
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@classmethod
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def create_tokenizer(cls, nlp=None):
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if cls.use_janome:
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return JapaneseTokenizer(cls, nlp)
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else:
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return JapaneseCharacterSegmenter(nlp.vocab)
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class Japanese(Language):
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lang = "ja"
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Defaults = JapaneseDefaults
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Tokenizer = JapaneseTokenizer
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def make_doc(self, text):
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return self.tokenizer(text)
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__all__ = ["Japanese"]
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