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Nama	Ukuran	Aksi
data	-	Open
__pycache__	-	Open
checker.py	43.83 MB	View DL Edit
cli.py	2.92 MB	View DL Edit
config.py	32.7 MB	View DL Edit
parser.py	27.63 MB	View DL Edit
utils.py	1.26 MB	View DL Edit
violations.py	12.12 MB	View DL Edit
wordlists.py	1.51 MB	View DL Edit
_version.py	400 B	View DL Edit
__init__.py	194 B	View DL Edit
__main__.py	288 B	View DL Edit

Edit file: /opt/cloudlinux/venv/lib/python3.11/site-packages/pydocstyle/wordlists.py

"""Wordlists loaded from package data.

We can treat them as part of the code for the imperative mood check, and
therefore we load them at import time, rather than on-demand.

"""
import pkgutil
import re
from typing import Dict, Iterator, Set

import snowballstemmer

#: Regular expression for stripping comments from the wordlists
COMMENT_RE = re.compile(r'\s*#.*')

#: Stemmer function for stemming words in English
stem = snowballstemmer.stemmer('english').stemWord

def load_wordlist(name: str) -> Iterator[str]:
    """Iterate over lines of a wordlist data file.

`name` should be the name of a package data file within the data/
    directory.

Whitespace and #-prefixed comments are stripped from each line.

"""
    data = pkgutil.get_data('pydocstyle', 'data/' + name)
    if data is not None:
        text = data.decode('utf8')
        for line in text.splitlines():
            line = COMMENT_RE.sub('', line).strip()
            if line:
                yield line

def make_imperative_verbs_dict(wordlist: Iterator[str]) -> Dict[str, Set[str]]:
    """Create a dictionary mapping stemmed verbs to the imperative form."""
    imperative_verbs = {}  # type: Dict[str, Set[str]]
    for word in wordlist:
        imperative_verbs.setdefault(stem(word), set()).add(word)
    return imperative_verbs

IMPERATIVE_VERBS = make_imperative_verbs_dict(load_wordlist('imperatives.txt'))

#: Words that are forbidden to appear as the first word in a docstring
IMPERATIVE_BLACKLIST = set(load_wordlist('imperatives_blacklist.txt'))

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