sphinx_pyppeteer_builder/typings/sphinx/search/__init__.pyi

"""
This type stub file was generated by pyright.
"""

import dataclasses
import functools
import html
import json
import pickle
import re
from __future__ import annotations
from importlib import import_module
from os import path
from typing import Any, IO, TYPE_CHECKING
from docutils import nodes
from docutils.nodes import Element, Node
from sphinx import addnodes, package_dir
from sphinx.environment import BuildEnvironment
from sphinx.util.index_entries import split_index_msg
from collections.abc import Iterable
from sphinx.search.en import SearchEnglish

"""Create a full-text search index for offline search."""
if TYPE_CHECKING:
    ...
class SearchLanguage:
    """
    This class is the base class for search natural language preprocessors.  If
    you want to add support for a new language, you should override the methods
    of this class.

    You should override `lang` class property too (e.g. 'en', 'fr' and so on).

    .. attribute:: stopwords

       This is a set of stop words of the target language.  Default `stopwords`
       is empty.  This word is used for building index and embedded in JS.

    .. attribute:: js_splitter_code

       Return splitter function of JavaScript version.  The function should be
       named as ``splitQuery``.  And it should take a string and return list of
       strings.

       .. versionadded:: 3.0

    .. attribute:: js_stemmer_code

       Return stemmer class of JavaScript version.  This class' name should be
       ``Stemmer`` and this class must have ``stemWord`` method.  This string is
       embedded as-is in searchtools.js.

       This class is used to preprocess search word which Sphinx HTML readers
       type, before searching index. Default implementation does nothing.
    """
    lang: str | None = ...
    language_name: str | None = ...
    stopwords: set[str] = ...
    js_splitter_code: str = ...
    js_stemmer_rawcode: str | None = ...
    js_stemmer_code = ...
    _word_re = ...
    def __init__(self, options: dict) -> None:
        ...
    
    def init(self, options: dict) -> None:
        """
        Initialize the class with the options the user has given.
        """
        ...
    
    def split(self, input: str) -> list[str]:
        """
        This method splits a sentence into words.  Default splitter splits input
        at white spaces, which should be enough for most languages except CJK
        languages.
        """
        ...
    
    def stem(self, word: str) -> str:
        """
        This method implements stemming algorithm of the Python version.

        Default implementation does nothing.  You should implement this if the
        language has any stemming rules.

        This class is used to preprocess search words before registering them in
        the search index.  The stemming of the Python version and the JS version
        (given in the js_stemmer_code attribute) must be compatible.
        """
        ...
    
    def word_filter(self, word: str) -> bool:
        """
        Return true if the target word should be registered in the search index.
        This method is called after stemming.
        """
        ...
    


def parse_stop_word(source: str) -> set[str]:
    """
    Parse snowball style word list like this:

    * http://snowball.tartarus.org/algorithms/finnish/stop.txt
    """
    ...

languages: dict[str, str | type[SearchLanguage]] = ...
class _JavaScriptIndex:
    """
    The search index as JavaScript file that calls a function
    on the documentation search object to register the index.
    """
    PREFIX = ...
    SUFFIX = ...
    def dumps(self, data: Any) -> str:
        ...
    
    def loads(self, s: str) -> Any:
        ...
    
    def dump(self, data: Any, f: IO) -> None:
        ...
    
    def load(self, f: IO) -> Any:
        ...
    


js_index = ...
@dataclasses.dataclass
class WordStore:
    words: list[str] = ...
    titles: list[tuple[str, str]] = ...
    title_words: list[str] = ...


class WordCollector(nodes.NodeVisitor):
    """
    A special visitor that collects words for the `IndexBuilder`.
    """
    def __init__(self, document: nodes.document, lang: SearchLanguage) -> None:
        ...
    
    def dispatch_visit(self, node: Node) -> None:
        ...
    


class IndexBuilder:
    """
    Helper class that creates a search index based on the doctrees
    passed to the `feed` method.
    """
    formats = ...
    def __init__(self, env: BuildEnvironment, lang: str, options: dict, scoring: str) -> None:
        ...
    
    def load(self, stream: IO, format: Any) -> None:
        """Reconstruct from frozen data."""
        ...
    
    def dump(self, stream: IO, format: Any) -> None:
        """Dump the frozen index to a stream."""
        ...
    
    def get_objects(self, fn2index: dict[str, int]) -> dict[str, list[tuple[int, int, int, str, str]]]:
        ...
    
    def get_terms(self, fn2index: dict) -> tuple[dict[str, list[str]], dict[str, list[str]]]:
        ...
    
    def freeze(self) -> dict[str, Any]:
        """Create a usable data structure for serializing."""
        ...
    
    def label(self) -> str:
        ...
    
    def prune(self, docnames: Iterable[str]) -> None:
        """Remove data for all docnames not in the list."""
        ...
    
    def feed(self, docname: str, filename: str, title: str, doctree: nodes.document) -> None:
        """Feed a doctree to the index."""
        ...
    
    def context_for_searchtool(self) -> dict[str, Any]:
        ...
    
    def get_js_stemmer_rawcodes(self) -> list[str]:
        """Returns a list of non-minified stemmer JS files to copy."""
        ...
    
    def get_js_stemmer_rawcode(self) -> str | None:
        ...
    
    def get_js_stemmer_code(self) -> str:
        """Returns JS code that will be inserted into language_data.js."""
        ...