kannadaLettersClassification
/
env
/lib
/python3.12
/site-packages
/prompt_toolkit
/formatted_text
/pygments.py
| from __future__ import annotations | |
| from typing import TYPE_CHECKING | |
| from prompt_toolkit.styles.pygments import pygments_token_to_classname | |
| from .base import StyleAndTextTuples | |
| if TYPE_CHECKING: | |
| from pygments.token import Token | |
| __all__ = [ | |
| "PygmentsTokens", | |
| ] | |
| class PygmentsTokens: | |
| """ | |
| Turn a pygments token list into a list of prompt_toolkit text fragments | |
| (``(style_str, text)`` tuples). | |
| """ | |
| def __init__(self, token_list: list[tuple[Token, str]]) -> None: | |
| self.token_list = token_list | |
| def __pt_formatted_text__(self) -> StyleAndTextTuples: | |
| result: StyleAndTextTuples = [] | |
| for token, text in self.token_list: | |
| result.append(("class:" + pygments_token_to_classname(token), text)) | |
| return result | |