182 lines
6.2 KiB
Python
182 lines
6.2 KiB
Python
from __future__ import annotations
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from collections.abc import Callable, MutableMapping
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import dataclasses as dc
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from typing import Any
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import warnings
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from markdown_it._compat import DATACLASS_KWARGS
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def convert_attrs(value: Any) -> Any:
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"""Convert Token.attrs set as ``None`` or ``[[key, value], ...]`` to a dict.
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This improves compatibility with upstream markdown-it.
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"""
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if not value:
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return {}
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if isinstance(value, list):
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return dict(value)
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return value
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@dc.dataclass(**DATACLASS_KWARGS)
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class Token:
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type: str
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"""Type of the token (string, e.g. "paragraph_open")"""
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tag: str
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"""HTML tag name, e.g. 'p'"""
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nesting: int
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"""Level change (number in {-1, 0, 1} set), where:
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- `1` means the tag is opening
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- `0` means the tag is self-closing
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- `-1` means the tag is closing
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"""
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attrs: dict[str, str | int | float] = dc.field(default_factory=dict)
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"""HTML attributes.
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Note this differs from the upstream "list of lists" format,
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although than an instance can still be initialised with this format.
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"""
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map: list[int] | None = None
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"""Source map info. Format: `[ line_begin, line_end ]`"""
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level: int = 0
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"""Nesting level, the same as `state.level`"""
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children: list[Token] | None = None
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"""Array of child nodes (inline and img tokens)."""
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content: str = ""
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"""Inner content, in the case of a self-closing tag (code, html, fence, etc.),"""
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markup: str = ""
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"""'*' or '_' for emphasis, fence string for fence, etc."""
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info: str = ""
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"""Additional information:
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- Info string for "fence" tokens
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- The value "auto" for autolink "link_open" and "link_close" tokens
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- The string value of the item marker for ordered-list "list_item_open" tokens
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"""
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meta: dict = dc.field(default_factory=dict)
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"""A place for plugins to store any arbitrary data"""
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block: bool = False
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"""True for block-level tokens, false for inline tokens.
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Used in renderer to calculate line breaks
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"""
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hidden: bool = False
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"""If true, ignore this element when rendering.
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Used for tight lists to hide paragraphs.
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"""
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def __post_init__(self):
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self.attrs = convert_attrs(self.attrs)
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def attrIndex(self, name: str) -> int:
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warnings.warn(
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"Token.attrIndex should not be used, since Token.attrs is a dictionary",
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UserWarning,
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)
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if name not in self.attrs:
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return -1
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return list(self.attrs.keys()).index(name)
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def attrItems(self) -> list[tuple[str, str | int | float]]:
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"""Get (key, value) list of attrs."""
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return list(self.attrs.items())
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def attrPush(self, attrData: tuple[str, str | int | float]) -> None:
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"""Add `[ name, value ]` attribute to list. Init attrs if necessary."""
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name, value = attrData
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self.attrSet(name, value)
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def attrSet(self, name: str, value: str | int | float) -> None:
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"""Set `name` attribute to `value`. Override old value if exists."""
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self.attrs[name] = value
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def attrGet(self, name: str) -> None | str | int | float:
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"""Get the value of attribute `name`, or null if it does not exist."""
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return self.attrs.get(name, None)
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def attrJoin(self, name: str, value: str) -> None:
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"""Join value to existing attribute via space.
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Or create new attribute if not exists.
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Useful to operate with token classes.
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"""
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if name in self.attrs:
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current = self.attrs[name]
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if not isinstance(current, str):
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raise TypeError(
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f"existing attr 'name' is not a str: {self.attrs[name]}"
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)
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self.attrs[name] = f"{current} {value}"
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else:
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self.attrs[name] = value
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def copy(self, **changes: Any) -> Token:
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"""Return a shallow copy of the instance."""
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return dc.replace(self, **changes)
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def as_dict(
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self,
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*,
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children: bool = True,
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as_upstream: bool = True,
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meta_serializer: Callable[[dict], Any] | None = None,
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filter: Callable[[str, Any], bool] | None = None,
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dict_factory: Callable[..., MutableMapping[str, Any]] = dict,
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) -> MutableMapping[str, Any]:
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"""Return the token as a dictionary.
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:param children: Also convert children to dicts
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:param as_upstream: Ensure the output dictionary is equal to that created by markdown-it
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For example, attrs are converted to null or lists
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:param meta_serializer: hook for serializing ``Token.meta``
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:param filter: A callable whose return code determines whether an
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attribute or element is included (``True``) or dropped (``False``).
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Is called with the (key, value) pair.
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:param dict_factory: A callable to produce dictionaries from.
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For example, to produce ordered dictionaries instead of normal Python
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dictionaries, pass in ``collections.OrderedDict``.
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"""
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mapping = dict_factory((f.name, getattr(self, f.name)) for f in dc.fields(self))
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if filter:
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mapping = dict_factory((k, v) for k, v in mapping.items() if filter(k, v))
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if as_upstream and "attrs" in mapping:
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mapping["attrs"] = (
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None
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if not mapping["attrs"]
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else [[k, v] for k, v in mapping["attrs"].items()]
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)
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if meta_serializer and "meta" in mapping:
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mapping["meta"] = meta_serializer(mapping["meta"])
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if children and mapping.get("children", None):
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mapping["children"] = [
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child.as_dict(
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children=children,
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filter=filter,
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dict_factory=dict_factory,
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as_upstream=as_upstream,
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meta_serializer=meta_serializer,
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)
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for child in mapping["children"]
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]
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return mapping
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@classmethod
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def from_dict(cls, dct: MutableMapping[str, Any]) -> Token:
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"""Convert a dict to a Token."""
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token = cls(**dct)
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if token.children:
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token.children = [cls.from_dict(c) for c in token.children] # type: ignore[arg-type]
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return token
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