markdown-it-py/markdown_it/token.py

182 lines
6.2 KiB
Python

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