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from typing import TYPE_CHECKING, Any, Optional, Union
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from ..types import ReactionTypeCustomEmoji, ReactionTypeEmoji, ReactionTypePaid
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from .base import TelegramMethod
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class SetMessageReaction(TelegramMethod[bool]):
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"""
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Use this method to change the chosen reactions on a message. Service messages can't be reacted to. Automatically forwarded messages from a channel to its discussion group have the same available reactions as messages in the channel. Bots can't use paid reactions. Returns :code:`True` on success.
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Source: https://core.telegram.org/bots/api#setmessagereaction
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"""
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__returning__ = bool
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__api_method__ = "setMessageReaction"
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chat_id: Union[int, str]
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"""Unique identifier for the target chat or username of the target channel (in the format :code:`@channelusername`)"""
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message_id: int
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"""Identifier of the target message. If the message belongs to a media group, the reaction is set to the first non-deleted message in the group instead."""
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reaction: Optional[
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list[Union[ReactionTypeEmoji, ReactionTypeCustomEmoji, ReactionTypePaid]]
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] = None
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"""A JSON-serialized list of reaction types to set on the message. Currently, as non-premium users, bots can set up to one reaction per message. A custom emoji reaction can be used if it is either already present on the message or explicitly allowed by chat administrators. Paid reactions can't be used by bots."""
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is_big: Optional[bool] = None
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"""Pass :code:`True` to set the reaction with a big animation"""
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if TYPE_CHECKING:
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# DO NOT EDIT MANUALLY!!!
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# This section was auto-generated via `butcher`
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def __init__(
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__pydantic__self__,
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*,
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chat_id: Union[int, str],
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message_id: int,
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reaction: Optional[
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list[Union[ReactionTypeEmoji, ReactionTypeCustomEmoji, ReactionTypePaid]]
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] = None,
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is_big: Optional[bool] = None,
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**__pydantic_kwargs: Any,
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) -> None:
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# DO NOT EDIT MANUALLY!!!
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# This method was auto-generated via `butcher`
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# Is needed only for type checking and IDE support without any additional plugins
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super().__init__(
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chat_id=chat_id,
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message_id=message_id,
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reaction=reaction,
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is_big=is_big,
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**__pydantic_kwargs,
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)
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