284 lines
10 KiB
Python
284 lines
10 KiB
Python
# Copyright 2018-2022 Streamlit Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from enum import Enum
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from textwrap import dedent
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from typing import (
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Any,
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Callable,
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cast,
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Iterable,
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Optional,
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overload,
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List,
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Sequence,
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Union,
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TypeVar,
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)
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import streamlit
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from streamlit.errors import StreamlitAPIException
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from streamlit.proto.MultiSelect_pb2 import MultiSelect as MultiSelectProto
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from streamlit.runtime.scriptrunner import ScriptRunContext, get_script_run_ctx
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from streamlit.type_util import Key, OptionSequence, ensure_indexable, is_type, to_key
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from streamlit.runtime.state import (
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register_widget,
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WidgetArgs,
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WidgetCallback,
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WidgetKwargs,
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)
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from .form import current_form_id
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from .utils import check_callback_rules, check_session_state_rules
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T = TypeVar("T")
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class MultiSelectMixin:
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@overload
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def multiselect(
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self,
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label: str,
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options: Sequence[T],
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default: Optional[Any] = None,
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format_func: Callable[[Any], Any] = str,
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key: Optional[Key] = None,
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help: Optional[str] = None,
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on_change: Optional[WidgetCallback] = None,
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args: Optional[WidgetArgs] = None,
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kwargs: Optional[WidgetKwargs] = None,
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*, # keyword-only arguments:
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disabled: bool = False,
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) -> List[T]:
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...
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@overload
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def multiselect(
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self,
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label: str,
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options: OptionSequence,
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default: Optional[Any] = None,
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format_func: Callable[[Any], Any] = str,
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key: Optional[Key] = None,
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help: Optional[str] = None,
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on_change: Optional[WidgetCallback] = None,
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args: Optional[WidgetArgs] = None,
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kwargs: Optional[WidgetKwargs] = None,
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*, # keyword-only arguments:
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disabled: bool = False,
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) -> List[Any]:
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...
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def multiselect(
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self,
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label: str,
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options: OptionSequence,
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default: Optional[Any] = None,
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format_func: Callable[[Any], Any] = str,
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key: Optional[Key] = None,
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help: Optional[str] = None,
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on_change: Optional[WidgetCallback] = None,
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args: Optional[WidgetArgs] = None,
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kwargs: Optional[WidgetKwargs] = None,
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*, # keyword-only arguments:
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disabled: bool = False,
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) -> List[Any]:
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"""Display a multiselect widget.
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The multiselect widget starts as empty.
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Parameters
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----------
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label : str
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A short label explaining to the user what this select widget is for.
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options : Sequence[V], numpy.ndarray, pandas.Series, pandas.DataFrame, or pandas.Index
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Labels for the select options. This will be cast to str internally
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by default. For pandas.DataFrame, the first column is selected.
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default: [V], V, or None
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List of default values. Can also be a single value.
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format_func : function
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Function to modify the display of selectbox options. It receives
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the raw option as an argument and should output the label to be
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shown for that option. This has no impact on the return value of
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the multiselect.
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key : str or int
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An optional string or integer to use as the unique key for the widget.
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If this is omitted, a key will be generated for the widget
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based on its content. Multiple widgets of the same type may
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not share the same key.
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help : str
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An optional tooltip that gets displayed next to the multiselect.
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on_change : callable
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An optional callback invoked when this multiselect's value changes.
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args : tuple
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An optional tuple of args to pass to the callback.
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kwargs : dict
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An optional dict of kwargs to pass to the callback.
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disabled : bool
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An optional boolean, which disables the multiselect widget if set
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to True. The default is False. This argument can only be supplied
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by keyword.
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Returns
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-------
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list
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A list with the selected options
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Example
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-------
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>>> options = st.multiselect(
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... 'What are your favorite colors',
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... ['Green', 'Yellow', 'Red', 'Blue'],
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... ['Yellow', 'Red'])
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>>>
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>>> st.write('You selected:', options)
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.. output::
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https://doc-multiselect.streamlitapp.com/
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height: 420px
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"""
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ctx = get_script_run_ctx()
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return self._multiselect(
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label=label,
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options=options,
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default=default,
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format_func=format_func,
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key=key,
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help=help,
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on_change=on_change,
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args=args,
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kwargs=kwargs,
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disabled=disabled,
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ctx=ctx,
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)
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def _multiselect(
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self,
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label: str,
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options: OptionSequence,
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default: Union[Iterable[Any], Any, None] = None,
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format_func: Callable[[Any], Any] = str,
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key: Optional[Key] = None,
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help: Optional[str] = None,
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on_change: Optional[WidgetCallback] = None,
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args: Optional[WidgetArgs] = None,
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kwargs: Optional[WidgetKwargs] = None,
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*, # keyword-only arguments:
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disabled: bool = False,
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ctx: Optional[ScriptRunContext] = None,
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) -> List[Any]:
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key = to_key(key)
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check_callback_rules(self.dg, on_change)
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check_session_state_rules(default_value=default, key=key)
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opt = ensure_indexable(options)
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@overload
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def _check_and_convert_to_indices( # type: ignore[misc]
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opt: Sequence[Any], default_values: None
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) -> Optional[List[int]]:
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...
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@overload
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def _check_and_convert_to_indices(
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opt: Sequence[Any], default_values: Union[Iterable[Any], Any]
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) -> List[int]:
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...
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def _check_and_convert_to_indices(
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opt: Sequence[Any], default_values: Union[Iterable[Any], Any, None]
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) -> Optional[List[int]]:
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"""Perform validation checks and return indices based on the default values."""
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if default_values is None and None not in opt:
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return None
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if not isinstance(default_values, list):
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# This if is done before others because calling if not x (done
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# right below) when x is of type pd.Series() or np.array() throws a
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# ValueError exception.
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if is_type(default_values, "numpy.ndarray") or is_type(
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default_values, "pandas.core.series.Series"
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):
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default_values = list(cast(Iterable[Any], default_values))
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elif not default_values or default_values in opt:
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default_values = [default_values]
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else:
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default_values = list(default_values)
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if len(default_values) != 0 and isinstance(default_values[0], Enum):
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str_default_values = [str(enum) for enum in default_values]
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mapped_opt_keys = [str(enum) for enum in opt]
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for value in str_default_values:
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if value not in mapped_opt_keys:
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raise StreamlitAPIException(
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"Every Multiselect default value must exist in options"
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)
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return [mapped_opt_keys.index(value) for value in str_default_values]
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for value in default_values:
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if value not in opt:
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raise StreamlitAPIException(
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"Every Multiselect default value must exist in options"
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)
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return [opt.index(value) for value in default_values]
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indices = _check_and_convert_to_indices(opt, default)
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multiselect_proto = MultiSelectProto()
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multiselect_proto.label = label
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default_value: List[int] = [] if indices is None else indices
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multiselect_proto.default[:] = default_value
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multiselect_proto.options[:] = [str(format_func(option)) for option in opt]
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multiselect_proto.form_id = current_form_id(self.dg)
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if help is not None:
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multiselect_proto.help = dedent(help)
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def deserialize_multiselect(
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ui_value: Optional[List[int]], widget_id: str = ""
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) -> List[Any]:
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current_value: List[int] = (
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ui_value if ui_value is not None else default_value
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)
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return [opt[i] for i in current_value]
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def serialize_multiselect(value: List[Any]) -> List[int]:
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return _check_and_convert_to_indices(opt, value)
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widget_state = register_widget(
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"multiselect",
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multiselect_proto,
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user_key=key,
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on_change_handler=on_change,
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args=args,
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kwargs=kwargs,
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deserializer=deserialize_multiselect,
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serializer=serialize_multiselect,
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ctx=ctx,
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)
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# This needs to be done after register_widget because we don't want
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# the following proto fields to affect a widget's ID.
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multiselect_proto.disabled = disabled
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if widget_state.value_changed:
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multiselect_proto.value[:] = serialize_multiselect(widget_state.value)
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multiselect_proto.set_value = True
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self.dg._enqueue("multiselect", multiselect_proto)
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if len(widget_state.value) != 0:
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if isinstance(widget_state.value[0], Enum):
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return [str(enum) for enum in widget_state.value]
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return widget_state.value
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@property
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def dg(self) -> "streamlit.delta_generator.DeltaGenerator":
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"""Get our DeltaGenerator."""
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return cast("streamlit.delta_generator.DeltaGenerator", self)
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