id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
178,330 | from __future__ import annotations
import collections
import dataclasses
import datetime
import functools
import hashlib
import inspect
import io
import os
import pickle
import sys
import tempfile
import threading
import uuid
import weakref
from enum import Enum
from typing import Any, Callable, Dict, Final, Pattern, T... | null |
178,331 | from __future__ import annotations
import collections
import dataclasses
import datetime
import functools
import hashlib
import inspect
import io
import os
import pickle
import sys
import tempfile
import threading
import uuid
import weakref
from enum import Enum
from typing import Any, Callable, Dict, Final, Pattern, T... | Return key for memoization. |
178,332 | from __future__ import annotations
import math
import threading
import types
from datetime import timedelta
from typing import Any, Callable, Final, TypeVar, cast, overload
from cachetools import TTLCache
from typing_extensions import TypeAlias
import streamlit as st
from streamlit.deprecation_util import show_deprecat... | True if the two validate functions are equal for the purposes of determining whether a given function cache needs to be recreated. |
178,333 | from __future__ import annotations
import math
import threading
import types
from datetime import timedelta
from typing import Any, Callable, Final, TypeVar, cast, overload
from cachetools import TTLCache
from typing_extensions import TypeAlias
import streamlit as st
from streamlit.deprecation_util import show_deprecat... | Return the StatsProvider for all @st.cache_resource functions. |
178,334 | from __future__ import annotations
import math
import os
import shutil
from typing import Final
from streamlit import util
from streamlit.file_util import get_streamlit_file_path, streamlit_read, streamlit_write
from streamlit.logger import get_logger
from streamlit.runtime.caching.storage.cache_storage_protocol import... | null |
178,335 | from __future__ import annotations
import contextlib
import hashlib
import threading
import types
from dataclasses import dataclass
from typing import (
TYPE_CHECKING,
Any,
Final,
Iterator,
Protocol,
Union,
runtime_checkable,
)
from google.protobuf.message import Message
import streamlit as ... | Replay the st element function calls that happened when executing a cache-decorated function. When a cache function is executed, we record the element and block messages produced, and use those to reproduce the DeltaGenerator calls, so the elements will appear in the web app even when execution of the function is skipp... |
178,336 | from __future__ import annotations
import contextlib
import hashlib
import threading
import types
from dataclasses import dataclass
from typing import (
TYPE_CHECKING,
Any,
Final,
Iterator,
Protocol,
Union,
runtime_checkable,
)
from google.protobuf.message import Message
import streamlit as ... | Generate a key for the given list of widgets used in a cache-decorated function. Keys are generated by hashing the IDs and values of the widgets in the given list. |
178,337 | from __future__ import annotations
from typing import Any, Final, Iterator, MutableMapping
from streamlit import logger as _logger
from streamlit import runtime
from streamlit.runtime.metrics_util import gather_metrics
from streamlit.runtime.state.common import require_valid_user_key
from streamlit.runtime.state.safe_s... | Get the SessionState object for the current session. Note that in streamlit scripts, this function should not be called directly. Instead, SessionState objects should be accessed via st.session_state. |
178,338 | from __future__ import annotations
from typing import Any, Final, Iterator, MutableMapping
from streamlit import logger as _logger
from streamlit import runtime
from streamlit.runtime.metrics_util import gather_metrics
from streamlit.runtime.state.common import require_valid_user_key
from streamlit.runtime.state.safe_s... | null |
178,339 | from __future__ import annotations
import json
import pickle
from copy import deepcopy
from dataclasses import dataclass, field, replace
from typing import (
TYPE_CHECKING,
Any,
Final,
Iterator,
KeysView,
List,
MutableMapping,
Union,
cast,
)
from typing_extensions import TypeAlias
im... | null |
178,340 | from __future__ import annotations
import json
import pickle
from copy import deepcopy
from dataclasses import dataclass, field, replace
from typing import (
TYPE_CHECKING,
Any,
Final,
Iterator,
KeysView,
List,
MutableMapping,
Union,
cast,
)
from typing_extensions import TypeAlias
im... | null |
178,341 | from __future__ import annotations
import textwrap
from types import MappingProxyType
from typing import TYPE_CHECKING, Final, Mapping
from typing_extensions import TypeAlias
from streamlit.errors import DuplicateWidgetID
from streamlit.proto.WidgetStates_pb2 import WidgetState, WidgetStates
from streamlit.runtime.stat... | Coalesce an older WidgetStates into a newer one, and return a new WidgetStates containing the result. For most widget values, we just take the latest version. However, any trigger_values (which are set by buttons) that are True in `old_states` will be set to True in the coalesced result, so that button presses don't go... |
178,342 | from __future__ import annotations
import hashlib
from dataclasses import dataclass, field
from datetime import date, datetime, time, timedelta
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Final,
Generic,
Sequence,
Tuple,
TypeVar,
Union,
)
from google.protobuf.message... | Compute the widget id for the given widget. This id is stable: a given set of inputs to this function will always produce the same widget id output. Only stable, deterministic values should be used to compute widget ids. Using nondeterministic values as inputs can cause the resulting widget id to change between runs. T... |
178,343 | from __future__ import annotations
import hashlib
from dataclasses import dataclass, field
from datetime import date, datetime, time, timedelta
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Final,
Generic,
Sequence,
Tuple,
TypeVar,
Union,
)
from google.protobuf.message... | True if the given session_state key has the structure of a widget ID with a user_key. |
178,344 | from __future__ import annotations
import hashlib
from dataclasses import dataclass, field
from datetime import date, datetime, time, timedelta
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Final,
Generic,
Sequence,
Tuple,
TypeVar,
Union,
)
from google.protobuf.message... | Raise an Exception if the given user_key is invalid. |
178,345 | from __future__ import annotations
import hashlib
from dataclasses import dataclass, field
from datetime import date, datetime, time, timedelta
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Final,
Generic,
Sequence,
Tuple,
TypeVar,
Union,
)
from google.protobuf.message... | null |
178,346 | from __future__ import annotations
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Iterable, Iterator, MutableMapping
from urllib import parse
from streamlit.constants import EMBED_QUERY_PARAMS_KEYS
from streamlit.errors import StreamlitAPIException
from streamlit.proto.ForwardMsg_pb2 import ... | null |
178,347 | from __future__ import annotations
import contextlib
import hashlib
import mimetypes
import os.path
from typing import Final, NamedTuple
from streamlit.logger import get_logger
from streamlit.runtime.media_file_storage import (
MediaFileKind,
MediaFileStorage,
MediaFileStorageError,
)
from streamlit.runtime... | Hash data, mimetype, and an optional filename to generate a stable file ID. Parameters ---------- data Content of in-memory file in bytes. Other types will throw TypeError. mimetype Any string. Will be converted to bytes and used to compute a hash. filename Any string. Will be converted to bytes and used to compute a h... |
178,348 | from __future__ import annotations
import contextlib
import hashlib
import mimetypes
import os.path
from typing import Final, NamedTuple
from streamlit.logger import get_logger
from streamlit.runtime.media_file_storage import (
MediaFileKind,
MediaFileStorage,
MediaFileStorageError,
)
from streamlit.runtime... | null |
178,349 | from __future__ import annotations
import os
import threading
from copy import deepcopy
from typing import (
Any,
Final,
ItemsView,
Iterator,
KeysView,
Mapping,
NoReturn,
ValuesView,
)
from blinker import Signal
import streamlit as st
import streamlit.watcher.path_watcher
from streamlit ... | null |
178,350 | from __future__ import annotations
import os
import threading
from copy import deepcopy
from typing import (
Any,
Final,
ItemsView,
Iterator,
KeysView,
Mapping,
NoReturn,
ValuesView,
)
from blinker import Signal
import streamlit as st
import streamlit.watcher.path_watcher
from streamlit ... | null |
178,351 | from __future__ import annotations
from typing import Any
from streamlit.proto.Delta_pb2 import Delta
from streamlit.proto.ForwardMsg_pb2 import ForwardMsg
The provided code snippet includes necessary dependencies for implementing the `_is_composable_message` function. Write a Python function `def _is_composable_messa... | True if the ForwardMsg is potentially composable with other ForwardMsgs. |
178,352 | from __future__ import annotations
from typing import Any
from streamlit.proto.Delta_pb2 import Delta
from streamlit.proto.ForwardMsg_pb2 import ForwardMsg
The provided code snippet includes necessary dependencies for implementing the `_maybe_compose_deltas` function. Write a Python function `def _maybe_compose_deltas... | Combines new_delta onto old_delta if possible. If the combination takes place, the function returns a new Delta that should replace old_delta in the queue. If the new_delta is incompatible with old_delta, the function returns None. In this case, the new_delta should just be appended to the queue as normal. |
178,353 | from __future__ import annotations
import re
from typing import Any, Callable
The provided code snippet includes necessary dependencies for implementing the `to_upper_camel_case` function. Write a Python function `def to_upper_camel_case(snake_case_str: str) -> str` to solve the following problem:
Converts snake_case ... | Converts snake_case to UpperCamelCase. Example ------- foo_bar -> FooBar |
178,354 | from __future__ import annotations
import re
from typing import Any, Callable
The provided code snippet includes necessary dependencies for implementing the `to_lower_camel_case` function. Write a Python function `def to_lower_camel_case(snake_case_str: str) -> str` to solve the following problem:
Converts snake_case ... | Converts snake_case to lowerCamelCase. Example ------- foo_bar -> fooBar fooBar -> foobar |
178,355 | from __future__ import annotations
import re
from typing import Any, Callable
The provided code snippet includes necessary dependencies for implementing the `convert_dict_keys` function. Write a Python function `def convert_dict_keys( func: Callable[[str], str], in_dict: dict[Any, Any] ) -> dict[Any, Any]` to solv... | Apply a conversion function to all keys in a dict. Parameters ---------- func : callable The function to apply. Takes a str and returns a str. in_dict : dict The dictionary to convert. If some value in this dict is itself a dict, it also gets recursively converted. Returns ------- dict A new dict with all the contents ... |
178,356 | from __future__ import annotations
import dataclasses
import functools
import hashlib
import os
import subprocess
import sys
from typing import Any, Callable, Final, Iterable, Mapping, TypeVar
from streamlit import env_util
The provided code snippet includes necessary dependencies for implementing the `memoize` functi... | Decorator to memoize the result of a no-args func. |
178,357 | from __future__ import annotations
import dataclasses
import functools
import hashlib
import os
import subprocess
import sys
from typing import Any, Callable, Final, Iterable, Mapping, TypeVar
from streamlit import env_util
The provided code snippet includes necessary dependencies for implementing the `repr_` function... | A clean repr for a class, excluding both values that are likely defaults, and those explicitly default for dataclasses. |
178,358 | from __future__ import annotations
import dataclasses
import functools
import hashlib
import os
import subprocess
import sys
from typing import Any, Callable, Final, Iterable, Mapping, TypeVar
from streamlit import env_util
FLOAT_EQUALITY_EPSILON: Final[float] = 0.000000000005
_Value = TypeVar("_Value")
The provided c... | Return zero-based index of the first item whose value is equal to x. Raises a ValueError if there is no such item. We need a custom implementation instead of the built-in list .index() to be compatible with NumPy array and Pandas Series. Parameters ---------- iterable : list, tuple, numpy.ndarray, pandas.Series x : Any... |
178,359 | from __future__ import annotations
import copy
import hashlib
import json
from typing import TYPE_CHECKING, Any, Collection, Dict, Final, Iterable, Union, cast
from typing_extensions import TypeAlias
import streamlit.elements.deck_gl_json_chart as deck_gl_json_chart
from streamlit import config, type_util
from streamli... | null |
178,360 | from __future__ import annotations
import copy
import hashlib
import json
from typing import TYPE_CHECKING, Any, Collection, Dict, Final, Iterable, Union, cast
from typing_extensions import TypeAlias
import streamlit.elements.deck_gl_json_chart as deck_gl_json_chart
from streamlit import config, type_util
from streamli... | null |
178,361 | from __future__ import annotations
import json
from typing import TYPE_CHECKING, Any, cast
from streamlit.proto.Json_pb2 import Json as JsonProto
from streamlit.runtime.metrics_util import gather_metrics
from streamlit.runtime.state import QueryParamsProxy, SessionStateProxy
from streamlit.user_info import UserInfoProx... | A repr function for json.dumps default arg, which tries to serialize sets as lists |
178,362 | from __future__ import annotations
from enum import Enum, EnumMeta
from typing import TYPE_CHECKING, Any, Hashable, Iterable, Sequence, cast, overload
import streamlit
from streamlit import config, runtime, type_util
from streamlit.elements.form import is_in_form
from streamlit.errors import StreamlitAPIException
from ... | null |
178,363 | from __future__ import annotations
from enum import Enum, EnumMeta
from typing import TYPE_CHECKING, Any, Hashable, Iterable, Sequence, cast, overload
import streamlit
from streamlit import config, runtime, type_util
from streamlit.elements.form import is_in_form
from streamlit.errors import StreamlitAPIException
from ... | null |
178,364 | from __future__ import annotations
from enum import Enum, EnumMeta
from typing import TYPE_CHECKING, Any, Hashable, Iterable, Sequence, cast, overload
import streamlit
from streamlit import config, runtime, type_util
from streamlit.elements.form import is_in_form
from streamlit.errors import StreamlitAPIException
from ... | Returns one of LabelVisibilityMessage enum constants.py based on string value. |
178,365 | from __future__ import annotations
from enum import Enum, EnumMeta
from typing import TYPE_CHECKING, Any, Hashable, Iterable, Sequence, cast, overload
import streamlit
from streamlit import config, runtime, type_util
from streamlit.elements.form import is_in_form
from streamlit.errors import StreamlitAPIException
from ... | null |
178,366 | from __future__ import annotations
from enum import Enum, EnumMeta
from typing import TYPE_CHECKING, Any, Hashable, Iterable, Sequence, cast, overload
import streamlit
from streamlit import config, runtime, type_util
from streamlit.elements.form import is_in_form
from streamlit.errors import StreamlitAPIException
from ... | null |
178,367 | from __future__ import annotations
from enum import Enum, EnumMeta
from typing import TYPE_CHECKING, Any, Hashable, Iterable, Sequence, cast, overload
import streamlit
from streamlit import config, runtime, type_util
from streamlit.elements.form import is_in_form
from streamlit.errors import StreamlitAPIException
from ... | Maybe Coerce a RegisterWidgetResult with an Enum member value to RegisterWidgetResult[option] if option is an EnumType, otherwise just return the original RegisterWidgetResult. |
178,368 | from __future__ import annotations
from enum import Enum, EnumMeta
from typing import TYPE_CHECKING, Any, Hashable, Iterable, Sequence, cast, overload
import streamlit
from streamlit import config, runtime, type_util
from streamlit.elements.form import is_in_form
from streamlit.errors import StreamlitAPIException
from ... | null |
178,369 | from __future__ import annotations
from enum import Enum, EnumMeta
from typing import TYPE_CHECKING, Any, Hashable, Iterable, Sequence, cast, overload
import streamlit
from streamlit import config, runtime, type_util
from streamlit.elements.form import is_in_form
from streamlit.errors import StreamlitAPIException
from ... | null |
178,370 | from __future__ import annotations
from enum import Enum, EnumMeta
from typing import TYPE_CHECKING, Any, Hashable, Iterable, Sequence, cast, overload
import streamlit
from streamlit import config, runtime, type_util
from streamlit.elements.form import is_in_form
from streamlit.errors import StreamlitAPIException
from ... | Maybe Coerce a RegisterWidgetResult with a sequence of Enum members as value to RegisterWidgetResult[Sequence[option]] if option is an EnumType, otherwise just return the original RegisterWidgetResult. |
178,371 | from __future__ import annotations
import json
from typing import TYPE_CHECKING, Any, Literal, cast
import streamlit.elements.lib.dicttools as dicttools
from streamlit.elements import arrow
from streamlit.elements.arrow import Data
from streamlit.errors import StreamlitAPIException
from streamlit.proto.ArrowVegaLiteCha... | Construct a Vega-Lite chart object. See DeltaGenerator.vega_lite_chart for docs. |
178,372 | from __future__ import annotations
import io
import re
from pathlib import Path
from typing import TYPE_CHECKING, Dict, Final, Union, cast
from typing_extensions import TypeAlias
import streamlit as st
from streamlit import runtime, type_util, url_util
from streamlit.elements.lib.subtitle_utils import process_subtitle_... | Marshalls a video proto, using url processors as needed. Parameters ---------- coordinates : str proto : the proto to fill. Must have a string field called "data". data : str, bytes, BytesIO, numpy.ndarray, or file opened with io.open(). Raw video data or a string with a URL pointing to the video to load. Includes supp... |
178,373 | from __future__ import annotations
import io
import re
from pathlib import Path
from typing import TYPE_CHECKING, Dict, Final, Union, cast
from typing_extensions import TypeAlias
import streamlit as st
from streamlit import runtime, type_util, url_util
from streamlit.elements.lib.subtitle_utils import process_subtitle_... | Marshalls an audio proto, using data and url processors as needed. Parameters ---------- coordinates : str proto : The proto to fill. Must have a string field called "url". data : str, bytes, BytesIO, numpy.ndarray, or file opened with io.open() Raw audio data or a string with a URL pointing to the file to load. If pas... |
178,374 | from __future__ import annotations
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Union, cast
from typing_extensions import TypeAlias
from streamlit import type_util
from streamlit.elements.lib.column_config_utils import (
INDEX_IDENTIFIER,
ColumnConfigMappingInput,
apply_data_specific_configs... | Marshall pandas.DataFrame into an Arrow proto. Parameters ---------- proto : proto.Arrow Output. The protobuf for Streamlit Arrow proto. data : pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, pyspark.sql.DataFrame, snowflake.snowpark.DataFrame, Iterable, dict, or None Something that is or can be converte... |
178,375 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class ColumnConfig(TypedDict, total=False):
"... | Configure a generic column in ``st.dataframe`` or ``st.data_editor``. The type of the column will be automatically inferred from the data type. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. To change the type of the column and enable type-specific configurat... |
178,376 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class NumberColumnConfig(TypedDict):
type: Li... | Configure a number column in ``st.dataframe`` or ``st.data_editor``. This is the default column type for integer and float values. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. When used with ``st.data_editor``, editing will be enabled with a numeric input w... |
178,377 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class TextColumnConfig(TypedDict):
type: Lite... | r"""Configure a text column in ``st.dataframe`` or ``st.data_editor``. This is the default column type for string values. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. When used with ``st.data_editor``, editing will be enabled with a text input widget. Param... |
178,378 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class LinkColumnConfig(TypedDict):
type: Lite... | Configure a link column in ``st.dataframe`` or ``st.data_editor``. The cell values need to be string and will be shown as clickable links. This command needs to be used in the column_config parameter of ``st.dataframe`` or ``st.data_editor``. When used with ``st.data_editor``, editing will be enabled with a text input ... |
178,379 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class CheckboxColumnConfig(TypedDict):
type: ... | Configure a checkbox column in ``st.dataframe`` or ``st.data_editor``. This is the default column type for boolean values. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. When used with ``st.data_editor``, editing will be enabled with a checkbox widget. Parame... |
178,380 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class SelectboxColumnConfig(TypedDict):
type:... | Configure a selectbox column in ``st.dataframe`` or ``st.data_editor``. This is the default column type for Pandas categorical values. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. When used with ``st.data_editor``, editing will be enabled with a selectbox w... |
178,381 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class BarChartColumnConfig(TypedDict):
type: ... | Configure a bar chart column in ``st.dataframe`` or ``st.data_editor``. Cells need to contain a list of numbers. Chart columns are not editable at the moment. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. Parameters ---------- label: str or None The label sh... |
178,382 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class LineChartColumnConfig(TypedDict):
type:... | Configure a line chart column in ``st.dataframe`` or ``st.data_editor``. Cells need to contain a list of numbers. Chart columns are not editable at the moment. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. Parameters ---------- label: str or None The label s... |
178,383 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class AreaChartColumnConfig(TypedDict):
type:... | Configure an area chart column in ``st.dataframe`` or ``st.data_editor``. Cells need to contain a list of numbers. Chart columns are not editable at the moment. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. Parameters ---------- label: str or None The label ... |
178,384 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class ImageColumnConfig(TypedDict):
type: Lit... | Configure an image column in ``st.dataframe`` or ``st.data_editor``. The cell values need to be one of: * A URL to fetch the image from. This can also be a relative URL of an image deployed via `static file serving <https://docs.streamlit.io/library/advanced-features/static-file-serving>`_. Note that you can NOT use an... |
178,385 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class ListColumnConfig(TypedDict):
type: Lite... | Configure a list column in ``st.dataframe`` or ``st.data_editor``. This is the default column type for list-like values. List columns are not editable at the moment. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. Parameters ---------- label: str or None The l... |
178,386 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class DatetimeColumnConfig(TypedDict):
type: ... | Configure a datetime column in ``st.dataframe`` or ``st.data_editor``. This is the default column type for datetime values. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. When used with ``st.data_editor``, editing will be enabled with a datetime picker widget... |
178,387 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class TimeColumnConfig(TypedDict):
type: Lite... | Configure a time column in ``st.dataframe`` or ``st.data_editor``. This is the default column type for time values. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. When used with ``st.data_editor``, editing will be enabled with a time picker widget. Parameters... |
178,388 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class DateColumnConfig(TypedDict):
type: Lite... | Configure a date column in ``st.dataframe`` or ``st.data_editor``. This is the default column type for date values. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. When used with ``st.data_editor``, editing will be enabled with a date picker widget. Parameters... |
178,389 | from __future__ import annotations
import datetime
from typing import Iterable, Literal, TypedDict
from typing_extensions import NotRequired, TypeAlias
from streamlit.runtime.metrics_util import gather_metrics
ColumnWidth: TypeAlias = Literal["small", "medium", "large"]
class ProgressColumnConfig(TypedDict):
type: ... | Configure a progress column in ``st.dataframe`` or ``st.data_editor``. Cells need to contain a number. Progress columns are not editable at the moment. This command needs to be used in the ``column_config`` parameter of ``st.dataframe`` or ``st.data_editor``. Parameters ---------- label : str or None The label shown at... |
178,390 | from __future__ import annotations
import json
from enum import Enum
from typing import TYPE_CHECKING, Dict, Final, Literal, Mapping, Union
from typing_extensions import TypeAlias
from streamlit.elements.lib.column_types import ColumnConfig, ColumnType
from streamlit.elements.lib.dicttools import remove_none_values
fro... | Determine the schema of a dataframe. Parameters ---------- data_df : pd.DataFrame The dataframe to determine the schema of. arrow_schema : pa.Schema The Arrow schema of the dataframe. Returns ------- DataframeSchema A mapping that contains the detected data type for the index and columns. The key is the column name in ... |
178,391 | from __future__ import annotations
import json
from enum import Enum
from typing import TYPE_CHECKING, Dict, Final, Literal, Mapping, Union
from typing_extensions import TypeAlias
from streamlit.elements.lib.column_types import ColumnConfig, ColumnType
from streamlit.elements.lib.dicttools import remove_none_values
fro... | Transforms a user-provided column config mapping into a valid column config mapping that can be used by the frontend. Parameters ---------- column_config: dict or None The user-provided column config mapping. Returns ------- dict The transformed column config mapping. |
178,392 | from __future__ import annotations
import json
from enum import Enum
from typing import TYPE_CHECKING, Dict, Final, Literal, Mapping, Union
from typing_extensions import TypeAlias
from streamlit.elements.lib.column_types import ColumnConfig, ColumnType
from streamlit.elements.lib.dicttools import remove_none_values
fro... | Apply data specific configurations to the provided dataframe. This will apply inplace changes to the dataframe and the column configurations depending on the data format. Parameters ---------- columns_config : ColumnConfigMapping A mapping of column names/ids to column configurations. data_df : pd.DataFrame The datafra... |
178,393 | from __future__ import annotations
import json
from enum import Enum
from typing import TYPE_CHECKING, Dict, Final, Literal, Mapping, Union
from typing_extensions import TypeAlias
from streamlit.elements.lib.column_types import ColumnConfig, ColumnType
from streamlit.elements.lib.dicttools import remove_none_values
fro... | Marshall the column config into the Arrow proto. Parameters ---------- proto : ArrowProto The proto to marshall into. column_config_mapping : ColumnConfigMapping The column config to marshall. |
178,394 | from __future__ import annotations
import contextlib
The provided code snippet includes necessary dependencies for implementing the `configure_streamlit_plotly_theme` function. Write a Python function `def configure_streamlit_plotly_theme() -> None` to solve the following problem:
Configure the Streamlit chart theme f... | Configure the Streamlit chart theme for Plotly. The theme is only configured if Plotly is installed. |
178,395 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Callable, Generic, Sequence, cast, overload
from streamlit.elements.form import current_form_id
from streamlit.elements.utils import (
check_callback_rules,
check_session_state... | null |
178,396 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Callable, Generic, Sequence, cast, overload
from streamlit.elements.form import current_form_id
from streamlit.elements.utils import (
check_callback_rules,
check_session_state... | null |
178,397 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Callable, Generic, Sequence, cast, overload
from streamlit.elements.form import current_form_id
from streamlit.elements.utils import (
check_callback_rules,
check_session_state... | Perform validation checks and return indices based on the default values. |
178,398 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Callable, Generic, Sequence, cast, overload
from streamlit.elements.form import current_form_id
from streamlit.elements.utils import (
check_callback_rules,
check_session_state... | null |
178,399 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Callable, Generic, Sequence, cast, overload
from streamlit.elements.form import current_form_id
from streamlit.elements.utils import (
check_callback_rules,
check_session_state... | null |
178,400 | from __future__ import annotations
from dataclasses import dataclass
from enum import Enum
from typing import TYPE_CHECKING, Literal, cast
from streamlit import runtime
from streamlit.elements.form import is_in_form
from streamlit.elements.image import AtomicImage, WidthBehaviour, image_to_url
from streamlit.elements.u... | Detects the avatar type and prepares the avatar data for the frontend. Parameters ---------- avatar : The avatar that was provided by the user. delta_path : str The delta path is used as media ID when a local image is served via the media file manager. Returns ------- Tuple[AvatarType, str] The detected avatar type and... |
178,401 | from __future__ import annotations
import json
from dataclasses import dataclass
from decimal import Decimal
from typing import (
TYPE_CHECKING,
Any,
Dict,
Final,
Iterable,
List,
Literal,
Mapping,
Set,
Tuple,
TypedDict,
TypeVar,
Union,
cast,
overload,
)
from t... | Apply edits to the provided dataframe (inplace). This includes cell edits, row additions and row deletions. Parameters ---------- df : pd.DataFrame The dataframe to apply the edits to. data_editor_state : EditingState The editing state of the data editor component. dataframe_schema: DataframeSchema The schema of the da... |
178,402 | from __future__ import annotations
import json
from dataclasses import dataclass
from decimal import Decimal
from typing import (
TYPE_CHECKING,
Any,
Dict,
Final,
Iterable,
List,
Literal,
Mapping,
Set,
Tuple,
TypedDict,
TypeVar,
Union,
cast,
overload,
)
from t... | Check if the index is supported by the data editor component. Parameters ---------- df_index : pd.Index The index to check. Returns ------- bool True if the index is supported, False otherwise. |
178,403 | from __future__ import annotations
import json
from dataclasses import dataclass
from decimal import Decimal
from typing import (
TYPE_CHECKING,
Any,
Dict,
Final,
Iterable,
List,
Literal,
Mapping,
Set,
Tuple,
TypedDict,
TypeVar,
Union,
cast,
overload,
)
from t... | Fix the column headers of the provided dataframe inplace to work correctly for data editing. |
178,404 | from __future__ import annotations
import json
from dataclasses import dataclass
from decimal import Decimal
from typing import (
TYPE_CHECKING,
Any,
Dict,
Final,
Iterable,
List,
Literal,
Mapping,
Set,
Tuple,
TypedDict,
TypeVar,
Union,
cast,
overload,
)
from t... | Check if the column names in the provided dataframe are valid. It's not allowed to have duplicate column names or column names that are named ``_index``. If the column names are not valid, a ``StreamlitAPIException`` is raised. |
178,405 | from __future__ import annotations
import json
from dataclasses import dataclass
from decimal import Decimal
from typing import (
TYPE_CHECKING,
Any,
Dict,
Final,
Iterable,
List,
Literal,
Mapping,
Set,
Tuple,
TypedDict,
TypeVar,
Union,
cast,
overload,
)
from t... | Check column type to data type compatibility. Iterates the index and all columns of the dataframe to check if the configured column types are compatible with the underlying data types. Parameters ---------- data_df : pd.DataFrame The dataframe to check the type compatibilities for. columns_config : ColumnConfigMapping ... |
178,406 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, List, Literal, Sequence, Union, cast, overload
from typing_extensions import TypeAlias
from streamlit import config
from streamlit.elements.form import current_form_id
from streamlit.elemen... | null |
178,407 | from __future__ import annotations
import io
import os
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, BinaryIO, Final, Literal, TextIO, Union, cast
from typing_extensions import TypeAlias
from streamlit import runtime, source_util
from streamlit.elements.form import curr... | null |
178,408 | from __future__ import annotations
import re
from dataclasses import dataclass
from datetime import date, datetime, time, timedelta
from textwrap import dedent
from typing import (
TYPE_CHECKING,
Any,
Final,
Literal,
Sequence,
Tuple,
Union,
cast,
overload,
)
from typing_extensions im... | null |
178,409 | from __future__ import annotations
import re
from dataclasses import dataclass
from datetime import date, datetime, time, timedelta
from textwrap import dedent
from typing import (
TYPE_CHECKING,
Any,
Final,
Literal,
Sequence,
Tuple,
Union,
cast,
overload,
)
from typing_extensions im... | null |
178,410 | from __future__ import annotations
import re
from dataclasses import dataclass
from datetime import date, datetime, time, timedelta
from textwrap import dedent
from typing import (
TYPE_CHECKING,
Any,
Final,
Literal,
Sequence,
Tuple,
Union,
cast,
overload,
)
from typing_extensions im... | null |
178,411 | from __future__ import annotations
from dataclasses import dataclass
from datetime import date, datetime, time, timedelta, timezone, tzinfo
from numbers import Integral, Real
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Final, Sequence, Tuple, TypeVar, Union, cast
from typing_extensions import Typ... | null |
178,412 | from __future__ import annotations
from dataclasses import dataclass
from datetime import date, datetime, time, timedelta, timezone, tzinfo
from numbers import Integral, Real
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Final, Sequence, Tuple, TypeVar, Union, cast
from typing_extensions import Typ... | null |
178,413 | from __future__ import annotations
from dataclasses import dataclass
from datetime import date, datetime, time, timedelta, timezone, tzinfo
from numbers import Integral, Real
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Final, Sequence, Tuple, TypeVar, Union, cast
from typing_extensions import Typ... | null |
178,414 | from __future__ import annotations
from dataclasses import dataclass
from datetime import date, datetime, time, timedelta, timezone, tzinfo
from numbers import Integral, Real
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Final, Sequence, Tuple, TypeVar, Union, cast
from typing_extensions import Typ... | Restore times/datetimes to original timezone (dates are always naive) |
178,415 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Any, Callable, Generic, Sequence, Tuple, cast
from typing_extensions import TypeGuard
from streamlit.elements.form import current_form_id
from streamlit.elements.utils import (
check_ca... | null |
178,416 | from __future__ import annotations
import ast
import contextlib
import inspect
import re
import types
from typing import TYPE_CHECKING, Any, Final, cast
import streamlit
from streamlit.proto.DocString_pb2 import DocString as DocStringProto
from streamlit.proto.DocString_pb2 import Member as MemberProto
from streamlit.r... | Construct a DocString object. See DeltaGenerator.help for docs. |
178,417 | from __future__ import annotations
from contextlib import nullcontext
from datetime import date
from enum import Enum
from typing import TYPE_CHECKING, Any, Collection, Literal, Sequence, cast
import streamlit.elements.arrow_vega_lite as arrow_vega_lite
from streamlit import type_util
from streamlit.color_util import (... | Function to use the chart's type, data columns and indices to figure out the chart's spec. |
178,418 | from __future__ import annotations
from contextlib import nullcontext
from datetime import date
from enum import Enum
from typing import TYPE_CHECKING, Any, Collection, Literal, Sequence, cast
import streamlit.elements.arrow_vega_lite as arrow_vega_lite
from streamlit import type_util
from streamlit.color_util import (... | Marshall chart's data into proto. |
178,419 | from __future__ import annotations
import io
from typing import TYPE_CHECKING, Any, cast
import streamlit.elements.image as image_utils
from streamlit import config
from streamlit.errors import StreamlitDeprecationWarning
from streamlit.proto.Image_pb2 import ImageList as ImageListProto
from streamlit.runtime.metrics_u... | null |
178,420 | from __future__ import annotations
import json
import urllib.parse
from typing import TYPE_CHECKING, Any, Dict, List, Literal, Union, cast
from typing_extensions import TypeAlias
from streamlit import type_util
from streamlit.elements.lib.streamlit_plotly_theme import (
configure_streamlit_plotly_theme,
)
from stre... | Marshall a proto with a Plotly spec. See DeltaGenerator.plotly_chart for docs. |
178,421 | from __future__ import annotations
import textwrap
from typing import TYPE_CHECKING, Literal, NamedTuple, cast
from streamlit import runtime
from streamlit.errors import StreamlitAPIException
from streamlit.proto import Block_pb2
from streamlit.runtime.metrics_util import gather_metrics
from streamlit.runtime.scriptrun... | null |
178,422 | from __future__ import annotations
from typing import TYPE_CHECKING, cast
from streamlit.errors import StreamlitAPIException
from streamlit.proto.Toast_pb2 import Toast as ToastProto
from streamlit.runtime.metrics_util import gather_metrics
from streamlit.string_util import clean_text, validate_emoji
from streamlit.typ... | null |
178,423 | from __future__ import annotations
from typing import TYPE_CHECKING, cast
from streamlit.proto.IFrame_pb2 import IFrame as IFrameProto
from streamlit.runtime.metrics_util import gather_metrics
The provided code snippet includes necessary dependencies for implementing the `marshall` function. Write a Python function `d... | Marshalls data into an IFrame proto. These parameters correspond directly to <iframe> attributes, which are described in more detail at https://developer.mozilla.org/en-US/docs/Web/HTML/Element/iframe. Parameters ---------- proto : IFrame protobuf The protobuf object to marshall data into. src : str The URL of the page... |
178,424 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Literal, Union, cast
from typing_extensions import TypeAlias
from streamlit.elements.utils import get_label_visibility_proto_value
from streamlit.errors import StreamlitAPIException
from st... | null |
178,425 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Literal, Union, cast
from typing_extensions import TypeAlias
from streamlit.elements.utils import get_label_visibility_proto_value
from streamlit.errors import StreamlitAPIException
from st... | null |
178,426 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Literal, Union, cast
from typing_extensions import TypeAlias
from streamlit.elements.utils import get_label_visibility_proto_value
from streamlit.errors import StreamlitAPIException
from st... | null |
178,427 | from __future__ import annotations
from dataclasses import dataclass
from textwrap import dedent
from typing import TYPE_CHECKING, Literal, Union, cast
from typing_extensions import TypeAlias
from streamlit.elements.utils import get_label_visibility_proto_value
from streamlit.errors import StreamlitAPIException
from st... | null |
178,428 | from __future__ import annotations
import hashlib
from typing import TYPE_CHECKING, Union, cast
from typing_extensions import TypeAlias
from streamlit import type_util
from streamlit.errors import StreamlitAPIException
from streamlit.proto.GraphVizChart_pb2 import GraphVizChart as GraphVizChartProto
from streamlit.runt... | Construct a GraphViz chart object. See DeltaGenerator.graphviz_chart for docs. |
178,429 | from __future__ import annotations
import hashlib
import json
from typing import TYPE_CHECKING, Any, Final, Mapping, cast
from streamlit import config
from streamlit.proto.DeckGlJsonChart_pb2 import DeckGlJsonChart as PydeckProto
from streamlit.runtime.metrics_util import gather_metrics
from streamlit.util import HASHL... | null |
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