142 lines
4.7 KiB
Python
142 lines
4.7 KiB
Python
# Copyright (c) Streamlit Inc. (2018-2022) Snowflake Inc. (2022-2025)
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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 __future__ import annotations
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from typing import Any, Callable, Generic, TypeVar
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from streamlit import type_util
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from streamlit.errors import MarkdownFormattedException, StreamlitAPIException
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from streamlit.runtime.caching.cache_type import CacheType, get_decorator_api_name
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CACHE_DOCS_URL = "https://docs.streamlit.io/develop/concepts/architecture/caching"
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def get_cached_func_name_md(func: Any) -> str:
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"""Get markdown representation of the function name."""
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if hasattr(func, "__name__"):
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return f"`{func.__name__}()`"
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if hasattr(type(func), "__name__"):
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return f"`{type(func).__name__}`"
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return f"`{type(func)}`"
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def get_return_value_type(return_value: Any) -> str:
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if hasattr(return_value, "__module__") and hasattr(type(return_value), "__name__"):
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return f"`{return_value.__module__}.{type(return_value).__name__}`"
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return get_cached_func_name_md(return_value)
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class UnhashableTypeError(Exception):
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pass
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class UnhashableParamError(StreamlitAPIException):
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def __init__(
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self,
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cache_type: CacheType,
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func: Callable[..., Any],
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arg_name: str | None,
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arg_value: Any,
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orig_exc: BaseException,
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) -> None:
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msg = self._create_message(cache_type, func, arg_name, arg_value)
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super().__init__(msg)
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self.with_traceback(orig_exc.__traceback__)
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@staticmethod
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def _create_message(
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cache_type: CacheType,
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func: Callable[..., Any],
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arg_name: str | None,
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arg_value: Any,
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) -> str:
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arg_name_str = arg_name if arg_name is not None else "(unnamed)"
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arg_type = type_util.get_fqn_type(arg_value)
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func_name = func.__name__
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arg_replacement_name = f"_{arg_name}" if arg_name is not None else "_arg"
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return (
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f"""
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Cannot hash argument '{arg_name_str}' (of type `{arg_type}`) in '{func_name}'.
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To address this, you can tell Streamlit not to hash this argument by adding a
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leading underscore to the argument's name in the function signature:
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```
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@st.{get_decorator_api_name(cache_type)}
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def {func_name}({arg_replacement_name}, ...):
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...
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```
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"""
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).strip("\n")
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class CacheKeyNotFoundError(Exception):
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pass
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class CacheError(Exception):
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pass
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class CacheReplayClosureError(StreamlitAPIException):
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def __init__(
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self,
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cache_type: CacheType,
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cached_func: Callable[..., Any],
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) -> None:
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func_name = get_cached_func_name_md(cached_func)
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decorator_name = get_decorator_api_name(cache_type)
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msg = (
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f"""
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While running {func_name}, a streamlit element is called on some layout block
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created outside the function. This is incompatible with replaying the cached
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effect of that element, because the referenced block might not exist when
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the replay happens.
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How to fix this:
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* Move the creation of $THING inside {func_name}.
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* Move the call to the streamlit element outside of {func_name}.
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* Remove the `@st.{decorator_name}` decorator from {func_name}.
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"""
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).strip("\n")
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super().__init__(msg)
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R = TypeVar("R")
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class UnserializableReturnValueError(MarkdownFormattedException, Generic[R]):
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def __init__(self, func: Callable[..., R], return_value: R) -> None:
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MarkdownFormattedException.__init__(
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self,
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f"""
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Cannot serialize the return value (of type {get_return_value_type(return_value)})
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in {get_cached_func_name_md(func)}. `st.cache_data` uses
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[pickle](https://docs.python.org/3/library/pickle.html) to serialize the
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function's return value and safely store it in the cache
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without mutating the original object. Please convert the return value to a
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pickle-serializable type. If you want to cache unserializable objects such
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as database connections or Tensorflow sessions, use `st.cache_resource`
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instead (see [our docs]({CACHE_DOCS_URL}) for differences).""",
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)
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class UnevaluatedDataFrameError(StreamlitAPIException):
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"""Used to display a message about uncollected dataframe being used."""
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pass
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