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Parameters ---------- decorator_metric_name The metric name to record for decorator usage. `@st.experimental_singleton` is deprecated, but we're still supporting it and tracking its usage separately from `@st.cache_resource`. deprecation_warning An optional deprecation warning to show when the API is accessed. N)r _decorator_deprecation_warning)r4ryrzs r(r5zCacheResourceAPI.__init__s&$))>PP$7!!!r*F.)boundr_r$cdSr.r')r4r_s r(__call__zCacheResourceAPI.__call__s r*TFr;r9rar=experimental_allow_widgetsrdr;r<r9rcrarbr=r"rr%rdreCallable[[F], F]cdSr.r')r4r;r9rar=rrds r(rzCacheResourceAPI.__call__s  r*F | Nonec :||||||||S)Nr)r}r4r_r;r9rar=rrds r(rzCacheResourceAPI.__call__s4 #%'A!   r*)rdc || fdSttttj|S)aDecorator to cache functions that return global resources (e.g. database connections, ML models). Cached objects are shared across all users, sessions, and reruns. They must be thread-safe because they can be accessed from multiple threads concurrently. If thread safety is an issue, consider using ``st.session_state`` to store resources per session instead. You can clear a function's cache with ``func.clear()`` or clear the entire cache with ``st.cache_resource.clear()``. To cache data, use ``st.cache_data`` instead. Learn more about caching at https://docs.streamlit.io/library/advanced-features/caching. Parameters ---------- func : callable The function that creates the cached resource. Streamlit hashes the function's source code. ttl : float, timedelta, str, or None The maximum time to keep an entry in the cache. Can be one of: * ``None`` if cache entries should never expire (default). * A number specifying the time in seconds. * A string specifying the time in a format supported by `Pandas's Timedelta constructor `_, e.g. ``"1d"``, ``"1.5 days"``, or ``"1h23s"``. * A ``timedelta`` object from `Python's built-in datetime library `_, e.g. ``timedelta(days=1)``. max_entries : int or None The maximum number of entries to keep in the cache, or None for an unbounded cache. When a new entry is added to a full cache, the oldest cached entry will be removed. Defaults to None. show_spinner : bool or str Enable the spinner. Default is True to show a spinner when there is a "cache miss" and the cached resource is being created. If string, value of show_spinner param will be used for spinner text. validate : callable or None An optional validation function for cached data. ``validate`` is called each time the cached value is accessed. It receives the cached value as its only parameter and it must return a boolean. If ``validate`` returns False, the current cached value is discarded, and the decorated function is called to compute a new value. This is useful e.g. to check the health of database connections. experimental_allow_widgets : bool Allow widgets to be used in the cached function. Defaults to False. Support for widgets in cached functions is currently experimental. Setting this parameter to True may lead to excessive memory use since the widget value is treated as an additional input parameter to the cache. We may remove support for this option at any time without notice. hash_funcs : dict or None Mapping of types or fully qualified names to hash functions. This is used to override the behavior of the hasher inside Streamlit's caching mechanism: when the hasher encounters an object, it will first check to see if its type matches a key in this dict and, if so, will use the provided function to generate a hash for it. See below for an example of how this can be used. Example ------- >>> import streamlit as st >>> >>> @st.cache_resource ... def get_database_session(url): ... # Create a database session object that points to the URL. ... return session ... >>> s1 = get_database_session(SESSION_URL_1) >>> # Actually executes the function, since this is the first time it was >>> # encountered. >>> >>> s2 = get_database_session(SESSION_URL_1) >>> # Does not execute the function. Instead, returns its previously computed >>> # value. This means that now the connection object in s1 is the same as in s2. >>> >>> s3 = get_database_session(SESSION_URL_2) >>> # This is a different URL, so the function executes. By default, all parameters to a cache_resource function must be hashable. Any parameter whose name begins with ``_`` will not be hashed. You can use this as an "escape hatch" for parameters that are not hashable: >>> import streamlit as st >>> >>> @st.cache_resource ... def get_database_session(_sessionmaker, url): ... # Create a database connection object that points to the URL. ... return connection ... >>> s1 = get_database_session(create_sessionmaker(), DATA_URL_1) >>> # Actually executes the function, since this is the first time it was >>> # encountered. >>> >>> s2 = get_database_session(create_sessionmaker(), DATA_URL_1) >>> # Does not execute the function. Instead, returns its previously computed >>> # value - even though the _sessionmaker parameter was different >>> # in both calls. 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