5inbUdZddlmZddlZddlZddlmZmZmZm Z m Z m Z m Z m Z ddlmZddlZddlmZddlmZddlmZdd lmZmZdd lmZdd lmZmZmZm Z m!Z!m"Z"dd l#m$Z$m%Z%m&Z&dd l'm(Z(m)Z)m*Z*m+Z+m,Z,ddl-m.Z.ddl/m0Z0ddl1m2Z2ddl3m4Z4m5Z5m6Z6m7Z7ddl8m9Z9erddl:m;Z;mZ>ddl?m@Z@eeAZBdeCd<e$ejZEe ddzZFdeCd<edZGe dZHGddeeGeHfZIGdd e6ZJeJZKd'd!ZLd(d"ZMGd#d$ZNGd%d&eeHZOy))z%@st.cache_data: pickle-based caching.) annotationsN) TYPE_CHECKINGAnyFinalLiteral TypeAliasTypeVarcastoverload) ParamSpec)runtime)StreamlitAPIException) get_logger) CacheErrorCacheKeyNotFoundError) CacheType)Cache CachedFuncCachedFuncInfo CacheScopeget_session_id_or_throwmake_cached_func_wrapper)CachedMessageReplayContext CachedResultMsgData) CacheStorageCacheStorageContextCacheStorageErrorCacheStorageKeyNotFoundErrorCacheStorageManager)InvalidCacheStorageContextError)MemoryCacheStorageManager)gather_metrics)CACHE_MEMORY_FAMILY CacheStat StatsProvidergroup_cache_stats)time_to_seconds)CallableSequence) timedelta) HashFuncsDictr_LOGGERdiskrCachePersistTypePRceZdZUdZded<ded<ded< d dfd Zedd Zedd Zedd Z dd Z dd Z xZ S)CachedDataFuncInfoz;Implements the CachedFuncInfo interface for @st.cache_data.r/persist int | None max_entriesfloat | timedelta | str | Nonettlc xt ||||||||_||_||_|j y)N) hash_funcs show_spinner show_timescope)super__init__r4r6r8validate_params) selffuncr4r6r8r;r<r:r= __class__s r/home/obispo/Crisostomo_bridge/mision_env/lib/python3.12/site-packages/streamlit/runtime/caching/cache_data_api.pyr?zCachedDataFuncInfo.__init__dsJ  !%   & c"tjSN)rDATArAs rD cache_typezCachedDataFuncInfo.cache_type|s ~~rEctSrG)CACHE_DATA_MESSAGE_REPLAY_CTXrIs rDcached_message_replay_ctxz,CachedDataFuncInfo.cached_message_replay_ctxs,,rEc`|jjd|jjS)z.A human-readable name for the cached function..)rB __module__ __qualname__rIs rD display_namezCachedDataFuncInfo.display_names+))&&'q)?)?(@AArEctj||j|j|j|j |j S)N)keyr4r6r8rRr=) _data_caches get_cacher4r6r8rRr=)rA function_keys rDget_function_cachez%CachedDataFuncInfo.get_function_cachesD%%LL((**** &  rEctj|jj|j|j |j y)z Validate the params passed to @st.cache_data are compatible with cache storage. When called, this method could log warnings if cache params are invalid for current storage. ) function_namer4r6r8N)rUvalidate_cache_paramsrB__name__r4r6r8rIs rDr@z"CachedDataFuncInfo.validate_paramss; **)),,LL(( + rE)FNglobal)rBCallable[P, R]r4r/r6r5r8r7r; bool | strr<boolr:HashFuncsDict | Noner=rreturnNone)rbr)rbr)rbstr)rWrdrbzCache[R]rbrc) r\rPrQ__doc____annotations__r?propertyrJrMrRrXr@ __classcell__rCs@rDr3r3]sE  '' +/$"  ,  ! ) 0--BB   rEr3ceZdZdZd dZed dZ d ddZddZd dZ d ddZ dd Z dd Z dd Z y) DataCachesz Manages all DataCache instances.cDtj|_i|_yrG) threadingLock _caches_lock_function_cachesrIs rDr?zDataCaches.__init__s%NN,MOrEctfSrG)r$rIs rDstats_familieszDataCaches.stats_familiess #%%rEc t|d}|dk(rd}n t}|j5|jj |} | ix} |j|<| j |} | 8| j |k(r)| j |k(r| j|k(r | cdddS| 3tjd||||| jjtjd|||||j|||||} |j} | j| } t|| ||||} | |j||<| cdddS#1swYyxYw) aReturn the mem cache for the given key. If it doesn't exist, create a new one with the given params. 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KL(**rEre)rbz Sequence[str])r])rTrdr4r/r6r5r8$int | float | timedelta | str | NonerRrdr=rrbzDataCache[Any]rrdrbrcrGrzSequence[str] | Nonerbdict[str, list[CacheStat]]) rZrdr4r/r6r5r8rrbrc) rWrdrZrdr4r/rx float | Noner6r5rbr)rbr )r\rPrQrfr?rhrsrVrrrr[r}r~rErDrlrls*P &&%W W"W W 2 W  WW Wr &'"59?1? #?0!!"! ! 2 !  !F   "  "      +rErlc.tj|yr)rUr)rs rDclear_session_cacher|sz*rEctS)z:Return the StatsProvider for all @st.cache_data functions.)rUrrErDget_data_cache_stats_providerrs rEc eZdZdZddZeddZedddddddd dd Z ddddddddd dd Z ddddd  dd Zed ddZ y) CacheDataAPIzjImplements the public st.cache_data API: the @st.cache_data decorator, and st.cache_data.clear(). c:t||j|_y)zCreate a CacheDataAPI instance. Parameters ---------- decorator_metric_name The metric name to record for decorator usage. N)r# _decorator)rAdecorator_metric_names rDr?zCacheDataAPI.__init__s) !4?? rEcyrGr)rArBs rD__call__zCacheDataAPI.__call__sBErENTFr])r8r6r;r<r4r:r=cyrGr)rAr8r6r;r<r4r:r=s rDrzCacheDataAPI.__call__s8;rEc 4|j||||||||S)N)r8r6r4r;r<r:r=)r) rArBr8r6r;r<r4r:r=s rDrzCacheDataAPI.__call__s2 #%!  rE)r<r:r=c  |durd n |durd n| dvrtd|ddvrtd d d  fd } || Stt|  S)a]!Decorator to cache functions that return data (e.g. dataframe transforms, database queries, ML inference). Cached objects can be global or session-scoped. Global cached data is available across all users, sessions, and reruns. Session-scoped cached data is only available in the current session and removed when the session disconnects. Cached objects are stored in "pickled" form, which means that the return value of a cached function must be pickleable. Each caller of the cached function gets its own copy of the cached data. You can clear a function's cache with ``func.clear()`` or clear the entire cache with ``st.cache_data.clear()``. A function's arguments must be hashable to cache it. Streamlit makes a best effort to hash a variety of objects, but the fallback hashing method requires that the argument be pickleable, also. If you have an unhashable argument (like a database connection) or an argument you want to exclude from caching, use an underscore prefix in the argument name. In this case, Streamlit will return a cached value when all other arguments match a previous function call. Alternatively, you can declare custom hashing functions with ``hash_funcs``. Objects cached by ``st.cache_data`` are returned as copies. To cache a shared resource or something you want to mutate in place, use ``st.cache_resource`` instead. To learn more about caching, see `Caching overview `_. .. note:: Caching async functions is not supported. To upvote this feature, see GitHub issue `#8308 `_. Parameters ---------- func : callable The function to cache. 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)``. Note that ``ttl`` will be ignored if ``persist="disk"`` or ``persist=True``. 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 data is being created. If string, value of show_spinner param will be used for spinner text. show_time : bool Whether to show the elapsed time next to the spinner text. If this is ``False`` (default), no time is displayed. If this is ``True``, elapsed time is displayed with a precision of 0.1 seconds. The time format is not configurable. persist : "disk", bool, or None Optional location to persist cached data to. Passing "disk" (or True) will persist the cached data to the local disk. None (or False) will disable persistence. The default is None. 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. scope : "global" or "session" The scope for the data cache. If this is ``"global"`` (default), the data is cached globally. If this is ``"session"``, the data is removed from the cache when the session disconnects. Because a session-scoped cache is cleared when a session disconnects, an unstable network connection can cause the cache to populate multiple times in a single session. If this is a problem, you might consider adjusting the ``server.websocketPingInterval`` configuration option. Example ------- >>> import streamlit as st >>> >>> @st.cache_data ... def fetch_and_clean_data(url): ... # Fetch data from URL here, and then clean it up. ... return data >>> >>> d1 = fetch_and_clean_data(DATA_URL_1) >>> # Actually executes the function, since this is the first time it was >>> # encountered. >>> >>> d2 = fetch_and_clean_data(DATA_URL_1) >>> # Does not execute the function. Instead, returns its previously computed >>> # value. This means that now the data in d1 is the same as in d2. >>> >>> d3 = fetch_and_clean_data(DATA_URL_2) >>> # This is a different URL, so the function executes. To set the ``persist`` parameter, use this command as follows: >>> import streamlit as st >>> >>> @st.cache_data(persist="disk") ... def fetch_and_clean_data(url): ... # Fetch data from URL here, and then clean it up. ... return data By default, all parameters to a cached 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_data ... def fetch_and_clean_data(_db_connection, num_rows): ... # Fetch data from _db_connection here, and then clean it up. ... return data >>> >>> connection = make_database_connection() >>> d1 = fetch_and_clean_data(connection, num_rows=10) >>> # Actually executes the function, since this is the first time it was >>> # encountered. >>> >>> another_connection = make_database_connection() >>> d2 = fetch_and_clean_data(another_connection, num_rows=10) >>> # Does not execute the function. Instead, returns its previously computed >>> # value - even though the _database_connection parameter was different >>> # in both calls. A cached function's cache can be procedurally cleared: >>> import streamlit as st >>> >>> @st.cache_data ... def fetch_and_clean_data(_db_connection, num_rows): ... # Fetch data from _db_connection here, and then clean it up. ... return data >>> >>> fetch_and_clean_data.clear(_db_connection, 50) >>> # Clear the cached entry for the arguments provided. >>> >>> fetch_and_clean_data.clear() >>> # Clear all cached entries for this function. To override the default hashing behavior, pass a custom hash function. You can do that by mapping a type (e.g. ``datetime.datetime``) to a hash function (``lambda dt: dt.isoformat()``) like this: >>> import streamlit as st >>> import datetime >>> >>> @st.cache_data(hash_funcs={datetime.datetime: lambda dt: dt.isoformat()}) ... def convert_to_utc(dt: datetime.datetime): ... return dt.astimezone(datetime.timezone.utc) Alternatively, you can map the type's fully-qualified name (e.g. ``"datetime.datetime"``) to the hash function instead: >>> import streamlit as st >>> import datetime >>> >>> @st.cache_data(hash_funcs={"datetime.datetime": lambda dt: dt.isoformat()}) ... def convert_to_utc(dt: datetime.datetime): ... return dt.astimezone(datetime.timezone.utc) Tr.FN)Nr.zUnsupported persist option 'z#'. Valid values are 'disk' or None.)r]sessionzUnsupported scope option 'z*'. Valid values are 'global' or 'session'.c <tt|S)NrBr4r;r<r6r8r:r=)rr3)fr:r6persist_stringr=r;r<r8s rDwrapperz(CacheDataAPI._decorator..wrappers0+"*!-' +)   rEr)rr^rbCachedFunc[P, R])rrr3) rArBr8r6r;r<r4r:r=rrs ```` `` @rDrzCacheDataAPI._decoratorsH d?#N  !N$N  /'.wi7Z[  - -',UG3]^    <N' &)#'%   rEclear_data_cachesc,tjy)z,Clear all in-memory and on-disk data caches.N)rUrrIs rDrzCacheDataAPI.clears  rE)rrdrbrc)rBr^rbr)r8r7r6r5r;r_r<r`r4CachePersistType | boolr:rar=rrbz,Callable[[Callable[P, R]], CachedFunc[P, R]]rG)rBzCallable[P, R] | Noner8r7r6r5r;r_r<r`r4rr:rar=rrbz?CachedFunc[P, R] | Callable[[Callable[P, R]], CachedFunc[P, R]]re) r\rPrQrfr?r rrr#rrrErDrrs  &EE/3"&#'+/+/$ ;, ; ; ! ;  ;) ;) ; ; 6 ; ;'+ /3"&#'+/+/$ # ,    !   ) )   I 2'+r  +/$r #r , r  r ! r r )r )r r  Ir h'(!)!rErceZdZdZ dfd Z d d dZd dZedd dZd d dZ xZ S)rz:Manages cached values for a single st.cache_data function.cvt|||_||_||_||_||_||_yrG)r>r?rTrRryrxr6r4)rArTryr4r6rxrRrCs rDr?zDataCache.__init__s= ( && rEct|jtr$td|jj SiS)Nr) isinstanceryr&r r)rArs rDrzDataCache.get_statss2 dllM 24dll6L6L6NO O rEc |jj|} tj|}t|ts%|jj|t|S#t$r}tt ||d}~wt $r}t t ||d}~wwxYw#tj$r}t d||d}~wwxYw)zRead a value and messages from the cache. Raise `CacheKeyNotFoundError` if the value doesn't exist, and `CacheError` if the value exists but can't be unpickled. NzFailed to unpickle ) ryrzrrrdrrpickleloadsrrdeleteUnpicklingError)rArT pickled_entryeentryexcs rD read_resultzDataCache.read_results  , LL,,S1M CLL/Ee\2 ##C(+--L, 7'A/Q 6  ,SV$! + ,%% C23%89s B Cs;A*A B1* B.3B B.B))B.1CCC_cache_data_objectcL tjj}tjj}t ||||}t j |}|jj||y#t jtf$r}td||d}~wwxYw)zbWrite a value and associated messages to the cache. 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