109 lines
3.7 KiB
Python
109 lines
3.7 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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import itertools
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from abc import abstractmethod
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from typing import TYPE_CHECKING, NamedTuple, Protocol, runtime_checkable
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if TYPE_CHECKING:
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from streamlit.proto.openmetrics_data_model_pb2 import Metric as MetricProto
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class CacheStat(NamedTuple):
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"""Describes a single cache entry.
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Properties
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----------
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category_name : str
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A human-readable name for the cache "category" that the entry belongs
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to - e.g. "st.memo", "session_state", etc.
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cache_name : str
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A human-readable name for cache instance that the entry belongs to.
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For "st.memo" and other function decorator caches, this might be the
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name of the cached function. If the cache category doesn't have
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multiple separate cache instances, this can just be the empty string.
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byte_length : int
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The entry's memory footprint in bytes.
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"""
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category_name: str
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cache_name: str
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byte_length: int
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def to_metric_str(self) -> str:
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return f'cache_memory_bytes{{cache_type="{self.category_name}",cache="{self.cache_name}"}} {self.byte_length}'
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def marshall_metric_proto(self, metric: MetricProto) -> None:
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"""Fill an OpenMetrics `Metric` protobuf object."""
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label = metric.labels.add()
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label.name = "cache_type"
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label.value = self.category_name
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label = metric.labels.add()
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label.name = "cache"
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label.value = self.cache_name
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metric_point = metric.metric_points.add()
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metric_point.gauge_value.int_value = self.byte_length
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def group_stats(stats: list[CacheStat]) -> list[CacheStat]:
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"""Group a list of CacheStats by category_name and cache_name and sum byte_length."""
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def key_function(individual_stat: CacheStat) -> tuple[str, str]:
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return individual_stat.category_name, individual_stat.cache_name
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result: list[CacheStat] = []
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sorted_stats = sorted(stats, key=key_function)
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grouped_stats = itertools.groupby(sorted_stats, key=key_function)
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for (category_name, cache_name), single_group_stats in grouped_stats:
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result.append(
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CacheStat(
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category_name=category_name,
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cache_name=cache_name,
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byte_length=sum(item.byte_length for item in single_group_stats),
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)
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)
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return result
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@runtime_checkable
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class CacheStatsProvider(Protocol):
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@abstractmethod
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def get_stats(self) -> list[CacheStat]:
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raise NotImplementedError
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class StatsManager:
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def __init__(self) -> None:
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self._cache_stats_providers: list[CacheStatsProvider] = []
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def register_provider(self, provider: CacheStatsProvider) -> None:
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"""Register a CacheStatsProvider with the manager.
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This function is not thread-safe. Call it immediately after
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creation.
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"""
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self._cache_stats_providers.append(provider)
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def get_stats(self) -> list[CacheStat]:
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"""Return a list containing all stats from each registered provider."""
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all_stats: list[CacheStat] = []
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for provider in self._cache_stats_providers:
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all_stats.extend(provider.get_stats())
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return all_stats
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