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Diffstat (limited to '.venv/lib/python3.12/site-packages/opentelemetry/sdk/trace/sampling.py')
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diff --git a/.venv/lib/python3.12/site-packages/opentelemetry/sdk/trace/sampling.py b/.venv/lib/python3.12/site-packages/opentelemetry/sdk/trace/sampling.py new file mode 100644 index 00000000..fb6990a0 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/opentelemetry/sdk/trace/sampling.py @@ -0,0 +1,453 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" +For general information about sampling, see `the specification <https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/trace/sdk.md#sampling>`_. + +OpenTelemetry provides two types of samplers: + +- `StaticSampler` +- `TraceIdRatioBased` + +A `StaticSampler` always returns the same sampling result regardless of the conditions. Both possible StaticSamplers are already created: + +- Always sample spans: ALWAYS_ON +- Never sample spans: ALWAYS_OFF + +A `TraceIdRatioBased` sampler makes a random sampling result based on the sampling probability given. + +If the span being sampled has a parent, `ParentBased` will respect the parent delegate sampler. Otherwise, it returns the sampling result from the given root sampler. + +Currently, sampling results are always made during the creation of the span. However, this might not always be the case in the future (see `OTEP #115 <https://github.com/open-telemetry/oteps/pull/115>`_). + +Custom samplers can be created by subclassing `Sampler` and implementing `Sampler.should_sample` as well as `Sampler.get_description`. + +Samplers are able to modify the `opentelemetry.trace.span.TraceState` of the parent of the span being created. For custom samplers, it is suggested to implement `Sampler.should_sample` to utilize the +parent span context's `opentelemetry.trace.span.TraceState` and pass into the `SamplingResult` instead of the explicit trace_state field passed into the parameter of `Sampler.should_sample`. + +To use a sampler, pass it into the tracer provider constructor. For example: + +.. code:: python + + from opentelemetry import trace + from opentelemetry.sdk.trace import TracerProvider + from opentelemetry.sdk.trace.export import ( + ConsoleSpanExporter, + SimpleSpanProcessor, + ) + from opentelemetry.sdk.trace.sampling import TraceIdRatioBased + + # sample 1 in every 1000 traces + sampler = TraceIdRatioBased(1/1000) + + # set the sampler onto the global tracer provider + trace.set_tracer_provider(TracerProvider(sampler=sampler)) + + # set up an exporter for sampled spans + trace.get_tracer_provider().add_span_processor( + SimpleSpanProcessor(ConsoleSpanExporter()) + ) + + # created spans will now be sampled by the TraceIdRatioBased sampler + with trace.get_tracer(__name__).start_as_current_span("Test Span"): + ... + +The tracer sampler can also be configured via environment variables ``OTEL_TRACES_SAMPLER`` and ``OTEL_TRACES_SAMPLER_ARG`` (only if applicable). +The list of built-in values for ``OTEL_TRACES_SAMPLER`` are: + + * always_on - Sampler that always samples spans, regardless of the parent span's sampling decision. + * always_off - Sampler that never samples spans, regardless of the parent span's sampling decision. + * traceidratio - Sampler that samples probabilistically based on rate. + * parentbased_always_on - (default) Sampler that respects its parent span's sampling decision, but otherwise always samples. + * parentbased_always_off - Sampler that respects its parent span's sampling decision, but otherwise never samples. + * parentbased_traceidratio - Sampler that respects its parent span's sampling decision, but otherwise samples probabilistically based on rate. + +Sampling probability can be set with ``OTEL_TRACES_SAMPLER_ARG`` if the sampler is traceidratio or parentbased_traceidratio. Rate must be in the range [0.0,1.0]. When not provided rate will be set to +1.0 (maximum rate possible). + +Prev example but with environment variables. Please make sure to set the env ``OTEL_TRACES_SAMPLER=traceidratio`` and ``OTEL_TRACES_SAMPLER_ARG=0.001``. + +.. code:: python + + from opentelemetry import trace + from opentelemetry.sdk.trace import TracerProvider + from opentelemetry.sdk.trace.export import ( + ConsoleSpanExporter, + SimpleSpanProcessor, + ) + + trace.set_tracer_provider(TracerProvider()) + + # set up an exporter for sampled spans + trace.get_tracer_provider().add_span_processor( + SimpleSpanProcessor(ConsoleSpanExporter()) + ) + + # created spans will now be sampled by the TraceIdRatioBased sampler with rate 1/1000. + with trace.get_tracer(__name__).start_as_current_span("Test Span"): + ... + +When utilizing a configurator, you can configure a custom sampler. In order to create a configurable custom sampler, create an entry point for the custom sampler +factory method or function under the entry point group, ``opentelemetry_traces_sampler``. The custom sampler factory method must be of type ``Callable[[str], Sampler]``, taking a single string argument and +returning a Sampler object. The single input will come from the string value of the ``OTEL_TRACES_SAMPLER_ARG`` environment variable. If ``OTEL_TRACES_SAMPLER_ARG`` is not configured, the input will +be an empty string. For example: + +.. code:: python + + setup( + ... + entry_points={ + ... + "opentelemetry_traces_sampler": [ + "custom_sampler_name = path.to.sampler.factory.method:CustomSamplerFactory.get_sampler" + ] + } + ) + # ... + class CustomRatioSampler(Sampler): + def __init__(rate): + # ... + # ... + class CustomSamplerFactory: + @staticmethod + def get_sampler(sampler_argument): + try: + rate = float(sampler_argument) + return CustomSampler(rate) + except ValueError: # In case argument is empty string. + return CustomSampler(0.5) + +In order to configure you application with a custom sampler's entry point, set the ``OTEL_TRACES_SAMPLER`` environment variable to the key name of the entry point. For example, to configured the +above sampler, set ``OTEL_TRACES_SAMPLER=custom_sampler_name`` and ``OTEL_TRACES_SAMPLER_ARG=0.5``. +""" + +import abc +import enum +import os +from logging import getLogger +from types import MappingProxyType +from typing import Optional, Sequence + +# pylint: disable=unused-import +from opentelemetry.context import Context +from opentelemetry.sdk.environment_variables import ( + OTEL_TRACES_SAMPLER, + OTEL_TRACES_SAMPLER_ARG, +) +from opentelemetry.trace import Link, SpanKind, get_current_span +from opentelemetry.trace.span import TraceState +from opentelemetry.util.types import Attributes + +_logger = getLogger(__name__) + + +class Decision(enum.Enum): + # IsRecording() == false, span will not be recorded and all events and attributes will be dropped. + DROP = 0 + # IsRecording() == true, but Sampled flag MUST NOT be set. + RECORD_ONLY = 1 + # IsRecording() == true AND Sampled flag` MUST be set. + RECORD_AND_SAMPLE = 2 + + def is_recording(self): + return self in (Decision.RECORD_ONLY, Decision.RECORD_AND_SAMPLE) + + def is_sampled(self): + return self is Decision.RECORD_AND_SAMPLE + + +class SamplingResult: + """A sampling result as applied to a newly-created Span. + + Args: + decision: A sampling decision based off of whether the span is recorded + and the sampled flag in trace flags in the span context. + attributes: Attributes to add to the `opentelemetry.trace.Span`. + trace_state: The tracestate used for the `opentelemetry.trace.Span`. + Could possibly have been modified by the sampler. + """ + + def __repr__(self) -> str: + return f"{type(self).__name__}({str(self.decision)}, attributes={str(self.attributes)})" + + def __init__( + self, + decision: Decision, + attributes: "Attributes" = None, + trace_state: Optional["TraceState"] = None, + ) -> None: + self.decision = decision + if attributes is None: + self.attributes = MappingProxyType({}) + else: + self.attributes = MappingProxyType(attributes) + self.trace_state = trace_state + + +class Sampler(abc.ABC): + @abc.abstractmethod + def should_sample( + self, + parent_context: Optional["Context"], + trace_id: int, + name: str, + kind: Optional[SpanKind] = None, + attributes: Attributes = None, + links: Optional[Sequence["Link"]] = None, + trace_state: Optional["TraceState"] = None, + ) -> "SamplingResult": + pass + + @abc.abstractmethod + def get_description(self) -> str: + pass + + +class StaticSampler(Sampler): + """Sampler that always returns the same decision.""" + + def __init__(self, decision: "Decision") -> None: + self._decision = decision + + def should_sample( + self, + parent_context: Optional["Context"], + trace_id: int, + name: str, + kind: Optional[SpanKind] = None, + attributes: Attributes = None, + links: Optional[Sequence["Link"]] = None, + trace_state: Optional["TraceState"] = None, + ) -> "SamplingResult": + if self._decision is Decision.DROP: + attributes = None + return SamplingResult( + self._decision, + attributes, + _get_parent_trace_state(parent_context), + ) + + def get_description(self) -> str: + if self._decision is Decision.DROP: + return "AlwaysOffSampler" + return "AlwaysOnSampler" + + +ALWAYS_OFF = StaticSampler(Decision.DROP) +"""Sampler that never samples spans, regardless of the parent span's sampling decision.""" + +ALWAYS_ON = StaticSampler(Decision.RECORD_AND_SAMPLE) +"""Sampler that always samples spans, regardless of the parent span's sampling decision.""" + + +class TraceIdRatioBased(Sampler): + """ + Sampler that makes sampling decisions probabilistically based on `rate`. + + Args: + rate: Probability (between 0 and 1) that a span will be sampled + """ + + def __init__(self, rate: float): + if rate < 0.0 or rate > 1.0: + raise ValueError("Probability must be in range [0.0, 1.0].") + self._rate = rate + self._bound = self.get_bound_for_rate(self._rate) + + # For compatibility with 64 bit trace IDs, the sampler checks the 64 + # low-order bits of the trace ID to decide whether to sample a given trace. + TRACE_ID_LIMIT = (1 << 64) - 1 + + @classmethod + def get_bound_for_rate(cls, rate: float) -> int: + return round(rate * (cls.TRACE_ID_LIMIT + 1)) + + @property + def rate(self) -> float: + return self._rate + + @property + def bound(self) -> int: + return self._bound + + def should_sample( + self, + parent_context: Optional["Context"], + trace_id: int, + name: str, + kind: Optional[SpanKind] = None, + attributes: Attributes = None, + links: Optional[Sequence["Link"]] = None, + trace_state: Optional["TraceState"] = None, + ) -> "SamplingResult": + decision = Decision.DROP + if trace_id & self.TRACE_ID_LIMIT < self.bound: + decision = Decision.RECORD_AND_SAMPLE + if decision is Decision.DROP: + attributes = None + return SamplingResult( + decision, + attributes, + _get_parent_trace_state(parent_context), + ) + + def get_description(self) -> str: + return f"TraceIdRatioBased{{{self._rate}}}" + + +class ParentBased(Sampler): + """ + If a parent is set, applies the respective delegate sampler. + Otherwise, uses the root provided at initialization to make a + decision. + + Args: + root: Sampler called for spans with no parent (root spans). + remote_parent_sampled: Sampler called for a remote sampled parent. + remote_parent_not_sampled: Sampler called for a remote parent that is + not sampled. + local_parent_sampled: Sampler called for a local sampled parent. + local_parent_not_sampled: Sampler called for a local parent that is + not sampled. + """ + + def __init__( + self, + root: Sampler, + remote_parent_sampled: Sampler = ALWAYS_ON, + remote_parent_not_sampled: Sampler = ALWAYS_OFF, + local_parent_sampled: Sampler = ALWAYS_ON, + local_parent_not_sampled: Sampler = ALWAYS_OFF, + ): + self._root = root + self._remote_parent_sampled = remote_parent_sampled + self._remote_parent_not_sampled = remote_parent_not_sampled + self._local_parent_sampled = local_parent_sampled + self._local_parent_not_sampled = local_parent_not_sampled + + def should_sample( + self, + parent_context: Optional["Context"], + trace_id: int, + name: str, + kind: Optional[SpanKind] = None, + attributes: Attributes = None, + links: Optional[Sequence["Link"]] = None, + trace_state: Optional["TraceState"] = None, + ) -> "SamplingResult": + parent_span_context = get_current_span( + parent_context + ).get_span_context() + # default to the root sampler + sampler = self._root + # respect the sampling and remote flag of the parent if present + if parent_span_context is not None and parent_span_context.is_valid: + if parent_span_context.is_remote: + if parent_span_context.trace_flags.sampled: + sampler = self._remote_parent_sampled + else: + sampler = self._remote_parent_not_sampled + else: + if parent_span_context.trace_flags.sampled: + sampler = self._local_parent_sampled + else: + sampler = self._local_parent_not_sampled + + return sampler.should_sample( + parent_context=parent_context, + trace_id=trace_id, + name=name, + kind=kind, + attributes=attributes, + links=links, + ) + + def get_description(self): + return f"ParentBased{{root:{self._root.get_description()},remoteParentSampled:{self._remote_parent_sampled.get_description()},remoteParentNotSampled:{self._remote_parent_not_sampled.get_description()},localParentSampled:{self._local_parent_sampled.get_description()},localParentNotSampled:{self._local_parent_not_sampled.get_description()}}}" + + +DEFAULT_OFF = ParentBased(ALWAYS_OFF) +"""Sampler that respects its parent span's sampling decision, but otherwise never samples.""" + +DEFAULT_ON = ParentBased(ALWAYS_ON) +"""Sampler that respects its parent span's sampling decision, but otherwise always samples.""" + + +class ParentBasedTraceIdRatio(ParentBased): + """ + Sampler that respects its parent span's sampling decision, but otherwise + samples probabilistically based on `rate`. + """ + + def __init__(self, rate: float): + root = TraceIdRatioBased(rate=rate) + super().__init__(root=root) + + +class _AlwaysOff(StaticSampler): + def __init__(self, _): + super().__init__(Decision.DROP) + + +class _AlwaysOn(StaticSampler): + def __init__(self, _): + super().__init__(Decision.RECORD_AND_SAMPLE) + + +class _ParentBasedAlwaysOff(ParentBased): + def __init__(self, _): + super().__init__(ALWAYS_OFF) + + +class _ParentBasedAlwaysOn(ParentBased): + def __init__(self, _): + super().__init__(ALWAYS_ON) + + +_KNOWN_SAMPLERS = { + "always_on": ALWAYS_ON, + "always_off": ALWAYS_OFF, + "parentbased_always_on": DEFAULT_ON, + "parentbased_always_off": DEFAULT_OFF, + "traceidratio": TraceIdRatioBased, + "parentbased_traceidratio": ParentBasedTraceIdRatio, +} + + +def _get_from_env_or_default() -> Sampler: + trace_sampler = os.getenv( + OTEL_TRACES_SAMPLER, "parentbased_always_on" + ).lower() + if trace_sampler not in _KNOWN_SAMPLERS: + _logger.warning("Couldn't recognize sampler %s.", trace_sampler) + trace_sampler = "parentbased_always_on" + + if trace_sampler in ("traceidratio", "parentbased_traceidratio"): + try: + rate = float(os.getenv(OTEL_TRACES_SAMPLER_ARG)) + except (ValueError, TypeError): + _logger.warning("Could not convert TRACES_SAMPLER_ARG to float.") + rate = 1.0 + return _KNOWN_SAMPLERS[trace_sampler](rate) + + return _KNOWN_SAMPLERS[trace_sampler] + + +def _get_parent_trace_state( + parent_context: Optional[Context], +) -> Optional["TraceState"]: + parent_span_context = get_current_span(parent_context).get_span_context() + if parent_span_context is None or not parent_span_context.is_valid: + return None + return parent_span_context.trace_state |