__init__.py

# 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.

# pylint: disable=too-many-lines
import abc
import atexit
import concurrent.futures
import fnmatch
import json
import logging
import os
import threading
import traceback
import typing
import weakref
from dataclasses import dataclass
from os import environ
from time import time_ns
from types import MappingProxyType, TracebackType
from typing import (
    Any,
    Callable,
    Dict,
    Iterator,
    List,
    Mapping,
    MutableMapping,
    Optional,
    Sequence,
    Type,
    Union,
)
from warnings import filterwarnings

from typing_extensions import deprecated

from opentelemetry import context as context_api
from opentelemetry import metrics as metrics_api
from opentelemetry import trace as trace_api
from opentelemetry.attributes import BoundedAttributes
from opentelemetry.sdk import util
from opentelemetry.sdk.environment_variables import (
    OTEL_ATTRIBUTE_COUNT_LIMIT,
    OTEL_ATTRIBUTE_VALUE_LENGTH_LIMIT,
    OTEL_EVENT_ATTRIBUTE_COUNT_LIMIT,
    OTEL_LINK_ATTRIBUTE_COUNT_LIMIT,
    OTEL_SDK_DISABLED,
    OTEL_SPAN_ATTRIBUTE_COUNT_LIMIT,
    OTEL_SPAN_ATTRIBUTE_VALUE_LENGTH_LIMIT,
    OTEL_SPAN_EVENT_COUNT_LIMIT,
    OTEL_SPAN_LINK_COUNT_LIMIT,
)
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import sampling
from opentelemetry.sdk.trace._tracer_metrics import TracerMetrics
from opentelemetry.sdk.trace.id_generator import IdGenerator, RandomIdGenerator
from opentelemetry.sdk.util import BoundedList
from opentelemetry.sdk.util.instrumentation import (
    InstrumentationInfo,
    InstrumentationScope,
)
from opentelemetry.semconv.attributes.exception_attributes import (
    EXCEPTION_ESCAPED,
    EXCEPTION_MESSAGE,
    EXCEPTION_STACKTRACE,
    EXCEPTION_TYPE,
)
from opentelemetry.trace import NoOpTracer, SpanContext
from opentelemetry.trace.status import Status, StatusCode
from opentelemetry.util import types
from opentelemetry.util._decorator import _agnosticcontextmanager

logger = logging.getLogger(__name__)

_DEFAULT_OTEL_ATTRIBUTE_COUNT_LIMIT = 128
_DEFAULT_OTEL_SPAN_ATTRIBUTE_COUNT_LIMIT = 128
_DEFAULT_OTEL_EVENT_ATTRIBUTE_COUNT_LIMIT = 128
_DEFAULT_OTEL_LINK_ATTRIBUTE_COUNT_LIMIT = 128
_DEFAULT_OTEL_SPAN_EVENT_COUNT_LIMIT = 128
_DEFAULT_OTEL_SPAN_LINK_COUNT_LIMIT = 128


_ENV_VALUE_UNSET = ""


class SpanProcessor:
    """Interface which allows hooks for SDK's `Span` start and end method
    invocations.

    Span processors can be registered directly using
    :func:`TracerProvider.add_span_processor` and they are invoked
    in the same order as they were registered.
    """

    def on_start(
        self,
        span: "Span",
        parent_context: Optional[context_api.Context] = None,
    ) -> None:
        """Called when a :class:`opentelemetry.trace.Span` is started.

        This method is called synchronously on the thread that starts the
        span, therefore it should not block or throw an exception.

        Args:
            span: The :class:`opentelemetry.trace.Span` that just started.
            parent_context: The parent context of the span that just started.
        """

    def _on_ending(self, span: "Span") -> None:
        """Called when a :class:`opentelemetry.trace.Span` is ending.

        This method is called synchronously on the thread that ends the
        span, therefore it should not block or throw an exception.

        Args:
            span: The :class:`opentelemetry.trace.Span` that is ending.
        """

    def on_end(self, span: "ReadableSpan") -> None:
        """Called when a :class:`opentelemetry.trace.Span` is ended.

        This method is called synchronously on the thread that ends the
        span, therefore it should not block or throw an exception.

        Args:
            span: The :class:`opentelemetry.trace.Span` that just ended.
        """

    def shutdown(self) -> None:
        """Called when a :class:`opentelemetry.sdk.trace.TracerProvider` is shutdown."""

    def force_flush(self, timeout_millis: int = 30000) -> bool:  # type: ignore[reportReturnType]
        """Export all ended spans to the configured Exporter that have not yet
        been exported.

        Args:
            timeout_millis: The maximum amount of time to wait for spans to be
                exported.

        Returns:
            False if the timeout is exceeded, True otherwise.
        """


# Temporary fix until https://github.com/PyCQA/pylint/issues/4098 is resolved
# pylint:disable=no-member
class SynchronousMultiSpanProcessor(SpanProcessor):
    """Implementation of class:`SpanProcessor` that forwards all received
    events to a list of span processors sequentially.

    The underlying span processors are called in sequential order as they were
    added.
    """

    _span_processors: tuple[SpanProcessor, ...]

    def __init__(self):
        # use a tuple to avoid race conditions when adding a new span and
        # iterating through it on "on_start" and "on_end".
        self._span_processors = ()
        self._lock = threading.Lock()

    def add_span_processor(self, span_processor: SpanProcessor) -> None:
        """Adds a SpanProcessor to the list handled by this instance."""
        with self._lock:
            self._span_processors += (span_processor,)

    def on_start(
        self,
        span: "Span",
        parent_context: Optional[context_api.Context] = None,
    ) -> None:
        for sp in self._span_processors:
            sp.on_start(span, parent_context=parent_context)

    def _on_ending(self, span: "Span") -> None:
        for sp in self._span_processors:
            # pylint: disable=protected-access
            sp._on_ending(span)

    def on_end(self, span: "ReadableSpan") -> None:
        for sp in self._span_processors:
            sp.on_end(span)

    def shutdown(self) -> None:
        """Sequentially shuts down all underlying span processors."""
        for sp in self._span_processors:
            sp.shutdown()

    def force_flush(self, timeout_millis: int = 30000) -> bool:
        """Sequentially calls force_flush on all underlying
        :class:`SpanProcessor`

        Args:
            timeout_millis: The maximum amount of time over all span processors
                to wait for spans to be exported. In case the first n span
                processors exceeded the timeout followup span processors will be
                skipped.

        Returns:
            True if all span processors flushed their spans within the
            given timeout, False otherwise.
        """
        deadline_ns = time_ns() + timeout_millis * 1000000
        for sp in self._span_processors:
            current_time_ns = time_ns()
            if current_time_ns >= deadline_ns:
                return False

            if not sp.force_flush((deadline_ns - current_time_ns) // 1000000):
                return False

        return True


class ConcurrentMultiSpanProcessor(SpanProcessor):
    """Implementation of :class:`SpanProcessor` that forwards all received
    events to a list of span processors in parallel.

    Calls to the underlying span processors are forwarded in parallel by
    submitting them to a thread pool executor and waiting until each span
    processor finished its work.

    Args:
        num_threads: The number of threads managed by the thread pool executor
            and thus defining how many span processors can work in parallel.
    """

    _span_processors: tuple[SpanProcessor, ...]

    def __init__(self, num_threads: int = 2):
        # use a tuple to avoid race conditions when adding a new span and
        # iterating through it on "on_start" and "on_end".
        self._span_processors = ()
        self._lock = threading.Lock()
        self._init_executor(num_threads)
        if hasattr(os, "register_at_fork"):
            # Only the main thread is kept in forked processed, the executor
            # needs to be re-instantiated to get a fresh pool of threads:
            weak_reinit = weakref.WeakMethod(self._init_executor)

            def _after_in_child() -> None:
                reinit = weak_reinit()
                if reinit is not None:
                    reinit(num_threads)

            os.register_at_fork(after_in_child=_after_in_child)

    def _init_executor(self, num_threads: int) -> None:
        self._executor = concurrent.futures.ThreadPoolExecutor(
            max_workers=num_threads
        )

    def add_span_processor(self, span_processor: SpanProcessor) -> None:
        """Adds a SpanProcessor to the list handled by this instance."""
        with self._lock:
            self._span_processors += (span_processor,)

    def _submit_and_await(
        self,
        func: Callable[[SpanProcessor], Callable[..., None]],
        *args: Any,
        **kwargs: Any,
    ):
        futures = []
        for sp in self._span_processors:
            future = self._executor.submit(func(sp), *args, **kwargs)
            futures.append(future)
        for future in futures:
            future.result()

    def on_start(
        self,
        span: "Span",
        parent_context: Optional[context_api.Context] = None,
    ) -> None:
        self._submit_and_await(
            lambda sp: sp.on_start, span, parent_context=parent_context
        )

    def _on_ending(self, span: "Span") -> None:
        # pylint: disable=protected-access
        self._submit_and_await(lambda sp: sp._on_ending, span)

    def on_end(self, span: "ReadableSpan") -> None:
        self._submit_and_await(lambda sp: sp.on_end, span)

    def shutdown(self) -> None:
        """Shuts down all underlying span processors in parallel."""
        self._submit_and_await(lambda sp: sp.shutdown)

    def force_flush(self, timeout_millis: int = 30000) -> bool:
        """Calls force_flush on all underlying span processors in parallel.

        Args:
            timeout_millis: The maximum amount of time to wait for spans to be
                exported.

        Returns:
            True if all span processors flushed their spans within the given
            timeout, False otherwise.
        """
        futures = []
        for sp in self._span_processors:
            future = self._executor.submit(sp.force_flush, timeout_millis)
            futures.append(future)

        timeout_sec = timeout_millis / 1e3
        done_futures, not_done_futures = concurrent.futures.wait(
            futures, timeout_sec
        )
        if not_done_futures:
            return False

        for future in done_futures:
            if not future.result():
                return False

        return True


class EventBase(abc.ABC):
    def __init__(self, name: str, timestamp: Optional[int] = None) -> None:
        self._name = name
        if timestamp is None:
            self._timestamp = time_ns()
        else:
            self._timestamp = timestamp

    @property
    def name(self) -> str:
        return self._name

    @property
    def timestamp(self) -> int:
        return self._timestamp

    @property
    @abc.abstractmethod
    def attributes(self) -> types.Attributes:
        pass


class Event(EventBase):
    """A text annotation with a set of attributes. The attributes of an event
    are immutable.

    Args:
        name: Name of the event.
        attributes: Attributes of the event.
        timestamp: Timestamp of the event. If `None` it will filled
            automatically.
    """

    def __init__(
        self,
        name: str,
        attributes: types.Attributes = None,
        timestamp: Optional[int] = None,
        limit: Optional[int] = _DEFAULT_OTEL_SPAN_ATTRIBUTE_COUNT_LIMIT,
    ) -> None:
        super().__init__(name, timestamp)
        self._attributes = attributes

    @property
    def attributes(self) -> types.Attributes:
        return self._attributes

    @property
    def dropped_attributes(self) -> int:
        if isinstance(self._attributes, BoundedAttributes):
            return self._attributes.dropped
        return 0


def _check_span_ended(func):
    def wrapper(self, *args, **kwargs):
        already_ended = False
        with self._lock:  # pylint: disable=protected-access
            if self._end_time is None:  # pylint: disable=protected-access
                func(self, *args, **kwargs)
            else:
                already_ended = True

        if already_ended:
            logger.warning("Tried calling %s on an ended span.", func.__name__)

    return wrapper


def _is_valid_link(context: SpanContext, attributes: types.Attributes) -> bool:
    return bool(
        context and (context.is_valid or (attributes or context.trace_state))
    )


class ReadableSpan:
    """Provides read-only access to span attributes.

    Users should NOT be creating these objects directly. `ReadableSpan`s are created as
    a direct result from using the tracing pipeline via the `Tracer`.

    """

    def __init__(
        self,
        name: str,
        context: Optional[trace_api.SpanContext] = None,
        parent: Optional[trace_api.SpanContext] = None,
        resource: Optional[Resource] = None,
        attributes: types.Attributes = None,
        events: Sequence[Event] = (),
        links: Sequence[trace_api.Link] = (),
        kind: trace_api.SpanKind = trace_api.SpanKind.INTERNAL,
        instrumentation_info: Optional[InstrumentationInfo] = None,
        status: Status = Status(StatusCode.UNSET),
        start_time: Optional[int] = None,
        end_time: Optional[int] = None,
        instrumentation_scope: Optional[InstrumentationScope] = None,
    ) -> None:
        self._name = name
        self._context = context
        self._kind = kind
        self._instrumentation_info = instrumentation_info
        self._instrumentation_scope = instrumentation_scope
        self._parent = parent
        self._start_time = start_time
        self._end_time = end_time
        self._attributes = attributes
        self._events = events
        self._links = links
        if resource is None:
            self._resource = Resource.create({})
        else:
            self._resource = resource
        self._status = status

    @property
    def dropped_attributes(self) -> int:
        if isinstance(self._attributes, BoundedAttributes):
            return self._attributes.dropped
        return 0

    @property
    def dropped_events(self) -> int:
        if isinstance(self._events, BoundedList):
            return self._events.dropped
        return 0

    @property
    def dropped_links(self) -> int:
        if isinstance(self._links, BoundedList):
            return self._links.dropped
        return 0

    @property
    def name(self) -> str:
        return self._name

    def get_span_context(self) -> Optional[trace_api.SpanContext]:
        return self._context

    @property
    def context(self):
        return self._context

    @property
    def kind(self) -> trace_api.SpanKind:
        return self._kind

    @property
    def parent(self) -> Optional[trace_api.SpanContext]:
        return self._parent

    @property
    def start_time(self) -> Optional[int]:
        return self._start_time

    @property
    def end_time(self) -> Optional[int]:
        return self._end_time

    @property
    def status(self) -> trace_api.Status:
        return self._status

    @property
    def attributes(self) -> types.Attributes:
        return MappingProxyType(self._attributes or {})

    @property
    def events(self) -> Sequence[Event]:
        return tuple(event for event in self._events)

    @property
    def links(self) -> Sequence[trace_api.Link]:
        return tuple(link for link in self._links)

    @property
    def resource(self) -> Resource:
        return self._resource

    @property
    @deprecated(
        "You should use instrumentation_scope. Deprecated since version 1.11.1."
    )
    def instrumentation_info(self) -> Optional[InstrumentationInfo]:
        return self._instrumentation_info

    @property
    def instrumentation_scope(self) -> Optional[InstrumentationScope]:
        return self._instrumentation_scope

    def to_json(self, indent: Optional[int] = 4):
        parent_id = None
        if self.parent is not None:
            parent_id = f"0x{trace_api.format_span_id(self.parent.span_id)}"

        start_time = None
        if self._start_time:
            start_time = util.ns_to_iso_str(self._start_time)

        end_time = None
        if self._end_time:
            end_time = util.ns_to_iso_str(self._end_time)

        status = {
            "status_code": str(self._status.status_code.name),
        }
        if self._status.description:
            status["description"] = self._status.description

        f_span = {
            "name": self._name,
            "context": (
                self._format_context(self._context) if self._context else None
            ),
            "kind": str(self.kind),
            "parent_id": parent_id,
            "start_time": start_time,
            "end_time": end_time,
            "status": status,
            "attributes": self._format_attributes(self._attributes),
            "events": self._format_events(self._events),
            "links": self._format_links(self._links),
            "resource": json.loads(self.resource.to_json()),
        }

        return json.dumps(f_span, indent=indent)

    @staticmethod
    def _format_context(context: SpanContext) -> Dict[str, str]:
        return {
            "trace_id": f"0x{trace_api.format_trace_id(context.trace_id)}",
            "span_id": f"0x{trace_api.format_span_id(context.span_id)}",
            "trace_state": repr(context.trace_state),
        }

    @staticmethod
    def _format_attributes(
        attributes: types.Attributes,
    ) -> Optional[Dict[str, Any]]:
        if attributes is not None and not isinstance(attributes, dict):
            return dict(attributes)
        return attributes

    @staticmethod
    def _format_events(events: Sequence[Event]) -> List[Dict[str, Any]]:
        return [
            {
                "name": event.name,
                "timestamp": util.ns_to_iso_str(event.timestamp),
                "attributes": Span._format_attributes(  # pylint: disable=protected-access
                    event.attributes
                ),
            }
            for event in events
        ]

    @staticmethod
    def _format_links(links: Sequence[trace_api.Link]) -> List[Dict[str, Any]]:
        return [
            {
                "context": Span._format_context(  # pylint: disable=protected-access
                    link.context
                ),
                "attributes": Span._format_attributes(  # pylint: disable=protected-access
                    link.attributes
                ),
            }
            for link in links
        ]


class SpanLimits:
    """The limits that should be enforce on recorded data such as events, links, attributes etc.

    This class does not enforce any limits itself. It only provides an a way read limits from env,
    default values and from user provided arguments.

    All limit arguments must be either a non-negative integer, ``None`` or ``SpanLimits.UNSET``.

    - All limit arguments are optional.
    - If a limit argument is not set, the class will try to read its value from the corresponding
      environment variable.
    - If the environment variable is not set, the default value, if any, will be used.

    Limit precedence:

    - If a model specific limit is set, it will be used.
    - Else if the corresponding global limit is set, it will be used.
    - Else if the model specific limit has a default value, the default value will be used.
    - Else if the global limit has a default value, the default value will be used.

    Args:
        max_attributes: Maximum number of attributes that can be added to a span, event, and link.
            Environment variable: OTEL_ATTRIBUTE_COUNT_LIMIT
            Default: {_DEFAULT_ATTRIBUTE_COUNT_LIMIT}
        max_events: Maximum number of events that can be added to a Span.
            Environment variable: OTEL_SPAN_EVENT_COUNT_LIMIT
            Default: {_DEFAULT_SPAN_EVENT_COUNT_LIMIT}
        max_links: Maximum number of links that can be added to a Span.
            Environment variable: OTEL_SPAN_LINK_COUNT_LIMIT
            Default: {_DEFAULT_SPAN_LINK_COUNT_LIMIT}
        max_span_attributes: Maximum number of attributes that can be added to a Span.
            Environment variable: OTEL_SPAN_ATTRIBUTE_COUNT_LIMIT
            Default: {_DEFAULT_OTEL_SPAN_ATTRIBUTE_COUNT_LIMIT}
        max_event_attributes: Maximum number of attributes that can be added to an Event.
            Default: {_DEFAULT_OTEL_EVENT_ATTRIBUTE_COUNT_LIMIT}
        max_link_attributes: Maximum number of attributes that can be added to a Link.
            Default: {_DEFAULT_OTEL_LINK_ATTRIBUTE_COUNT_LIMIT}
        max_attribute_length: Maximum length an attribute value can have. Values longer than
            the specified length will be truncated.
        max_span_attribute_length: Maximum length a span attribute value can have. Values longer than
            the specified length will be truncated.
    """

    UNSET = -1

    def __init__(
        self,
        max_attributes: Optional[int] = None,
        max_events: Optional[int] = None,
        max_links: Optional[int] = None,
        max_span_attributes: Optional[int] = None,
        max_event_attributes: Optional[int] = None,
        max_link_attributes: Optional[int] = None,
        max_attribute_length: Optional[int] = None,
        max_span_attribute_length: Optional[int] = None,
    ):
        # span events and links count
        self.max_events = self._from_env_if_absent(
            max_events,
            OTEL_SPAN_EVENT_COUNT_LIMIT,
            _DEFAULT_OTEL_SPAN_EVENT_COUNT_LIMIT,
        )
        self.max_links = self._from_env_if_absent(
            max_links,
            OTEL_SPAN_LINK_COUNT_LIMIT,
            _DEFAULT_OTEL_SPAN_LINK_COUNT_LIMIT,
        )

        # attribute count
        global_max_attributes = self._from_env_if_absent(
            max_attributes, OTEL_ATTRIBUTE_COUNT_LIMIT
        )
        self.max_attributes = (
            global_max_attributes
            if global_max_attributes is not None
            else _DEFAULT_OTEL_ATTRIBUTE_COUNT_LIMIT
        )

        self.max_span_attributes = self._from_env_if_absent(
            max_span_attributes,
            OTEL_SPAN_ATTRIBUTE_COUNT_LIMIT,
            (
                global_max_attributes
                if global_max_attributes is not None
                else _DEFAULT_OTEL_SPAN_ATTRIBUTE_COUNT_LIMIT
            ),
        )
        self.max_event_attributes = self._from_env_if_absent(
            max_event_attributes,
            OTEL_EVENT_ATTRIBUTE_COUNT_LIMIT,
            (
                global_max_attributes
                if global_max_attributes is not None
                else _DEFAULT_OTEL_EVENT_ATTRIBUTE_COUNT_LIMIT
            ),
        )
        self.max_link_attributes = self._from_env_if_absent(
            max_link_attributes,
            OTEL_LINK_ATTRIBUTE_COUNT_LIMIT,
            (
                global_max_attributes
                if global_max_attributes is not None
                else _DEFAULT_OTEL_LINK_ATTRIBUTE_COUNT_LIMIT
            ),
        )

        # attribute length
        self.max_attribute_length = self._from_env_if_absent(
            max_attribute_length,
            OTEL_ATTRIBUTE_VALUE_LENGTH_LIMIT,
        )
        self.max_span_attribute_length = self._from_env_if_absent(
            max_span_attribute_length,
            OTEL_SPAN_ATTRIBUTE_VALUE_LENGTH_LIMIT,
            # use global attribute length limit as default
            self.max_attribute_length,
        )

    def __repr__(self):
        return f"{type(self).__name__}(max_span_attributes={self.max_span_attributes}, max_events_attributes={self.max_event_attributes}, max_link_attributes={self.max_link_attributes}, max_attributes={self.max_attributes}, max_events={self.max_events}, max_links={self.max_links}, max_attribute_length={self.max_attribute_length})"

    @classmethod
    def _from_env_if_absent(
        cls, value: Optional[int], env_var: str, default: Optional[int] = None
    ) -> Optional[int]:
        if value == cls.UNSET:
            return None

        err_msg = "{} must be a non-negative integer but got {}"

        # if no value is provided for the limit, try to load it from env
        if value is None:
            # return default value if env var is not set
            if env_var not in environ:
                return default

            str_value = environ.get(env_var, "").strip().lower()
            if str_value == _ENV_VALUE_UNSET:
                return None

            try:
                value = int(str_value)
            except ValueError:
                raise ValueError(err_msg.format(env_var, str_value))

        if value < 0:
            raise ValueError(err_msg.format(env_var, value))
        return value


_UnsetLimits = SpanLimits(
    max_attributes=SpanLimits.UNSET,
    max_events=SpanLimits.UNSET,
    max_links=SpanLimits.UNSET,
    max_span_attributes=SpanLimits.UNSET,
    max_event_attributes=SpanLimits.UNSET,
    max_link_attributes=SpanLimits.UNSET,
    max_attribute_length=SpanLimits.UNSET,
    max_span_attribute_length=SpanLimits.UNSET,
)

# not removed for backward compat. please use SpanLimits instead.
SPAN_ATTRIBUTE_COUNT_LIMIT = SpanLimits._from_env_if_absent(  # pylint: disable=protected-access
    None,
    OTEL_SPAN_ATTRIBUTE_COUNT_LIMIT,
    _DEFAULT_OTEL_SPAN_ATTRIBUTE_COUNT_LIMIT,
)


class Span(trace_api.Span, ReadableSpan):
    """See `opentelemetry.trace.Span`.

    Users should create `Span` objects via the `Tracer` instead of this
    constructor.

    Args:
        name: The name of the operation this span represents
        context: The immutable span context
        parent: This span's parent's `opentelemetry.trace.SpanContext`, or
            None if this is a root span
        sampler: The sampler used to create this span
        trace_config: TODO
        resource: Entity producing telemetry
        attributes: The span's attributes to be exported
        events: Timestamped events to be exported
        links: Links to other spans to be exported
        span_processor: `SpanProcessor` to invoke when starting and ending
            this `Span`.
        limits: `SpanLimits` instance that was passed to the `TracerProvider`
    """

    def __new__(cls, *args, **kwargs):
        if cls is Span:
            raise TypeError("Span must be instantiated via a tracer.")
        return super().__new__(cls)

    # pylint: disable=too-many-locals
    def __init__(
        self,
        name: str,
        context: trace_api.SpanContext,
        parent: Optional[trace_api.SpanContext] = None,
        sampler: Optional[sampling.Sampler] = None,
        trace_config: None = None,  # TODO
        resource: Optional[Resource] = None,
        attributes: types.Attributes = None,
        events: Optional[Sequence[Event]] = None,
        links: Sequence[trace_api.Link] = (),
        kind: trace_api.SpanKind = trace_api.SpanKind.INTERNAL,
        span_processor: SpanProcessor = SpanProcessor(),
        instrumentation_info: Optional[InstrumentationInfo] = None,
        record_exception: bool = True,
        set_status_on_exception: bool = True,
        limits=_UnsetLimits,
        instrumentation_scope: Optional[InstrumentationScope] = None,
        *,
        record_end_metrics: Optional[Callable[[], None]] = None,
    ) -> None:
        if resource is None:
            resource = Resource.create({})
        super().__init__(
            name=name,
            context=context,
            parent=parent,
            kind=kind,
            resource=resource,
            instrumentation_info=instrumentation_info,
            instrumentation_scope=instrumentation_scope,
        )
        self._sampler = sampler
        self._trace_config = trace_config
        self._record_exception = record_exception
        self._set_status_on_exception = set_status_on_exception
        self._span_processor = span_processor
        self._limits = limits
        self._lock = threading.Lock()
        self._attributes = BoundedAttributes(
            self._limits.max_span_attributes,
            attributes,
            immutable=False,
            max_value_len=self._limits.max_span_attribute_length,
        )
        self._events = self._new_events()
        if events:
            for event in events:
                event._attributes = BoundedAttributes(
                    self._limits.max_event_attributes,
                    event.attributes,
                    max_value_len=self._limits.max_attribute_length,
                )
                self._events.append(event)

        self._links = self._new_links(links)

        self._record_end_metrics = record_end_metrics

    def __repr__(self):
        return f'{type(self).__name__}(name="{self._name}", context={self._context})'

    def _new_events(self):
        return BoundedList(self._limits.max_events)

    def _new_links(self, links: Sequence[trace_api.Link]):
        if not links:
            return BoundedList(self._limits.max_links)

        valid_links = []
        for link in links:
            if link and _is_valid_link(link.context, link.attributes):
                # pylint: disable=protected-access
                link._attributes = BoundedAttributes(
                    self._limits.max_link_attributes,
                    link.attributes,
                    max_value_len=self._limits.max_attribute_length,
                )
                valid_links.append(link)

        return BoundedList.from_seq(self._limits.max_links, valid_links)

    def get_span_context(self) -> trace_api.SpanContext:
        return typing.cast(trace_api.SpanContext, self._context)

    def set_attributes(
        self, attributes: Mapping[str, types.AttributeValue]
    ) -> None:
        with self._lock:
            if self._end_time is not None:
                logger.warning("Setting attribute on ended span.")
                return

            for key, value in attributes.items():
                self._attributes[key] = value

    def set_attribute(self, key: str, value: types.AttributeValue) -> None:
        return self.set_attributes({key: value})

    @_check_span_ended
    def _add_event(self, event: EventBase) -> None:
        self._events.append(event)

    def add_event(
        self,
        name: str,
        attributes: types.Attributes = None,
        timestamp: Optional[int] = None,
    ) -> None:
        attributes = BoundedAttributes(
            self._limits.max_event_attributes,
            attributes,
            max_value_len=self._limits.max_attribute_length,
        )
        self._add_event(
            Event(
                name=name,
                attributes=attributes,
                timestamp=timestamp,
            )
        )

    @_check_span_ended
    def _add_link(self, link: trace_api.Link) -> None:
        self._links.append(link)

    def add_link(
        self,
        context: SpanContext,
        attributes: types.Attributes = None,
    ) -> None:
        if not _is_valid_link(context, attributes):
            return

        attributes = BoundedAttributes(
            self._limits.max_link_attributes,
            attributes,
            max_value_len=self._limits.max_attribute_length,
        )
        self._add_link(
            trace_api.Link(
                context=context,
                attributes=attributes,
            )
        )

    def _readable_span(self) -> ReadableSpan:
        return ReadableSpan(
            name=self._name,
            context=self._context,
            parent=self._parent,
            resource=self._resource,
            attributes=self._attributes,
            events=self._events,
            links=self._links,
            kind=self.kind,
            status=self._status,
            start_time=self._start_time,
            end_time=self._end_time,
            instrumentation_info=self._instrumentation_info,
            instrumentation_scope=self._instrumentation_scope,
        )

    def start(
        self,
        start_time: Optional[int] = None,
        parent_context: Optional[context_api.Context] = None,
    ) -> None:
        with self._lock:
            if self._start_time is not None:
                logger.warning("Calling start() on a started span.")
                return
            self._start_time = (
                start_time if start_time is not None else time_ns()
            )

        self._span_processor.on_start(self, parent_context=parent_context)

    def end(self, end_time: Optional[int] = None) -> None:
        with self._lock:
            if self._start_time is None:
                raise RuntimeError("Calling end() on a not started span.")
            if self._end_time is not None:
                logger.warning("Calling end() on an ended span.")
                return

            self._end_time = end_time if end_time is not None else time_ns()

        if self._record_end_metrics:
            self._record_end_metrics()
        # pylint: disable=protected-access
        self._span_processor._on_ending(self)
        self._span_processor.on_end(self._readable_span())

    @_check_span_ended
    def update_name(self, name: str) -> None:
        self._name = name

    def is_recording(self) -> bool:
        return self._end_time is None

    @_check_span_ended
    def set_status(
        self,
        status: typing.Union[Status, StatusCode],
        description: typing.Optional[str] = None,
    ) -> None:
        # Ignore future calls if status is already set to OK
        # Ignore calls to set to StatusCode.UNSET
        if isinstance(status, Status):
            if (
                self._status
                and self._status.status_code is StatusCode.OK
                or status.status_code is StatusCode.UNSET
            ):
                return
            if description is not None:
                logger.warning(
                    "Description %s ignored. Use either `Status` or `(StatusCode, Description)`",
                    description,
                )
            self._status = status
        elif isinstance(status, StatusCode):
            if (
                self._status
                and self._status.status_code is StatusCode.OK
                or status is StatusCode.UNSET
            ):
                return
            self._status = Status(status, description)

    def __exit__(
        self,
        exc_type: Optional[Type[BaseException]],
        exc_val: Optional[BaseException],
        exc_tb: Optional[TracebackType],
    ) -> None:
        """Ends context manager and calls `end` on the `Span`."""
        if exc_val is not None and self.is_recording():
            # Record the exception as an event
            # pylint:disable=protected-access
            if self._record_exception:
                self.record_exception(exception=exc_val, escaped=True)
            # Records status if span is used as context manager
            # i.e. with tracer.start_span() as span:
            if self._set_status_on_exception:
                self.set_status(
                    Status(
                        status_code=StatusCode.ERROR,
                        description=(f"{type(exc_val).__name__}: {exc_val}"),
                    )
                )

        super().__exit__(exc_type, exc_val, exc_tb)

    def record_exception(
        self,
        exception: BaseException,
        attributes: types.Attributes = None,
        timestamp: Optional[int] = None,
        escaped: bool = False,
    ) -> None:
        """Records an exception as a span event."""
        # TODO: keep only exception as first argument after baseline is 3.10
        stacktrace = "".join(
            traceback.format_exception(
                type(exception), value=exception, tb=exception.__traceback__
            )
        )
        module = type(exception).__module__
        qualname = type(exception).__qualname__
        exception_type = (
            f"{module}.{qualname}"
            if module and module != "builtins"
            else qualname
        )
        _attributes: MutableMapping[str, types.AttributeValue] = {
            EXCEPTION_TYPE: exception_type,
            EXCEPTION_MESSAGE: str(exception),
            EXCEPTION_STACKTRACE: stacktrace,
            EXCEPTION_ESCAPED: str(escaped),
        }
        if attributes:
            _attributes.update(attributes)
        self.add_event(
            name="exception", attributes=_attributes, timestamp=timestamp
        )


class _Span(Span):
    """Protected implementation of `opentelemetry.trace.Span`.

    This constructor exists to prevent the instantiation of the `Span` class
    by other mechanisms than through the `Tracer`.
    """


@dataclass
class _TracerConfig:
    is_enabled: bool

    @classmethod
    def default(cls):
        return cls(is_enabled=True)


class Tracer(trace_api.Tracer):
    """See `opentelemetry.trace.Tracer`."""

    def __init__(
        self,
        sampler: sampling.Sampler,
        resource: Resource,
        span_processor: Union[
            SynchronousMultiSpanProcessor, ConcurrentMultiSpanProcessor
        ],
        id_generator: IdGenerator,
        instrumentation_info: InstrumentationInfo,
        span_limits: SpanLimits,
        instrumentation_scope: InstrumentationScope,
        *,
        meter_provider: Optional[metrics_api.MeterProvider] = None,
        _tracer_config: Optional[_TracerConfig] = None,
    ) -> None:
        self.sampler = sampler
        self.resource = resource
        self.span_processor = span_processor
        self.id_generator = id_generator
        self.instrumentation_info = instrumentation_info
        self._span_limits = span_limits
        self._instrumentation_scope = instrumentation_scope
        self._tracer_config = _tracer_config or _TracerConfig.default()

        meter_provider = meter_provider or metrics_api.get_meter_provider()
        self._tracer_metrics = TracerMetrics(meter_provider)

    def _set_tracer_config(self, tracer_config: _TracerConfig):
        self._tracer_config = tracer_config

    def _is_enabled(self) -> bool:
        """If the tracer is not enabled, start_span will create a NonRecordingSpan"""
        return self._tracer_config.is_enabled

    @_agnosticcontextmanager  # pylint: disable=protected-access
    def start_as_current_span(
        self,
        name: str,
        context: Optional[context_api.Context] = None,
        kind: trace_api.SpanKind = trace_api.SpanKind.INTERNAL,
        attributes: types.Attributes = None,
        links: Optional[Sequence[trace_api.Link]] = (),
        start_time: Optional[int] = None,
        record_exception: bool = True,
        set_status_on_exception: bool = True,
        end_on_exit: bool = True,
    ) -> Iterator[trace_api.Span]:
        span = self.start_span(
            name=name,
            context=context,
            kind=kind,
            attributes=attributes,
            links=links,
            start_time=start_time,
            record_exception=record_exception,
            set_status_on_exception=set_status_on_exception,
        )
        with trace_api.use_span(
            span,
            end_on_exit=end_on_exit,
            record_exception=record_exception,
            set_status_on_exception=set_status_on_exception,
        ) as span:
            yield span

    def start_span(  # pylint: disable=too-many-locals
        self,
        name: str,
        context: Optional[context_api.Context] = None,
        kind: trace_api.SpanKind = trace_api.SpanKind.INTERNAL,
        attributes: types.Attributes = None,
        links: Optional[Sequence[trace_api.Link]] = (),
        start_time: Optional[int] = None,
        record_exception: bool = True,
        set_status_on_exception: bool = True,
    ) -> trace_api.Span:
        links = links or ()
        parent_span_context = trace_api.get_current_span(
            context
        ).get_span_context()

        if parent_span_context is not None and not isinstance(
            parent_span_context, trace_api.SpanContext
        ):
            raise TypeError(
                "parent_span_context must be a SpanContext or None."
            )

        if not self._is_enabled():
            return trace_api.NonRecordingSpan(context=parent_span_context)

        # is_valid determines root span
        if parent_span_context is None or not parent_span_context.is_valid:
            parent_span_context = None
            trace_id = self.id_generator.generate_trace_id()
        else:
            trace_id = parent_span_context.trace_id

        # The sampler decides whether to create a real or no-op span at the
        # time of span creation. No-op spans do not record events, and are not
        # exported.
        # The sampler may also add attributes to the newly-created span, e.g.
        # to include information about the sampling result.
        # The sampler may also modify the parent span context's tracestate
        sampling_result = self.sampler.should_sample(
            context, trace_id, name, kind, attributes, links
        )

        trace_flags = (
            trace_api.TraceFlags(trace_api.TraceFlags.SAMPLED)
            if sampling_result.decision.is_sampled()
            else trace_api.TraceFlags(trace_api.TraceFlags.DEFAULT)
        )
        span_context = trace_api.SpanContext(
            trace_id,
            self.id_generator.generate_span_id(),
            is_remote=False,
            trace_flags=trace_flags,
            trace_state=sampling_result.trace_state,
        )

        record_end_metrics = self._tracer_metrics.start_span(
            parent_span_context, sampling_result.decision
        )

        # Only record if is_recording() is true
        if sampling_result.decision.is_recording():
            # pylint:disable=protected-access
            span = _Span(
                name=name,
                context=span_context,
                parent=parent_span_context,
                sampler=self.sampler,
                resource=self.resource,
                attributes=sampling_result.attributes.copy(),
                span_processor=self.span_processor,
                kind=kind,
                links=links,
                instrumentation_info=self.instrumentation_info,
                record_exception=record_exception,
                set_status_on_exception=set_status_on_exception,
                limits=self._span_limits,
                instrumentation_scope=self._instrumentation_scope,
                record_end_metrics=record_end_metrics,
            )
            span.start(start_time=start_time, parent_context=context)
        else:
            span = trace_api.NonRecordingSpan(context=span_context)
        return span


_TracerConfiguratorT = Callable[[InstrumentationScope], _TracerConfig]
_InstrumentationScopePredicateT = Callable[[InstrumentationScope], bool]
_TracerConfiguratorRulesT = Sequence[
    tuple[_InstrumentationScopePredicateT, _TracerConfig]
]


# TODO: share this with configurators for other signals
def _scope_name_matches_glob(
    glob_pattern: str,
) -> _InstrumentationScopePredicateT:
    def inner(scope: InstrumentationScope) -> bool:
        return fnmatch.fnmatch(scope.name, glob_pattern)

    return inner


class _RuleBasedTracerConfigurator:
    def __init__(
        self,
        *,
        rules: _TracerConfiguratorRulesT,
        default_config: _TracerConfig,
    ):
        self._rules = rules
        self._default_config = default_config

    def __call__(self, tracer_scope: InstrumentationScope) -> _TracerConfig:
        for predicate, tracer_config in self._rules:
            if predicate(tracer_scope):
                return tracer_config

        # if no rule matched return the default config
        return self._default_config


def _default_tracer_configurator(
    tracer_scope: InstrumentationScope,
) -> _TracerConfig:
    """Default Tracer Configurator implementation

    In order to update Tracers configs you need to call
    TracerProvider._set_tracer_configurator with a function
    implementing this interface returning a Tracer Config."""
    return _RuleBasedTracerConfigurator(
        rules=[],
        default_config=_TracerConfig.default(),
    )(tracer_scope=tracer_scope)


def _disable_tracer_configurator(
    tracer_scope: InstrumentationScope,
) -> _TracerConfig:
    return _RuleBasedTracerConfigurator(
        rules=[],
        default_config=_TracerConfig(is_enabled=False),
    )(tracer_scope=tracer_scope)


class TracerProvider(trace_api.TracerProvider):
    """See `opentelemetry.trace.TracerProvider`."""

    def __init__(
        self,
        sampler: Optional[sampling.Sampler] = None,
        resource: Optional[Resource] = None,
        shutdown_on_exit: bool = True,
        active_span_processor: Union[
            SynchronousMultiSpanProcessor, ConcurrentMultiSpanProcessor, None
        ] = None,
        id_generator: Optional[IdGenerator] = None,
        span_limits: Optional[SpanLimits] = None,
        *,
        meter_provider: Optional[metrics_api.MeterProvider] = None,
        _tracer_configurator: Optional[_TracerConfiguratorT] = None,
    ) -> None:
        self._active_span_processor = (
            active_span_processor or SynchronousMultiSpanProcessor()
        )
        if id_generator is None:
            self.id_generator = RandomIdGenerator()
        else:
            self.id_generator = id_generator
        if resource is None:
            self._resource = Resource.create({})
        else:
            self._resource = resource
        if not sampler:
            sampler = sampling._get_from_env_or_default()
        self.sampler = sampler
        self._span_limits = span_limits or SpanLimits()
        disabled = environ.get(OTEL_SDK_DISABLED, "")
        self._disabled = disabled.lower().strip() == "true"
        self._atexit_handler = None
        self._meter_provider = meter_provider

        if shutdown_on_exit:
            self._atexit_handler = atexit.register(self.shutdown)

        self._tracer_configurator = (
            _tracer_configurator or _default_tracer_configurator
        )
        self._tracers_lock = threading.Lock()
        self._tracers: dict[InstrumentationScope, Tracer] = {}

    def _set_tracer_configurator(
        self, *, tracer_configurator: _TracerConfiguratorT
    ):
        """This is the function used to update the TracerProvider TracerConfigurator

        Setting a new TracerConfigurator for a TracerProvider will update the
        TracerConfig of all Tracers create by this TracerProvider.
        """
        self._tracer_configurator = tracer_configurator
        with self._tracers_lock:
            for instrumentation_scope, tracer in self._tracers.items():
                tracer_config = self._apply_tracer_configurator(
                    instrumentation_scope
                )
                # pylint: disable-next=protected-access
                tracer._set_tracer_config(tracer_config)

    @property
    def resource(self) -> Resource:
        return self._resource

    def _apply_tracer_configurator(
        self, instrumentation_scope: InstrumentationScope
    ):
        try:
            return self._tracer_configurator(instrumentation_scope)
        except Exception:  # pylint: disable=broad-exception-caught
            logger.exception(
                "Failed to create a Tracer Config for %s, using default Tracer config",
                instrumentation_scope,
            )
            return _TracerConfig.default()

    def get_tracer(
        self,
        instrumenting_module_name: str,
        instrumenting_library_version: typing.Optional[str] = None,
        schema_url: typing.Optional[str] = None,
        attributes: typing.Optional[types.Attributes] = None,
    ) -> "trace_api.Tracer":
        if self._disabled:
            return NoOpTracer()
        if not instrumenting_module_name:  # Reject empty strings too.
            instrumenting_module_name = ""
            logger.error("get_tracer called with missing module name.")
        if instrumenting_library_version is None:
            instrumenting_library_version = ""

        filterwarnings(
            "ignore",
            message=(
                r"You should use InstrumentationScope. Deprecated since version 1.11.1."
            ),
            category=DeprecationWarning,
            module="opentelemetry.sdk.trace",
        )

        instrumentation_info = InstrumentationInfo(
            instrumenting_module_name,
            instrumenting_library_version,
            schema_url,
        )

        instrumentation_scope = InstrumentationScope(
            instrumenting_module_name,
            instrumenting_library_version,
            schema_url,
            attributes,
        )

        with self._tracers_lock:
            if instrumentation_scope in self._tracers:
                return self._tracers[instrumentation_scope]

            tracer_config = self._apply_tracer_configurator(
                instrumentation_scope
            )
            tracer = Tracer(
                self.sampler,
                self.resource,
                self._active_span_processor,
                self.id_generator,
                instrumentation_info,
                self._span_limits,
                instrumentation_scope,
                meter_provider=self._meter_provider,
                _tracer_config=tracer_config,
            )
            self._tracers[instrumentation_scope] = tracer

        return tracer

    def add_span_processor(self, span_processor: SpanProcessor) -> None:
        """Registers a new :class:`SpanProcessor` for this `TracerProvider`.

        The span processors are invoked in the same order they are registered.
        """

        # no lock here because add_span_processor is thread safe for both
        # SynchronousMultiSpanProcessor and ConcurrentMultiSpanProcessor.
        self._active_span_processor.add_span_processor(span_processor)

    def shutdown(self) -> None:
        """Shut down the span processors added to the tracer provider."""
        self._active_span_processor.shutdown()
        if self._atexit_handler is not None:
            atexit.unregister(self._atexit_handler)
            self._atexit_handler = None

    def force_flush(self, timeout_millis: int = 30000) -> bool:
        """Requests the active span processor to process all spans that have not
        yet been processed.

        By default force flush is called sequentially on all added span
        processors. This means that span processors further back in the list
        have less time to flush their spans.
        To have span processors flush their spans in parallel it is possible to
        initialize the tracer provider with an instance of
        `ConcurrentMultiSpanProcessor` at the cost of using multiple threads.

        Args:
            timeout_millis: The maximum amount of time to wait for spans to be
                processed.

        Returns:
            False if the timeout is exceeded, True otherwise.
        """
        return self._active_span_processor.force_flush(timeout_millis)