# Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations

import abc
import atexit
import base64
import concurrent.futures
import json
import logging
import os
import threading
import traceback
import warnings
from collections.abc import Callable
from dataclasses import dataclass, field
from os import environ
from threading import Lock
from time import time_ns
from typing import (  # noqa
    Any,
    cast,
    overload,
)
from weakref import WeakMethod, WeakSet

from typing_extensions import deprecated

from opentelemetry._logs import Logger as APILogger
from opentelemetry._logs import LoggerProvider as APILoggerProvider
from opentelemetry._logs import (
    LogRecord,
    NoOpLogger,
    SeverityNumber,
    get_logger,
    get_logger_provider,
)
from opentelemetry.attributes import _VALID_ANY_VALUE_TYPES, BoundedAttributes
from opentelemetry.context import get_current
from opentelemetry.context.context import Context
from opentelemetry.metrics import MeterProvider, get_meter_provider
from opentelemetry.sdk._logs._internal._exceptions import (
    _copy_log_record_with_exception,
    _create_log_record_with_exception,
    _set_log_record_exception_attributes,
)
from opentelemetry.sdk._logs._internal._logger_metrics import (
    LoggerMetricsT,
    create_logger_metrics,
)
from opentelemetry.sdk.environment_variables import (
    OTEL_ATTRIBUTE_COUNT_LIMIT,
    OTEL_ATTRIBUTE_VALUE_LENGTH_LIMIT,
    OTEL_LOGRECORD_ATTRIBUTE_COUNT_LIMIT,
    OTEL_LOGRECORD_ATTRIBUTE_VALUE_LENGTH_LIMIT,
    OTEL_PYTHON_SDK_INTERNAL_METRICS_ENABLED,
    OTEL_SDK_DISABLED,
)
from opentelemetry.sdk.environment_variables._internal import (
    parse_boolean_environment_variable,
)
from opentelemetry.sdk.resources import (
    Resource,
    _get_process_dependent_resource,
)
from opentelemetry.sdk.util import ns_to_iso_str
from opentelemetry.sdk.util._configurator import RuleBasedConfigurator
from opentelemetry.sdk.util.instrumentation import (
    InstrumentationScope,
)
from opentelemetry.semconv.attributes import (
    code_attributes,
    exception_attributes,
)
from opentelemetry.trace import (
    format_span_id,
    format_trace_id,
)
from opentelemetry.util.types import AnyValue, _ExtendedAttributes

# pylint: disable=too-many-lines

_DEFAULT_OTEL_ATTRIBUTE_COUNT_LIMIT = 128
_ENV_VALUE_UNSET = ""

_logger = logging.getLogger(__name__)


class BytesEncoder(json.JSONEncoder):
    def default(self, o):
        if isinstance(o, bytes):
            return base64.b64encode(o).decode()
        return super().default(o)


class LogRecordDroppedAttributesWarning(UserWarning):
    """Custom warning to indicate dropped log attributes due to limits.

    This class is used to filter and handle these specific warnings separately
    from other warnings, ensuring that they are only shown once without
    interfering with default user warnings.
    """


warnings.simplefilter("once", LogRecordDroppedAttributesWarning)


@deprecated(
    "Use LogRecordDroppedAttributesWarning. Since logs are not stable yet this WILL be removed in future releases."
)
class LogDroppedAttributesWarning(LogRecordDroppedAttributesWarning):
    pass


class LogRecordLimits:
    """This class is based on a SpanLimits class in the Tracing module.

    This class represents the limits that should be enforced on recorded data such as events, links, attributes etc.

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

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

    - 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 log record (global fallback).
            Environment variable: ``OTEL_ATTRIBUTE_COUNT_LIMIT``
            Default: {_DEFAULT_OTEL_ATTRIBUTE_COUNT_LIMIT}
        max_attribute_length: Maximum length an attribute value can have (global fallback). Values
            longer than the specified length will be truncated.
        max_log_record_attributes: Maximum number of attributes that can be added to a log record.
            Environment variable: ``OTEL_LOGRECORD_ATTRIBUTE_COUNT_LIMIT``
            Falls back to ``max_attributes`` when unset.
        max_log_record_attribute_length: Maximum length a log record attribute value can have.
            Environment variable: ``OTEL_LOGRECORD_ATTRIBUTE_VALUE_LENGTH_LIMIT``
            Falls back to ``max_attribute_length`` when unset.
    """

    def __init__(
        self,
        max_attributes: int | None = None,
        max_attribute_length: int | None = None,
        max_log_record_attributes: int | None = None,
        max_log_record_attribute_length: int | None = None,
    ):
        # global 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
        )

        # global attribute length
        self.max_attribute_length = self._from_env_if_absent(
            max_attribute_length,
            OTEL_ATTRIBUTE_VALUE_LENGTH_LIMIT,
        )

        self.max_log_record_attributes = self._from_env_if_absent(
            max_log_record_attributes,
            OTEL_LOGRECORD_ATTRIBUTE_COUNT_LIMIT,
            default=self.max_attributes,
        )

        self.max_log_record_attribute_length = self._from_env_if_absent(
            max_log_record_attribute_length,
            OTEL_LOGRECORD_ATTRIBUTE_VALUE_LENGTH_LIMIT,
            default=self.max_attribute_length,
        )

    def __repr__(self):
        return (
            f"{type(self).__name__}("
            f"max_attributes={self.max_attributes}, "
            f"max_attribute_length={self.max_attribute_length}, "
            f"max_log_record_attributes={self.max_log_record_attributes}, "
            f"max_log_record_attribute_length={self.max_log_record_attribute_length})"
        )

    @classmethod
    def _from_env_if_absent(cls, value: int | None, env_var: str, default: int | None = None) -> int | 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


@deprecated("Use LogRecordLimits. Since logs are not stable yet this WILL be removed in future releases.")
class LogLimits(LogRecordLimits):
    pass


@dataclass(frozen=True)
class ReadableLogRecord:
    """Readable LogRecord should be kept exactly in-sync with ReadWriteLogRecord, only difference is the frozen=True param."""

    log_record: LogRecord
    resource: Resource
    instrumentation_scope: InstrumentationScope | None = None
    limits: LogRecordLimits | None = None

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

    def to_json(self, indent: int | None = 4) -> str:
        return json.dumps(
            {
                "body": self.log_record.body,
                "severity_number": self.log_record.severity_number.value
                if self.log_record.severity_number is not None
                else None,
                "severity_text": self.log_record.severity_text,
                "attributes": (dict(self.log_record.attributes) if bool(self.log_record.attributes) else None),
                "dropped_attributes": self.dropped_attributes,
                "timestamp": ns_to_iso_str(self.log_record.timestamp)
                if self.log_record.timestamp is not None
                else None,
                "observed_timestamp": ns_to_iso_str(self.log_record.observed_timestamp),
                "trace_id": (
                    f"0x{format_trace_id(self.log_record.trace_id)}" if self.log_record.trace_id is not None else ""
                ),
                "span_id": (
                    f"0x{format_span_id(self.log_record.span_id)}" if self.log_record.span_id is not None else ""
                ),
                "trace_flags": self.log_record.trace_flags,
                "resource": json.loads(self.resource.to_json()),
                "event_name": self.log_record.event_name if self.log_record.event_name else "",
            },
            indent=indent,
            cls=BytesEncoder,
        )


@dataclass
class ReadWriteLogRecord:
    """A ReadWriteLogRecord instance represents an event being logged.
    ReadWriteLogRecord instances are created and emitted via `Logger`
    every time something is logged. They contain all the information
    pertinent to the event being logged.
    """

    log_record: LogRecord
    resource: Resource | None = Resource.create({})
    instrumentation_scope: InstrumentationScope | None = None
    limits: LogRecordLimits = field(default_factory=LogRecordLimits)

    def __post_init__(self):
        self.log_record.attributes = BoundedAttributes(
            maxlen=self.limits.max_log_record_attributes,
            attributes=self.log_record.attributes if self.log_record.attributes else None,
            immutable=False,
            max_value_len=self.limits.max_log_record_attribute_length,
            extended_attributes=True,
        )
        if self.dropped_attributes > 0:
            warnings.warn(
                "Log record attributes were dropped due to limits",
                LogRecordDroppedAttributesWarning,
                stacklevel=2,
            )

    def __eq__(self, other: object) -> bool:
        if not isinstance(other, ReadWriteLogRecord):
            return NotImplemented
        return self.__dict__ == other.__dict__

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

    @classmethod
    def _from_api_log_record(
        cls,
        *,
        record: LogRecord,
        resource: Resource,
        instrumentation_scope: InstrumentationScope | None = None,
    ) -> ReadWriteLogRecord:
        return cls(
            log_record=record,
            resource=resource,
            instrumentation_scope=instrumentation_scope,
        )


class LogRecordProcessor(abc.ABC):
    """Interface to hook the log record emitting action.

    Log processors can be registered directly using
    :func:`LoggerProvider.add_log_record_processor` and they are invoked
    in the same order as they were registered.

    Implementers of custom log processors should be aware of the following:

    Error Handling
    --------------
    According to the OpenTelemetry error handling principles, the SDK should
    not throw unhandled exceptions at runtime. When implementing a custom
    ``LogRecordProcessor``, it is the **processor's responsibility** to handle
    any exceptions that may be raised by the exporter's ``export()`` method.

    The ``LogRecordExporter.export()`` method may raise exceptions (e.g.,
    network errors, timeouts). If these exceptions are not caught, they will
    propagate up and potentially crash the application.

    Custom processor implementations should wrap exporter calls in a
    try/except block. See ``SimpleLogRecordProcessor`` for a reference
    implementation::

        def on_emit(self, log_record: ReadWriteLogRecord):
            try:
                self._exporter.export((log_record,))
            except Exception:  # pylint: disable=broad-exception-caught
                logger.exception("Exception while exporting logs.")

    The ``BatchLogRecordProcessor`` handles this implicitly since export
    operations occur in a background thread where exceptions cannot bubble
    up to the caller.
    """

    @abc.abstractmethod
    def on_emit(self, log_record: ReadWriteLogRecord) -> None:
        """Emits the ``ReadWriteLogRecord``.

        Implementers should handle any exceptions raised during log processing
        to prevent application crashes. See the class docstring for details
        on error handling expectations.
        """

    @abc.abstractmethod
    def shutdown(self) -> None:
        """Called when a :class:`opentelemetry.sdk._logs.Logger` is shutdown"""

    @abc.abstractmethod
    def force_flush(self, timeout_millis: int = 30000) -> bool:
        """Export all the received logs to the configured Exporter that have not yet
        been exported.

        Args:
            timeout_millis: The maximum amount of time to wait for logs 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 SynchronousMultiLogRecordProcessor(LogRecordProcessor):
    """Implementation of class:`LogRecordProcessor` that forwards all received
    events to a list of log processors sequentially.

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

    def __init__(self):
        # use a tuple to avoid race conditions when adding a new log and
        # iterating through it on "emit".
        self._log_record_processors = ()  # type: tuple[LogRecordProcessor, ...]
        self._lock = threading.Lock()

    def add_log_record_processor(self, log_record_processor: LogRecordProcessor) -> None:
        """Adds a Logprocessor to the list of log processors handled by this instance"""
        with self._lock:
            self._log_record_processors += (log_record_processor,)

    def on_emit(self, log_record: ReadWriteLogRecord) -> None:
        for lp in self._log_record_processors:
            lp.on_emit(log_record)

    def shutdown(self) -> None:
        """Shutdown the log processors one by one"""
        for lp in self._log_record_processors:
            lp.shutdown()

    def force_flush(self, timeout_millis: int = 30000) -> bool:
        """Force flush the log processors one by one

        Args:
            timeout_millis: The maximum amount of time to wait for logs to be
                exported. If the first n log processors exceeded the timeout
                then remaining log processors will not be flushed.

        Returns:
            True if all the log processors flushes the logs within timeout,
            False otherwise.
        """
        deadline_ns = time_ns() + timeout_millis * 1000000
        all_flushed = True
        for lp in self._log_record_processors:
            current_ts = time_ns()
            if current_ts >= deadline_ns:
                return False

            if lp.force_flush((deadline_ns - current_ts) // 1000000) is False:
                all_flushed = False

        return all_flushed


class ConcurrentMultiLogRecordProcessor(LogRecordProcessor):
    """Implementation of :class:`LogRecordProcessor` that forwards all received
    events to a list of log processors in parallel.

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

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

    def __init__(self, max_workers: int = 2):
        # use a tuple to avoid race conditions when adding a new log and
        # iterating through it on "emit".
        self._log_record_processors = ()  # type: tuple[LogRecordProcessor, ...]
        self._lock = threading.Lock()
        self._executor = concurrent.futures.ThreadPoolExecutor(max_workers=max_workers)

    def add_log_record_processor(self, log_record_processor: LogRecordProcessor):
        with self._lock:
            self._log_record_processors += (log_record_processor,)

    def _submit_and_wait(
        self,
        func: Callable[[LogRecordProcessor], Callable[..., None]],
        *args: Any,
        **kwargs: Any,
    ):
        futures = []
        for lp in self._log_record_processors:
            future = self._executor.submit(func(lp), *args, **kwargs)
            futures.append(future)
        for future in futures:
            future.result()

    def on_emit(self, log_record: ReadWriteLogRecord) -> None:
        self._submit_and_wait(lambda lp: lp.on_emit, log_record)

    def shutdown(self) -> None:
        self._submit_and_wait(lambda lp: lp.shutdown)

    def force_flush(self, timeout_millis: int = 30000) -> bool:
        """Force flush the log processors in parallel.

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

        Returns:
            True if all the log processors flushes the logs within timeout,
            False otherwise.
        """
        futures = []
        for lp in self._log_record_processors:
            future = self._executor.submit(lp.force_flush, timeout_millis)
            futures.append(future)

        done_futures, not_done_futures = concurrent.futures.wait(futures, timeout_millis / 1e3)

        if not_done_futures:
            return False

        for future in done_futures:
            if future.result() is False:
                return False

        return True


# skip natural LogRecord attributes
# http://docs.python.org/library/logging.html#logrecord-attributes
_RESERVED_ATTRS = frozenset(
    (
        "asctime",
        "args",
        "created",
        "exc_info",
        "exc_text",
        "filename",
        "funcName",
        "getMessage",
        "message",
        "levelname",
        "levelno",
        "lineno",
        "module",
        "msecs",
        "msg",
        "name",
        "pathname",
        "process",
        "processName",
        "relativeCreated",
        "stack_info",
        "thread",
        "threadName",
        "taskName",
    )
)


class LoggingHandler(logging.Handler):
    """A handler class which writes logging records, in OTLP format, to
    a network destination or file. Supports signals from the `logging` module.
    https://docs.python.org/3/library/logging.html
    """

    def __init__(
        self,
        level: int = logging.NOTSET,
        logger_provider: APILoggerProvider | None = None,
    ) -> None:
        super().__init__(level=level)
        self._logger_provider = logger_provider or get_logger_provider()

        warnings.warn(
            "`LoggingHandler` in `opentelemetry-sdk` is deprecated. Use the "
            "handler from `opentelemetry-instrumentation-logging` instead.",
            DeprecationWarning,
        )

    @staticmethod
    def _get_attributes(record: logging.LogRecord) -> _ExtendedAttributes:
        attributes = {k: v for k, v in vars(record).items() if k not in _RESERVED_ATTRS}

        # Add standard code attributes for logs.
        attributes[code_attributes.CODE_FILE_PATH] = record.pathname
        attributes[code_attributes.CODE_FUNCTION_NAME] = record.funcName
        attributes[code_attributes.CODE_LINE_NUMBER] = record.lineno

        if record.exc_info:
            exctype, value, tb = record.exc_info
            if exctype is not None:
                attributes[exception_attributes.EXCEPTION_TYPE] = exctype.__name__
            if value is not None and value.args:
                attributes[exception_attributes.EXCEPTION_MESSAGE] = str(value.args[0])
            if tb is not None:
                # https://opentelemetry.io/docs/specs/semconv/exceptions/exceptions-spans/#stacktrace-representation
                attributes[exception_attributes.EXCEPTION_STACKTRACE] = "".join(
                    traceback.format_exception(*record.exc_info)
                )
        return attributes

    def _translate(self, record: logging.LogRecord) -> LogRecord:
        timestamp = int(record.created * 1e9)
        observered_timestamp = time_ns()
        attributes = self._get_attributes(record)
        severity_number = std_to_otel(record.levelno)
        if self.formatter:
            body = self.format(record)
        else:
            # `record.getMessage()` uses `record.msg` as a template to format
            # `record.args` into. There is a special case in `record.getMessage()`
            # where it will only attempt formatting if args are provided,
            # otherwise, it just stringifies `record.msg`.
            #
            # Since the OTLP body field has a type of 'any' and the logging module
            # is sometimes used in such a way that objects incorrectly end up
            # set as record.msg, in those cases we would like to bypass
            # `record.getMessage()` completely and set the body to the object
            # itself instead of its string representation.
            # For more background, see: https://github.com/open-telemetry/opentelemetry-python/pull/4216
            if not record.args and not isinstance(record.msg, str):
                #  if record.msg is not a value we can export, cast it to string
                if not isinstance(record.msg, _VALID_ANY_VALUE_TYPES):
                    body = str(record.msg)
                else:
                    body = record.msg
            else:
                body = record.getMessage()

        # Map Python log level names to OTel severity text as defined in
        # https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/logs/data-model.md#displaying-severity
        # Python "WARNING" -> OTel "WARN" (see #3548)
        # Python "CRITICAL" -> OTel "FATAL" (see #4984)
        _python_to_otel_severity_text = {
            "WARNING": "WARN",
            "CRITICAL": "FATAL",
        }
        level_name = _python_to_otel_severity_text.get(record.levelname, record.levelname)

        return LogRecord(
            timestamp=timestamp,
            observed_timestamp=observered_timestamp,
            context=get_current() or None,
            severity_text=level_name,
            severity_number=severity_number,
            body=body,
            attributes=attributes,
        )

    def emit(self, record: logging.LogRecord) -> None:
        """
        Emit a record. Skip emitting if logger is NoOp.

        The record is translated to OTel format, and then sent across the pipeline.
        """
        logger = get_logger(record.name, logger_provider=self._logger_provider)
        if not isinstance(logger, NoOpLogger):
            logger.emit(self._translate(record))

    def flush(self) -> None:
        """
        Flushes the logging output. Skip flushing if logging_provider has no force_flush method.
        """
        if hasattr(self._logger_provider, "force_flush") and callable(
            self._logger_provider.force_flush  # type: ignore[reportAttributeAccessIssue]
        ):
            # This is done in a separate thread to avoid a potential deadlock, for
            # details see https://github.com/open-telemetry/opentelemetry-python/pull/4636.
            thread = threading.Thread(target=self._logger_provider.force_flush)  # type: ignore[reportAttributeAccessIssue]
            thread.start()


@dataclass
class _LoggerConfig:
    is_enabled: bool = True

    @classmethod
    def default(cls) -> _LoggerConfig:
        return _LoggerConfig()


class Logger(APILogger):
    def __init__(
        self,
        resource: Resource,
        multi_log_record_processor: SynchronousMultiLogRecordProcessor | ConcurrentMultiLogRecordProcessor,
        instrumentation_scope: InstrumentationScope,
        *,
        logger_metrics: LoggerMetricsT,
        _logger_config: _LoggerConfig,
    ):
        super().__init__(
            instrumentation_scope.name,
            instrumentation_scope.version,
            instrumentation_scope.schema_url,
            instrumentation_scope.attributes,
        )
        self._resource = resource
        self._multi_log_record_processor = multi_log_record_processor
        self._instrumentation_scope = instrumentation_scope
        self._logger_metrics = logger_metrics
        self._logger_config = _logger_config

    def _is_enabled(self) -> bool:
        return self._logger_config.is_enabled

    def _set_logger_config(self, logger_config: _LoggerConfig) -> None:
        self._logger_config = logger_config

    def _set_resource(self, resource: Resource) -> None:
        self._resource = resource

    @property
    def instrumentation_scope(self):
        return self._instrumentation_scope

    @property
    def resource(self):
        return self._resource

    # pylint: disable=arguments-differ
    def emit(
        self,
        record: LogRecord | None = None,
        *,
        timestamp: int | None = None,
        observed_timestamp: int | None = None,
        context: Context | None = None,
        severity_number: SeverityNumber | None = None,
        severity_text: str | None = None,
        body: AnyValue | None = None,
        attributes: _ExtendedAttributes | None = None,
        event_name: str | None = None,
        exception: BaseException | None = None,
    ) -> None:
        """Emits the :class:`ReadWriteLogRecord` by setting instrumentation scope
        and forwarding to the processor.
        """
        if not self._is_enabled():
            return
        # If a record is provided, use it directly
        if record is not None:
            if not isinstance(record, ReadWriteLogRecord):
                if record.exception is not None:
                    record = _copy_log_record_with_exception(record)
                # pylint:disable=protected-access
                writable_record = ReadWriteLogRecord._from_api_log_record(
                    record=record,
                    resource=self._resource,
                    instrumentation_scope=self._instrumentation_scope,
                )
            else:
                _set_log_record_exception_attributes(record.log_record)
                writable_record = record
        else:
            # Create a record from individual parameters
            log_record = _create_log_record_with_exception(
                timestamp=timestamp,
                observed_timestamp=observed_timestamp,
                context=context,
                severity_number=severity_number,
                severity_text=severity_text,
                body=body,
                attributes=attributes,
                event_name=event_name,
                exception=exception,
            )
            # pylint:disable=protected-access
            writable_record = ReadWriteLogRecord._from_api_log_record(
                record=log_record,
                resource=self._resource,
                instrumentation_scope=self._instrumentation_scope,
            )

        self._logger_metrics.emit_log()
        self._multi_log_record_processor.on_emit(writable_record)


_LoggerConfiguratorT = Callable[[InstrumentationScope], _LoggerConfig]
_RuleBasedLoggerConfigurator = RuleBasedConfigurator[_LoggerConfig]


def _default_logger_configurator(
    _logger_scope: InstrumentationScope,
) -> _LoggerConfig:
    return _LoggerConfig.default()


def _disable_logger_configurator(
    _logger_scope: InstrumentationScope,
) -> _LoggerConfig:
    return _LoggerConfig(is_enabled=False)


class LoggerProvider(APILoggerProvider):
    def __init__(
        self,
        resource: Resource | None = None,
        shutdown_on_exit: bool = True,
        multi_log_record_processor: SynchronousMultiLogRecordProcessor
        | ConcurrentMultiLogRecordProcessor
        | None = None,
        *,
        meter_provider: MeterProvider | None = None,
        _logger_configurator: _LoggerConfiguratorT | None = None,
    ):
        if resource is None:
            self._resource = Resource.create({})
        else:
            self._resource = resource
        self._multi_log_record_processor = multi_log_record_processor or SynchronousMultiLogRecordProcessor()
        self._logger_metrics = create_logger_metrics(
            meter_provider or get_meter_provider(),
            parse_boolean_environment_variable(OTEL_PYTHON_SDK_INTERNAL_METRICS_ENABLED),
        )
        disabled = environ.get(OTEL_SDK_DISABLED, "")
        self._disabled = disabled.lower().strip() == "true"
        self._logger_configurator = _logger_configurator or _default_logger_configurator
        self._at_exit_handler = None
        if shutdown_on_exit:
            self._at_exit_handler = atexit.register(self.shutdown)
        self._logger_cache = {}
        self._logger_cache_lock = Lock()
        self._active_loggers: WeakSet[Logger] = WeakSet()
        self._active_loggers_lock = Lock()
        if hasattr(os, "register_at_fork"):
            weak_at_fork = WeakMethod(self._handle_fork)

            def _after_in_child() -> None:
                if at_fork := weak_at_fork():
                    at_fork()

            os.register_at_fork(after_in_child=_after_in_child)

    def _handle_fork(self) -> None:
        self._logger_cache_lock = Lock()
        self._active_loggers_lock = Lock()
        self._update_resource(_get_process_dependent_resource())

    @property
    def resource(self):
        return self._resource

    def _update_resource(self, resource: Resource) -> None:
        with self._active_loggers_lock:
            self._resource = self._resource.merge(resource)
            for logger in list(self._active_loggers):
                # pylint: disable-next=protected-access
                logger._set_resource(self._resource)

    def _get_logger_no_cache(
        self,
        name: str,
        version: str | None = None,
        schema_url: str | None = None,
        attributes: _ExtendedAttributes | None = None,
    ) -> Logger:
        scope = InstrumentationScope(name, version, schema_url, attributes)

        return Logger(
            self._resource,
            self._multi_log_record_processor,
            scope,
            logger_metrics=self._logger_metrics,
            _logger_config=self._apply_logger_configurator(scope),
        )

    def _get_logger_cached(
        self,
        name: str,
        version: str | None = None,
        schema_url: str | None = None,
    ) -> Logger:
        with self._logger_cache_lock:
            key = (name, version, schema_url)
            if key in self._logger_cache:
                return self._logger_cache[key]

            self._logger_cache[key] = self._get_logger_no_cache(name, version, schema_url)
            return self._logger_cache[key]

    def get_logger(
        self,
        name: str,
        version: str | None = None,
        schema_url: str | None = None,
        attributes: _ExtendedAttributes | None = None,
    ) -> APILogger:
        if self._disabled:
            return NoOpLogger(
                name,
                version=version,
                schema_url=schema_url,
                attributes=attributes,
            )
        logger = (
            self._get_logger_cached(name, version, schema_url)
            if attributes is None
            else self._get_logger_no_cache(name, version, schema_url, attributes)
        )
        with self._active_loggers_lock:
            self._active_loggers.add(logger)
        return logger

    def add_log_record_processor(self, log_record_processor: LogRecordProcessor):
        """Registers a new :class:`LogRecordProcessor` for this `LoggerProvider` instance.

        The log processors are invoked in the same order they are registered.
        """
        self._multi_log_record_processor.add_log_record_processor(log_record_processor)

    def _set_logger_configurator(self, *, logger_configurator: _LoggerConfiguratorT):
        """Set a new LoggerConfigurator for this LoggerProvider.

        Setting a new LoggerConfigurator will result in the configurator being called
        for each outstanding Logger and for any newly created loggers thereafter.
        Therefore, it is important that the provided function returns quickly.
        """
        self._logger_configurator = logger_configurator
        with self._active_loggers_lock:
            for logger in list(self._active_loggers):
                # pylint: disable-next=protected-access
                logger._set_logger_config(self._apply_logger_configurator(logger.instrumentation_scope))

    def _apply_logger_configurator(self, instrumentation_scope: InstrumentationScope) -> _LoggerConfig:
        try:
            return self._logger_configurator(instrumentation_scope)
        # pylint: disable-next=broad-exception-caught
        except Exception:
            _logger.exception(
                "logger configurator failed for scope '%s', using default config",
                instrumentation_scope.name,
            )
            return _LoggerConfig.default()

    def shutdown(self) -> None:
        """Shuts down the log processors."""
        self._multi_log_record_processor.shutdown()
        if self._at_exit_handler is not None:
            atexit.unregister(self._at_exit_handler)
            self._at_exit_handler = None

    def force_flush(self, timeout_millis: int = 30000) -> bool:
        """Force flush the log processors.

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

        Returns:
            True if all the log processors flushes the logs within timeout,
            False otherwise.
        """
        return self._multi_log_record_processor.force_flush(timeout_millis)


_STD_TO_OTEL = {
    10: SeverityNumber.DEBUG,
    11: SeverityNumber.DEBUG2,
    12: SeverityNumber.DEBUG3,
    13: SeverityNumber.DEBUG4,
    14: SeverityNumber.DEBUG4,
    15: SeverityNumber.DEBUG4,
    16: SeverityNumber.DEBUG4,
    17: SeverityNumber.DEBUG4,
    18: SeverityNumber.DEBUG4,
    19: SeverityNumber.DEBUG4,
    20: SeverityNumber.INFO,
    21: SeverityNumber.INFO2,
    22: SeverityNumber.INFO3,
    23: SeverityNumber.INFO4,
    24: SeverityNumber.INFO4,
    25: SeverityNumber.INFO4,
    26: SeverityNumber.INFO4,
    27: SeverityNumber.INFO4,
    28: SeverityNumber.INFO4,
    29: SeverityNumber.INFO4,
    30: SeverityNumber.WARN,
    31: SeverityNumber.WARN2,
    32: SeverityNumber.WARN3,
    33: SeverityNumber.WARN4,
    34: SeverityNumber.WARN4,
    35: SeverityNumber.WARN4,
    36: SeverityNumber.WARN4,
    37: SeverityNumber.WARN4,
    38: SeverityNumber.WARN4,
    39: SeverityNumber.WARN4,
    40: SeverityNumber.ERROR,
    41: SeverityNumber.ERROR2,
    42: SeverityNumber.ERROR3,
    43: SeverityNumber.ERROR4,
    44: SeverityNumber.ERROR4,
    45: SeverityNumber.ERROR4,
    46: SeverityNumber.ERROR4,
    47: SeverityNumber.ERROR4,
    48: SeverityNumber.ERROR4,
    49: SeverityNumber.ERROR4,
    50: SeverityNumber.FATAL,
    51: SeverityNumber.FATAL2,
    52: SeverityNumber.FATAL3,
    53: SeverityNumber.FATAL4,
}


def std_to_otel(levelno: int) -> SeverityNumber:
    """
    Map python log levelno as defined in https://docs.python.org/3/library/logging.html#logging-levels
    to OTel log severity number as defined here: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/logs/data-model.md#field-severitynumber
    """
    if levelno < 10:
        return SeverityNumber.UNSPECIFIED
    if levelno > 53:
        return SeverityNumber.FATAL4
    return _STD_TO_OTEL[levelno]
