structure saas with tools

This commit is contained in:
Davidson Gomes
2025-04-25 15:30:54 -03:00
commit 1aef473937
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# 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.
from opentelemetry.sdk._logs._internal import (
LogData,
LogDroppedAttributesWarning,
Logger,
LoggerProvider,
LoggingHandler,
LogLimits,
LogRecord,
LogRecordProcessor,
)
__all__ = [
"LogData",
"Logger",
"LoggerProvider",
"LoggingHandler",
"LogLimits",
"LogRecord",
"LogRecordProcessor",
"LogDroppedAttributesWarning",
]

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# 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.
from __future__ import annotations
import abc
import atexit
import concurrent.futures
import json
import logging
import threading
import traceback
import warnings
from os import environ
from threading import Lock
from time import time_ns
from typing import Any, Callable, Tuple, Union # noqa
from opentelemetry._logs import Logger as APILogger
from opentelemetry._logs import LoggerProvider as APILoggerProvider
from opentelemetry._logs import LogRecord as APILogRecord
from opentelemetry._logs import (
NoOpLogger,
SeverityNumber,
get_logger,
get_logger_provider,
std_to_otel,
)
from opentelemetry.attributes import _VALID_ANY_VALUE_TYPES, BoundedAttributes
from opentelemetry.sdk.environment_variables import (
OTEL_ATTRIBUTE_COUNT_LIMIT,
OTEL_ATTRIBUTE_VALUE_LENGTH_LIMIT,
OTEL_SDK_DISABLED,
)
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.util import ns_to_iso_str
from opentelemetry.sdk.util.instrumentation import InstrumentationScope
from opentelemetry.semconv.trace import SpanAttributes
from opentelemetry.trace import (
format_span_id,
format_trace_id,
get_current_span,
)
from opentelemetry.trace.span import TraceFlags
from opentelemetry.util.types import AnyValue, Attributes
_logger = logging.getLogger(__name__)
_DEFAULT_OTEL_ATTRIBUTE_COUNT_LIMIT = 128
_ENV_VALUE_UNSET = ""
class LogDroppedAttributesWarning(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", LogDroppedAttributesWarning)
class LogLimits:
"""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, ``None`` or ``LogLimits.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_OTEL_ATTRIBUTE_COUNT_LIMIT}
max_attribute_length: Maximum length an attribute value can have. Values longer than
the specified length will be truncated.
"""
UNSET = -1
def __init__(
self,
max_attributes: int | None = None,
max_attribute_length: int | None = None,
):
# 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
)
# attribute length
self.max_attribute_length = self._from_env_if_absent(
max_attribute_length,
OTEL_ATTRIBUTE_VALUE_LENGTH_LIMIT,
)
def __repr__(self):
return f"{type(self).__name__}(max_attributes={self.max_attributes}, max_attribute_length={self.max_attribute_length})"
@classmethod
def _from_env_if_absent(
cls, value: int | None, env_var: str, default: int | None = None
) -> int | None:
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
_UnsetLogLimits = LogLimits(
max_attributes=LogLimits.UNSET,
max_attribute_length=LogLimits.UNSET,
)
class LogRecord(APILogRecord):
"""A LogRecord instance represents an event being logged.
LogRecord instances are created and emitted via `Logger`
every time something is logged. They contain all the information
pertinent to the event being logged.
"""
def __init__(
self,
timestamp: int | None = None,
observed_timestamp: int | None = None,
trace_id: int | None = None,
span_id: int | None = None,
trace_flags: TraceFlags | None = None,
severity_text: str | None = None,
severity_number: SeverityNumber | None = None,
body: AnyValue | None = None,
resource: Resource | None = None,
attributes: Attributes | None = None,
limits: LogLimits | None = _UnsetLogLimits,
):
super().__init__(
**{
"timestamp": timestamp,
"observed_timestamp": observed_timestamp,
"trace_id": trace_id,
"span_id": span_id,
"trace_flags": trace_flags,
"severity_text": severity_text,
"severity_number": severity_number,
"body": body,
"attributes": BoundedAttributes(
maxlen=limits.max_attributes,
attributes=attributes if bool(attributes) else None,
immutable=False,
max_value_len=limits.max_attribute_length,
),
}
)
self.resource = (
resource if isinstance(resource, Resource) else Resource.create({})
)
if self.dropped_attributes > 0:
warnings.warn(
"Log record attributes were dropped due to limits",
LogDroppedAttributesWarning,
stacklevel=2,
)
def __eq__(self, other: object) -> bool:
if not isinstance(other, LogRecord):
return NotImplemented
return self.__dict__ == other.__dict__
def to_json(self, indent: int | None = 4) -> str:
return json.dumps(
{
"body": self.body,
"severity_number": self.severity_number.value
if self.severity_number is not None
else None,
"severity_text": self.severity_text,
"attributes": (
dict(self.attributes) if bool(self.attributes) else None
),
"dropped_attributes": self.dropped_attributes,
"timestamp": ns_to_iso_str(self.timestamp),
"observed_timestamp": ns_to_iso_str(self.observed_timestamp),
"trace_id": (
f"0x{format_trace_id(self.trace_id)}"
if self.trace_id is not None
else ""
),
"span_id": (
f"0x{format_span_id(self.span_id)}"
if self.span_id is not None
else ""
),
"trace_flags": self.trace_flags,
"resource": json.loads(self.resource.to_json()),
},
indent=indent,
)
@property
def dropped_attributes(self) -> int:
if self.attributes:
return self.attributes.dropped
return 0
class LogData:
"""Readable LogRecord data plus associated InstrumentationLibrary."""
def __init__(
self,
log_record: LogRecord,
instrumentation_scope: InstrumentationScope,
):
self.log_record = log_record
self.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.
"""
@abc.abstractmethod
def emit(self, log_data: LogData):
"""Emits the `LogData`"""
@abc.abstractmethod
def shutdown(self):
"""Called when a :class:`opentelemetry.sdk._logs.Logger` is shutdown"""
@abc.abstractmethod
def force_flush(self, timeout_millis: int = 30000):
"""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 emit(self, log_data: LogData) -> None:
for lp in self._log_record_processors:
lp.emit(log_data)
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
for lp in self._log_record_processors:
current_ts = time_ns()
if current_ts >= deadline_ns:
return False
if not lp.force_flush((deadline_ns - current_ts) // 1000000):
return False
return True
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 emit(self, log_data: LogData):
self._submit_and_wait(lambda lp: lp.emit, log_data)
def shutdown(self):
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 not future.result():
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=logging.NOTSET,
logger_provider=None,
) -> None:
super().__init__(level=level)
self._logger_provider = logger_provider or get_logger_provider()
@staticmethod
def _get_attributes(record: logging.LogRecord) -> Attributes:
attributes = {
k: v for k, v in vars(record).items() if k not in _RESERVED_ATTRS
}
# Add standard code attributes for logs.
attributes[SpanAttributes.CODE_FILEPATH] = record.pathname
attributes[SpanAttributes.CODE_FUNCTION] = record.funcName
attributes[SpanAttributes.CODE_LINENO] = record.lineno
if record.exc_info:
exctype, value, tb = record.exc_info
if exctype is not None:
attributes[SpanAttributes.EXCEPTION_TYPE] = exctype.__name__
if value is not None and value.args:
attributes[SpanAttributes.EXCEPTION_MESSAGE] = str(
value.args[0]
)
if tb is not None:
# https://github.com/open-telemetry/opentelemetry-specification/blob/9fa7c656b26647b27e485a6af7e38dc716eba98a/specification/trace/semantic_conventions/exceptions.md#stacktrace-representation
attributes[SpanAttributes.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()
span_context = get_current_span().get_span_context()
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()
# related to https://github.com/open-telemetry/opentelemetry-python/issues/3548
# Severity Text = WARN as defined in https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/logs/data-model.md#displaying-severity.
level_name = (
"WARN" if record.levelname == "WARNING" else record.levelname
)
logger = get_logger(record.name, logger_provider=self._logger_provider)
return LogRecord(
timestamp=timestamp,
observed_timestamp=observered_timestamp,
trace_id=span_context.trace_id,
span_id=span_context.span_id,
trace_flags=span_context.trace_flags,
severity_text=level_name,
severity_number=severity_number,
body=body,
resource=logger.resource,
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
):
self._logger_provider.force_flush()
class Logger(APILogger):
def __init__(
self,
resource: Resource,
multi_log_record_processor: Union[
SynchronousMultiLogRecordProcessor,
ConcurrentMultiLogRecordProcessor,
],
instrumentation_scope: InstrumentationScope,
):
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
@property
def resource(self):
return self._resource
def emit(self, record: LogRecord):
"""Emits the :class:`LogData` by associating :class:`LogRecord`
and instrumentation info.
"""
log_data = LogData(record, self._instrumentation_scope)
self._multi_log_record_processor.emit(log_data)
class LoggerProvider(APILoggerProvider):
def __init__(
self,
resource: Resource | None = None,
shutdown_on_exit: bool = True,
multi_log_record_processor: SynchronousMultiLogRecordProcessor
| ConcurrentMultiLogRecordProcessor
| 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()
)
disabled = environ.get(OTEL_SDK_DISABLED, "")
self._disabled = disabled.lower().strip() == "true"
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()
@property
def resource(self):
return self._resource
def _get_logger_no_cache(
self,
name: str,
version: str | None = None,
schema_url: str | None = None,
attributes: Attributes | None = None,
) -> Logger:
return Logger(
self._resource,
self._multi_log_record_processor,
InstrumentationScope(
name,
version,
schema_url,
attributes,
),
)
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: Attributes | None = None,
) -> Logger:
if self._disabled:
return NoOpLogger(
name,
version=version,
schema_url=schema_url,
attributes=attributes,
)
if attributes is None:
return self._get_logger_cached(name, version, schema_url)
return self._get_logger_no_cache(name, version, schema_url, attributes)
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 shutdown(self):
"""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)

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# 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.
from __future__ import annotations
import abc
import collections
import enum
import logging
import os
import sys
import threading
import weakref
from os import environ, linesep
from time import time_ns
from typing import IO, Callable, Deque, List, Optional, Sequence
from opentelemetry.context import (
_SUPPRESS_INSTRUMENTATION_KEY,
attach,
detach,
set_value,
)
from opentelemetry.sdk._logs import LogData, LogRecord, LogRecordProcessor
from opentelemetry.sdk.environment_variables import (
OTEL_BLRP_EXPORT_TIMEOUT,
OTEL_BLRP_MAX_EXPORT_BATCH_SIZE,
OTEL_BLRP_MAX_QUEUE_SIZE,
OTEL_BLRP_SCHEDULE_DELAY,
)
from opentelemetry.util._once import Once
_DEFAULT_SCHEDULE_DELAY_MILLIS = 5000
_DEFAULT_MAX_EXPORT_BATCH_SIZE = 512
_DEFAULT_EXPORT_TIMEOUT_MILLIS = 30000
_DEFAULT_MAX_QUEUE_SIZE = 2048
_ENV_VAR_INT_VALUE_ERROR_MESSAGE = (
"Unable to parse value for %s as integer. Defaulting to %s."
)
_logger = logging.getLogger(__name__)
class LogExportResult(enum.Enum):
SUCCESS = 0
FAILURE = 1
class LogExporter(abc.ABC):
"""Interface for exporting logs.
Interface to be implemented by services that want to export logs received
in their own format.
To export data this MUST be registered to the :class`opentelemetry.sdk._logs.Logger` using a
log processor.
"""
@abc.abstractmethod
def export(self, batch: Sequence[LogData]):
"""Exports a batch of logs.
Args:
batch: The list of `LogData` objects to be exported
Returns:
The result of the export
"""
@abc.abstractmethod
def shutdown(self):
"""Shuts down the exporter.
Called when the SDK is shut down.
"""
class ConsoleLogExporter(LogExporter):
"""Implementation of :class:`LogExporter` that prints log records to the
console.
This class can be used for diagnostic purposes. It prints the exported
log records to the console STDOUT.
"""
def __init__(
self,
out: IO = sys.stdout,
formatter: Callable[[LogRecord], str] = lambda record: record.to_json()
+ linesep,
):
self.out = out
self.formatter = formatter
def export(self, batch: Sequence[LogData]):
for data in batch:
self.out.write(self.formatter(data.log_record))
self.out.flush()
return LogExportResult.SUCCESS
def shutdown(self):
pass
class SimpleLogRecordProcessor(LogRecordProcessor):
"""This is an implementation of LogRecordProcessor which passes
received logs in the export-friendly LogData representation to the
configured LogExporter, as soon as they are emitted.
"""
def __init__(self, exporter: LogExporter):
self._exporter = exporter
self._shutdown = False
def emit(self, log_data: LogData):
if self._shutdown:
_logger.warning("Processor is already shutdown, ignoring call")
return
token = attach(set_value(_SUPPRESS_INSTRUMENTATION_KEY, True))
try:
self._exporter.export((log_data,))
except Exception: # pylint: disable=broad-exception-caught
_logger.exception("Exception while exporting logs.")
detach(token)
def shutdown(self):
self._shutdown = True
self._exporter.shutdown()
def force_flush(self, timeout_millis: int = 30000) -> bool: # pylint: disable=no-self-use
return True
class _FlushRequest:
__slots__ = ["event", "num_log_records"]
def __init__(self):
self.event = threading.Event()
self.num_log_records = 0
_BSP_RESET_ONCE = Once()
class BatchLogRecordProcessor(LogRecordProcessor):
"""This is an implementation of LogRecordProcessor which creates batches of
received logs in the export-friendly LogData representation and
send to the configured LogExporter, as soon as they are emitted.
`BatchLogRecordProcessor` is configurable with the following environment
variables which correspond to constructor parameters:
- :envvar:`OTEL_BLRP_SCHEDULE_DELAY`
- :envvar:`OTEL_BLRP_MAX_QUEUE_SIZE`
- :envvar:`OTEL_BLRP_MAX_EXPORT_BATCH_SIZE`
- :envvar:`OTEL_BLRP_EXPORT_TIMEOUT`
"""
_queue: Deque[LogData]
_flush_request: _FlushRequest | None
_log_records: List[LogData | None]
def __init__(
self,
exporter: LogExporter,
schedule_delay_millis: float | None = None,
max_export_batch_size: int | None = None,
export_timeout_millis: float | None = None,
max_queue_size: int | None = None,
):
if max_queue_size is None:
max_queue_size = BatchLogRecordProcessor._default_max_queue_size()
if schedule_delay_millis is None:
schedule_delay_millis = (
BatchLogRecordProcessor._default_schedule_delay_millis()
)
if max_export_batch_size is None:
max_export_batch_size = (
BatchLogRecordProcessor._default_max_export_batch_size()
)
if export_timeout_millis is None:
export_timeout_millis = (
BatchLogRecordProcessor._default_export_timeout_millis()
)
BatchLogRecordProcessor._validate_arguments(
max_queue_size, schedule_delay_millis, max_export_batch_size
)
self._exporter = exporter
self._max_queue_size = max_queue_size
self._schedule_delay_millis = schedule_delay_millis
self._max_export_batch_size = max_export_batch_size
self._export_timeout_millis = export_timeout_millis
self._queue = collections.deque([], max_queue_size)
self._worker_thread = threading.Thread(
name="OtelBatchLogRecordProcessor",
target=self.worker,
daemon=True,
)
self._condition = threading.Condition(threading.Lock())
self._shutdown = False
self._flush_request = None
self._log_records = [None] * self._max_export_batch_size
self._worker_thread.start()
if hasattr(os, "register_at_fork"):
weak_reinit = weakref.WeakMethod(self._at_fork_reinit)
os.register_at_fork(after_in_child=lambda: weak_reinit()()) # pylint: disable=unnecessary-lambda
self._pid = os.getpid()
def _at_fork_reinit(self):
self._condition = threading.Condition(threading.Lock())
self._queue.clear()
self._worker_thread = threading.Thread(
name="OtelBatchLogRecordProcessor",
target=self.worker,
daemon=True,
)
self._worker_thread.start()
self._pid = os.getpid()
def worker(self):
timeout = self._schedule_delay_millis / 1e3
flush_request: Optional[_FlushRequest] = None
while not self._shutdown:
with self._condition:
if self._shutdown:
# shutdown may have been called, avoid further processing
break
flush_request = self._get_and_unset_flush_request()
if (
len(self._queue) < self._max_export_batch_size
and flush_request is None
):
self._condition.wait(timeout)
flush_request = self._get_and_unset_flush_request()
if not self._queue:
timeout = self._schedule_delay_millis / 1e3
self._notify_flush_request_finished(flush_request)
flush_request = None
continue
if self._shutdown:
break
start_ns = time_ns()
self._export(flush_request)
end_ns = time_ns()
# subtract the duration of this export call to the next timeout
timeout = self._schedule_delay_millis / 1e3 - (
(end_ns - start_ns) / 1e9
)
self._notify_flush_request_finished(flush_request)
flush_request = None
# there might have been a new flush request while export was running
# and before the done flag switched to true
with self._condition:
shutdown_flush_request = self._get_and_unset_flush_request()
# flush the remaining logs
self._drain_queue()
self._notify_flush_request_finished(flush_request)
self._notify_flush_request_finished(shutdown_flush_request)
def _export(self, flush_request: Optional[_FlushRequest] = None):
"""Exports logs considering the given flush_request.
If flush_request is not None then logs are exported in batches
until the number of exported logs reached or exceeded the num of logs in
flush_request, otherwise exports at max max_export_batch_size logs.
"""
if flush_request is None:
self._export_batch()
return
num_log_records = flush_request.num_log_records
while self._queue:
exported = self._export_batch()
num_log_records -= exported
if num_log_records <= 0:
break
def _export_batch(self) -> int:
"""Exports at most max_export_batch_size logs and returns the number of
exported logs.
"""
idx = 0
while idx < self._max_export_batch_size and self._queue:
record = self._queue.pop()
self._log_records[idx] = record
idx += 1
token = attach(set_value(_SUPPRESS_INSTRUMENTATION_KEY, True))
try:
self._exporter.export(self._log_records[:idx]) # type: ignore
except Exception: # pylint: disable=broad-exception-caught
_logger.exception("Exception while exporting logs.")
detach(token)
for index in range(idx):
self._log_records[index] = None
return idx
def _drain_queue(self):
"""Export all elements until queue is empty.
Can only be called from the worker thread context because it invokes
`export` that is not thread safe.
"""
while self._queue:
self._export_batch()
def _get_and_unset_flush_request(self) -> Optional[_FlushRequest]:
flush_request = self._flush_request
self._flush_request = None
if flush_request is not None:
flush_request.num_log_records = len(self._queue)
return flush_request
@staticmethod
def _notify_flush_request_finished(
flush_request: Optional[_FlushRequest] = None,
):
if flush_request is not None:
flush_request.event.set()
def _get_or_create_flush_request(self) -> _FlushRequest:
if self._flush_request is None:
self._flush_request = _FlushRequest()
return self._flush_request
def emit(self, log_data: LogData) -> None:
"""Adds the `LogData` to queue and notifies the waiting threads
when size of queue reaches max_export_batch_size.
"""
if self._shutdown:
return
if self._pid != os.getpid():
_BSP_RESET_ONCE.do_once(self._at_fork_reinit)
self._queue.appendleft(log_data)
if len(self._queue) >= self._max_export_batch_size:
with self._condition:
self._condition.notify()
def shutdown(self):
self._shutdown = True
with self._condition:
self._condition.notify_all()
self._worker_thread.join()
self._exporter.shutdown()
def force_flush(self, timeout_millis: Optional[int] = None) -> bool:
if timeout_millis is None:
timeout_millis = self._export_timeout_millis
if self._shutdown:
return True
with self._condition:
flush_request = self._get_or_create_flush_request()
self._condition.notify_all()
ret = flush_request.event.wait(timeout_millis / 1e3)
if not ret:
_logger.warning("Timeout was exceeded in force_flush().")
return ret
@staticmethod
def _default_max_queue_size():
try:
return int(
environ.get(OTEL_BLRP_MAX_QUEUE_SIZE, _DEFAULT_MAX_QUEUE_SIZE)
)
except ValueError:
_logger.exception(
_ENV_VAR_INT_VALUE_ERROR_MESSAGE,
OTEL_BLRP_MAX_QUEUE_SIZE,
_DEFAULT_MAX_QUEUE_SIZE,
)
return _DEFAULT_MAX_QUEUE_SIZE
@staticmethod
def _default_schedule_delay_millis():
try:
return int(
environ.get(
OTEL_BLRP_SCHEDULE_DELAY, _DEFAULT_SCHEDULE_DELAY_MILLIS
)
)
except ValueError:
_logger.exception(
_ENV_VAR_INT_VALUE_ERROR_MESSAGE,
OTEL_BLRP_SCHEDULE_DELAY,
_DEFAULT_SCHEDULE_DELAY_MILLIS,
)
return _DEFAULT_SCHEDULE_DELAY_MILLIS
@staticmethod
def _default_max_export_batch_size():
try:
return int(
environ.get(
OTEL_BLRP_MAX_EXPORT_BATCH_SIZE,
_DEFAULT_MAX_EXPORT_BATCH_SIZE,
)
)
except ValueError:
_logger.exception(
_ENV_VAR_INT_VALUE_ERROR_MESSAGE,
OTEL_BLRP_MAX_EXPORT_BATCH_SIZE,
_DEFAULT_MAX_EXPORT_BATCH_SIZE,
)
return _DEFAULT_MAX_EXPORT_BATCH_SIZE
@staticmethod
def _default_export_timeout_millis():
try:
return int(
environ.get(
OTEL_BLRP_EXPORT_TIMEOUT, _DEFAULT_EXPORT_TIMEOUT_MILLIS
)
)
except ValueError:
_logger.exception(
_ENV_VAR_INT_VALUE_ERROR_MESSAGE,
OTEL_BLRP_EXPORT_TIMEOUT,
_DEFAULT_EXPORT_TIMEOUT_MILLIS,
)
return _DEFAULT_EXPORT_TIMEOUT_MILLIS
@staticmethod
def _validate_arguments(
max_queue_size, schedule_delay_millis, max_export_batch_size
):
if max_queue_size <= 0:
raise ValueError("max_queue_size must be a positive integer.")
if schedule_delay_millis <= 0:
raise ValueError("schedule_delay_millis must be positive.")
if max_export_batch_size <= 0:
raise ValueError(
"max_export_batch_size must be a positive integer."
)
if max_export_batch_size > max_queue_size:
raise ValueError(
"max_export_batch_size must be less than or equal to max_queue_size."
)

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# 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.
import threading
import typing
from opentelemetry.sdk._logs import LogData
from opentelemetry.sdk._logs.export import LogExporter, LogExportResult
class InMemoryLogExporter(LogExporter):
"""Implementation of :class:`.LogExporter` that stores logs in memory.
This class can be used for testing purposes. It stores the exported logs
in a list in memory that can be retrieved using the
:func:`.get_finished_logs` method.
"""
def __init__(self):
self._logs = []
self._lock = threading.Lock()
self._stopped = False
def clear(self) -> None:
with self._lock:
self._logs.clear()
def get_finished_logs(self) -> typing.Tuple[LogData, ...]:
with self._lock:
return tuple(self._logs)
def export(self, batch: typing.Sequence[LogData]) -> LogExportResult:
if self._stopped:
return LogExportResult.FAILURE
with self._lock:
self._logs.extend(batch)
return LogExportResult.SUCCESS
def shutdown(self) -> None:
self._stopped = True

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@@ -0,0 +1,35 @@
# 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.
from opentelemetry.sdk._logs._internal.export import (
BatchLogRecordProcessor,
ConsoleLogExporter,
LogExporter,
LogExportResult,
SimpleLogRecordProcessor,
)
# The point module is not in the export directory to avoid a circular import.
from opentelemetry.sdk._logs._internal.export.in_memory_log_exporter import (
InMemoryLogExporter,
)
__all__ = [
"BatchLogRecordProcessor",
"ConsoleLogExporter",
"LogExporter",
"LogExportResult",
"SimpleLogRecordProcessor",
"InMemoryLogExporter",
]