import functools import inspect import logging import os import random import sys from typing import Any, Callable, Dict, Union from ..shared import constants from ..shared.functions import resolve_env_var_choice, resolve_truthy_env_var_choice from .exceptions import InvalidLoggerSamplingRateError from .filters import SuppressFilter from .formatter import JsonFormatter from .lambda_context import build_lambda_context_model logger = logging.getLogger(__name__) is_cold_start = True def _is_cold_start() -> bool: """Verifies whether is cold start Returns ------- bool cold start bool value """ cold_start = False global is_cold_start if is_cold_start: cold_start = is_cold_start is_cold_start = False return cold_start # PyCharm does not support autocomplete via getattr # so we need to return to subclassing removed in #97 # All methods/properties continue to be proxied to inner logger # https://github.com/awslabs/aws-lambda-powertools-python/issues/107 class Logger(logging.Logger): # lgtm [py/missing-call-to-init] """Creates and setups a logger to format statements in JSON. Includes service name and any additional key=value into logs It also accepts both service name or level explicitly via env vars Environment variables --------------------- POWERTOOLS_SERVICE_NAME : str service name LOG_LEVEL: str logging level (e.g. INFO, DEBUG) POWERTOOLS_LOGGER_SAMPLE_RATE: float samping rate ranging from 0 to 1, 1 being 100% sampling Parameters ---------- service : str, optional service name to be appended in logs, by default "service_undefined" level : str, int optional logging.level, by default "INFO" child: bool, optional create a child Logger named ., False by default sample_rate: float, optional sample rate for debug calls within execution context defaults to 0.0 stream: sys.stdout, optional valid output for a logging stream, by default sys.stdout Example ------- **Setups structured logging in JSON for Lambda functions with explicit service name** >>> from aws_lambda_powertools import Logger >>> logger = Logger(service="payment") >>> >>> def handler(event, context): logger.info("Hello") **Setups structured logging in JSON for Lambda functions using env vars** $ export POWERTOOLS_SERVICE_NAME="payment" $ export POWERTOOLS_LOGGER_SAMPLE_RATE=0.01 # 1% debug sampling >>> from aws_lambda_powertools import Logger >>> logger = Logger() >>> >>> def handler(event, context): logger.info("Hello") **Append payment_id to previously setup logger** >>> from aws_lambda_powertools import Logger >>> logger = Logger(service="payment") >>> >>> def handler(event, context): logger.structure_logs(append=True, payment_id=event["payment_id"]) logger.info("Hello") **Create child Logger using logging inheritance via child param** >>> # app.py >>> import another_file >>> from aws_lambda_powertools import Logger >>> logger = Logger(service="payment") >>> >>> # another_file.py >>> from aws_lambda_powertools import Logger >>> logger = Logger(service="payment", child=True) Raises ------ InvalidLoggerSamplingRateError When sampling rate provided is not a float """ def __init__( self, service: str = None, level: Union[str, int] = None, child: bool = False, sampling_rate: float = None, stream: sys.stdout = None, **kwargs, ): self.service = resolve_env_var_choice( choice=service, env=os.getenv(constants.SERVICE_NAME_ENV, "service_undefined") ) self.sampling_rate = resolve_env_var_choice( choice=sampling_rate, env=os.getenv(constants.LOGGER_LOG_SAMPLING_RATE, 0.0) ) self._is_deduplication_disabled = resolve_truthy_env_var_choice( env=os.getenv(constants.LOGGER_LOG_DEDUPLICATION_ENV, "false") ) self.log_level = self._get_log_level(level) self.child = child self._handler = logging.StreamHandler(stream) if stream is not None else logging.StreamHandler(sys.stdout) self._default_log_keys = {"service": self.service, "sampling_rate": self.sampling_rate} self._logger = self._get_logger() self._init_logger(**kwargs) def __getattr__(self, name): # Proxy attributes not found to actual logger to support backward compatibility # https://github.com/awslabs/aws-lambda-powertools-python/issues/97 return getattr(self._logger, name) def _get_logger(self): """ Returns a Logger named {self.service}, or {self.service.filename} for child loggers""" logger_name = self.service if self.child: logger_name = f"{self.service}.{self._get_caller_filename()}" return logging.getLogger(logger_name) def _init_logger(self, **kwargs): """Configures new logger""" # Skip configuration if it's a child logger or a pre-configured logger # to prevent the following: # a) multiple handlers being attached # b) different sampling mechanisms # c) multiple messages from being logged as handlers can be duplicated is_logger_preconfigured = getattr(self._logger, "init", False) if self.child or is_logger_preconfigured: return self._configure_sampling() self._logger.setLevel(self.log_level) self._logger.addHandler(self._handler) self.structure_logs(**kwargs) # Pytest Live Log feature duplicates log records for colored output # but we explicitly add a filter for log deduplication. # This flag disables this protection when you explicit want logs to be duplicated (#262) if not self._is_deduplication_disabled: logger.debug("Adding filter in root logger to suppress child logger records to bubble up") for handler in logging.root.handlers: # It'll add a filter to suppress any child logger from self.service # Example: `Logger(service="order")`, where service is Order # It'll reject all loggers starting with `order` e.g. order.checkout, order.shared handler.addFilter(SuppressFilter(self.service)) # as per bug in #249, we should not be pre-configuring an existing logger # therefore we set a custom attribute in the Logger that will be returned # std logging will return the same Logger with our attribute if name is reused logger.debug(f"Marking logger {self.service} as preconfigured") self._logger.init = True def _configure_sampling(self): """Dynamically set log level based on sampling rate Raises ------ InvalidLoggerSamplingRateError When sampling rate provided is not a float """ try: if self.sampling_rate and random.random() <= float(self.sampling_rate): logger.debug("Setting log level to Debug due to sampling rate") self.log_level = logging.DEBUG except ValueError: raise InvalidLoggerSamplingRateError( f"Expected a float value ranging 0 to 1, but received {self.sampling_rate} instead." f"Please review POWERTOOLS_LOGGER_SAMPLE_RATE environment variable." ) def inject_lambda_context(self, lambda_handler: Callable[[Dict, Any], Any] = None, log_event: bool = None): """Decorator to capture Lambda contextual info and inject into logger Parameters ---------- lambda_handler : Callable Method to inject the lambda context log_event : bool, optional Instructs logger to log Lambda Event, by default False Environment variables --------------------- POWERTOOLS_LOGGER_LOG_EVENT : str instruct logger to log Lambda Event (e.g. `"true", "True", "TRUE"`) Example ------- **Captures Lambda contextual runtime info (e.g memory, arn, req_id)** from aws_lambda_powertools import Logger logger = Logger(service="payment") @logger.inject_lambda_context def handler(event, context): logger.info("Hello") **Captures Lambda contextual runtime info and logs incoming request** from aws_lambda_powertools import Logger logger = Logger(service="payment") @logger.inject_lambda_context(log_event=True) def handler(event, context): logger.info("Hello") Returns ------- decorate : Callable Decorated lambda handler """ # If handler is None we've been called with parameters # Return a partial function with args filled if lambda_handler is None: logger.debug("Decorator called with parameters") return functools.partial(self.inject_lambda_context, log_event=log_event) log_event = resolve_truthy_env_var_choice( choice=log_event, env=os.getenv(constants.LOGGER_LOG_EVENT_ENV, "false") ) @functools.wraps(lambda_handler) def decorate(event, context): lambda_context = build_lambda_context_model(context) cold_start = _is_cold_start() self.structure_logs(append=True, cold_start=cold_start, **lambda_context.__dict__) if log_event: logger.debug("Event received") self.info(event) return lambda_handler(event, context) return decorate def structure_logs(self, append: bool = False, **kwargs): """Sets logging formatting to JSON. Optionally, it can append keyword arguments to an existing logger so it is available across future log statements. Last keyword argument and value wins if duplicated. Parameters ---------- append : bool, optional [description], by default False """ # Child loggers don't have handlers attached, use its parent handlers handlers = self._logger.parent.handlers if self.child else self._logger.handlers for handler in handlers: if append: # Update existing formatter in an existing logger handler handler.formatter.update_formatter(**kwargs) else: # Set a new formatter for a logger handler handler.setFormatter(JsonFormatter(**self._default_log_keys, **kwargs)) @staticmethod def _get_log_level(level: Union[str, int]) -> Union[str, int]: """ Returns preferred log level set by the customer in upper case """ if isinstance(level, int): return level log_level: str = level or os.getenv("LOG_LEVEL") if log_level is None: return logging.INFO return log_level.upper() @staticmethod def _get_caller_filename(): """ Return caller filename by finding the caller frame """ # Current frame => _get_logger() # Previous frame => logger.py # Before previous frame => Caller frame = inspect.currentframe() caller_frame = frame.f_back.f_back.f_back return caller_frame.f_globals["__name__"] def set_package_logger( level: Union[str, int] = logging.DEBUG, stream: sys.stdout = None, formatter: logging.Formatter = None ): """Set an additional stream handler, formatter, and log level for aws_lambda_powertools package logger. **Package log by default is suppressed (NullHandler), this should only used for debugging. This is separate from application Logger class utility** Example ------- **Enables debug logging for AWS Lambda Powertools package** >>> from aws_lambda_powertools.logging.logger import set_package_logger >>> set_package_logger() Parameters ---------- level: str, int log level, DEBUG by default stream: sys.stdout log stream, stdout by default formatter: logging.Formatter log formatter, "%(asctime)s %(name)s [%(levelname)s] %(message)s" by default """ if formatter is None: formatter = logging.Formatter("%(asctime)s %(name)s [%(levelname)s] %(message)s") if stream is None: stream = sys.stdout logger = logging.getLogger("aws_lambda_powertools") logger.setLevel(level) handler = logging.StreamHandler(stream) handler.setFormatter(formatter) logger.addHandler(handler)