def test_with_unserialisable_value_in_message(stdout):
logger = Logger(level="DEBUG", stream=stdout)
class X:
pass
msg = {"x": X()}
logger.debug(msg)
log_dict = json.loads(stdout.getvalue())
assert log_dict["message"]["x"].startswith("<")
def test_with_unserializable_value_in_message(stdout, service_name):
logger = Logger(service=service_name, level="DEBUG", stream=stdout)
class Unserializable:
pass
msg = {"x": Unserializable()}
logger.debug(msg)
log_dict = json.loads(stdout.getvalue())
assert log_dict["message"]["x"].startswith("<")
def test_setup_sampling_rate_env_var(monkeypatch, stdout, service_name):
# GIVEN Logger is initialized
# WHEN samping rate is explicitly set to 100% via POWERTOOLS_LOGGER_SAMPLE_RATE env
sampling_rate = "1"
monkeypatch.setenv("POWERTOOLS_LOGGER_SAMPLE_RATE", sampling_rate)
logger = Logger(service=service_name, stream=stdout)
logger.debug("I am being sampled")
# THEN sampling rate should be equals POWERTOOLS_LOGGER_SAMPLE_RATE value
# log level should be DEBUG
# and debug log statements should be in stdout
log = capture_logging_output(stdout)
assert sampling_rate == log["sampling_rate"]
assert "DEBUG" == log["level"]
assert "I am being sampled" == log["message"]
def test_with_unserializable_value_in_message_custom(stdout):
class Unserializable:
pass
# GIVEN a custom json_default
logger = Logger(level="DEBUG", stream=stdout, json_default=lambda o: f"<non-serializable: {type(o).__name__}>")
# WHEN we log a message
logger.debug({"x": Unserializable()})
log_dict = json.loads(stdout.getvalue())
# THEN json_default should not be in the log message and the custom unserializable handler should be used
assert log_dict["message"]["x"] == "<non-serializable: Unserializable>"
assert "json_default" not in log_dict
def test_setup_sampling_rate(monkeypatch, stdout):
# GIVEN samping rate is explicitly defined via POWERTOOLS_LOGGER_SAMPLE_RATE env
# WHEN logger is setup
# THEN sampling rate should be equals POWERTOOLS_LOGGER_SAMPLE_RATE value and should sample debug logs
sampling_rate = "1"
monkeypatch.setenv("POWERTOOLS_LOGGER_SAMPLE_RATE", sampling_rate)
monkeypatch.setenv("LOG_LEVEL", "INFO")
logger = Logger(stream=stdout)
logger.debug("I am being sampled")
log = json.loads(stdout.getvalue())
assert sampling_rate == log["sampling_rate"]
assert "DEBUG" == log["level"]
assert "I am being sampled" == log["message"]
def event_log(s3_bucket: str, s3_key: str, function_name: str,
logger: Logger) -> EventLog:
logger.append_keys(s3_bucket=s3_bucket, s3_key=s3_key)
logger.debug(f"processing s3 event")
log = EventLog(
status=STATUS_PROCESSING,
s3_key=s3_key,
s3_bucket=s3_bucket,
function=function_name,
region=os.environ.get('AWS_REGION', 'no region set'),
received_time=datetime.now(timezone.utc), # TODO get from s3 record
)
log.logger = logger
log.save()
try:
yield log
log.mark_processed()
except Exception as e:
if logger.log_level == 'DEBUG':
logger.exception(f"error processing s3 object")
log.mark_failed(str(e))
raise
import json
import os
import boto3
from aws_lambda_powertools import Logger, Metrics, Tracer
from boto3.dynamodb.conditions import Key
from shared import get_cart_id, get_headers, handle_decimal_type
logger = Logger()
tracer = Tracer()
metrics = Metrics()
dynamodb = boto3.resource("dynamodb")
logger.debug("Initializing DDB Table %s", os.environ["TABLE_NAME"])
table = dynamodb.Table(os.environ["TABLE_NAME"])
@metrics.log_metrics(capture_cold_start_metric=True)
@logger.inject_lambda_context(log_event=True)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
"""
Update cart table to use user identifier instead of anonymous cookie value as a key. This will be called when a user
is logged in.
"""
cart_id, _ = get_cart_id(event["headers"])
try:
# Because this method is authorized at API gateway layer, we don't need to validate the JWT claims here
