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Description:

origolambdahelpers 0.1.0

Logging for Lambda
Based on Structlog.
Structured and enriched logging for AWS Lambda functions.
TL;DR:

Decorate handler with logging_wrapper
Encrich logs with key/value pairs using log_add
Time functions with log_duration
Log exceptions with log_exception

Usage
Wrap your lambda handler with logging_wrapper. Badabing badabom, you're good to go!
You can set the service name using the logging.init method, or configure it using
the SERVICE_NAME environment variable.
from dataplatform.awslambda import logging
from dataplatform.awslambda.logging import logging_wrapper

logging.init("my_fantastic_lambda")

@logging_wrapper
def handler(event, context):
if error:
return {
"statusCode": 500,
"body": "Automatically logs bodies from error responses even!",
}

Encriching logs
By automagic logs will be enriched with git revisions, cold start y/n call
duration and much more, but to add even more magic you can use log_add and
log_duration.
from dataplatform.awslambda.logging import logging_wrapper, log_add, log_duration

@logging_wrapper
def handler(event, context):
log_add(dataset=event["dataset"], foo=context["foo"])
log_duration(
lambda: slow_thinger(event["dataset"]),
"my_slow_thinger"
)
... and so on

def slow_thinger():
sleep(9999999999999999)

Exceptions
Struct log can extract exception info if we log the exception to the special
exc_info
key.
For convenience we catch and log uncaught exceptions using this already.
If you need to process an exception you can use log_exception to log it to
the exc_info key.
from dataplatform.awslambda.logging import logging_wrapper, log_exception

@logging_wrapper
def handler(event, context):
try:
thing()
except MyException as e:
log_exception(e)
return { ... }