def around(self):
self.subject = AWSLambda(
function_arn="the_lambda_function_arn",
memory_limit_mb=None,
execution_env=None,
agent_id="a509707f-12db-462d-b5c9-18bc19c69bf0")
LambdaContext.get()
yield
LambdaContext._singleton = None
def get_metadata_for_configure_agent_call(self, lambda_context=None):
"""
This gathers metadata from self and from given lambda context to build a map used for the configure_agent call
:param lambda_context: a LambdaContext object which contains mainly the context from lambda framework.
See https://docs.aws.amazon.com/lambda/latest/dg/python-context.html for details about the context.
:return: a map with all metadata we want to send in configure_agent call.
"""
# get the singleton lambda context. The decorator should set it.
if lambda_context is None:
lambda_context = LambdaContext.get()
as_map = {
COMPUTE_PLAFORM_KEY: COMPUTE_PLAFORM_VALUE,
LAMBDA_FUNCTION_ARN_KEY: self.function_arn,
AGENT_ID_KEY: self.agent_id
}
if self.memory_limit_mb:
as_map[LAMBDA_MEMORY_LIMIT_IN_MB_KEY] = str(self.memory_limit_mb)
if self.execution_env:
as_map[EXECUTION_ENVIRONMENT_KEY] = self.execution_env
'''
Adding a specific condition to ignore MagicMock instances from being added to the metadata since
it causes boto to raise a ParamValidationError, similar to https://github.com/boto/botocore/issues/2063.
'''
if lambda_context.context is not None and not isinstance(
lambda_context.context, MagicMock):
as_map[AWS_REQUEST_ID_KEY] = lambda_context.context.aws_request_id
as_map[LAMBDA_REMAINING_TIME_IN_MILLISECONDS_KEY] = \
str(lambda_context.context.get_remaining_time_in_millis())
if lambda_context.last_execution_duration:
as_map[LAMBDA_PREVIOUS_EXECUTION_TIME_IN_MILLISECONDS_KEY] = \
str(int(lambda_context.last_execution_duration.total_seconds() * 1000))
return as_map
def profiler_decorate(event, context):
start_time = datetime.now()
global _profiler
if _profiler is None:
_profiler = profiler_factory(profiling_group_name=profiling_group_name,
region_name=region_name,
environment_override=environment_override,
context=context, env=env)
LambdaContext.get().context = context
if not _profiler.start():
# if start() failed, there is high chance it will fail again
# so we disable the profiler to prevent further attempts.
_profiler = _EmptyProfiler()
try:
return function(event, context)
finally:
LambdaContext.get().last_execution_duration = datetime.now() - start_time
_profiler.pause()
def before(self):
self.context = Mock()
self.context.invoked_function_arn = "the_lambda_function_arn"
self.context.aws_request_id = "the_aws_request_id"
self.context.get_remaining_time_in_millis = Mock(
return_value=30125)
self.subject = AWSLambda(
function_arn="the_lambda_function_arn",
memory_limit_mb=512,
execution_env="AWS_Lambda_python3.8",
agent_id="a509707f-12db-462d-b5c9-18bc19c69bf0")
self.lambda_context = LambdaContext()
self.lambda_context.context = self.context
self.lambda_context.last_execution_duration = timedelta(
seconds=1, milliseconds=234, microseconds=987)
def test_it_can_return_last_execution_duration_independently(self):
LambdaContext.get().last_execution_duration = timedelta(
seconds=1, milliseconds=234, microseconds=987)
metadata = self.subject.get_metadata_for_configure_agent_call()
assert metadata[
"LambdaPreviousExecutionTimeInMilliseconds"] == "1234"
def test_last_call_duration_is_set_in_lambda_context_singleton(self):
self.handler({}, self.context)
assert LambdaContext.get().last_execution_duration
def test_context_is_set_in_lambda_context_singleton(self):
self.handler({}, self.context)
assert LambdaContext.get().context is self.context