AWS Lambda context object in Python - AWS Lambda

AWS Lambda context object in Python


End of support for the Python 2.7 runtime started on July 15, 2021. For more information, see Runtime support policy.

When Lambda runs your function, it passes a context object to the handler. This object provides methods and properties that provide information about the invocation, function, and execution environment. For more information on how the context object is passed to the function handler, see Lambda function handler in Python.

Context methods

  • get_remaining_time_in_millis – Returns the number of milliseconds left before the execution times out.

Context properties

  • function_name – The name of the Lambda function.

  • function_version – The version of the function.

  • invoked_function_arn – The Amazon Resource Name (ARN) that's used to invoke the function. Indicates if the invoker specified a version number or alias.

  • memory_limit_in_mb – The amount of memory that's allocated for the function.

  • aws_request_id – The identifier of the invocation request.

  • log_group_name – The log group for the function.

  • log_stream_name – The log stream for the function instance.

  • identity – (mobile apps) Information about the Amazon Cognito identity that authorized the request.

    • cognito_identity_id – The authenticated Amazon Cognito identity.

    • cognito_identity_pool_id – The Amazon Cognito identity pool that authorized the invocation.

  • client_context – (mobile apps) Client context that's provided to Lambda by the client application.

    • client.installation_id

    • client.app_title

    • client.app_version_name

    • client.app_version_code

    • client.app_package_name

    • custom – A dict of custom values set by the mobile client application.

    • env – A dict of environment information provided by the AWS SDK.

The following example shows a handler function that logs context information.


import time def lambda_handler(event, context): print("Lambda function ARN:", context.invoked_function_arn) print("CloudWatch log stream name:", context.log_stream_name) print("CloudWatch log group name:", context.log_group_name) print("Lambda Request ID:", context.aws_request_id) print("Lambda function memory limits in MB:", context.memory_limit_in_mb) # We have added a 1 second delay so you can see the time remaining in get_remaining_time_in_millis. time.sleep(1) print("Lambda time remaining in MS:", context.get_remaining_time_in_millis())

In addition to the options listed above, you can also use the AWS X-Ray SDK for Instrumenting Python code in AWS Lambda to identify critical code paths, trace their performance and capture the data for analysis.