Amazon Web Services SDK

The Python library boto3 for the AWS SDK is supported. The Python library aws-cdk (v1 and v2) is only supported for AWS Lambdas.

AWS Lambda in AWS deployment frameworks

New in 1.4.0-beta7

The AWS Lambda functions declared in deployment framework configuration files are analyzed by a different extensions (com.castsoftware.cloudconfig). The Python analyzer will be responsible, however, of creating the link between Lambda Function objects having the runtime property value consistent with a python runtime (python3.5, ...) and the corresponding handler (a Python method object) during the application-level analysis step. It is highly recommended to add the com.castsoftware.cloudconfig extension so that proper migration of AWS objects takes place upon upgrading com.castsoftware.python extension from versions < 1.4.0-beta7.

Available in 1.4.0-beta6 and below (deprecated)

Serverless framework, Serverless Application Model (SAM), and Cloudformation are supported. These are frameworks using *.yml and *.yaml (or *.json, currently not supported in this extension) file to set up AWS environment. 
Whenever the runtime set in these files is pythonX.Y, the com.castsoftware.python extension is responsible for creating the corresponding Python AWS Lambda Function, Python AWS Lambda Operation (which represent AWS APIGateway events), and Python AWS Simple Queue objects. 

Example

In the .yml deployment file below (taken from the Serverless examples for AWS) a Lambda function is defined (hello) and the handler's method name is referred:

service: aws-python # NOTE: update this with your service name

frameworkVersion: '2'


provider:
  name: aws
  runtime: python3.8
  lambdaHashingVersion: 20201221

functions:
  hello:
    handler: handler.hello

Where the Python code of the handler:

# handler.py

def hello(event, context):
    body = {
        "message": "Go Serverless v2.0! Your function executed successfully!",
        "input": event,
    }

    return {"statusCode": 200, "body": json.dumps(body)}

The results in Enlighten:

AWS Lambda (Boto3)

Example

A simple example showing representation of an invocation of a AWS Lambda function:

def func():
    lambda_client.invoke(FunctionName='otherfunctionname',
                     InvocationType='RequestResponse',
                     Payload=lambda_payload)

AWS SQS (Boto3)

Code samples

In this code, the module sqs_send_message.py publishes a message into the "SQS_QUEUE_URL" queue and in sqs_receive_message.py is received:

# Adapted from https://boto3.amazonaws.com/v1/documentation/api/latest/guide/sqs-example-sending-receiving-msgs.html#example
# sqs_receive_message.py

import boto3

# Create SQS client
sqs = boto3.client('sqs')

queue_url = 'SQS_QUEUE_URL'

# Receive message from SQS queue
response = sqs.receive_message(QueueUrl=queue_url, ...)

and

# Adapted from https://boto3.amazonaws.com/v1/documentation/api/latest/guide/sqs-example-sending-receiving-msgs.html#example
# sqs_send_message.py
 
import boto3

# Create SQS client
sqs = boto3.client('sqs')

queue_url = 'SQS_QUEUE_URL'

# Send message to SQS queue
response = sqs.send_message(QueueUrl=queue_url, ...)

The results derived from the analysis of the above code can be seen Enlighten:

Click to enlarge

AWS SNS (Boto3)

There are two different APIs to manage SNS services, one based on a low-level client and the higher-level one based on resources.

The supported protocols are the following:

Example

The code example below shows a basic usage of the boto3 library and the results as seen in Enlighten after analysis of the code.

import boto3

client = boto3.client('sns', region_name='eu-west-3')
topicArn1 = client.create_topic( Name = "TOPIC1")['TopicArn']

def publish(topic):
    client.publish(TopicArn=topic, Message='<your message>')

def subscribe(topic):
    client.subscribe(TopicArn=topic, Protocol="email", Endpoint="lili@lala.com")
    client.subscribe(TopicArn=topic, Protocol="sms", Endpoint="123456789")
    client.subscribe(TopicArn=topic, Protocol="sqs", Endpoint="arn:partition:service:region:account-id:queueName")
    client.subscribe(TopicArn=topic, Protocol="http", Endpoint="http://foourl")
    client.subscribe(TopicArn=topic, Protocol="lambda", Endpoint="fooarn:function:lambda_name:v2")
    
publish(topicArn1)
subscribe(topicArn1)

The callLink links between the Publisher and the respective Subscribers are created by the Web Services Linker extension during application level.

We can also have direct sms deliveries from calls to publish API methods:

import boto3
AWS_REGION = "us-east-1"

def send_sms_from_resource():
    sns = boto3.resource("sns", region_name=AWS_REGION)
    platform_endpoint = sns.PlatformEndpoint('endpointArn')
    platform_endpoint.publish(PhoneNumber='123456789')

def send_sms():
    conn = boto3.client("sns", region_name=AWS_REGION)
    conn.publish(PhoneNumber='123456789')

Where the corresponding objects and links are:

AWS DynamoDB (Boto3)

See DynamoDB support for Python source code.

AWS S3 (Boto3)

In the absence of a create_bucket call, references to buckets in other method calls are used to create table objects. In the case the name is well resolved, a regular S3 Bucket is created, otherwise an Unknown S3 Bucket is created. A maximum of one Unknown S3 Bucket per file is created, however a maximum of one per project (as it is already the case in analyzers for other languages such as TypeScript) is under consideration by CAST.

The long list of methods added to the last arrow in the table above correspond to methods that act on S3 Buckets and presumably using the AWS SDK API behind the scenes (those few methods only acting on the boto3 client object are not considered).

AWS-CDK

AWS Lambda (AWS-CDK)

Limitations

• Monolithic pattern for lambda functions is not properly supported