Working with S3 Buckets

Create a S3 Bucket

    

        
            
            
    
    from cdev.aws.s3 import Bucket


myBucket = Bucket("demo_bucket")

You can use the cdev run bucket commands to push and pull objects to the bucket from your computer.

cdev run bucket.cp <local.json> bucket://<bucket-info>

cdev output <component_name>.bucket.demo_bucket.bucket_name

aws s3 cp <local_file> s3://<your-bucket-name>

Creating Multiple Buckets

Note that a Bucket does not currently have any available settings and configuration, which means we must provide a nonce value to distinguish between the two resources. To learn more about how the nonce value works within the larger Cdev framework please read our deep dive on our architecture.

    

        
            
            
    
    from cdev.aws.s3 import Bucket



myBucket = Bucket("demo_bucket")

myBucket2 = Bucket("demo_bucket2", nonce="123")

Use a Serverless function to read objects from a S3 Bucket

The Bucket object provides the permissions and output to configure a Serverless function to be able to integrate and read objects.

    

        
            
            
    
    import os
import boto3

from cdev.aws.s3 import Bucket
from cdev.aws.lambda_function import ServerlessFunction


myBucket = Bucket("demo_bucket")


s3_client = boto3.client('s3')

@ServerlessFunction("read_function", environment={"BUCKET_NAME": myBucket.output.bucket_name}, permissions=[myBucket.available_permissions.LIST_BUCKET])
def read_object(event, context):

  bucket_name = os.environ.get('BUCKET_NAME')

  print(
    s3_client.list_objects(
      Bucket=bucket_name
    ).get('Contents')
  )

Use a Serverless function to write objects to a S3 Bucket

The Bucket object provides the permissions and output to configure a Serverless function to be able to integrate and write objects.

    

        
            
            
    
    import os
import boto3

from cdev.aws.s3 import Bucket
from cdev.aws.lambda_function import ServerlessFunction


myBucket = Bucket("demo_bucket")


s3_client = boto3.client('s3')

@ServerlessFunction("write_function", environment={"BUCKET_NAME": myBucket.output.bucket_name}, permissions=[myBucket.available_permissions.READ_AND_WRITE_BUCKET])
def write_object(event, context):

  bucket_name = os.environ.get('BUCKET_NAME')

  print(
    s3_client.put_object(Body='Text Test', Bucket=bucket_name, Key="filename.txt")
  )

Use a Serverless function to handle events from a S3 Bucket

The Bucket object provides the permissions and output to configure a Serverless function to be triggered from events from a S3 Bucket.

    

        
            
            
    
    import os
import boto3

from cdev.aws.s3 import Bucket, Bucket_Event_Type
from cdev.aws.lambda_function import ServerlessFunction


myBucket = Bucket("demo_bucket")
myBucket_event = myBucket.create_event_trigger(Bucket_Event_Type.Object_Created)


s3_client = boto3.client('s3')


@ServerlessFunction("handle_event_function", events=[myBucket_event], environment={"BUCKET_NAME": myBucket.output.bucket_name}, permissions=[myBucket.available_permissions.LIST_BUCKET])
def handle_event(event, context):

  bucket_name = os.environ.get('BUCKET_NAME')

  result = s3_client.list_objects(Bucket=bucket_name).get('Contents')

  print(result)

  return {"message": str(result)}