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New pattern - S3 Lambda resizing image (python)
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‎s3-lambda-resizing-python/README.md‎

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# AWS Amazon S3 to AWS Lambda - Create a Lambda function that resizes images uploaded to S3
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The SAM template deploys a Lambda function, an S3 bucket and the IAM resources required to run the application. A Lambda function consumes <code>ObjectCreated</code> events from an Amazon S3 bucket. The Lambda code checks the uploaded file is an image and creates a thumbnail version of the image in the same bucket.
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Important: this application uses various AWS services and there are costs associated with these services after the Free Tier usage - please see the [AWS Pricing page](https://aws.amazon.com/pricing/) for details. You are responsible for any AWS costs incurred. No warranty is implied in this example.
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## Requirements
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* [Create an AWS account](https://portal.aws.amazon.com/gp/aws/developer/registration/index.html) if you do not already have one and log in. The IAM user that you use must have sufficient permissions to make necessary AWS service calls and manage AWS resources.
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* [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/install-cliv2.html) installed and configured
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* [Git Installed](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
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* [AWS Serverless Application Model](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-sam-cli-install.html) (AWS SAM) installed
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## Deployment Instructions
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1. Create a new directory, navigate to that directory in a terminal and clone the GitHub repository:
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```
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git clone https://github.com/aws-samples/serverless-patterns
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```
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1. Change directory to the pattern directory:
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```
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cd s3-lambda
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```
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1. From the command line, use AWS SAM to build and deploy the AWS resources for the pattern as specified in the template.yml file:
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```
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sam build
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sam deploy --guided
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```
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1. During the prompts:
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* Enter a stack name
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* Enter the desired AWS Region
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* Allow SAM CLI to create IAM roles with the required permissions.
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Once you have run `sam deploy --guided` mode once and saved arguments to a configuration file (samconfig.toml), you can use `sam deploy` in future to use these defaults.
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1. Note the outputs from the SAM deployment process. These contain the resource names and/or ARNs which are used for testing.
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## How it works
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* Use the AWS CLI upload an image to S3
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* If the object is a .jpg or a .png, the code creates a thumbnail and saves it to the target bucket.
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* The code assumes that the destination bucket exists and its name is a concatenation of the source bucket name followed by the string -resized
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==============================================
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## Testing
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Run the following S3 CLI command to upload an image to the S3 bucket. Note, you must edit the {SourceBucketName} placeholder with the name of the S3 Bucket. This is provided in the stack outputs.
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```bash
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aws s3 cp './events/example.jpg' s3://{SourceBucketName}
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```
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Run the following command to check that a new version of the image has been created in the destination bucket.
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```bash
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aws s3 ls s3://{DestinationBucketName}
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```
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## Cleanup
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1. Delete the stack
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```bash
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aws cloudformation delete-stack --stack-name STACK_NAME
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```
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1. Confirm the stack has been deleted
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```bash
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aws cloudformation list-stacks --query "StackSummaries[?contains(StackName,'STACK_NAME')].StackStatus"
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```
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----
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Copyright 2021 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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SPDX-License-Identifier: MIT-0

‎s3-lambda-resizing-python/events/event.json‎

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{
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"Records": [
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{
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"eventVersion": "2.1",
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"eventSource": "aws:s3",
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"awsRegion": "us-east-1",
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"eventTime": "2024-07-03T19:37:27.192Z",
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"eventName": "ObjectCreated:Put",
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"userIdentity": {
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"principalId": "AWS:AIDAINPONIXQXHT3IKHL2"
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},
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"requestParameters": {
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"sourceIPAddress": "205.255.255.255"
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},
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"responseElements": {
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"x-amz-request-id": "D82B88E5F771F645",
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"x-amz-id-2": "vlR7PnpV2Ce81l0PRw6jlUpck7Jo5ZsQjryTjKlc5aLWGVHPZLj5NeC6qMa0emYBDXOo6QBU0Wo="
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},
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"s3": {
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"s3SchemaVersion": "1.0",
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"configurationId": "828aa6fc-f7b5-4305-8584-487c791949c1",
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"bucket": {
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"name": "<provide-source-bucket-name-here>",
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"ownerIdentity": {
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"principalId": "A3I5XTEXAMAI3E"
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},
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"arn": "arn:aws:s3:::lambda-artifacts-deafc19498e3f2df"
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},
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"object": {
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"key": "<provide-source-object-key-here>",
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"size": 1305107,
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"eTag": "b21b84d653bb07b05b1e6b33684dc11b",
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"sequencer": "0C0F6F405D6ED209E1"
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}
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}
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}
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]
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}

‎s3-lambda-resizing-python/events/white_dog.jpeg‎

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‎s3-lambda-resizing-python/example-pattern.json‎

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{
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"title": "AWS Amazon S3 to AWS Lambda Image Resizing",
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"description": "Create a Lambda function that resizes images uploaded to S3.",
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"language": "Python",
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"level": "200",
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"framework": "SAM",
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"introBox": {
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"headline": "How it works",
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"text": [
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"A Lambda function consumes events from an Amazon S3 bucket. The Lambda code checks the uploaded file is an image and creates a thumbnail version of the image in the destination bucket.",
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"This pattern deploys a Lambda function and two S3 buckets."
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]
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},
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"gitHub": {
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"template": {
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"repoURL": "https://github.com/aws-samples/serverless-patterns/tree/main/s3-lambda-resizing-python",
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"templateURL": "serverless-patterns/s3-lambda-resizing-python",
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"projectFolder": "s3-lambda-resizing-python",
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"templateFile": "template.yaml"
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}
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},
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"resources": {
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"bullets": [
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{
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"text": "Process S3 events with Lambda",
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"link": "https://docs.aws.amazon.com/lambda/latest/dg/with-s3.html"
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}
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]
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},
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"deploy": {
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"text": [
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"sam deploy --guided"
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]
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},
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"testing": {
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"text": [
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"See the GitHub repo for detailed testing instructions."
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]
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},
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"cleanup": {
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"text": [
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"Delete the application: <code>sam delete</code>."
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]
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}
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}

‎s3-lambda-resizing-python/hello_world/__init__.py‎

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‎s3-lambda-resizing-python/hello_world/app.py‎

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import boto3
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import uuid
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from urllib.parse import unquote_plus
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from PIL import Image
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s3_client = boto3.client('s3')
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def resize_image(image_path, resized_path):
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with Image.open(image_path) as image:
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image.thumbnail(tuple(x / 2 for x in image.size))
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image.save(resized_path)
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def lambda_handler(event, context):
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for record in event['Records']:
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bucket = record['s3']['bucket']['name']
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key = unquote_plus(record['s3']['object']['key'])
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tmpkey = key.replace('/', '')
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download_path = '/tmp/{}{}'.format(uuid.uuid4(), tmpkey)
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upload_path = '/tmp/resized-{}'.format(tmpkey)
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s3_client.download_file(bucket, key, download_path)
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resize_image(download_path, upload_path)
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s3_client.upload_file(upload_path, '{}-resized'.format(bucket), 'resized-{}'.format(key))

‎s3-lambda-resizing-python/hello_world/requirements.txt‎

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pillow
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boto3

‎s3-lambda-resizing-python/template.yaml‎

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AWSTemplateFormatVersion: '2010-09-09'
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Transform: AWS::Serverless-2016-10-31
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Description: Image resizing service (tag:s3-lambda)
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Parameters:
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SourceBucketName:
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Type: String
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DestinationBucketName:
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Type: String
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Resources:
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## S3 bucket
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SourceBucket:
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Type: AWS::S3::Bucket
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Properties:
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BucketName: !Ref SourceBucketName
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DestinationBucket:
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Type: AWS::S3::Bucket
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Properties:
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BucketName: !Ref DestinationBucketName
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## Lambda function
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ResizerFunction:
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Type: AWS::Serverless::Function
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Properties:
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CodeUri: src/
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Handler: app.lambda_handler
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Runtime: python3.12
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MemorySize: 2048
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Layers:
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- !Sub 'arn:aws:lambda:${AWS::Region}:175033217214:layer:graphicsmagick:2'
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Policies:
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- S3ReadPolicy:
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BucketName: !Ref SourceBucketName
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- S3CrudPolicy:
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BucketName: !Ref DestinationBucketName
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Environment:
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Variables:
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DESTINATION_BUCKETNAME: !Ref DestinationBucketName
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Events:
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FileUpload:
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Type: S3
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Properties:
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Bucket: !Ref SourceBucket
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Events: s3:ObjectCreated:*
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Filter:
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S3Key:
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Rules:
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- Name: suffix
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Value: '.jpg'
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Outputs:
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SourceBucketName:
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Value: !Ref SourceBucketName
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Description: S3 Bucket for object storage
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DestinationBucketName:
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Value: !Ref DestinationBucketName
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Description: S3 destination Bucket for object storage
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FunctionArn:
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Value: !Ref ResizerFunction
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Description: ResizerFunction function Arn

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