Writing Lambda function

In this step we create a new Lambda function to write data to DynamoDB on SAM.

  1. Open template.yaml file in fcj-book-shop folder.

  2. Add the following scripts at the end of the file to create a Lambda function that writes data to DynamoDB.

    • Firstly, we will create bookImageShopBucketName and bookImageResizeShopBucketName parameters.

      bookImageShopBucketName:
  Type: String
  Default: book-image-shop-by-myself

bookImageResizeShopBucketName:
  Type: String
  Default: book-image-resize-shop-by-myself

      LambdaCreateFunction

    • Next, we will create BookImageShop and BookImageResizeShop which saves the image after resizing with CORS rule and policy settings.

      BookImageShop:
  Type: AWS::S3::Bucket
  Properties:
    BucketName: !Ref bookImageShopBucketName
    PublicAccessBlockConfiguration:
      BlockPublicAcls: false
      BlockPublicPolicy: false
      IgnorePublicAcls: false
      RestrictPublicBuckets: false

BookImageResizeShop:
  Type: AWS::S3::Bucket
  Properties:
    BucketName: !Ref bookImageResizeShopBucketName
    PublicAccessBlockConfiguration:
      BlockPublicAcls: false
      BlockPublicPolicy: false
      IgnorePublicAcls: false
      RestrictPublicBuckets: false
    CorsConfiguration:
      CorsRules:
        - AllowedHeaders:
            - "*"
          AllowedMethods:
            - GET
            - PUT
            - POST
            - DELETE
          AllowedOrigins:
            - "*"

BookImageResizeShopPolicy:
  Type: AWS::S3::BucketPolicy
  Properties:
    Bucket: !Ref BookImageResizeShop
    PolicyDocument:
      Version: 2012-10-17
      Statement:
        - Action:
            - "s3:GetObject"
          Effect: Allow
          Principal: "*"
          Resource: !Join
            - ""
            - - "arn:aws:s3:::"
              - !Ref BookImageResizeShop
              - /*

      LambdaCreateFunction

    • Then, we add the following scripts to create BookCreate function.

      BookCreate:
  Type: AWS::Serverless::Function
  Properties:
    CodeUri: fcj-book-shop/book_create
    Handler: book_create.lambda_handler
    Runtime: python3.11
    Environment:
      Variables:
        BUCKET_NAME: !Ref BookImageShop
        BUCKET_RESIZE_NAME: !Ref BookImageResizeShop
        TABLE_NAME: !Ref BooksTable
    FunctionName: book_create
    Architectures:
      - x86_64
    Policies:
      - Statement:
          - Sid: BookCreateItem
            Effect: Allow
            Action:
              - dynamodb:PutItem
              - s3:PutObject
            Resource:
              - !Sub arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/${booksTableName}
              - !Join
                - ""
                - - "arn:aws:s3:::"
                  - !Ref BookImageShop
                  - /*

      LambdaCreateFunction

      If you create S3 bucket name is different from the one in the lab, please update Policies | Resources of book_create function with that name.

  3. The directory structure is as follows.

    fcj-book-shop
├── fcj-book-shop
│   ├── books_list
│   │   └── books_list.py
│   ├── book_create
│       └── book_create.py
│       └── requirements.txt
└── template.yaml

    • Create book_create folder in fcj-book-shop/fcj-book-shop/ folder.

    • Create book_create.py file and copy the below code block to it.

      import base64
from multipart import MultipartParser
from io import BytesIO
import boto3
import os

BUCKET = os.environ['BUCKET_NAME']
BUCKET_RESIZE = os.environ['BUCKET_RESIZE_NAME']
TABLE = os.environ['TABLE_NAME']

s3_client = boto3.client('s3')
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table(TABLE)

header_res = {
    "Content-Type": "application/json",
    "Access-Control-Allow-Origin": "*",
    "Access-Control-Allow-Methods": "OPTIONS,POST,GET,DELETE",
    "Access-Control-Allow-Headers": "Content-Type,X-Amz-Date,Authorization,X-Api-Key,X-Amz-Security-Token",
}


def parse_multipart(body, boundary):
    parser = MultipartParser(stream=body, boundary=boundary)

    fields = {}
    files = {}

    for part in parser:
        if part.filename:
            files[part.name] = {
                'file-name': part.filename,
                'content': part.raw
            }

        else:
            fields[part.name] = part.value

    return fields, files


def upload_to_s3(key, bucket, body):
    try:
        s3_client.put_object(Key=key, Bucket=bucket, Body=body)
    except Exception as e:
        print(f"Error uploading image to S3: {e}")
        raise Exception(f'Error uploading image to S3: {e}')


def create_new_item(table, item):
    try:
        table.put_item(Item=item)
    except Exception as e:
        print(f"Error creating new item in DynamoDB table: {e}")
        raise Exception(f'Error creating new item in DynamoDB table: {e}')


def lambda_handler(event, context):
    content_type = event['headers'].get(
        'Content-Type', '') or event['headers'].get('content-type', '')

    try:
        body = event['body']

        if event['isBase64Encoded']:
            body = BytesIO(base64.b64decode(body))

        boundary = content_type.split("boundary=")[1]

        fields, files = parse_multipart(body, boundary)

        # Upload image to s3
        file_name = files['image']['file-name']
        file_content = files['image']['content']

        upload_to_s3(file_name, BUCKET, file_content)
        s3_url = f'https://{BUCKET_RESIZE}.s3.amazonaws.com/{file_name}'

        # Create new item in DB
        item = {
            'id': fields.get('id', 0),
            'rv_id': 0,
            'name': fields.get('name', ''),
            'author': fields.get('author', ''),
            'price': fields.get('price', ''),
            'category': fields.get('category', ''),
            'description': fields.get('description', ''),
            'image': s3_url
        }

        create_new_item(table, item)

        return {
            "statusCode": 200,
            "headers": header_res,
            "body": "Successfully created item!",
        }

    except Exception as e:
        print(f"Error processing form data: {e}")
        raise Exception(f'Error processing form data: {e}')

    • In fcj-book-shop/fcj-book-shop/book_create folder, create requirements.txt file.

    • Copy the below code block to it.

    multipart

  4. Run the following command to deploy SAM.

    sam build
sam validate
sam deploy

    LambdaCreateFunction

  5. Open AWS Lambda console.

    • Click book_create function created. LambdaCreateFunction
    • At book_create page.
      • Click Configuration tab.
      • Select Permissions on the left menu.
      • Click on the role that the function is executing. LambdaCreateFunction
    • At fcj-book-shop-BookCreateRole-… page.
      • Check the permissions granted to the function. LambdaCreateFunction

  6. Open Amazon S3 console.

    • The book-image-resize-shop-by-myself and book-image-shop-by-myself has been created. LambdaCreateFunction
    • Click on book-image-resize-shop-by-myself bucket. At book-image-resize-shop-by-myself page.
      • Click Permissions tab.
      • Check the Bucket policy information. LambdaCreateFunction
      • Scroll down to the bottom, and check the Cross-origin resource sharing (CORS). LambdaCreateFunction