How to Produce a DynamoDB Table and Include Products to it utilizing Python 3 from Lambda

To develop a DynamoDB table and include products to it utilizing Python 3 from AWS Lambda, you can utilize the AWS SDK for Python, likewise referred to as Boto3. Here’s a detailed guide:

1. Establish your AWS environment:
   • Set up Boto3 by running pip set up boto3 in your regional advancement environment.
   • Establish your AWS qualifications and configure your AWS CLI or environment variables. You can discover in-depth directions in the AWS documents.
2. Produce a Lambda function in the AWS Management Console:
   • Go to the AWS Management Console and browse to the Lambda service.
   • Click “Produce function” and follow the directions to develop a brand-new Lambda function.
   • Pick the preferred runtime as Python 3.x.
3. Compose the Python code to develop the DynamoDB table and include products:
   • In the Lambda function code editor, get in the following code:

 import boto3

def lambda_handler( occasion, context):.
# Produce a DynamoDB customer.
dynamodb = boto3.client(' dynamodb').

# Specify the table name and schema.
table_name='YourTableName'.
table_schema =[
        {
            'AttributeName': 'ID',
            'AttributeType': 'N'
        },
        {
            'AttributeName': 'Name',
            'AttributeType': 'S'
        }
    ]

# Produce the DynamoDB table.
dynamodb.create _ table(.
TableName= table_name,.
KeySchema =[
            {
                'AttributeName': 'ID',
                'KeyType': 'HASH'
            }
        ],.
AttributeDefinitions= table_schema,.
ProvisionedThroughput= {
' ReadCapacityUnits': 5,.
' WriteCapacityUnits': 5.
}
).

# Wait on the table to be produced.
dynamodb.get _ waiter(' table_exists'). wait( TableName= table_name).

# Include products to the table.
products =[
        {
            'ID': {'N': '1'},
            'Name': {'S': 'Item 1'}
        },
        {
            'ID': {'N': '2'},
            'Name': {'S': 'Item 2'}
        }
    ]

with dynamodb.batch _ author( TableName= table_name) as batch:.
for product in products:.
batch.put _ product( Product= product).

return {
' statusCode': 200,.
' body': 'DynamoDB table produced and products included effectively.'.
}

4. Set up the Lambda function:
   • In the AWS Lambda function setup, define the following:
     • Handler: Go into the name of the Python file and the lambda_handler function. For instance, filename.lambda _ handler
     • Runtime: Python 3.x.
     • Timeout: Set a suitable timeout based upon the predicted execution time of your code.
     • Function: Pick or develop an execution function with proper DynamoDB consents.
5. Conserve and evaluate the Lambda function:
   • Conserve the Lambda function by clicking the “Conserve” button.
   • Check the function by clicking the “Test” button and setting up a test occasion.
   • Screen the execution logs and look for any mistakes or exceptions.

When you conjure up the Lambda function, it will develop a DynamoDB table with the defined schema and include the products to it utilizing a batch compose operation. Make certain to change ' YourTableName' with the preferred name for your DynamoDB table.

Make Sure that the IAM function designated to the Lambda function has the required consents to develop and compose to DynamoDB tables.