Using a DynamoDB Table Basic I/O

Convert the following provided CSV records:

Monitor Lizard,319,Duncan,Moss,4,Male,Null,Spiky
Iguana,146,Jessica,Seaweed,10,Female,Null,Rough
Iguana,159,Paul,Basil,3,Male,Null,Rough
Chinchilla,631,Shadam,Stone,2,Male,Soft,Null
Chinchilla,805,Irulan,Snow,1,Female,Soft,Null
Red-tailed Boa,3,Vladimir,Abalone/Brick,18,Male,Null,Smooth
Red-tailed Boa,9,Feyd-Rautha,Ash/Caramel,8,Male,Null,Smooth

To make them, DynamoDB JSON syntax is shown below:

{
    "age": {
        "N": "4"
    },
    "color": {
        "S": "Moss"
    },
    "gender": {
        "S": "Male"
    },
    "name": {
        "S": "Duncan"
    },
    "pet_id": {
        "N": "319"
    },
    "pet_species": {
        "S": "Monitor Lizard"
    },
    "scale_texture": {
        "S": "Spiky"
    }
}

Add the records to the PetInventory DynamoDB table using the PutItem API call.

This can be accomplished in one of the following ways:

• With the Create Item button in the AWS Management Console.
• With the aws dynamodb put-item command in the AWS CLI.
• With the Boto3 SDK put_item method for the Client or Table interfaces.

Update the records in the table with the UpdateItem API call to add the missing pet_available attribute.

This can be done in one of the following ways:

• Editing the item in the AWS Management Console.
• With the aws dynamodb update-item command in the AWS CLI.
• With the Boto3 SDK update_item method.

Manually confirm all data has been updated in the table correctly in one of the following ways:

• Review the table output in the AWS Management Console.
• Run aws dynamodb scan --table-name PetInventory in the AWS CLI.

1. Run the confirmlab.py and confirmlabfinal.py scripts:

python3 confirmlab.py

python3 confirmlabfinal.py

1. Ensure the output matches the output provided in the lab information.