CRUD operations on DynamoDB with Flask APIs

Flask with DynamoDB using boto3 module.

Technologies we’ll be using:

• Flask — Python Web Framework
• boto3 — Python module with necessary functions to work with AWS services like dynamoDB, S3.
• DynamoDB — Document based database service by AWS.

Install the dependencies for the project using pip in the terminal.

$ pip install flask
$ pip install boto3
$ pip install python-decouple

• Let’s create a python file to contain all our dynamoDB handler functions.

$ touch dynamodb_handler.py

• In the dynamodb_handler.py file, import the boto3 module.

import boto3

• Pass the credentials as environment variables

Create a .env file and include all the credentials in key=value format. E.g.,

AWS_ACCESS_KEY_ID='someaccessid'
AWS_SECRET_ACCESS_KEY='somesecretaccesskey'
REGION_NAME='us-west-1'

Now import the credentials to our python file

from decouple import config
AWS_ACCESS_KEY_ID     = config("AWS_ACCESS_KEY_ID")
AWS_SECRET_ACCESS_KEY = config("AWS_SECRET_ACCESS_KEY")
REGION_NAME           = config("REGION_NAME")

• Set Client and Resource

client = boto3.client(
    'dynamodb',
    aws_access_key_id     = AWS_ACCESS_KEY_ID,
    aws_secret_access_key = AWS_SECRET_ACCESS_KEY,
    region_name           = REGION_NAME,
)
resource = boto3.resource(
    'dynamodb',
    aws_access_key_id     = AWS_ACCESS_KEY_ID,
    aws_secret_access_key = AWS_SECRET_ACCESS_KEY,
    region_name           = REGION_NAME,
)

To create a new table, use create_table()

def CreatATableBook():
        
    client.create_table(
        AttributeDefinitions = [ # Name and type of the attributes 
            {
                'AttributeName': 'id', # Name of the attribute
                'AttributeType': 'N'   # N -> Number (S -> String, B-> Binary)
            }
        ],
        TableName = 'Book', # Name of the table 
        KeySchema = [       # Partition key/sort key attribute 
            {
                'AttributeName': 'id',
                'KeyType'      : 'HASH' 
                # 'HASH' -> partition key, 'RANGE' -> sort key
            }
        ],
        BillingMode = 'PAY_PER_REQUEST',
        Tags = [ # OPTIONAL 
            {
                'Key' : 'test-resource',
                'Value': 'dynamodb-test'
            }
        ]
    )

In order to access and modify the entries of the table, we have to get the table using the resource.

BookTable = resource.Table('Book')

CREATE

Add a new entry in the Book table.

def addItemToBook(id, title, author):
    response = BookTable.put_item(
        Item = {
            'id'     : id,
            'title'  : title,
            'author' : author,
            'likes'  : 0
        }
    )
    return response

READ

Read an entry from the Book collection.

def GetItemFromBook(id):
    response = BookTable.get_item(
        Key = {
            'id'     : id
        },
        AttributesToGet=[
            'title', 'author'
        ]
    )
    return response

UPDATE

Update an entry in the Book collection using the ‘id’ attribute.

def UpdateItemInBook(id, data:dict):
    response = BookTable.update_item(
        Key = {
            'id': id
        },
        AttributeUpdates={
            'title': {
                'Value'  : data['title'],
                'Action' : 'PUT' # available options -> DELETE(delete), PUT(set), ADD(increment)
            },
            'author': {
                'Value'  : data['author'],
                'Action' : 'PUT'
            }
        },
        ReturnValues = "UPDATED_NEW" # returns the new updated values
    )
    return response

Update (increment) ‘likes’ property for an entry.

def LikeABook(id):
    response = BookTable.update_item(
        Key = {
            'id': id
        },
        AttributeUpdates = {
            'likes': {
                'Value'  : 1,   # Add '1' to the existing value
                'Action' : 'ADD'
            }
        },
        ReturnValues = "UPDATED_NEW"
    )
    # The 'likes' value will be of type Decimal, which should be  converted to python int type, to pass the response in json format.
    response['Attributes']['likes'] = int(response['Attributes']['likes'])
    return response

DELETE

Delete an entry from the collection

def DeleteAnItemFromBook(id):
    response = BookTable.delete_item(
        Key = {
            'id': id
        }
    )
    return response

Flask APIs to handle dynamoDB operations

Let’s create a simple flask application with APIs to perform operations on our Book table.

Try running the app, using

$ python app.py

Click here to view Boto3 Documentation

Github repo — https://github.com/SharmilaS22/aws-dynamodb-flask

Happy Learning!