Introduction to Amazon CodeWhisperer: Your AI Coding Companion

Amazon CodeWhisperer is a powerful AI tool designed to assist developers in writing code more efficiently. Leveraging machine learning, CodeWhisperer offers code suggestions, completes entire functions, and generates unit tests. This step-by-step guide will demonstrate how to integrate and utilize Amazon CodeWhisperer to enhance your app development process through challenges and practical examples.

Prerequisites and Initial Setup for CodeWhisperer

Before diving into the challenges, ensure you have the following:

  • An AWS account
  • AWS CLI installed and configured
  • Amazon CodeWhisperer access
  • Basic understanding of Python and AWS services

To set up Amazon CodeWhisperer:

  1. Enable CodeWhisperer in your AWS Management Console.
  2. Configure your IDE (e.g., Visual Studio Code) to use CodeWhisperer by installing the AWS Toolkit.
  3. Connect your AWS account to the IDE to start using CodeWhisperer.

User API Challenge: Enhancing Input Validation

Challenge Overview and Existing Code

In this challenge, we will enhance input validation for a User API. The existing code accepts user data but lacks robust validation.

def create_user(user_data):

    # Existing code to create user

    pass

Test-Driven Development with Pytest

Using pytest, we will implement test-driven development to validate email addresses and zip codes and ensure mandatory fields are present.

import re

import pytest

def validate_email(email):

    pattern = r’^\S+@\S+\.\S+$’

    return re.match(pattern, email) is not None

def validate_zip_code(zip_code):

    pattern = r’^\d{5}(-\d{4})?$’

    return re.match(pattern, zip_code) is not None

def test_validate_email():

    assert validate_email(‘test@example.com’)

    assert not validate_email(‘invalid-email’)

def test_validate_zip_code():

    assert validate_zip_code(‘12345’)

    assert validate_zip_code(‘12345-6789’)

    assert not validate_zip_code(‘1234’)

def test_mandatory_fields():

    user_data = {‘name’: ‘John Doe’, ’email’: ‘john@example.com’}

    assert ‘name’ in user_data

    assert ’email’ in user_data

Image API Challenge: Moderating Image Uploads with Rekognition

Integrating Amazon Rekognition for Image Moderation

This challenge will incorporate Amazon Rekognition to moderate image uploads, ensuring content appropriateness.

import boto3

rekognition_client = boto3.client(‘rekognition’)

def moderate_image(image_bytes):

    response = rekognition_client.detect_moderation_labels(

        Image={‘Bytes’: image_bytes}

    )

    return response[‘ModerationLabels’]

Modifying Code for Content Filtering

Enhance your image upload handler to incorporate the moderation logic.

def handle_image_upload(image_bytes):

    moderation_labels = moderate_image(image_bytes)

    if moderation_labels:

        return “Image contains inappropriate content”, 400

    # Proceed with image upload

Testing and Troubleshooting Image Moderation

Test the moderation function with different image samples to ensure it works correctly.

def test_moderate_image():

    with open(‘test_image.jpg’, ‘rb’) as image_file:

        image_bytes = image_file.read()

    labels = moderate_image(image_bytes)

    assert isinstance(labels, list)

Deals API Challenge: Generating XML Responses

Understanding the Challenge and Existing Code

The Deals API currently responds with JSON. We will modify it to support XML responses.

import json

def get_deals():

    deals = {‘deal1’: ‘50% off’, ‘deal2’: ‘Buy 1 Get 1 Free’}

    return json.dumps(deals)

Implementing JSON to XML Conversion

Create a function to convert JSON responses to XML.

import dicttoxml

def convert_to_xml(json_data):

    xml = dicttoxml.dicttoxml(json_data)

    return xml

Modifying Lambda Handler for XML Support

Update the Lambda handler to return XML if requested.

def lambda_handler(event, context):

    deals = get_deals()

    if event[‘headers’][‘Accept’] == ‘application/xml’:

        return {

            ‘statusCode’: 200,

            ‘headers’: {‘Content-Type’: ‘application/xml’},

            ‘body’: convert_to_xml(json.loads(deals))

        }

    return {

        ‘statusCode’: 200,

        ‘headers’: {‘Content-Type’: ‘application/json’},

        ‘body’: deals

    }

 

Products API Challenge: Generating Unit Tests with CodeWhisperer

Enhancing Test Coverage with Additional Test Cases

Leverage CodeWhisperer to generate and improve unit tests for the Products API.

def test_get_product():

    product = get_product(‘123’)

    assert product[‘id’] == ‘123’

    assert ‘name’ in product

Conclusion and Further Learning with CodeWhisperer

Amazon CodeWhisperer significantly boosts productivity by providing intelligent code suggestions, automating repetitive tasks, and generating tests. Integrating CodeWhisperer into your development workflow can enhance code quality and speed development. Continue exploring CodeWhisperer’s capabilities to fully leverage its potential in your projects.

References

10 ways to build applications faster with Amazon CodeWhisperer

Optimize software development with Amazon CodeWhisperer