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:
- Enable CodeWhisperer in your AWS Management Console.
- Configure your IDE (e.g., Visual Studio Code) to use CodeWhisperer by installing the AWS Toolkit.
- 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