AWS Lambda Testing with DynamoDB and Amazon Q Developer

---

Project Overview

This project demonstrates a professional approach to testing AWS Lambda functions with Python, DynamoDB, and Amazon Q Developer.

Automated testing is crucial to ensure:

- **Reliability:** Applications work as intended.  
- **Maintainability:** Changes do not break existing functionality.  
- **Documentation:** Tests serve as live documentation.  

In this project, we:

1. Implemented "save_to_dynamodb_table" to store "JobPosting" objects to DynamoDB.
2. Created sample data and fixtures for testing.
3. Used Moto to mock DynamoDB (no real AWS resources are affected).
4. Refactored tests to be descriptive, independent, and maintainable.
5. Leveraged Amazon Q Developer to identify test scenarios, generate tests, and improve code quality.

Reference: AWS DevOps & Developer Productivity Blog — “Testing your applications with Amazon Q Developer,” July 29, 2024”

---

Project Structure

project/ ├─ src/ │ ├─ models.py │ ├─ save_to_dynamodb.py ├─ tests/ │ ├─ conftest.py │ ├─ test_save_to_dynamodb.py ├─ README.md

• src/models.py – Defines JobPosting, Salary, EmploymentType.
• src/save_to_dynamodb.py – Function to save job postings to DynamoDB.
• tests/conftest.py – Fixtures for environment variables and mock data.
• tests/test_save_to_dynamodb.py – Unit tests using pytest and Moto.

---

Installation

1. Clone the repository:

   git clone <your-repo-url>
   cd <project-folder>

2. Install dependencies:

   pip install -r requirements.txt

3. Running Tests

   Run all tests:

    pytest -q

4. Run a specific test file:

   pytest -q tests/test_save_to_dynamodb.py

5. Generate coverage report:

   pytest --cov=src tests/

Sample Fixture and Data

import os
import pytest
from datetime import datetime
from src.models import JobPosting, Salary, EmploymentType

@pytest.fixture
def mock_table_name():
    os.environ["TABLE_NAME"] = "mock-table"
    yield
    del os.environ["TABLE_NAME"]


job_posting = JobPosting(
    id="123e4567-e89b-12d3-a456-426655440000",
    title="Software Engineer",
    description="Build web applications using Python and Django.",
    salary=Salary(amount=100000, currency="USD"),
    location="Remote",
    company="Acme Corp",
    employment_type=EmploymentType.FULL_TIME,
    application_deadline=datetime(2023, 1, 15)
)

Using Moto to Mock DynamoDB

from moto import mock_dynamodb2
import boto3
from src.save_to_dynamodb import save_to_dynamodb_table

@mock_dynamodb2
def test_save_to_dynamodb_table(mock_table_name):
    dynamodb = boto3.resource("dynamodb", region_name="us-east-1")
    table = dynamodb.create_table(
        TableName="mock-table",
        KeySchema=[{"AttributeName": "id", "KeyType": "HASH"}],
        AttributeDefinitions=[{"AttributeName": "id", "AttributeType": "S"}],
        ProvisionedThroughput={"ReadCapacityUnits": 5, "WriteCapacityUnits": 5},
    )
  
    save_to_dynamodb_table(job_posting)
    item = table.get_item(Key={"id": job_posting.id})["Item"]
    assert item["title"] == job_posting.title

	```

Note: All tests run against a mocked DynamoDB. No real AWS resources are affected.

Benefits of Amazon Q Developer

• Learning & Guidance: Explains testing concepts interactively.
• Scenario Identification: Suggests unit test scenarios, including edge cases.
• Test Generation & Refactoring: Generates and refactors unit tests for clarity.
• Dependency Mocking: Provides guidance on mocking external services.
• Improved Code Quality: Reduces human error and accelerates development.

Try It Yourself

1. Ensure Python 3.11+ is installed.
2. Install dependencies: pip install -r requirements.txt
3. Run tests: pytest -q
4. Modify or add new JobPosting test cases.
5. Observe results in the terminal or generate coverage report.

Best Practices Implemented

• Independent tests: No reliance on global state.
• Fixtures for setup/teardown: Environment variables and sample data.
• Descriptive test names: Clearly indicate purpose.
• Complete assertions: All relevant properties verified.
• Mocking external dependencies: DynamoDB is mocked with Moto.

Conclusion

This project demonstrates a professional workflow for testing serverless Python applications:

• Mocked DynamoDB tables with Moto.
• Fixtures for reliable setup and teardown.
• Descriptive, maintainable, and independent tests.
• Full integration with Amazon Q Developer to accelerate and improve test writing.

It is ready to be extended with additional features or serve as an educational example for testing AWS Lambda functions.