This project is a Kata for clean coding with AWS SAM (Serverless Application Model).
Kata projects have the following requirements at the time of this writing:
- To demonstrate clean code practice
- To follow strict type-checking
- To have full unit-test coverage
- To have full integration testing coverage
- To follow strict access and security policies
- To have automated scripts for set up and tear down
This Kata was developed with
- IntelliJ Idea, Ultimate version, 2020.3.3
- Python 3.9
- Python Plugin 203.7717.81
- AWS Plugin 1.25-33
The information in this Readme file is edited from the auto-generated Readme which was created using the
sam init command
boot3-stubs package was installed to allow for autocomplete and type matching in the IDE
The lambda in this scenario returns all objects in an S3 bucket.
- It expects the bucket name to be in the
event.queryStringParameters- otherwise, it will return a 400 (bad request) complaining about missing bucket name
- If the bucket does not exist, it returns a 404 (not found) complaining about the bucket not present
- If the bucket is not accessible, it returns a 403 (not authorized) complaining about lack of access
- If the bucket can be queried successfully, it will be returned via the json response.
- Otherwise, an error will be returned.
The Kata sets up and tears down its own testing environment. This means that the Kata will create all resources it needs for testing its scenarios on the fly, then destroys them on exit.
-
For Unit tests
- The
mockandmotolibraries are used to mock the s3 resource usage in the lambda file - The
setUp()function is used to create a bucket in mocked s3 resource, create some files and upload it at the start of each test - The
tearDown()function is used to delete the files and the bucket at the end of each test.
- The
-
For Integration tests:
- The
setUpClass()class method is used to create the files and the bucket, whose name is read from the environment variable, at the start of the test suite. this means the bucket will be created only once for all tests.- Such approach is needed because tests can run close to each other, and if the buckets keeps being created and deleted, the next test may fail.
- The
tearDownClass()class method is used to remove the files and the bucket when all tests are done. - The
setUp()method is used to get the endpoint for the lambda to call at each test.
- The
This project contains source code and supporting files for a serverless application that you can deploy with the SAM CLI. It includes the following files and folders.
- get_s3_objects - Code for the application's Lambda function.
- events - Invocation events that you can use to invoke the function.
- tests - Unit and Integration tests for the application code.
- template.yaml - A template that defines the application's AWS resources.
The application uses several AWS resources, including Lambda functions and an API Gateway API. These resources are defined in the template.yaml file in this project. You can update the template to add AWS resources through the same deployment process that updates your application code.
Unit tests can run without deploying the application. To run unit tests, first install the requirements for each test:
local-s3-app$ pip install -r tests/requirements.txt --userFrom that point, y 8000 ou can run the tests from the command line. For example, a CI/CD tool, can run the unit tests using the following command
# unit test
local-s3-app$ PYTHONPATH=".:/usr/local/lib/python3.9/site-packages:$PYTHONPATH" /usr/local/bin/python3.9 tests/unit/test_handler.pyThis will ensure that the current directory is searched for required files and modules, however based on the operating
system or the directory structure, the above command may require some editing. for example, in some operating systems,
paths are separated by ; instead of :
Please note that recent versions of python are required to support strict type checking and mocking.
In the case of IntelliJ Idea, directly form inside the IDE. This allows you to put breakpoints in Lambda and inspect local variables and other state information.
Build your application with the sam build --use-container command.
local-s3-app$ sam build --use-containerThe SAM CLI installs dependencies defined in get_s3_objects/requirements.txt, creates a deployment package, and saves it in the .aws-sam/build folder.
Test a single function by invoking it directly with a test event. An event is a JSON document that represents the input that the function receives from the event source. Test events are included in the events folder in this project.
Run functions locally and invoke them with the sam local invoke command.
local-s3-app$ sam local invoke GetS3ObjectsFunction --event events/event.jsonThe SAM CLI can also emulate your application's API. Use the sam local start-api to run the API locally on port 3000.
local-s3-app$ sam local start-api
local-s3-app$ curl http://localhost:3000/The SAM CLI reads the application template to determine the API's routes and the functions that they invoke. The Events property on each function's definition includes the route and method for each path.
Events:
GetS3ObjectsAPI:
Type: Api
Properties:
Path: /GetS3Objects
Method: getThe Serverless Application Model Command Line Interface (SAM CLI) is an extension of the AWS CLI that adds functionality for building and testing Lambda applications. It uses Docker to run your functions in an Amazon Linux environment that matches Lambda. It can also emulate your application's build environment and API.
To use the SAM CLI, you need the following tools.
- SAM CLI - Install the SAM CLI
- Python 3 installed
- Docker - Install Docker community edition
To build and deploy your application for the first time, run the following in your shell:
sam build --use-container
sam deploy --guidedThe first command will build the source of your application. The second command will package and deploy your application to AWS.
If you are using a specific profile, you need to add that to the end of the deploy command:
sam deploy --guided --profile myprofileGuided deployment presents a series of prompts:
- Stack Name: The name of the stack to deploy to CloudFormation. This should be unique to your account and region, and a good starting point would be something matching your project name.
- AWS Region: The AWS region you want to deploy your app to.
- Confirm changes before deploy: If set to yes, any change sets will be shown to you before execution for manual review. If set to no, the AWS SAM CLI will automatically deploy application changes.
- Allow SAM CLI IAM role creation: Many AWS SAM templates, including this example, create AWS IAM roles required for the AWS Lambda function(s) included to access AWS services. By default, these are scoped down to minimum required permissions. To deploy an AWS CloudFormation stack which creates or modifies IAM roles, the
CAPABILITY_IAMvalue forcapabilitiesmust be provided. If permission isn't provided through this prompt, to deploy this example you must explicitly pass--capabilities CAPABILITY_IAMto thesam deploycommand. - Save arguments to samconfig.toml: If set to yes, your choices will be saved to a configuration file inside the project, so that in the future you can just re-run
sam deploywithout parameters to deploy changes to your application.
You can find your API Gateway Endpoint URL in the output values displayed after deployment.
The application template uses AWS Serverless Application Model (AWS SAM) to define application resources. AWS SAM is an extension of AWS CloudFormation with a simpler syntax for configuring common serverless application resources such as functions, triggers, and APIs. For resources not included in the SAM specification, you can use standard AWS CloudFormation resource types.
To simplify troubleshooting, SAM CLI has a command called sam logs. sam logs lets you fetch logs generated by your deployed Lambda function from the command line. In addition to printing the logs on the terminal, this command has several nifty features to help you quickly find the bug.
NOTE: This command works for all AWS Lambda functions; not just the ones you deploy using SAM.
So, assuming the stack-name was local-s3-app, you will get the logs like this:
local-s3-app$ sam logs -n GetS3ObjectsFunction --stack-name local-s3-app --tailYou can find more information and examples about filtering Lambda function logs in the SAM CLI Documentation.
Once your application is deployed, integration tests can run with the following command
# integration test, requiring deploying the stack first.
local-s3-app$ AWS_SAM_STACK_NAME=<stack-name> AWS_DEFAULT_REGION=<region> AWS_PROFILE=<profile> BUCKET_NAME=<bucketName> python -m pytest tests/integration -v- The
AWS_SAM_STACK_NAMEis the name of the stack you used to deploy your app. you will use this to get logs, add resources, and clean up. - The
AWS_DEFAULT_REGIONis the region in which you have deployed the stack. - The
AWS_PROFILEis optional, in case you would use a non-default profile for deployment - The
BUCKET_NAMEis specific to this Kata and is a name of bucket to create for tests. it should start withs3kata. it will be destroyed when the tests are done.
NOTE that since the bucket is created on the fly, it will be a private bucket. for the lambda to access that, we need to have a policy
this policy is set in the template file, as shown below:
Policies:
- S3ReadPolicy:
BucketName: s3kata*This means that the bucket name for integration tests should start with s3kata
To delete the sample application that you created, use the AWS CLI. Assuming you used your project name for the stack name, you can run the following:
aws cloudformation delete-stack --stack-name <stack-name>See the AWS SAM developer guide for an introduction to SAM specification, the SAM CLI, and serverless application concepts.