This repository is a lab from the NYU DevOps and Agile Methodologies graduate course CSCI-GA.2820-001 on Behavior Driven Development with Flask and Behave
The sample code is using Flask micro-framework and is intended to be deployed to Kubernetes using K3D. It also uses PostgreSQL as a database.
One of my favorite quotes is:
"If it's worth building, it's worth testing. If it's not worth testing, why are you wasting your time working on it?"
As Software Engineers we need to have the discipline to ensure that our code works as expected and continues to do so regardless of any changes, refactoring, or the introduction of new functionality.
This lab introduces Test Driven Development using PyUnit
and PyTest
. It also explores the use of using RSpec syntax with Python through the introduction of the compare
library that introduces the expects
statement to make test cases more readable.
It also introduces Behavior Driven Development using Behave
as a way to define Acceptance Tests that customer can understand and developers can execute!
This lab uses Docker and Visual Studio Code with the Remote Containers extension to provide a consistent repeatable disposable development environment for all of the labs in this course.
You will need the following software installed:
- Docker Desktop
- Visual Studio Code
- Remote Containers extension from the Visual Studio Marketplace
All of these can be installed manually by clicking on the links above or you can use a package manager like Homebrew on Mac of Chocolatey on Windows.
Alternately, you can use Vagrant and VirtualBox to create a consistent development environment in a virtual machine (VM).
You can read more about creating these environments in my article: Creating Reproducible Development Environments
To bring up the development environment you should clone this repo, change into the repo directory:
git clone https://github.com/nyu-devops/lab-flask-bdd.git
cd lab-flask-bdd
Depending on which development environment you created, pick from the following:
Open Visual Studio Code using the code .
command. VS Code will prompt you to reopen in a container and you should say yes. This will take a while as it builds the Docker image and creates a container from it to develop in.
code .
Note that there is a period .
after the code
command. This tells Visual Studio Code to open the editor and load the current folder of files.
Once the environment is loaded you should be placed at a bash
prompt in the /app
folder inside of the development container. This folder is mounted to the current working directory of your repository on your computer. This means that any file you edit while inside of the /app
folder in the container is actually being edited on your computer. You can then commit your changes to git
from either inside or outside of the container.
This repository has both unit tests and integration tests. You can now run pytest
and behave
to run the TDD and BDD tests respectively. (see below: Behave requires the service under test to be running)
This repo also has unit tests that you can run pytest
pytest
Pytest is configured to automatically include the flags --pspec --cov=service --cov-fail-under=95 --disable-warnings
so that red-green-refactor is meaningful. If you are in a command shell that supports colors, passing tests will be green while failing tests will be red using the pytest-pspec
plugin. You will also see a code coverage report at the end which uses the pytest-cov
and coverage
plugin.
These tests require the service to be running because unlike the the TDD unit tests that test the code locally, these BDD integration tests are using Selenium to manipulate a web page on a running server.
Start the server in a separate bash shell:
honcho start
Then start behave
in your original bash shell:
behave
You will see the results of the tests scroll down yur screen using the familiar red/green/refactor colors.
You can also use Kubernetes to host your application and test against it with BDD. The commands to do this are:
make cluster
make build
make push
make deploy
What did these commands do?
Command | What does it do? |
---|---|
make cluster | Creates a local Kubernetes cluster using k3d |
make build | Builds the Docker image |
make push | Pushes the image to the local Docker registry |
make deploy | Deploys the application using the image that was just built and pushed |
Now you can just run behave
against the application running in the local Kubernetes cluster
behave
You can use the curl
command to query what images you have pushed to your local Docker registry. This will return JSON
so you might want to use the silent flag -s
and pipe it through jq
like this:
curl -XGET http://localhost:5000/v2/_catalog -s | jq
That will return all of the image names without the tags.
To get the tags use:
curl -XGET http://localhost:5000/v2/<image-name>/tags/list -s | jq
./service/routes.py -- the main Service using Python Flask
./service/models.py -- the data models for persistence
./service/common -- a collection of status, error handlers and logging setup
./tests/test_routes.py -- unit test cases for the server
./tests/test_models.py -- unit test cases for the model
./features/pets.feature -- Behave feature file
./features/steps/web_steps.py -- Behave step definitions
Copyright (c) 2016, 2024, John J. Rofrano. All rights reserved.
Licensed under the Apache License. See LICENSE
This repository is part of the NYU graduate class CSCI-GA.2810-001: DevOps and Agile Methodologies taught by John Rofrano, Adjunct Instructor, NYU Courant Institute, Graduate Division, Computer Science.