Artsy Docker development toolkit
Hokusai is a Docker + Kubernetes CLI for application developers.
Hokusai "dockerizes" applications and manages their lifecycle throughout development, testing, and release cycles.
Hokusai currently only supports Kubernetes deployments on AWS, configured to pull from ECS container repositories (ECR), although other providers may be added in the future.
At Artsy, as we began working with Kubernetes, while impressed with its design, capabilities, and flexibility, we were in need of tooling we could deliver to agile development teams that addressed the day-to-day tasks of application development, delivery, introspection and maintenance, while providing a clean and uncomplicated interface.
Transitioning teams to the Docker / Kubernetes ecosystem can be intimidating, and comes with a steep learning curve. We set out to create a Heroku-like CLI that would shepherd the application developer into the ecosystems of Docker and Kubernetes, and while introducing new tooling and concepts, outlining a clear practice for dependency management, local development, testing and CI, image repository structure, deployment and orchestration.
We recommend installing via Homebrew:
$ brew update $ brew tap artsy/formulas $ brew install hokusai
If you previously installed Hokusai via an alternate installation method, you may need to force the
$ brew link --overwrite hokusai
If you previously installed Hokusai via Pip, you may want to first uninstall it:
$ pip uninstall hokusai
curl -sSL https://raw.githubusercontent.com/artsy/hokusai/main/get-hokusai.sh | sudo bash
Note: This method installs Hokusai to
Python 3.7+ is required.
pip install hokusai
Note: If Pip fails at upgrading your system Python packages, try:
pip install hokusai --ignore-installed
We also maintain Hokusai Docker images for running Hokusai in Docker.
Release artifacts are available on Github.
Release artifacts are also available in AWS S3. You can use this convenience script or Curl to fetch them.
A note on Python 2.x
Hokusai currently supports Python 3.7+ only. The last version that supported Python 2.x was v0.5.18.
We assume that you already have Kubernetes cluster, Git, Docker, and Docker-Compose set up, and that you have an AWS account. Perform the following steps to setup Hokusai:
hokusai configure --kubectl-version <kubectl version> --s3-bucket <bucket name> --s3-key <file key>
Provide the Kubectl version matching that of your Kubernetes clusters, as well as the S3 bucket name/key where your org's Kubectl config file is stored.
For system administrators: see Administering Hokusai for instructions on preparing AWS and Kubernetes, and on publishing a Kubectl config file.
For Artsy developers: see artsy/README for the current way of installing and configuring hokusai.
Enable Bash autocompletion:
eval "$(_HOKUSAI_COMPLETE=source hokusai)"
See Getting Started to start using Hokusai for your project.
A full command reference can be found in Command Reference.
Hokusai can be used to simplify the process of spinning up a "review app" instance of your project, based on a feature branch or pull request.
Full details are in the Review App reference.
To work on Hokusai itself, please set up:
When installing on MacOS, please make sure to use brew-installed
readline libraries, and xcode-installed
zlib library. And make sure these libraries are correctly linked. Like so:
brew install openssl readline zlib echo 'export PATH="/firstname.lastname@example.org/bin:$PATH"' >> ~/.bash_profile echo 'export LDFLAGS="-Lemail@example.com/lib"' >> ~/.bash_profile echo 'export CPPFLAGS="-Ifirstname.lastname@example.org/include"' >> ~/.bash_profile echo 'export PKG_CONFIG_PATH="/email@example.com/lib/pkgconfig"' >> ~/.bash_profile
Hokusai is currently tested on Python 3.9.10 so we recommend using that Python version.
If you use Pyenv to install Python, you should see an output similar to this:
pyenv install 3.9.10 python-build: use openssl from homebrew python-build: use readline from homebrew Downloading Python-3.9.10.tar.xz... -> https://www.python.org/ftp/python/3.9.10/Python-3.9.10.tar.xz Installing Python-3.9.10... python-build: use tcl-tk from homebrew python-build: use readline from homebrew python-build: use zlib from xcode sdk Installed Python-3.9.10 to $HOME/.pyenv/versions/3.9.10
With the desired Python version installed, activate it globally:
pyenv global 3.9.10
Note: If you want to create a PyInstaller distribution (by running
make build) you need to install Python with development dylibs. Use the environment variable
PYTHON_CONFIGURE_OPTS="--enable-framework" on Darwin and
PYTHON_CONFIGURE_OPTS="--enable-shared" on Linux when running
We recommend using a virtual environment to isolate Hokusai's dependencies from that of other projects on your local environment.
The Pyenv install comes with pyenv-virtualenv which can be used to create virtual environments.
pip install poetry
Install dependencies and Hokusai in editable mode:
To update dependencies:
Minikube is used for integration tests.
brew install minikube minikube start --kubernetes-version=<version of your Kubernetes clusters, example: v1.2.3>
To run all tests:
To run only unit tests:
Only integration tests:
Only specific modules, TestClasses, or even methods:
python -m unittest test.unit.test_module.TestClass.test_method
DEBUG=1 environment variable to print boto logging
main branch automatically create Hokusai beta version for testing.
The beta can be installed by:
$ brew update $ brew tap artsy/formulas $ brew install hokusai-beta
curl -sSL https://raw.githubusercontent.com/artsy/hokusai/main/get-hokusai.sh | sudo bash -s beta
To create a new release, perform the following:
- bump Hokusai version in these files:
- update CHANGELOG
- open a PR to merge
The project is named for the great Japanese artist Katsushika Hokusai (1760-1849).
This project is the work of engineers at Artsy, the world's leading and largest online art marketplace and platform for discovering art. One of our core Engineering Principles is being Open Source by Default which means we strive to share as many details of our work as possible.
You can learn more about this work from our blog and by following @ArtsyOpenSource or explore our public data by checking out our API. If you're interested in a career at Artsy, read through our job postings!
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