jbernal0019/ChRIS_ultron_backEnd

Back end for ChRIS Ultron.

ChRIS_ultron_backEnd

ChRIS is an open-source platform for containerized medical compute.

https://chrisproject.org/

TL;DR

With Docker Compose and just installed, run

git clone https://github.com/FNNDSC/ChRIS_ultron_backEnd.git
cd ChRIS_ultron_backEnd
just

Introduction

The ChRIS backend, a.k.a. ChRIS Ultron Backend or CUBE for short, is a component of the ChRIS system. It is responsible for maintaining the database of users, files, plugins, and pipelines.

Here lives the code of CUBE. It is a Django project using PostgreSQL and Celery. The HTTP API primarily supports the collection+json content-type.

Development

Development is mainly supported on Linux. MacOS and WSL on Windows also work (because Docker Desktop is a Linux VM). You will need at least 8GM RAM, 20GB disk space, and a good internet connection.

Install Docker (version 27 or above) or Podman (version 5.2 or above), Docker Compose, and just.

Docker Installation Instructions

• For MacOS and Windows, see: https://docs.docker.com/get-started/get-docker/
• For Linux, see: https://docs.docker.com/engine/install/

[!CAUTION] On Linux, the official Docker Documentation will try to trick you into installing "Docker Desktop." Do not install "Docker Desktop." Look for "Docker Engine" instead.

[!CAUTION] On Ubuntu, make sure you follow the instructions here: https://docs.docker.com/engine/install/ubuntu/. If you do not follow the instructions, Ubuntu will try to install Docker using snap, which will cause many problems.

Podman Setup Instructions

Rootless Podman is supported. You must install and configure Podman to use docker-compose, not podman-compose. podman-compose is missing features, see issues #575 and #866.

A Podman daemon must be running, because ChRIS runs containers of its own. To start the Podman daemon on Linux, run

systemctl --user start podman.service

If both Podman and Docker are installed, Podman will be used by default. A preference to use either Podman or Docker can be set by running

just prefer podman  # or
just prefer docker

With Podman, RabbitMQ might fail to start. Simply retry the command. See FNNDSC#573

Just Commands

Development is handled by just. Running CUBE in development mode is as-simple-as running the command

just

The first run of just will take 5-20 minutes because it needs to pull and build container images. Subsequent runs should only take 1-5 minutes.

CUBE is now running at http://localhost:8000/api/v1/. You can click around in the web browser. Alternatively, check out chrs and/or ChRIS_ui.

Run tests:

just test-all                       # run all tests
just test-unit                      # run unit tests
just test-integration               # run integration tests
just test feeds.tests.test_views    # run chris_backend/feeds/tests/test_views.py

Shut down and clean up:

just nuke

List all just commands:

just --list --unsorted

Development Tips and Tricks

Recreate containers after changing docker-compose_just.yml

If you modify docker-compose_just.yml, you need to recreate/restart the affected services.

just up

Rebuild the image after changing package dependencies

If you modify Dockerfile or requirements/*.txt, you need to rebuild the image and recreate your containers.

just rebuild && just up

Trying HTTP requests from the CLI

For CLI tools, I recommend xh and jnv or jq. Example:

xh -a chris:chris1234 :8000/api/v1/ | jnv

Interactive shell

It is often easiest to debug things using a shell.

just bash    # run bash in a container
# -- or --
just shell   # run a Python REPL

In the Python REPL, you can import models and interact with them. Here is some common starter code:

from django.conf import settings
from django.contrib.auth.models import User, Group
from plugins.models import *
from plugininstances.models import *
from core.storage import connect_storage

storage = connect_storage(settings)

Alternative Development Script

Old development scripts usage is described in OLD_DEVELOP.md.

IDE Setup

Visual Studio Code and PyCharm both support using Docker containers to run the Python interpreter. Run just build, then point your IDE to use the container image localhost/fnndsc/cube:dev.

Not all text editors support using Docker, or configuring the LSP might be inconvenient. In these cases, you need to install Python and the dependencies on-the-metal.

Installing Python Dependencies On-The-Metal

The traditional but worst approach is to install Python 3.11, then run

python -m venv venv
source venv/bin/activate
pip install -r requirements/local.txt

Some dependencies (such as python-ldap) build C code during installation, requiring clang to be installed. Alternatively, my recommendation is to use micromamba to install Python 3.11 and python-ldap, then use pip to install everything else. Install micromamba, then run

micromamba create -p ./.mambaenv -c conda-forge -y python=3.11 python-ldap=3.4
micromamba -p ./.mambaenv run pip install -r requirements/local.txt

Now the environment is ready. Activate the environment

micromamba activate -p ./.mambaenv

And you are ready to run your LSP + text editor.

Production Deployment

See https://chrisproject.org/docs/run/helm

GitHub Actions

This repository can also be used as a GitHub Actions step for running CUBE integration tests, e.g.

name: CI

on:
  push:
    branches: [ master ]
  pull_request:
    branches: [ master ]

jobs:
  test:
    runs-on: ubuntu-24.04
    steps:
      - name: Build something else
        uses: docker/build-push-action@v6
        with:
          tags: localhost/fnndsc/pman:dev
          load: true
      - name: Run ChRIS backend integration tests
        uses: FNNDSC/ChRIS_ultron_backEnd@master
        # all inputs are optional
        with:
          engine: docker  # or podman
          command: test-integration  # or test-unit, ...
        # optionally change image used for pman, pfcon, or cube
        env:
          CUBE_IMAGE: localhost/fnndsc/cube:dev
          PFCON_IMAGE: localhost/fnndsc/pfcon:dev
          PMAN_IMAGE: localhost/fnndsc/pman:dev

Documentation

Caution

Everything below in this section is outdated.

REST API reference

Available here.

Install Sphinx and the http extension (useful to document the REST API)

pip install Sphinx
pip install sphinxcontrib-httpdomain

Build the html documentation

cd docs/
make html

ChRIS REST API design.

Available here.

ChRIS backend database design.

Available here.