metacell/scidash repository overview

⁠SciDash

SciDash is a project that enables the reproducible execution and visualization of data-driven unit test (SciUnit) for assessing model quality.

SciDash is a geppetto / django-based client-server web application.

⁠Installation

We recommend you to use a virtual environment for the installation, so you can keep all the dependencies within that environment.

Dependencies

Install pygeppetto-django from sources

git clone https://github.com/MetaCell/pygeppetto-django.git -b development
cd pygeppetto-django
RUN pip install -e .

Install Redis server (for the sockets communication)

For Ubuntu 16:
sudo apt-get install redis-server
For OS X:
brew install redis

Install PostgreSQL server

• instructions⁠ for Ubuntu
• application⁠ for MacOS

Install SciDash

git clone https://github.com/MetaCell/scidash
cd scidash
python install.py

Optional for development to enable dynamic refresh of client code when editing html/js/css:

cd statis/org.geppetto.frontend/src/main/webapp
npm run build-dev-noTest:watch

Also you should create an .env file in the project root, an example can be found in the folder: deploy/dotenv.

Configure Database Run:

# navigate to scidash root folder
cd deploy/scripts
# impersonate postgres user (may not be necessary depending on your access rights)
su postgres
# run db creation script located in the scidash folder
./db_create_psql.sh
# to return to your shell user only necessary if you used su
logout
./manage.py migrate

⁠Start the server

python manage.py runserver

Go to http://localhost:8000/⁠ and enjoy!

⁠Deployment

For scidash test deployment there are configurations in deploy folder $PROJECT_ROOT/deploy/kubernetes/scidash

What is what:

scidash-service.yaml

This configuration describes kubernetes service (what is service⁠) for scidash deployment.

Section with general information:

kind: Service
apiVersion: v1
metadata:
  name: scidash
  namespace: scidash-testing
  labels:
    app: scidash

Section with port mappings and other important information:

spec:
  type: LoadBalancer
  ports:
  - port: 80
    targetPort: 8000
  selector:
    app: scidash

This service in general is k8 resource with load balancer which provides access to the open ports from your pods (what is pods⁠)

scidash-deployment.yaml

This file provides management for deploying (and updating) pod with containers (application container and redis container).

To better understanding you can compare k8 pods with composition created by docker-compose.

Section with general information:

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  labels:
    app: scidash
  name: scidash
  namespace: scidash-testing

Start of actual specification for deployment:

spec:
  replicas: 1 # Count of the similar pods that should by launched
  selector:
    matchLabels:
      app: scidash
  strategy:
    rollingUpdate:
      maxSurge: 50%
      maxUnavailable: 50%
    type: RollingUpdate

Containers descriptions start here in template:

  template:
    metadata:
      labels:
        app: scidash
    spec:
      containers:

      - image: r.cfcr.io/tarelli/metacell/scidash:deployment
        imagePullPolicy: Always
        name: scidash
        ports:
        - containerPort: 8000 # Ports that should be exposed
          protocol: TCP

Also example for environment description. And as you can see here it uses secrets (what is secret⁠) as a source for sensible data.

        env:
          - name: DB_USER
            valueFrom:
              secretKeyRef:
                name: scidash-secret
                key: DB_USER
          - name: DB_PASSWORD
            valueFrom:
              secretKeyRef:
                name: scidash-secret
                key: DB_PASSWORD

Every secret should be mounted as a volume

        volumeMounts:
          - name: scidash-secret
            mountPath: /scidash-secret

And described in volumes section on the same level as containers:

      volumes:
        - name: scidash-secret
          secret:
            secretName: scidash-secret

Also codefresh repository requires especial secret for pulling images:

      imagePullSecrets:
      - name: codefresh-generated-r.cfcr.io-cfcr-scidash-testing

You can create it here:

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