indigoapi

An API for small fast data analysis jobs at Diamond Light Source

This is where you should write a short paragraph that describes what your module does, how it does it, and why people should use it.

Source	https://github.com/DiamondLightSource/indigoapi
PyPI	pip install indigoapi
Docker	docker run ghcr.io/diamondlightsource/indigoapi:latest
Releases	https://github.com/DiamondLightSource/indigoapi/releases

This is where you should put some images or code snippets that illustrate some relevant examples. If it is a library then you might put some introductory code here:

from indigoapi import __version__

print(f"Hello indigoapi {__version__}")

Or if it is a commandline tool then you might put some example commands here:

To start the api server run in dev mode:

uvicorn indigoapi.main:start_api --reload --factory --host 127.0.0.1 --port 8000

The structure of this app is defined below. IndigoAPI can add jobs to the queue in one of two ways. Either you send a request, via the client or any http request to the API endpoint which adds it to the queue.

Alternatively jobs can be added automatically by listening to a RabbitMQ message stream.

Either way jobs are added to the queue and run first-in-first-out. Once jobs are run, results can be returned to the client or via a reuqest with the specific job uuid.

Results are kept for a defined period of time, periodically the expired results are checked and removed.

         HTTP Client ────────
              │             │
              ▼             ▼
          IndigoAPI ──► Results        
              │ 
              ▼ 
        QueueManager 
              │                  
              ▼
            Workers
              ▲
              │

RabbitMQ ──► RabbitListener

python -m indigoapi --version

1. Build and push your Docker image

Your chart references an image like:

image: repository: ghcr.io/diamondlightsource/indigoapi tag: latest

So first build and push it.

Example:

podman build -t ghcr.io/diamondlightsource/indigoapi:latest . podman push ghcr.io/diamondlightsource/indigoapi:latest

2. Check the chart renders correctly

Before installing, render the templates:

helm template indigoapi ./helm/indigoapi

You should see:

Deployment Service ConfigMap

You can also validate against Kubernetes:

helm template indigoapi ./helm/indigoapi | kubectl apply --dry-run=client -f - 3. Install the chart

From the root of your repo:

helm install indigoapi ./helm/indigoapi

indigoapi here is the release name.

Helm will create:

Deployment Service ConfigMap

in your cluster.

4. Check the deployment

Check pods:

kubectl get pods

Example result:

indigoapi-0.1.0-7f6c5c9fbb-abcde Running

Check services:

kubectl get svc 5. Test the API

Port forward the service:

kubectl port-forward svc/indigoapi-0.1.0 8000:8000

http://localhost:8000/docs