Use Case:

Job Processor with Celery


A simple job processing scenario, showcasing a Flask and Celery by using Upstash Redis.

You have a server, where you process customer's jobs for them: apply some training for their models, apply image, text processing etc. You can reduce the server load and keep the responsiveness by using Celery: Allowing you to run processes in the background.

Once a request is made to /run endpoint with necessary parameters (id, email, difficulty), the server generates a background job using Celery and responds with an enqued message to the requester. Depending on the workload, Celery completes the job in an unknown amount of time. After the processing is finished, Celery sends a message to the server via /notify endpoint. In there, customers can be notified that their processing is complete, or even sent some reports regarding that (which is also a usecase for Celery).

Since Upstash Redis can also be used as a durable storage, we can and have configured Celery to use Upstash Redis as a backend database. Meaning, all the results of the tasks from Celery are kept in storage for later retrieval. Once a request is made to /result with id parameter, corresponding result is returned from the backend database.

Install Dependencies

pip install -r requirements.txt

Run Flask Server

flask --app server run

Start Celery Worker

celery -A tasks worker --loglevel=INFO

Run a Job

curl -X POST http://localhost:5000/run -H 'Content-Type: application/json' -d '{"id":"<id>", "email":"", "difficulty":"hard"}'

Get Results of a Job

Once a notification is sent to /notify, get the result:

curl -X POST http://localhost:5000/result -H 'Content-Type: application/json' -d '{"id":"<id>"}'

Learn More

To learn more about Upstash and its services, check out the following resources: