flask-celery VS Flask

Celery

How can I test if a task (task_id) is still processed in celery? I have the following scenario:

I recently integrated celery (django-celery to be more specific) in one of my applications. I have a model in the application as follows.

I am trying to write a small application that receives video files, and convert them to a uniform format after they have been uploaded (thus added to the database). I have searched the web for the best solution for this, and have decided to use Django's signals with Celery. But for now I'm trying to create a proof-of-concept to see if it works.

Since a few days ago the page no longer loads.

https://celeryproject.org/

I'm using Celery to manage asynchronous tasks. Occasionally, however, the celery process goes down which causes none of the tasks to get executed. I would like to be able to check the status of celery and make sure everything is working fine, and if I detect any problems display an error message to the user. From the Celery Worker documentation it looks like I might be able to use ping or inspect for this, but ping feels hacky and it's not clear exactly how inspect is meant to be used (if inspect().registered() is empty?).

I recently switch to Celery 3.0. Before that I was using Flask-Celery in order to integrate Celery with Flask. Although it had many issues like hiding some powerful Celery functionalities but it allowed me to use the full context of Flask app and especially Flask-SQLAlchemy.

I'd suggest Flask or some of the smaller projects in the Pallets ecosystem:

https://github.com/pallets/flask

#!/usr/bin/python # # https://flask.palletsprojects.com/en/3.0.x/installation/ # from flask import Flask, jsonify, request contacts = [ { "id": "1", "firstname": "Lorem", "lastname": "Ipsum", "email": "[email protected]", }, { "id": "2", "firstname": "Mauris", "lastname": "Quis", "email": "[email protected]", }, { "id": "3", "firstname": "Donec Purus", "lastname": "Purus", "email": "[email protected]", } ] app = Flask(__name__, static_url_path='', static_folder='public',) @app.route("/contact//save", methods=["PUT"]) def save_contact(id): data = request.json contacts[id - 1] = data return jsonify(contacts[id - 1]) @app.route("/contact/", methods=["GET"]) @app.route("/contact//edit", methods=["GET"]) def get_contact(id): return jsonify(contacts[id - 1]) @app.route('/') def root(): return app.send_static_file('index.html') if __name__ == '__main__': app.run(debug=True)

I was looking at all the big projects like numpy, pytorch, flask, etc.

Explore here.

I may use Flask-Admin initially to offload the "CRUD" operations to have an initial prototype fast but then drop it ASAP because I don't want to write a "flask-admin application" to fight against later on. If the application is mainly "CRUD", then Flask-Admin is suitable.

Now...

Would you do a breakdown/list of all the jobs you've done by sector/vertical and by function/role and by application functionality?

- [0]: https://flask.palletsprojects.com

- [1]: https://flask-admin.readthedocs.io/en/latest

- [2]: https://flask.palletsprojects.com/en/2.3.x/patterns/celery

- [3]: https://sentry.io

- [4]: https://posthog.com

- [5]: https://www.docker.com

In the lab to follow, we will be setting up an end-to-end DevOps workflow for a Flask microservice with GitHub Actions, using a self-managed custom runner for maximal control over the pipeline execution environment and automating deployments to a local Kubernetes cluster. Furthermore, we will construct separate pipelines for our "development" and "production" environments to further elaborate on the concepts of continuous deployment and delivery.

Flask Micro web Framework: You will use Flask to build a Flask web application.

In an earlier post I mentioned a bunch of Open Source web applications. Let's now focus on the ones written in Python using Flask the light-weight web framework.