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Frameworks & web · #flask
Stop fighting circular imports in Flask. Learn how to use the Application Factory pattern to manage multiple configurations and decouple your routes using Blueprints.
Learn how to diagnose and fix '405 Method Not Allowed' errors in Flask by aligning HTTP request methods with route decorators and verifying with cURL.
Learn how Flask’s application factory pattern isolates configuration, prevents state leakage between tests, and enables lazy extension setup with a concrete, step‑by‑step example.
Architecture note on using Flask Blueprints with an application factory: requirements, minimal design, trust boundaries, operational checks, failure modes and verification steps.
Following the tutorial here I have the following 2 files: app.py from flask import Flask, request app = Flask(__name__) @app.route('/', methods=['GET']) def hello(): """Return a friendly HTTP greeting.""" who = request.args.get('who', 'World') return f'Hello {who}!\n' if __name__ == '__main__': # Used when running locally only. When deploying to Cloud Run, #
I am trying to get a Flask and Docker application to work but when I try and run it using my docker-compose up command in my Visual Studio terminal, it gives me an ImportError called ImportError: cannot import name 'json' from itsdangerous . I have tried to look for possible solutions to this problem but as of right now there are not many on here or anywhere
I'm developing an Angular + Flask application that uses Microsoft's OAuth2 (On-Behalf-Of-User Flow). I'm trying to call an API from the backend, but I get an exception. Here is the configuration in app.module.ts : export function MSALInstanceFactory(): IPublicClientApplication { return new PublicClientApplication({ auth: { clientId: '<application_id_of_sp
I want to determine whether storing large temporary objects in the Flask `g` proxy for each request leads to a memory leak, and how to confirm that a fix using `teardown_appcontext` actually releases those objects. The goal is to observe memory growth over many requests and ensure it stabilizes after the cleanup. I am working with a standard Flask applicatio
I am running a Flask application and hosting it on Kubernetes from a Docker container. Gunicorn is managing workers that reply to API requests. The following warning message is a regular occurrence, and it seems like requests are being canceled for some reason. On Kubernetes, the pod is showing no odd behavior or restarts and stays within 80% of its memory a
python
docker
angular