AIOHTTP VS Flask

> AIOHTTP: The Python int constructor is used to parse Content-Lengths and chunk-sizes, so _, +, and - are misinterpreted.

Fun. I believe the fix is incomplete here[1]. Python's int() constructor accepts integers comprised of any unicode numeral, for example, int("٦٦٦") == 666, and "٦٦٦".isdecimal() == True.

[1] https://github.com/aio-libs/aiohttp/pull/7663/files#diff-197...

aiohttp

If you want speed, I would try to rewrite everything using an asynchronous library like aiohttp.

requests does not support async out-of-the-box, so we will use aiohttp to avoid complications. requests can do the job, and there is no substantial performance difference. But the code is more readable using aiohttp.

I'm using aiohttp to build an API server that sends TCP requests off to a seperate server. The module that sends the TCP requests is synchronous and a black box for my purposes. So my problem is that these requests are blocking the entire API. I need a way to wrap the module requests in an asynchronous coroutine that won't block the rest of the API.

aiohttp - Everything that I need and nothing that I don't.

Use aiohttp to download the content of each page of lists. As of this Code Review post, this is the only step we execute.

In this beginner-friendly guide, we will create a simple API using Python and Flask a lightweight and easy-to-use web framework for Python that allows developers to create APIs and web applications quickly. This API will take a number as input and return some basic properties, such as whether it is even or odd, and its square. We will also deploy the API so that it can be accessed from anywhere.

Flask Documentation. "Flask, Web Development." https://flask.palletsprojects.com/.

Informasi lengkap mengenai Flask bisa Anda baca di dokumentasi resmi Flask: https://flask.palletsprojects.com/

Let's see how it works, with a simple example, running on Flask.

Flask Official Documentation

Now that we have installed and configured Knative Serving and Eventing, backed by a kafka cluster hosted on Confluent Cloud, let's create a simple Knative service and deploy the service to the Knative cluster. In this article, we'll build our services using Python utilizing Flask, [Gunicorn[(https://gunicorn.org/)], and Werkzeug to implement the service end-point.

On the one hand, there are frameworks like Django and Flask that are great for building production-grade web apps. But they only handle the backend - you still need to use JavaScript and a frontend framework, as well as writing a lot of boilerplate code to connect the frontend and backend.

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)