looking for an #OSS #APIgateway

* API keys (API users) + Oauth (website) for auth
* rate limiting + protection against content crawling
* queuing requests to prevent overloading our self-hosted AI models
* ability to track usage so that we can charge expensive API calls to users/orgs
* basic monitoring

API will most likely be written in #NestJS, another likely using #FastAPI (or something else in #Python). I like #GitOps. Doesn’t need to handle insane traffic just make the above things easier.

クラスメソッドによる2025年OSS支援(5件)を紹介します
https://dev.classmethod.jp/articles/oss-sponser-2025/

#dev_classmethod #OSS #runn #Hono #MkDocs #fastapi

クラスメソッドによる2025年OSS支援(5件)を紹介します | DevelopersIO

クラスメソッドによる2025年OSS支援(5件)を紹介します | DevelopersIO

BlackWave: Как я создал симулятор соцсети с тысячами ИИ-ботов и почему перешёл на Python

Эта статья — не просто рассказ о разработке. Это путь от сумасшедшей идеи «социальной сети для одного» до полноценной open-source платформы, где каждый бот — личность. Я поделюсь тем, как строил архитектуру, зачем отказался от C# в пользу Python и почему важно, чтобы ИИ-боты вели себя не как алгоритмы, а как настоящие люди. Читать

https://habr.com/ru/articles/918848/

#Python #Django #fastapi #искусственный_интеллект #социальные_сети #открытый_код #docker #dockercompose #ai #векторные_базы_данных

BlackWave: Как я создал симулятор соцсети с тысячами ИИ-ботов и почему перешёл на Python

Привет, Хабр! Меня зовут Владислав, в сети я известен как Metimol. Хочу поделиться историей создания моего open-source проекта BlackWave — симулятора социальной сети, где реальные пользователи могут...

Хабр
Continuing my exploration into the idea of having locally-executable APIs/applications that will eventually be deployed as #Python #AWS #LambdaFunctions. At this point, I have a working local #FastAPI process that maps requests to a defined Lambda Function handler.
https://goblinfish-code.blogspot.com/2025/06/local-aws-api-gateway-development-with_01470362335.html
Local AWS API Gateway development with Python: The initial FastAPI implementation

Based on some LinkedIn conversations prompted by my post there about the previous post on this topic , I feel like I shoul...

@paarth @scastano #fastapi is actually based on starlette, not flask

It's been a while since I've posted an update for Rack Root, but I've actually made some progress on it lately.

I've finished my refactor to use SQLAlchemy for the database connections and also (finally) figured out how I want to join tables together and relate things.

I also changed some API endpoints. For example, if you look for /network/$id/gateway and there's no gateway, you get a 404. I also changed the UX around gateways. When you make a new network, there's no gateway assigned, so that part of the page has a green + icon. When you set a gateway, that icon is now a red delete icon. Those update the field and icon dynamically without having to refresh the whole page.

The new networks page also will look at the result and see if you got an HTTP 201. If so, you get redirected to the new page. Else, you get an error message. I'm not sure if I want to add more detail to that, it would require the frontend to parse and guess what went wrong. Maybe that's an assignment for another day.

Finally, there's a new Delete network button on the network detail page.

#rackroot #homelab #vuetify #fastapi #sqlalchemy #frontend #backend #fullstack #pytest

I was studying linear regression, and I decided to do a very basic project to consolidate some concepts. And I thought why not put it on GitHub for other people to take a look at. (API that predicts the sale price of a car)

#FastAPI #Python #MachineLearning #ScikitLearn #DataScience #Portfolio #API

https://github.com/GustavoGarciaPereira/projeto_carros_api

GitHub - GustavoGarciaPereira/projeto_carros_api: Projeto de estudo para criar uma API de previsão de preços de carros com FastAPI e Scikit-learn. O objetivo é praticar o fluxo completo de deploy de um modelo de Regressão Linear.

Projeto de estudo para criar uma API de previsão de preços de carros com FastAPI e Scikit-learn. O objetivo é praticar o fluxo completo de deploy de um modelo de Regressão Linear. - GustavoGarciaPe...

GitHub

Школы программирования против репетиторов и самообучения

Решил написать этот пост, т.к. несмотря на некоторое падение интереса к онлайн-обучению, каждый, кто решает освоить для себя новую профессию, сталкивается с выбором, куда направить усилия, а заодно и средства, чтобы это было с максимальной отдачей и не привело к выгоранию.

https://habr.com/ru/articles/917476/

#степик #онлайнкурсы #репетитор #django #fastapi #flask #aiogram #asyncio #основы_python #ооп_программирование

Школы программирования против репетиторов и самообучения

Решил написать этот пост, т.к. несмотря на некоторое падение интереса к онлайн-обучению, это направление сохраняет свою актуальность и каждый, кто решает освоить для себя новую профессию, сталкивается...

Хабр

Mit #ChatGPT, #Python, #FastAPI den Windows-Desktop automatisch aufräumen lassen.

Dank #ModelContextProtocol ( #MCP ) wird KI steuerbar. Hier ein kleines Praxis Testprojekt zum Thema Model context protocol

Jetzt lesen:
https://www.marcogriep.de/posts/model-context-protocol-mcp-windows-desktop-automatisch-aufraumen-mit-chatgpt-python-fastapi-tkinter/

#softwareentwicklung

Model Context Protocol (MCP): Windows-Desktop automatisch aufräumen mit ChatGPT, Python ,FastAPI , TKINTER

Erfahren Sie Schritt für Schritt, wie Sie mit Python, FastAPI, ChatGPT und einer einfachen GUI Ihren Windows-Desktop automatisch aufräumen. Perfekt für den Einstieg in MCP und Automatisierung mit KI.

Griep Marco - IT-Beratung, Softwareentwicklung & IT-Trainings

https://kitfucoda.medium.com/beyond-hardcoding-my-breakthrough-in-testable-parallel-python-cac762f691a0

The revelation came when I was adding a scheduler to the chatbot: What if I remove the hardcoding on the synchronization primitives? That worked right away, and as a bonus, it fixed all the unexplained problems I had with tests. It is interesting to see how a sudden flash of insight impacts the thought process and changes how code is written.

As shown in the article last week, we start from the main process, beginning with the setup of a ProcessPoolExecutor. All the synchronization primitives are sent individually to the run() function this time, given the simplified scope of this article. The setup for the FastAPI web module handles receiving a batch of data.

The background processing module was very basic, mostly just a proof-of-concept. Comparing the tests for the FastAPI application and the background module, the benefit is more apparent in the latter case. With the explicit passing of the queue object as an argument, there’s no more guesswork on which queue to patch in test.

Plus, as we are ensuring both the test and application are referring to the same queue now, we can pass real data into test, and ensure they are being received properly. Documenting the insight into blog posts can be seen as my attempt to think out loud. Perhaps we can go through the process of adapting it to our setup in a more generalized form in a future article.

#Python #FastAPI #AsynchronousProgramming #SoftwareArchitecture #UnitTesting #opentowork #fedihire #getfedihired

Beyond Hardcoding: My Breakthrough in Testable Parallel Python

Last week, we talked about removing hardcoded synchronization primitives. The refactoring was prompted by my revision to a take-home assignment I submitted for a job application. This week, let’s get…

Medium