What's your favorite #Python micro web framework? 🧴Flask 🍼 Bottle 🍒 Cherrypy 🕸️ Web.py Or something else?

If you need to create a new website with #Python, which framework do you choose? 🐍Django 🐍FastAPI 🐍Flask 🐍Cherrypy 🐍Pyramid 🐍Masonite 🐍Streamlit 🐍Web2py or something else?

Every python backend framework : Django – the full-package framework. it comes with ORM, authentication, admin panel, security features, and more out of the box. best for large, full-featured applications where you don’t want to assemble everything manually. scalable and production-proven. Flask – a lightweight micro-framework. it gives you the basics and lets you choose your own tools (database, auth, etc.). great for small to medium projects or when you want full control over architecture. FastAPI – modern, async-first framework built for high performance APIs. It uses Python type hints and automatically generates interactive API docs. extremely fast and ideal for building scalable APIs and backend services today. Pyramid – flexible and scalable. It doesn’t force a strict structure like Django but provides more guidance than Flask. good for projects that may grow large over time. Tornado – designed for real-time applications. handles thousands of simultaneous connections using non-blocking I/O. best for chat apps, live updates, and streaming systems. Sanic – async micro-framework similar to Flask but optimized for speed. great when you want Flask-like simplicity with async performance. Bottle – minimalist single-file framework with zero dependencies. Ideal for small tools, prototypes, or learning how frameworks work internally. Falcon – focused purely on building high-performance REST APIs. minimal abstraction, very fast, and great when you want clean, efficient API services. CherryPy – one of the oldest frameworks still maintained. object-oriented and comes with its own production-ready server. simple but powerful. Starlette – lightweight async framework and the foundation of FastAPI. gives you async power and flexibility without extra automation. In short: Django = full system. Flask = flexible core. FastAPI = modern high-speed API king. Others = specialized tools depending on your use case.

WEEKLY UPDATE IS HERE. SOCIAL FEATURES ARE NOW IN THE GAME AND CAN BE ITERATED ON. EXPECT A DEPLOYMENT TOMORROW. So, why do I know how to do all this stuff? I am a self-taught programmer, I essentially dropped out of high-school (I stopped showing up senior year, but they dropped my classes and missing work so I could still graduate), and never went to college. From a young age (around 8), I was always interested in computers and programming, however I could never fully grasp and understand the concepts. I kept trying periodically, but nothing seemed to stick. It wasn’t till I was 14 years old, shortly after my favorite childhood game, Disney’s Toontown Online, closed and I finally found the ability to read and understand code. I simply loved the game, hated to see it closed, and wanted to help bring it back. I taught myself how to code by just reading Python, and my first project was creating a private server out of a mishmash of Python’s Twisted Networking library, XMLRPC web requests, Panda3D (Toontown’s Game Engine) and a CherryPy database. I just wanted to walk around the world again with my friends, and I was able to create a project to do that through my mishmash of technology. I set it up so you’d send your position data through an XMLRPC request, and in response, get all the other player locations in the area. From then, I learned from Disney’s networking architecture as well as a fan’s recreation of their architecture. This was my introduction to distributed networking. Shortly after this, I set out to create a project to preserve the historical updates of the game. I wrote my own implementation of Disney’s architecture in C#, and the project still runs today. It’s sorta like the Wayback Machine but for Disney’s Toontown Online. My favorite childhood game died, so I taught myself how to program to bring it back. Now my favorite memecoin died, so I am bringing back memes through the Memeverse. I truly believe this project is retail’s ticket back in to memecoins. I have always been a passion driven developer, with the mindset I’d just randomly get rich as fuck. Never really liked doing it as a job, way too boring that way. I have gone across a multitude of topics including reverse engineering, and AI. I kinda just have the mindset of wanting to learn every inch of computer science. I was first introduced to data oriented programming when Unity added an ECS system. At the same time, I was also learning how to write CPU and Memory optimal code by reading the C# standard library source. This is where my obsession for performance began. I started caring about memory layouts, parallelization, batching, and lock-free, wait-free code. I also have friends who have designed and deployed large scale tested MMO architectures (they did theirs in a micro-service orchestration), and learned the importance of needing to batch socket io. I carried the backend for a still running indie title when I briefly worked at an indie publisher, and also created a ranking system for the game (Glicko-2, what chess uses). The backend was done with micro-services. There was another game I worked on backend for too, but it was ultimately unsuccessful, and is no longer online. I have always been super competitive, and have tried my ass off in a lot of games. I also try my ass off in programming. Every system I design I try to make better than the last. The Memeverse architecture is essentially a slimmed down versions of Disney’s (they have lectures online you can watch explaining how they designed everything) that has been optimized to be data-oriented and highly parallelized. Doing an MMO under a micro-service orchestration leaves systems prone to many race conditions, and less hardware optimal. You just don’t get the same bang for your buck because you can’t create a system that churns like crazy and scales on hardware. Too many problems to worry about when the system is all split up. The architecture powering Memeverse has been built off of my experience with Disney’s design, my own personal iterations, and my friends’ experience. Combine that with my high-performance mindset and you get a monolithic world server that can process tons of data. The end goal deployment for Memeverse is to have multiple regions with player limits, similar to Nexon’s Maplestory. Once the rebrand is complete, I will be abandoning my @SackboyShill account, and be moving to my main (which I’ve never actually sent out a tweet on, only a couple replies). That is when I will fully dox myself. I’d just rather wait to fully affiliate myself with Memeverse, and not an in progress rebrand. Thank you again for the continued support.

that mistake started more than 20 years ago ;) My first full time Python job was writing Web stuff using Zope (the what?) Zope, (and Plone), Turbogears, Cherrypy, Web.py, Pylons, Pyramid, Django, Flask, ... only the last two are actively being used.

I need something to help orgs in #starCitizen let's discuss this. It would be great to start an open source project that I can work on publicly here if requested. If you have a suggestion for a web framework like django, flask, bottle, Pyramid, CherryPy, ETC. I am willing to take any suggestions I am not sure what would work best for my use case. I need to be able to integrate the following; - matrix/discord notifications (will be migrating to matrix soon due to the future enshitification of discord) - SSO (google, discord, etc.) - inventory management - inventory request ticketing system - Operations Scheduling - Participation tracker (track time of individual in operation maybe with weights) - easy themeing (simply because my graphics design skills are dull as hell) - analytics based on object collections Cargo components salvaged materials - handle UEXcorp.space Trading API - handle starcitizen-api.com/ REST API I know something like this isn't really put together, I haven't found a single solution for all of these, but I have found some business solutions to handle a few of these. I am willing to mix and mash and create and open source project to work with other in game Organizations to build this. I am calling on my #informationsecurity #hackers #sysadmin #developers friends to give me a few suggestions from open source projects and I will create a public repo as it is built. I would like a project to work on to learn some regolith.rocks/ is close when it comes to operations and mining calculators, but I do want to make something open source that the organizations can self host if they need to.

MicroPieは、まるで古き良きCherryPyのスピリットを、現代のASGIスタックに蘇らせたかのようなフレームワークだ。この軽量Webフレームワークは、CherryPyの「シンプルで自己完結型な設計哲学」を現代の非同期処理モデルで再解釈している。 CherryPyは2000年代初頭から活躍するWSGIベースのWebフレームワークで、Pythonのクラスや関数をそのままルーティングに活かす直感的な設計が魅力だった。MicroPieもまた、この「コードそのものがアプリケーション構造である」という思想を引き継ぎつつ、ASGI対応によって非同期処理や高速IOをネイティブに扱える現代的な仕様に進化させている。 たとえば、CherryPyが持っていた「ミドルウェア不要で即動く」「依存ライブラリを極限まで排除する」という思想が、MicroPieではさらに徹底されている。全体のコードサイズはわずか40KB、インストール時の外部依存は一切なし。実行可能なサンプルサーバーも数行で済み、起動も爆速だ。 一方で、FastAPIのような巨大フレームワークとは異なり、OpenAPI生成や依存注入といった“便利機能”は排除されており、あくまで「最低限の機能だけを残す」ことに注力している。その潔さが、CherryPyに親しんだ開発者や、現代的なマイクロサービス構成を追求するエンジニアたちの心をくすぐる。 つまり、MicroPieはCherryPyのミニマリズムを現代風にチューンアップしたASGI時代の後継者とも言える存在だ。教育的価値の高さ、IoTや軽量アプリへの親和性、そして“書いて動く”という素朴な快感を再び思い出させてくれる。 buff.ly/l1d4fLy

Speaking of pi, did you know that #Python has a mini web framework called Cherrypy? 🐍🥧🍒 It's been around a long time but never got as popular as Flask or FastAPI I think it was the first mini web framework I ever tried!

🐍 Python: A universe of possibilities! If there's one language that stands out for its versatility, it's Python. Whether for Machine Learning, Web, Automation, Games or Web Scraping, there are libraries and frameworks that make development more efficient and productive. 📌 Here are some of the main categories and essential tools: 🔹 Machine Learning: Numpy, Pandas, TensorFlow, Scikit-Learn, Matplotlib, Seaborn. 🔹 Web Development: Django, Flask, Dash, CherryPy, Falcon. 🔹 Automation Testing: PyTest, Robot, Splinter, PyUnit. 🔹 Game Development: PyGame, Arcade, Panda3D, PyOpenGL. 🔹 Image Processing: OpenCV, Scikit-Image, SimpleITK, PGMAGICK. 🔹 Web Scraping: Selenium, BeautifulSoup, Scrapy, Requests. 💡 Whatever your goal, Python has a solution for you! #DataScience #MachineLearning

🐍 Python: Um universo de possibilidades! Se tem uma linguagem que se destaca pela versatilidade, essa linguagem é Python. Seja para Machine Learning, Web, Automação, Games ou Web Scraping, existem bibliotecas e frameworks que tornam o desenvolvimento mais eficiente e produtivo. 📌 Aqui estão algumas das principais categorias e ferramentas essenciais: 🔹 Aprendizado de Máquina: Numpy, Pandas, TensorFlow, Scikit-Learn, Matplotlib, Seaborn. 🔹 Desenvolvimento Web: Django, Flask, Dash, CherryPy, Falcon. 🔹 Testes de Automação: PyTest, Robot, Splinter, PyUnit. 🔹 Desenvolvimento de Jogos: PyGame, Arcade, Panda3D, PyOpenGL. 🔹 Processamento de Imagem: OpenCV, Scikit-Image, SimpleITK, PGMAGICK. 🔹 Web Scraping: Selenium, BeautifulSoup, Scrapy, Requests. 💡 Seja qual for o seu objetivo, Python tem uma solução para você! #DataScience #MachineLearning

暴轮: 对新手友好的只有 BASIC 的 GOTO 20 我学python用1个礼拜, 但真正明白什么是 class 是一年后写了些 CherryPy 之后. 融会贯通是在读完PyObject_ 代码之后.

I don't tweet often, but when I do it is b/c someone mentions CherryPy (or Emacs). Great stuff @jamwt @dowskimania

I'm lucky to have worked with Christian (ahem, dowski) at three of four companies over the last 17 years. Such an amazing developer and human being! Still grateful to @aminusfu for the introduction so many years ago. Three cheers to CherryPy and the Python webdev community.

2. Artificial Intelligence -Deep learning: Theano, SciPy, OpenCV, PyTorch, DeepLearning4JS -Machine learning: TensorFlow, Keras, Pandas 3. App Development -Web: Flask, Django, CheryPy, Web2Py, FastAPI, TurboGears -Mobile: Kivy, Beawear, CherryPy -Desktop: PyQt, Tkinter

Day 4 of #180daysofcode learning full stack #django development. ◖ Today I explore more about web development libraries like CherryPy, Request and Bottle. #python #webdevelopment #coding #programming

How do you explore routes anywhere? Express JS, Sinatra, Flask, CherryPy, Tapir, etc… So many frameworks missing basic exploitability

CherryPy: A minimalist web framework that allows developers to build web applications in a similar way to building any other object-oriented Python program.

📢 PSA I just cut a release of #Cheroot v10.0.1: github.com/cherrypy/cheroot/… A lot of people were waiting for the TLS fixes. And I also kept Python 3.6 support in the meta as an exception — Ceph folks asked as they use #CherryPy too! #python #Packaging #release #automation #PyPI

2024's top Python web frameworks: 🐍 1. Django: Feature-rich for complex apps 2. Flask: Lightweight, great for beginners 3. FastAPI: High-performance APIs 4. Pyramid: Flexible, modular design 5. Tornado: Ideal for real-time apps 6. Bottle: Quick, for small projects 7. CherryPy: Minimalist, WSGI integrated 8. Falcon: Speedy REST APIs 9. Dash: Perfect for data visualization 10. Giotto: Clean syntax, great for async

CherryPy ❕ It is a popular open-source, object-oriented Python framework that follows a minimalistic approach. It is one of the oldest #Python frameworks. The #CherryPy web framework enables the use of any data access and templating technology. #developers #Connect #Coding