TGTGInsightтелеграм анализLIVE / telegram public index
← Такты, стеки, два колеса

TGINSIGHT SIMILAR POSTS

Намери подобно съдържание

Изходен канал @clockstackwheels · Post #1237 · преди 27 дни

В 2023 году мы с коллегой сделали доклад на DotNext по DDD и архитектуре систем. И там, в числе прочего, показали, что устройство сложного проекта, спроектированного по определённым правилам, может иметь фрактальную структуру. Но мысль эту особо не развивали. В 2024 году Влад Хононов — автор одной из самых известных книг по DDD — сделал доклад на DotNext по теме «Фрактальная геометрия в проектировании систем». Разумеется, он никаким образом на нашу идею не опирался, а работал над своей системой уже несколько лет к моменту доклада. У него там прям интересные научные обоснования, более серьёзный теоретический фундамент с введением новых понятий и принципов. Но факт близости хода мысли приятен. Типа, мы с коллегой делали систему, которая показала те же свойства, что и системы крутого эксперта в архитектуре. Прям рекомендую доклад по второй ссылке всем, кто работает в компаниях, где по какому-то странному недосмотру есть архитектура, борьба с техдолгом и попытки не допустить превращения кода в лапшу с высоким зацеплением. #dev@clockstackwheels

Hashtags

Резултати

Намерени 13 подобни публикации

Търсене: #flask

当前筛选 #flask清除筛选
djangoproject

@djangoproject · Post #592 · 11.04.2018 г., 19:22

https://juliensalinas.com/en/python-flask-vs-django/ Python #Flask vs #Django My experience of Flask is not as extensive as my experience of Django, but still recently I’ve developed some of my projects with Flask and I could not help comparing those 2 Python web frameworks. This will be a quick comparison which will not focus on code but rather on “philosophical” considerations.

Repositorio data science

@repo_science · Post #3160 · 10.05.2023 г., 21:54

#Python#Flask#APIs 🐍 REST APIs with Flask and Python in 2023 Build professional REST APIs with Python, Flask, Docker, Flask-Smorest, and Flask-SQLAlchemy 🗣️ Jose Salvatierra, Teclado by Jose Salvatierra 🌟 4.6 - 20097 votes 🔗Link ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----

djangoproject

@djangoproject · Post #162 · 15.09.2016 г., 03:22

https://github.com/realpython/discover-flask/blob/master/readme.md #Flask is a micro web #framework powered by Python. Its #API is fairly small, making it easy to learn and simple to use. But don't let this fool you, as it's powerful enough to support enterprise-level applications handling large amounts of traffic. You can start small with an app contained entirely in one file, then slowly scale up to multiple files and folders in a well-structured manner as your site becomes more and more complex.

djangoproject

@djangoproject · Post #501 · 14.11.2017 г., 17:01

http://pyvideo.org/pydx-2016/python-blockchain-and-byte-size-change.html In this talk, I will answer the question of what is #bitcoin and the #blockchain and will end with a quick tutorial on how to create a blockchain application in #Flask. We will not only make a bitcoin application, but we will also reflect upon the implications of this cutting edge technology to the greater society.

Repositorio data science

@repo_science · Post #3250 · 31.05.2023 г., 11:52

#python#flask#django#html#css#bootstrap 🐍 Python Web Dev Pro: Flask, Django, HTML, CSS & Bootstrap Elevate Your Web Development Skills: Master Back-End & Front-End Technologies with Python, Flask, Django, and Responsive 🔗Link ----- Main channel:@repo_science Coupons: @freecoupons_reposcience -----

djangoproject

@djangoproject · Post #539 · 28.12.2017 г., 12:20

Dash, announced this year, is an open source library for building web applications, especially those that make good use of #data visualization, in pure Python. It is built on top of #Flask, #Plotly.js and #React, and provides abstractions that free you from having to learn those frameworks and let you become productive quickly. #Dash is a #Python framework for building analytical web applications. No JavaScript required. https://plot.ly/products/dash/

GitHub Trends

@githubtrending · Post #15433 · 23.01.2026 г., 14:30

#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles. https://github.com/OpenBMB/UltraRAG

12
ПредишнаСтр. 1 от 2Следваща