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Source channel @olddriverGDstudy · Post #40 · Mar 17

秀哥语录: 开水烫鸡把,锻炼起来 123的兄弟,我给你们说个方法 蛮有效的,就是开水烫几把 你每天洗澡的时候,水温稍微调高一点点 比如平时40度,你就45 用淋浴头冲,冲龟头,每天冲个五分钟 正经点,靠,虽然开水烫几把名字不正经 但是真的有用 你快,是因为敏感,每天冲,可以降低敏感度 一边冲,一边两个指头按压捏,每天五分钟 养成习惯,慢慢就好了 到后期,你可以用毛巾,湿水 然后慢慢尝试那毛巾擦龟头,上下撸 什么时候毛巾擦龟头,你不抖了,就好了 慢慢来啊,过犹不及,慢慢锻炼,降低龟头敏感度 可以尝试下,多少有点用 另外就是心里调节了 不要老是想,不要在意长短 学会去享受,要自信,自我暗示,我是来爽的,不是来比赛的 心里 生理 双管齐下,从此告别123 #秀哥语录#语录

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Search: #flask

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Dejavu's Blog

@dejavuBlog · Post #3487 · 03/24/2026, 01:25 PM

《Flask 从入门到进阶》正式发售 非常棒的 #Python#Flask 教程 https://github.com/helloflask/flask-tutorial 在线阅读

djangoproject

@djangoproject · Post #592 · 04/11/2018, 07:22 PM

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 · 05/10/2023, 09:54 PM

#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 #161 · 09/15/2016, 03:19 AM

http://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-i-hello-world inShare This is the first article in a series where I will be documenting my experience writing #web_applications in Python using the #Flask microframework.

djangoproject

@djangoproject · Post #162 · 09/15/2016, 03:22 AM

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 #134 · 09/01/2016, 02:54 PM

http://www.meetup.com/flask-nyc/ This is a group for anyone interested in #Flask, #Python, #web_development, and any related technologies. To stay up to date with group events, follow us on Twitter @FlaskNYC. Want to read up on Flask?

djangoproject

@djangoproject · Post #501 · 11/14/2017, 05:01 PM

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 · 05/31/2023, 11:52 AM

#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 · 12/28/2017, 12:20 PM

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 · 01/23/2026, 02:30 PM

#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

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