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Изворен канал @pythonotes · Post #76 · 27 апр.

Ранее я делал серию постов про битовые операторы. Вот вам ещё один наглядный пример как это используется в Python в модуле re. Чтобы указать флаг для компилятора нам надо указать его после передаваемой строки. Например, добавляем флаг для игнорирования переноса строки. pattern = re.compile(r"(\w+)+") words = pattern.search(text, re.DOTALL) А как указать несколько флагов? Ведь явно будут ситуации когда нам потребуется больше одного. Кто читал посты по битовые операторы уже понял как. pattern.search(text, re.DOTALL | re.VERBOSE) А теперь смотрим исходники, что находится в этих атрибутах? Не удивительно, степени двойки. Почему? Потому что каждое следующее значение это сдвиг единицы влево. >>> for n in [1, 2, 4, 8, 16, 32, 64, 128, 256]: >>> print(bin(n)) 0b1 0b10 0b100 0b1000 0b10000 0b100000 0b1000000 0b10000000 0b100000000 Чтобы было понятней, давайте напишем тоже самое но иначе, добавим ведущие нули: 000000001 000000010 000000100 000001000 000010000 000100000 001000000 010000000 100000000 Не понятно что тут происходит? Читай три поста про битовые операторы начиная с этого ➡️https://t.me/pythonotes/45 В общем, это пример применения побитовых операций в самом Python. Теперь вы знаете Python еще немного лучше) #tricks#regex#libs

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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

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