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Canal fuente @python_academy · Post #1529 · 21 nov
Исследование структуры кода с помощью модуля ast При работе с кодом на Python, иногда возникает необходимость анализа его структуры. Для этого идеально подходит модуль ast (Abstract Syntax Trees), который предоставляет мощные инструменты для работы с абстрактными синтаксическими деревьями. Что такое ast? ast - это модуль Python, который позволяет разбирать и анализировать исходный код на Python, представляя его в виде абстрактного синтаксического дерева (AST). AST представляет собой структурированное представление кода, которое легко интерпретировать и анализировать. Пример использования модуля ast: import ast code = "print('Hello, ast!')" tree = ast.parse(code) print(ast.dump(tree)) В данном примере мы использовали функцию ast.parse для разбора строки кода с помощью модуля ast. Функция ast.dump выводит структуру AST в удобочитаемом формате. Анализ структуры кода: import ast code = """ def greet(name): print(f'Hello, {name}!') """ tree = ast.parse(code) for node in ast.walk(tree): if isinstance(node, ast.FunctionDef): print(f"Найдена функция: {node.name}") elif isinstance(node, ast.Print): print("Обнаружен оператор печати") В данном примере мы использовали модуль ast для анализа структуры кода. Функция ast.walk позволяет обойти все узлы AST, а затем мы проверяем их типы для выделения определенных элементов, таких как функции или операторы. Модуль ast также предоставляет возможности для более сложных операций, таких как изменение кода, создание новых выражений и многое другое. #python#ast#анализкода
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@cryptoprofitcoach · Post #9012 · 05/05/2024, 17:13
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@githubtrending · Post #15623 · 16/04/2026, 12:00
#python DFlash is a lightweight block diffusion model that speeds up large language models like Qwen3.5 and Llama through speculative decoding, generating draft tokens in parallel for over 6x faster inference with no quality loss—up to 2.5x better than top methods. It supports easy integration with vLLM, SGLang, Transformers, or MLX via simple installs and commands, with ready models on Hugging Face. You benefit by running quicker AI generation on your hardware, boosting throughput to ~430 tokens/second and GPU use over 90% for efficient tasks like math or coding. https://github.com/z-lab/dflash
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@githubtrending · Post #15606 · 06/04/2026, 12:30
#python PersonaPlex is a real-time speech model for natural, low-latency conversations. Control its voice with audio prompts and role via simple text—like a friendly teacher, customer service rep, or casual chat partner—with natural male/female voices. Install easily, launch a web demo server, and test offline. You benefit by creating personalized AI interactions for apps, role-play, or fun talks, with quick setup and low GPU needs via CPU offload. https://github.com/NVIDIA/personaplex
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@githubtrending · Post #15590 · 27/03/2026, 11:30
#python AI Scientist-v2 is an autonomous AI system that generates research ideas, runs experiments, analyzes data, and writes full scientific papers using agentic tree search—no human templates needed. It produced the first entirely AI-written paper accepted via peer review at an ICLR workshop. You benefit by quickly exploring ML topics, automating discovery to save time and costs (about $20 per run on Linux with GPU), and scaling your research productivity for faster breakthroughs. Install via conda, set API keys, ideate with a Markdown file, then launch experiments. Run in a safe sandbox due to code risks. https://github.com/SakanaAI/AI-Scientist-v2
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@githubtrending · Post #15560 · 14/03/2026, 12:00
#python Dimensional OS (DimOS) is a simple Python-based operating system for robots like quadrupeds, humanoids, drones, and arms from Unitree, Xarm, and more—no ROS needed. Install easily with one command, run simulations or real hardware, and use natural language like "explore the room" for agent control with navigation, perception, spatial memory, and multi-agent systems. You benefit by quickly building and testing advanced robot apps locally, saving time and enabling seamless hardware integration without complex setups. https://github.com/dimensionalOS/dimos
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@githubtrending · Post #15555 · 12/03/2026, 12:00
#python OpenRAG is an intelligent document search platform that combines three powerful open-source tools—Docling, OpenSearch, and Langflow—to transform your documents into an AI-powered knowledge system. You upload files of any format (PDFs, Word documents, images, audio), and the system intelligently parses and indexes them for semantic search. Then you chat with your documents through a simple interface, getting accurate answers backed by relevant sources. The benefit is that you get enterprise-grade document retrieval and AI conversations ready to use immediately, without building complex systems from scratch, while maintaining full control over how documents are processed and searched. https://github.com/langflow-ai/openrag
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@githubtrending · Post #15544 · 06/03/2026, 12:30
#python Webnovel Writer is a free Claude Code plugin for creating long web novels. It reduces AI forgetting and errors with smart RAG tools, letting you init projects (/webnovel-init), plan plots (/webnovel-plan), write chapters (/webnovel-write), review (1-5), and view dashboards. Install via marketplace, add Python deps, set API keys, and use commands easily. Benefits: Saves time on consistent long stories, boosts creativity for serials, and tracks progress without manual fixes—perfect for steady novel output. https://github.com/lingfengQAQ/webnovel-writer
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@githubtrending · Post #15540 · 05/03/2026, 12:00
#python SEO Machine is a Claude Code tool for businesses to easily create long SEO blog posts. Use commands like /research for keyword and competitor analysis, /write for 2000+ word optimized articles in your brand voice, /rewrite to update old content, and /optimize for final SEO scores (0-100). It integrates Google Analytics, Search Console, and DataForSEO for real data, plus agents for meta tags, links, and readability. Customize with your brand files for perfect fit. You save hours on research/writing, get higher Google rankings, more traffic, and content that converts readers to customers. https://github.com/TheCraigHewitt/seomachine
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@githubtrending · Post #15529 · 28/02/2026, 12:30
#python Hermes Agent is a free, open-source AI that installs on your server, learns your projects and preferences over time, and handles tasks via Telegram, Discord, Slack, WhatsApp, or terminal. It builds reusable skills from solved problems, runs scheduled automations like daily reports, and uses secure sandboxes (Docker/SSH) for safe code execution with any AI model. You benefit by getting a smart, growing assistant that automates work, remembers everything, and stays reachable anywhere—saving hours on repetitive tasks while boosting productivity. https://github.com/NousResearch/hermes-agent
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@githubtrending · Post #15519 · 24/02/2026, 12:00
#python PersonaLive creates real-time portrait animations from a single image, using driving videos for expressive faces and head moves. It runs on a 12GB GPU for infinite-length videos, with easy web UI for live streaming or offline generation, plus ComfyUI and TensorRT speed boosts. You get smooth, high-quality animations fast for streams, content, or art—up to 22x quicker than others, saving time and hardware costs. https://github.com/GVCLab/PersonaLive
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@githubtrending · Post #15517 · 23/02/2026, 12:00
#python Agent Skills for Context Engineering offers free, open skills to master context engineering—curating AI model inputs like prompts, tools, history, and docs for top performance despite limited attention. Learn fundamentals, architectures (multi-agent, memory), tools, evaluation, and new skills like hosted agents and BDI mental states via Claude Code plugins or any platform. Examples include digital brain OS and book-writing pipelines. You gain reliable AI agents that cut errors, boost speed (up to 55% faster tasks), reduce costs, and deliver accurate results for projects. https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering
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@githubtrending · Post #15512 · 20/02/2026, 14:00
#python Hugging Face Skills are ready-to-use folders with instructions, scripts, and tools for AI agents to handle tasks like creating datasets, training models, running evaluations, managing jobs, and publishing papers. They work seamlessly with tools like Claude Code, OpenAI Codex, Gemini CLI, and Cursor—just install via simple commands and mention the skill in your instructions, such as "Use the HF model trainer skill." This saves you time by automating complex Hugging Face Hub operations, letting your agent execute them accurately without manual coding. https://github.com/huggingface/skills
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