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Canal fuente @python_academy · Post #2172 · 16 sept

Типизация в Python с использованием модуля typing В Python модуль typing предоставляет возможность добавлять подсказки типов для переменных, функций и классов, что делает код более явным и понятным. Зачем использовать типизацию? 1. Ясность и понятность кода: Добавление аннотаций типов помогает читателям быстро понять, какие данные ожидаются и какие типы переменных возвращаются из функций. 2. Предотвращение ошибок: Статические анализаторы кода, такие как mypy, могут обнаруживать потенциальные ошибки до выполнения программы, что уменьшает количество багов. 3. Документация кода: Подсказки типов могут служить формой документации, особенно полезной при совместной разработке. Разработчики могут быстро понимать интерфейсы функций и классов. Пример использования типизации для переменных и функций: from typing import List, Tuple def multiply(a: int, b: int) -> int: return a * b def process_list(data: List[int]) -> Tuple[int, int]: sum_values = sum(data) average = sum_values / len(data) return sum_values, average # Пример использования result1 = multiply(5, 3)# Ожидается int data_list = [1, 2, 3, 4, 5] result2 = process_list(data_list)# Ожидается Tuple[int, int] Здесь a: int и b: int указывают на типы аргументов функции, а -> int и -> Tuple[int, int] - на типы возвращаемых значений. Это помогает читателям кода лучше понимать ожидаемую структуру данных и типы переменных. Типизация делает ваш код более структурированным, улучшает его читабельность и может служить документацией, облегчая разработку. #python#typing

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@repo_science · Post #3250 · 31/05/2023, 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 -----

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@githubtrending · Post #14786 · 04/06/2025, 12:00

#python#crawler#crawling#framework#hacktoberfest#python#scraping#web_scraping#web_scraping_python Scrapy is a powerful tool for extracting data from websites. It works on many platforms and requires Python 3.9 or higher. Scrapy is free, stable, and can handle complex tasks efficiently. It allows you to manage multiple requests at once, making it fast and efficient for large-scale data extraction. Scrapy also supports various formats for storing data and has features like auto-throttling to prevent overwhelming websites. This makes it a great choice for users who need to collect data from many websites quickly and reliably. https://github.com/scrapy/scrapy

GitHub Trends

@githubtrending · Post #15009 · 31/07/2025, 11:30

#python#adb#airtest#cv#fate_grand_order#fgo#qt6 This program automates playing Fate/Grand Order on Android in multiple languages (Chinese, Japanese, English, Taiwanese). It can run on Windows, Linux, Mac, Android, and Docker, requiring minimal setup. It smartly controls battles by choosing skills, cards, and support servants without needing manual input or special equipment. It also automates weekly missions, friend support selection, and item management, saving you time and effort. You can run it on your phone or PC, even using tools like AidLux or AzurLaneAutoScript. It helps you farm efficiently without worrying about complicated setups or "best" cards, making the game easier and less time-consuming[5]. https://github.com/hgjazhgj/FGO-py

GitHub Trends

@githubtrending · Post #14927 · 08/07/2025, 12:00

#python#agent#alibaba#artificial_intelligence#information_seeking#llm#multi_agent#rag#web_agent You can use advanced AI models like WebSailor and WebDancer from Alibaba's Tongyi Lab to perform complex web tasks such as searching, browsing, and answering questions automatically. These models are trained to think deeply and handle difficult information-seeking tasks that were hard before. WebSailor excels in reasoning and can solve very challenging problems, while WebDancer learns to search and reason on its own through a special training process. Using these tools helps you get accurate, multi-step answers from the web quickly and efficiently, saving you time and effort in research or information gathering. They are open-source and come with demos to try out easily[3]. https://github.com/Alibaba-NLP/WebAgent

GitHub Trends

@githubtrending · Post #15194 · 03/10/2025, 12:30

#python#agent_framework#agentic_ai#agents#ai#dotnet#multi_agent#orchestration#python#sdk#workflows Microsoft Agent Framework is an open-source toolkit that helps you build and manage AI agents and multi-agent workflows using Python or .NET. It combines the best features of previous Microsoft AI projects to let you create simple chatbots or complex workflows where multiple agents work together. It supports many AI models, connects easily to external tools and APIs, and runs anywhere—on cloud or on-premises. The framework also includes features like human review, workflow checkpointing, and monitoring to make your AI applications reliable and adaptable. This means you can build powerful, flexible AI solutions faster and with less code. https://github.com/microsoft/agent-framework

GitHub Trends

@githubtrending · Post #15419 · 17/01/2026, 09:30

#python#agent#ai#aippt#editable_pptx#langgraph#paper2slides#ppt_generator Paper2Any turns paper PDFs, images, or text into editable diagrams, technical roadmaps, experiment plots, PPT slides, and more with one click. Key tools include Paper2Figure for scientific visuals, Paper2PPT for custom decks with table extraction, PDF2PPT for layout-perfect conversions, and AI beautification. Install via GitHub on Python 3.11+, Linux preferred; try online demo or scripts. You save hours recreating figures or slides for research, talks, or reports, getting pro-quality, customizable outputs fast. https://github.com/OpenDCAI/Paper2Any

GitHub Trends

@githubtrending · Post #15617 · 15/04/2026, 12:30

#python#ai#deep_learning#filetype#keras_classification_models#keras_models#mime_types#onnx Magika is a fast AI tool from Google that detects file types with ~99% accuracy across 200+ formats, using a tiny model that works in milliseconds on one CPU. Install easily via pip, brew, or scripts for CLI/Python/JS/Go use; scan files, directories, or streams with options like JSON output or recursion. It boosts your safety by routing files to scanners, like in Gmail/Drive, helping spot threats quickly without size limits. https://github.com/google/magika

GitHub Trends

@githubtrending · Post #14688 · 09/05/2025, 12:00

#python#diffusion_models#dit#image_to_video#image_to_video_generation#text_to_video#text_to_video_generation LTX-Video is a powerful AI model that creates high-quality, realistic videos in real time, running faster than you can watch them. It can generate videos from text descriptions, images, or existing videos, and supports advanced features like keyframe animation and video extension. You can use it online or run it locally with easy setup. It offers great control over video details, smooth motion, and works well even on consumer hardware. This helps you quickly create custom videos for storytelling, social media, or prototyping, saving time and boosting creativity with detailed, lifelike results[2][4][5]. https://github.com/Lightricks/LTX-Video

GitHub Trends

@githubtrending · Post #15360 · 23/12/2025, 14:30

#python#docker#fastapi#kbqa#kgqa#llms#neo4j#rag#vue Yuxi-Know (语析) is a free, open-source platform built with LangGraph, Vue.js, FastAPI, and LightRAG to create smart agents using RAG knowledge bases and knowledge graphs. The latest v0.4.0-beta (Dec 2025) adds file uploads, multimodal image support, mind maps from files, evaluation tools, dark mode, and better graph visuals. It helps you quickly build and deploy custom AI agents for Q&A, analysis, and searches without starting from scratch, saving time and effort on development. https://github.com/xerrors/Yuxi-Know

GitHub Trends

@githubtrending · Post #15326 · 11/12/2025, 11:30

#python#agents#gcp#gemini#genai_agents#generative_ai#llmops#mlops#observability You can quickly create and deploy AI agents using the Agent Starter Pack, a Python package with ready-made templates and full infrastructure on Google Cloud. It handles everything except your agent’s logic, including deployment, monitoring, security, and CI/CD pipelines. You can start a project in just one minute, customize agents for tasks like document search or real-time chat, and extend them as needed. This saves you time and effort by providing production-ready tools and integration with Google Cloud services, letting you focus on building smart AI agents without worrying about backend setup or deployment details. https://github.com/GoogleCloudPlatform/agent-starter-pack

GitHub Trends

@githubtrending · Post #15330 · 14/12/2025, 11:30

#python#dictionary_attack#password#password_strength#weak_passwords#wordlist#wordlist_generator **CUPP** is a free Python 3 tool that creates custom password wordlists from personal details like names, birthdays, pet names, or nicknames, using interactive questions or existing dictionaries. Run it with options like `-i` for profiling or `-l` to download huge wordlists. This helps you in legal penetration tests or investigations by generating targeted lists for efficient brute-force or dictionary attacks, cracking weak passwords faster than generic ones. https://github.com/Mebus/cupp

GitHub Trends

@githubtrending · Post #15385 · 02/01/2026, 12:30

#python#deep_learning#inference#openai#quantization#speech_recognition#speech_to_text#transformer#whisper Faster-Whisper is a fast version of OpenAI's Whisper that transcribes audio up to 4x quicker with the same accuracy, using less memory on CPU or GPU—benchmarks show it beats original Whisper (e.g., 1m03s vs 2m23s for 13-min audio on GPU). Install via `pip install faster-whisper`, no FFmpeg needed, and use simple Python code like `WhisperModel("large-v3").transcribe("audio.mp3")` for segments with timestamps. You benefit by getting quick, efficient speech-to-text for real-time apps, saving time and resources on long files or batches. https://github.com/SYSTRAN/faster-whisper

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