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Canal fuente @python_academy · Post #1518 · 12 nov

Автоматическое форматирование Python кода с помощью Black Сегодня мы расскажем вам о незаменимом инструменте для поддержания структуры и читаемости вашего Python кода - Black. Black - это автоматический форматтер кода, который помогает вам избавиться от несогласованных стилей и выравнивает ваш код согласно официальным рекомендациям PEP 8. Что такое Black? Black - это инструмент для автоматического форматирования Python кода, разработанный с учетом строгих принципов. Он призван обеспечить единообразие в структуре кода и упростить его чтение для всех участников проекта. Преимущества использования Black: - Единообразие: Black гарантирует, что ваш код будет соответствовать стандартам PEP 8, что делает его более читаемым и понятным. - Автоматизация:Black автоматически форматирует код, что позволяет избежать рутинных задач по выравниванию и форматированию. - Интеграция:Black легко интегрируется в ваш рабочий процесс с помощью популярных инструментов разработки, таких как VSCode, PyCharm и других. - Кастомизация: Вы можете настроить некоторые параметры Black, чтобы адаптировать его к вашим потребностям. Как использовать Black? Для начала, установите Black с помощью pip: pip install black Затем, вы можете использовать Black для форматирования вашего кода следующим образом: black your_python_file.py Black автоматически примет ваш код и приведет его к согласованному стилю. Вы также можете настроить некоторые аспекты форматирования, чтобы сделать его идеально подходящим для вашего проекта. #python#Black#форматирование#код#PEP8

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@githubtrending · Post #14907 · 03/07/2025, 13:30

#python#agents#generative_ai_tools#llamacpp#llm#onnx#openvino#parsing#retrieval_augmented_generation#small_specialized_models llmware is a powerful, easy-to-use platform that helps you build AI applications using small, specialized language models designed for business tasks like question-answering, summarization, and data extraction. It supports private, secure deployment on your own machines without needing expensive GPUs, making it cost-effective and safe for enterprise use. You can organize and search your documents, run smart queries, and combine knowledge with AI to get accurate answers quickly. It also offers many ready-to-use models and examples, plus tools for building chatbots and agents that automate complex workflows. This helps you save time, improve accuracy, and securely leverage AI for your business needs[1][3][5]. https://github.com/llmware-ai/llmware

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@githubtrending · Post #15362 · 23/12/2025, 15:30

#python#audio_generation#diffusion#image_generation#inference#model_serving#multimodal#pytorch#transformer#video_generation vLLM-Omni is a free, open-source tool that makes serving AI models for text, images, videos, and audio fast, easy, and cheap. It builds on vLLM for top speed using smart memory tricks, overlapping tasks, and flexible resource sharing across GPUs. You get 2x higher throughput, 35% less delay, and simple setup with Hugging Face models via OpenAI API—perfect for building quick multi-modal apps like chatbots or media generators without high costs. https://github.com/vllm-project/vllm-omni

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@githubtrending · Post #14845 · 20/06/2025, 11:30

#jupyter_notebook#ai#artificial_intelligence#chatgpt#deep_learning#from_scratch#gpt#language_model#large_language_models#llm#machine_learning#python#pytorch#transformer You can learn how to build your own large language model (LLM) like GPT from scratch with clear, step-by-step guidance, including coding, training, and fine-tuning, all explained with examples and diagrams. This approach mirrors how big models like ChatGPT are made but is designed to run on a regular laptop without special hardware. You also get access to code for loading pretrained models and fine-tuning them for tasks like text classification or instruction following. This helps you deeply understand how LLMs work inside and lets you create your own functional AI assistant, gaining practical skills in AI development[1][2][3][4]. https://github.com/rasbt/LLMs-from-scratch

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@githubtrending · Post #14684 · 08/05/2025, 12:00

#python#apple_silicon#audio_processing#mlx#multimodal#speech_recognition#speech_synthesis#speech_to_text#text_to_speech#transformers MLX-Audio is a powerful tool for converting text into speech and speech into new audio. It works well on Apple Silicon devices, like M-series chips, making it fast and efficient. You can choose from different languages and voices, and even adjust how fast the speech is. It also includes a web interface where you can see audio in 3D and play your own files. This tool is helpful for making audiobooks, interactive media, and personal projects because it's easy to use and provides high-quality audio quickly. https://github.com/Blaizzy/mlx-audio

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@githubtrending · Post #15288 · 10/11/2025, 15:00

#python#hackintosh#hackintosh_efi#lzhoang2601#lzhoang2801#macos#opencore#opencore_efi#opencoresimplify OpCore Simplify is a tool that makes it much easier to set up OpenCore EFI for Hackintosh systems by automatically creating the right configuration for your specific hardware. It checks your hardware, adds needed patches and drivers, and builds a ready-to-use EFI folder, saving you time and reducing mistakes. This means you can start installing macOS on your PC with a solid setup, even if you are new to Hackintosh. https://github.com/lzhoang2801/OpCore-Simplify

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@githubtrending · Post #14953 · 13/07/2025, 12:00

#python#documentation#gotchas#interview_questions#pitfalls#python#python_interview_questions#snippets#wats#wtf Python is a high-level, easy-to-read programming language widely used in many fields like web development, data science, and AI. The "What the f*ck Python?" project helps you understand tricky, surprising Python behaviors through clear examples and explanations. It reveals lesser-known features and common pitfalls, making it easier to write better code and debug problems. By exploring these examples, you can deepen your knowledge of Python’s internals, improve your coding skills, and avoid common mistakes, which benefits both beginners and experienced programmers alike[3]. https://github.com/satwikkansal/wtfpython

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@githubtrending · Post #14958 · 14/07/2025, 12:30

#python#agent#agentic_ai#grpo#kimi_ai#llms#lora#qwen#qwen3#reinforcement_learning#rl ART is a tool that helps you train smart agents for real-world tasks using reinforcement learning, especially with the GRPO method. The standout feature is RULER, which lets you skip the hard work of designing reward functions by using a large language model to automatically score how well your agent is doing—just describe your task, and RULER takes care of the rest. This makes building and improving agents much faster and easier, works for any task, and often performs as well as or better than hand-crafted rewards. You can install ART with a simple command and start training agents right away, even on your own computer or with cloud resources. https://github.com/OpenPipe/ART

GitHub Trends

@githubtrending · Post #14879 · 28/06/2025, 14:30

#cplusplus#cpp#hacktoberfest#iot#iot_device#iot_edge#microcontroller#microsoft_for_beginners#python#raspberry_pi#rpi You can learn the basics of the Internet of Things (IoT) through a free 12-week course with 24 lessons that guide you step-by-step in building real projects like plant monitoring, vehicle tracking, and smart cooking timers. Each lesson includes quizzes, instructions, challenges, and solutions to help you understand sensors, cloud connections, security, and AI on devices. The course uses real hardware or virtual options, making it easy to practice hands-on skills. This project-based learning helps you gain practical IoT knowledge useful for many industries, improving your tech skills and job readiness. https://github.com/microsoft/IoT-For-Beginners

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