Удаление страниц PDF-файла
Библиотека PyMuPDF включает в себя довольно много сложных методов, которые упрощают удаление страниц из файла PDF. Он позволяет указать либо одну страницу (используя метод deletePage()), либо диапазон номеров страниц (используя метод deletePageRange()), либо список с номерами страниц (используя метод select()).
В следующем примере показано, как использовать список для выбора страниц, которые нужно сохранить в исходном документе. Имейте в виду, что страницы, которые не указаны, не будут частью выходного документа. В нашем случае выходной документ содержит только первую, вторую и четвертую страницы.
#python
#rich_text_format#lcd_display#python#serial_communication#smart_display#smart_screen#system_monitor#system_monitoring#turing_smart_screen#xuanfang
**turing-smart-screen-python** is free open-source Python software (3.9+) for small USB-C IPS smart screens like Turing 3.5"/5", XuanFang, and others on Windows, Linux, Raspberry Pi, or macOS. Use it as a standalone system monitor showing CPU/GPU usage, temps, memory, and custom data via easy themes (with editor and community shares), or integrate into your Python projects to display text, images, progress bars, brightness, rotation, and RGB LEDs. It auto-detects ports with a simple GUI wizard—no coding needed. You benefit by turning your screen into a customizable HW dashboard or app display affordably, cross-platform, without vendor limits.
https://github.com/mathoudebine/turing-smart-screen-python
#python#danbooru#deviantart#downloader#flickr#gallery#kemono#mangadex#pixiv#tumblr#twitter
gallery-dl is a free, easy-to-use command-line tool that lets you download image galleries and collections from many popular image hosting sites. It works on Windows, macOS, and Linux, and you can install it using pip, package managers like Homebrew or Chocolatey, or as a standalone executable. You can customize it with configuration files, use login credentials or browser cookies for private content, and even filter downloads by tags or chapters. This tool helps you quickly save large amounts of images or videos from websites, making it convenient to archive or organize media offline. It supports many sites and offers flexible options for advanced users.
https://github.com/mikf/gallery-dl
#python#agent#ai#aiagent#awesome#chatgpt#hacktoberfest#hacktoberfest2025#llm#long_short_term_memory#memori_ai#memory#memory_management#python#rag#state_management
Memori is an open-source memory engine that gives AI language models human-like memory using standard SQL databases like PostgreSQL, MySQL, or SQLite.[1][2] With just one line of code, you can enable any LLM to remember conversations, learn from interactions, and maintain context across sessions.[1] The key benefits are significant cost savings of 80-90% compared to expensive vector databases, complete data ownership and transparency since memories are stored in SQL databases you control, and zero vendor lock-in allowing you to export and move your data anywhere.[1][3] Memori works with popular frameworks like OpenAI, Anthropic, and LangChain, making it easy to integrate into existing projects without complex setup.[1]
https://github.com/GibsonAI/Memori
#python#agent#ai_agent#apple#computer_use#cua#lume#macos#manus#operator#swift#virtualization#virtualization_framework
The information provided doesn't directly relate to Discord bots or their benefits. However, if we consider the broader context of automation and AI tools like those mentioned in the text, these technologies can enhance user experiences by automating tasks and providing interactive features. For example, AI agents can control virtual environments, which might be useful in various applications, including gaming or educational settings. This kind of automation can save time and increase efficiency, similar to how Discord bots automate tasks and engage communities[1][2].
https://github.com/trycua/cua
#MongoDB#Excel#DataModeling#Aggregations#Java#Python#Csharp#Nodejs
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#html#data_science#education#machine_learning#machine_learning_algorithms#machinelearning#machinelearning_python#microsoft_for_beginners#ml#python#r#scikit_learn#scikit_learn_python
Microsoft’s "Machine Learning for Beginners" is a free, 12-week course with 26 lessons designed to teach classic machine learning using Python and Scikit-learn. It includes quizzes, projects, and assignments to help you learn by doing, with lessons themed around global cultures to keep it engaging. You can access solutions, videos, and even R language versions. The course is beginner-friendly, flexible, and helps build practical skills step-by-step, making it easier to understand and apply machine learning concepts in real-world scenarios. This structured approach boosts your learning retention and prepares you for further study or career growth in ML[1][5].
https://github.com/microsoft/ML-For-Beginners
#python#agent_computer_interface#ai_agents#computer_automation#computer_use#grounding#gui_agents#in_context_reinforcement_learning#memory#mllm#planning#retrieval_augmented_generation
Agent S2 is a smart AI assistant that handles computer tasks by breaking them into smaller steps and using specialized tools for each part, making it highly adaptable and efficient across different systems like Windows and Android. It outperforms other AI tools in completing complex tasks, learns from experience, and adjusts plans as needed, helping users automate digital work more reliably and effectively.
https://github.com/simular-ai/Agent-S
#python#agent#agentic_rag#ai_agents#clawbot#context_database#context_engineering#filesystem#llm#memory#openclaw#opencode#rag#skill
OpenViking is a free open-source tool that acts as a context database for AI agents, using a simple file system to organize memories, resources, and skills under viking:// paths. It fixes issues like scattered data, high token costs, weak searches, and untraceable errors with tiered loading (L0 abstracts, L1 overviews, L2 details loaded on demand), recursive directory retrieval, visual traces, and auto-session memory updates. You benefit by building smarter, cheaper agents faster—like managing files—saving up to 96% on tokens while boosting task success by 50%+.
https://github.com/volcengine/OpenViking
#python#download_music#hacktoberfest#mp3#music#playlists#python#song#song_lyrics#spotdl#spotdl_cli#spotify#youtube_music
spotDL is a fast, easy tool that downloads songs from Spotify playlists by finding them on YouTube, including album art, lyrics, and metadata. You install it via Python’s pip and need FFmpeg for audio processing. It works mainly through the command line and supports batch downloads, syncing playlists, and updating metadata. Audio quality is up to 128 kbps for free users and 256 kbps for YouTube Music Premium users. This tool helps you get your Spotify music offline with metadata, but the quality depends on YouTube sources. It’s great if you want a free, quick way to save Spotify songs with details included.
https://github.com/spotDL/spotify-downloader
#python#3d#3d_aigc#3d_generation#diffusion_models#hunyuan3d#image_to_3d#shape#shape_generation#text_to_3d#texture_generation
Hunyuan3D 2.0 is a powerful tool that creates detailed 3D models with textures in two steps: first building the shape, then adding colors and materials. It works efficiently on standard computers (as low as 5GB VRAM for basic models) and offers multiple ways to use it, like coding, Blender plugins, or online demos, making it accessible for creating game-ready 3D assets, VR/AR content, or custom designs without needing advanced hardware.
https://github.com/Tencent/Hunyuan3D-2
#python#agent#agentic_ai#agentic_framework#agentic_workflow#ai#ai_agents#ai_companion#ai_roleplay#benchmark#framework#llm#mcp#memory#open_source#python#sandbox
MemU lets AI systems take in conversations, documents, and media, turn them into structured memories, and store them in a clear three-layer file system. It offers both fast embedding search and deeper LLM-based retrieval, works with many data types, and supports cloud or self-hosted setups with simple APIs. This helps you build AI agents that truly remember past interactions, retrieve the right context when needed, and improve over time, making your applications more accurate, personal, and efficient.
https://github.com/NevaMind-AI/memU
#engineering#machinelearning#cloud#datascience#python#engineer#aws#mathematics#google
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