RT Avi Chawla (@_avichawla)uv is incredibly fast.- Creating virtual envs. with uv is ~80x faster than python -m venv.- Package installation is 4-12x faster without caching, and ~100x with caching.Here's how to use uv for Python package management (with code): https://t.co/Gyz8T3ovn4 ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs. https://t.co/IEp7s3JaPtAvi Chawla (@_avichawla):uv is incredibly fast.- Creating virtual envs. with uv is ~80x faster than python -m venv.- Package installation is 4-12x faster without caching, and ~100x with caching.Here's how to use uv for Python package management (with code): https://t.co/Gyz8T3ovn4 ...

5️⃣ Reproduce an env.Finally, uv gives 100% reproducible installs.Say you cloned a project that used uv. You can run `uv sync` to precisely match the project.This works across OS, and even if the project you cloned used a different Python version. https://t.co/pXS9tX3oi8 ...

uv is incredibly fast.- Creating virtual envs. with uv is ~80x faster than python -m venv.- Package installation is 4-12x faster without caching, and ~100x with caching.Here's how to use uv for Python package management (with code): https://t.co/Gyz8T3ovn4 ...

Core Insights - The article discusses the introduction of "uv," a free and open-source tool developed by Astral, which significantly enhances the Python ecosystem by simplifying installation, package management, and virtual environment setup [3][4][6]. Group 1: Tool Overview - "uv" is described as a major breakthrough in the Python ecosystem over the past decade, built with Rust for speed and cross-platform compatibility [4][6][7]. - The installation process for "uv" is straightforward, requiring only a single command, and it does not interfere with existing Python installations [8][13]. Group 2: Project Management Features - "uv" utilizes virtual environments by default, allowing for isolation of different codebases and dependencies, which is crucial for managing Python projects [14]. - It automatically constructs the Python environment based on the "pyproject.toml" file, which specifies project dependencies and Python version requirements [14][15]. Group 3: Commands and Usability - Users can initialize a new project with "uv init," which creates essential files like "pyproject.toml" and "README.md" [16]. - The command "uv sync" installs a valid Python version and all dependencies into a new virtual environment, creating a "uv.lock" file for reproducibility [19][20]. Group 4: Dependency Management - Dependencies can be added easily using the command "uv add," which updates the "pyproject.toml" file automatically [25][27]. - "uv" allows for fixing specific Python versions for projects, ensuring consistency across different machines [28]. Group 5: Quick Tool Execution - The "uvx" command enables users to run tools quickly without setting up a virtual environment, making it convenient for one-off tasks [30][34]. - This feature is particularly useful for running tools like Ruff or starting Jupyter Lab without the overhead of environment activation [30][33]. Group 6: User Experience and Feedback - The article highlights positive user experiences, noting that "uv" simplifies Python environment management, especially in collaborative settings with multiple developers [35][36]. - Users express excitement about the speed and usability of "uv," comparing it favorably to existing tools like pyenv and poetry [38][40].

机器之心报道 编辑：Panda uv，我们也该报道一下它了。 这个用 Rust 写的 Python 包和项目管理工具近日在 Hacker News 上再次引发广泛关注。原因很简单，来自英国的天文学家和科学传播者 Emily L. Hunt 博士在自己的 博客上发布了一篇文章，称「uv 是近十年来 Python 生态系统发生的最好的事情」。 博客不长，但被分享到 Hacker News 后却引发了广泛共鸣和讨论，也收获了上千点赞（虽然很多讨论的焦点是 Rust）。 不过在看这篇博客之前，我们先简单了解一下 uv 这个项目本身。 简单来说，uv 是一个面向 Python 生态系统的高速「一体化」工具，可用于包管理、环境管理、项目初始化、工具执行、Python 版本管理等。其由 Astral（同样推 出了知名工具 Ruff）开发，底层使用 Rust 语言实现，以追求极致性能。对于已有的工作流、pip、virtualenv、pipx、poetry 等工具，uv 提供极强的兼容性并且在某 些场景下速度可提升 10–100 倍。 截至目前，该项目在 GitHub 已经收获了超 7.1 万 star！ 项目：https:/ ...

Core Feature Update - Python 3.14 allows disabling the Global Interpreter Lock (GIL) [1] - This enables true parallel execution of multi-threaded Python code, improving performance [1] Technology Adoption - uv fully supports the GIL disabling feature in Python 3.14 [1]

uv is incredibly fast!- Creating virtual envs. with uv is ~80x faster than python -m venv.- Package installation is 4–12x faster without caching, and ~100x with caching.Check a detailed guide to uv in the thread below: https://t.co/fhaBTZ1IEcAvi Chawla (@_avichawla):uv in Python, clearly explained (with code): ...