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    <title>Anaconda repository updates</title>
    <link>http://repo.continuum.io/pkgs/</link>
    <description>Recent updates to the conda default repository</description>
    <language>en</language>
    <copyright>Copyright 2026, Anaconda, Inc.</copyright>
    <pubDate>Tue, 06 Oct 2026 19:00:33 GMT</pubDate>
    <item>
      <title>pyclipper 1.4.0 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64]</title>
      <description>&quot;Pyclipper is a Cython wrapper exposing public functions and classes of the C++  translation of the Angus Johnson’s Clipper library (ver. 6.4.2).&quot;</description>
      <link>https://github.com/fonttools/pyclipper#readme</link>
      <comments>https://github.com/fonttools/pyclipper</comments>
      <guid>https://pypi.org/packages/source/p/pyclipper/pyclipper-1.4.0.tar.gz</guid>
      <pubDate>Tue, 06 Oct 2026 12:36:29 GMT</pubDate>
      <source>https://github.com/fonttools/pyclipper</source>
    </item>
    <item>
      <title>langgraph-sdk 0.4.5 [linux-64, linux-aarch64, osx-arm64, win-64]</title>
      <description>This repository contains the Python SDK for interacting with the LangGraph Platform REST API.</description>
      <link>https://github.com/langchain-ai/langgraph/blob/main/libs/sdk-py/README.md</link>
      <comments>https://github.com/langchain-ai/langgraph/tree/main/libs/sdk-py</comments>
      <pubDate>Tue, 06 Oct 2026 11:23:00 GMT</pubDate>
      <source>https://www.github.com/langchain-ai/langgraph</source>
    </item>
    <item>
      <title>pyproj 3.8.0 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64]</title>
      <description>Python interface to PROJ (cartographic projections and coordinate transformations library).</description>
      <link>https://pyproj4.github.io/pyproj/stable</link>
      <comments>https://github.com/pyproj4/pyproj</comments>
      <guid>https://pypi.org/packages/source/p/pyproj/pyproj-3.8.0.tar.gz</guid>
      <pubDate>Tue, 06 Oct 2026 10:42:52 GMT</pubDate>
      <source>https://github.com/pyproj4/pyproj</source>
    </item>
    <item>
      <title>wayland-protocols 1.49 [linux-64, linux-aarch64]</title>
      <description>wayland-protocols contains Wayland protocols that add functionality not available in the Wayland core protocol. Such protocols either add completely new functionality, or extend the functionality of some other protocol either in Wayland core, or some other protocol in wayland-protocols.  A protocol in wayland-protocols consists of a directory containing a set of XML files containing the protocol specification, and a README file containing detailed state and a list of maintainers.</description>
      <link>https://gitlab.freedesktop.org/wayland/wayland-protocols</link>
      <comments>https://gitlab.freedesktop.org/wayland/wayland-protocols</comments>
      <guid>https://gitlab.freedesktop.org/wayland/wayland-protocols/-/archive/1.49/wayland-protocols-1.49.tar.bz2</guid>
      <pubDate>Tue, 06 Oct 2026 10:23:19 GMT</pubDate>
      <source>https://gitlab.freedesktop.org/wayland/wayland-protocols</source>
    </item>
    <item>
      <title>rattler-build 0.76.1 [linux-64, linux-aarch64, osx-arm64, win-64]</title>
      <description>The rattler-build tooling and library creates cross-platform relocatable binaries / packages from a simple recipe format. The recipe format is heavily inspired by conda-build and boa, and the output of a regular rattler-build run is a package that can be installed using mamba, conda or rattler.</description>
      <link>https://rattler.build</link>
      <comments>https://github.com/prefix-dev/rattler-build</comments>
      <guid>https://github.com/prefix-dev/rattler-build/archive/refs/tags/v0.76.1.tar.gz</guid>
      <pubDate>Tue, 06 Oct 2026 09:47:42 GMT</pubDate>
      <source>https://github.com/prefix-dev/rattler-build</source>
    </item>
    <item>
      <title>spopt 0.8.0 [linux-64, linux-aarch64, osx-arm64, win-64]</title>
      <description>Spopt is an open-source Python library for solving optimization problems with spatial data. Originating from the `region` module in [PySAL](http://pysal.org) (Python Spatial Analysis Library), it is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions.</description>
      <link>https://pysal.org/spopt</link>
      <comments>https://github.com/pysal/spopt</comments>
      <guid>https://pypi.org/packages/source/s/spopt/spopt-0.8.0.tar.gz</guid>
      <pubDate>Tue, 06 Oct 2026 09:16:51 GMT</pubDate>
      <source>https://pysal.org/spopt</source>
    </item>
    <item>
      <title>uvloop 0.23.0 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64]</title>
      <description>uvloop is a fast, drop-in replacement of the built-in asyncio event loop. uvloop is implemented in Cython and uses libuv under the hood.</description>
      <link>https://uvloop.readthedocs.io</link>
      <comments>https://github.com/MagicStack/uvloop</comments>
      <guid>https://pypi.org/packages/source/u/uvloop/uvloop-0.23.0.tar.gz</guid>
      <pubDate>Tue, 06 Oct 2026 09:15:56 GMT</pubDate>
      <source>https://github.com/MagicStack/uvloop</source>
    </item>
    <item>
      <title>crcmod 1.7 [linux-64, linux-aarch64, osx-arm64, win-64]</title>
      <description>Python module for generating objects that compute the Cyclic Redundancy Check (CRC)</description>
      <link>https://crcmod.sourceforge.net/</link>
      <comments>https://sourceforge.net/projects/crcmod/</comments>
      <guid>https://pypi.io/packages/source/c/crcmod/crcmod-1.7.tar.gz</guid>
      <pubDate>Tue, 06 Oct 2026 09:13:53 GMT</pubDate>
      <source>https://crcmod.sourceforge.net/</source>
    </item>
    <item>
      <title>nbgrader 0.9.6 [linux-64, linux-aarch64, osx-64, osx-arm64, win-64]</title>
      <description>nbgrader is a tool that facilitates creating and grading assignments in the Jupyter notebook. It allows instructors to easily create notebook-based assignments that include both coding exercises and written free-responses. nbgrader then also provides a streamlined interface for quickly grading completed assignments.</description>
      <link>https://nbgrader.readthedocs.io</link>
      <comments>https://github.com/jupyter/nbgrader</comments>
      <guid>https://pypi.io/packages/source/n/nbgrader/nbgrader-0.9.6.tar.gz</guid>
      <pubDate>Tue, 06 Oct 2026 07:52:01 GMT</pubDate>
      <source>https://github.com/jupyter/nbgrader</source>
    </item>
    <item>
      <title>onnxruntime-cpp 1.30.0 [linux-64, linux-aarch64, osx-arm64, win-64]</title>
      <description>ONNX Runtime is a cross-platform machine-learning model accelerator, with a flexible interface to integrate hardware-specific libraries. ONNX Runtime can be used with models from PyTorch, Tensorflow/Keras, TFLite, scikit-learn, and other frameworks.</description>
      <link>https://onnxruntime.ai/docs</link>
      <comments>https://github.com/microsoft/onnxruntime</comments>
      <guid>https://github.com/microsoft/onnxruntime/archive/refs/tags/v1.30.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 22:35:52 GMT</pubDate>
      <source>https://onnxruntime.ai</source>
    </item>
    <item>
      <title>onnxruntime-novec-cpp 1.30.0 [linux-64, linux-aarch64, osx-arm64, win-64]</title>
      <description>ONNX Runtime is a cross-platform machine-learning model accelerator, with a flexible interface to integrate hardware-specific libraries. ONNX Runtime can be used with models from PyTorch, Tensorflow/Keras, TFLite, scikit-learn, and other frameworks.</description>
      <link>https://onnxruntime.ai/docs</link>
      <comments>https://github.com/microsoft/onnxruntime</comments>
      <guid>https://github.com/microsoft/onnxruntime/archive/refs/tags/v1.30.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 22:34:19 GMT</pubDate>
      <source>https://onnxruntime.ai</source>
    </item>
    <item>
      <title>onnxruntime 1.30.0 [linux-64, linux-aarch64, osx-64, osx-arm64, win-64]</title>
      <description>ONNX Runtime is a cross-platform machine-learning model accelerator, with a flexible interface to integrate hardware-specific libraries. ONNX Runtime can be used with models from PyTorch, Tensorflow/Keras, TFLite, scikit-learn, and other frameworks.</description>
      <link>https://onnxruntime.ai/docs</link>
      <comments>https://github.com/microsoft/onnxruntime</comments>
      <guid>https://github.com/microsoft/onnxruntime/archive/refs/tags/v1.30.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 22:29:47 GMT</pubDate>
      <source>https://onnxruntime.ai</source>
    </item>
    <item>
      <title>onnxruntime-novec 1.30.0 [linux-64, linux-aarch64, osx-64, osx-arm64, win-64]</title>
      <description>ONNX Runtime is a cross-platform machine-learning model accelerator, with a flexible interface to integrate hardware-specific libraries. ONNX Runtime can be used with models from PyTorch, Tensorflow/Keras, TFLite, scikit-learn, and other frameworks.</description>
      <link>https://onnxruntime.ai/docs</link>
      <comments>https://github.com/microsoft/onnxruntime</comments>
      <guid>https://github.com/microsoft/onnxruntime/archive/refs/tags/v1.30.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 22:29:39 GMT</pubDate>
      <source>https://onnxruntime.ai</source>
    </item>
    <item>
      <title>huggingface_hub 1.33.0 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, noarch, osx-64, osx-arm64, win-64]</title>
      <description>The huggingface_hub is a client library to interact with the Hugging Face Hub. The Hugging Face Hub is a platform with over 35K models, 4K datasets, and 2K demos in which people can easily collaborate in their ML workflows. The Hub works as a central place where anyone can share, explore, discover, and experiment with open-source Machine Learning.  With huggingface_hub, you can easily download and upload models, datasets, and Spaces. You can extract useful information from the Hub, and do much more. Some example use cases:  - Downloading and caching files from a Hub repository. - Creating repositories and uploading an updated model every few epochs. - Extract metadata from all models that match certain criteria (e.g. models for text-classification). - List all files from a specific repository.</description>
      <link>https://huggingface.co/docs/huggingface_hub/index</link>
      <comments>https://github.com/huggingface/huggingface_hub</comments>
      <guid>https://pypi.org/packages/source/h/huggingface_hub/huggingface_hub-1.33.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 21:00:10 GMT</pubDate>
      <source>https://github.com/huggingface/huggingface_hub</source>
    </item>
    <item>
      <title>sphinx-book-theme 1.4.0 [linux-64, linux-aarch64, osx-arm64, win-64]</title>
      <description>A clean book theme for scientific explanations and documentation with Sphinx. This theme is based on pydata-sphinx-theme and provides a clean, modern look for documentation websites with features like collapsible sidebars, interactive elements, and support for Jupyter notebooks.</description>
      <link>https://sphinx-book-theme.readthedocs.io</link>
      <comments>https://github.com/executablebooks/sphinx-book-theme</comments>
      <guid>https://github.com/executablebooks/sphinx-book-theme/archive/refs/tags/v1.4.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 18:46:43 GMT</pubDate>
      <source>https://sphinx-book-theme.readthedocs.io</source>
    </item>
    <item>
      <title>numba 0.68.0 [linux-32, linux-64, linux-aarch64, linux-ppc64le, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Numba is an Open Source NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the remarkable LLVM compiler infrastructure to compile Python syntax to machine code.&quot;</description>
      <link>https://numba.readthedocs.io</link>
      <comments>https://github.com/numba/numba</comments>
      <guid>https://pypi.org/packages/source/n/numba/numba-0.68.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 17:16:22 GMT</pubDate>
      <source>https://numba.pydata.org</source>
    </item>
    <item>
      <title>wasmtime-py 49.0.0 [linux-64, linux-aarch64, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>The wasmtime-py package has initial support for running WebAssembly components in Python with high-level bindings.</description>
      <link>https://docs.wasmtime.dev/lang-python.html</link>
      <comments>https://github.com/bytecodealliance/wasmtime-py</comments>
      <guid>https://github.com/bytecodealliance/wasmtime-py/archive/refs/tags/49.0.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 16:39:42 GMT</pubDate>
      <source>https://github.com/bytecodealliance/wasmtime-py</source>
    </item>
    <item>
      <title>llvmlite 0.50.0 [linux-32, linux-64, linux-aarch64, linux-ppc64le, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>llvmlite provides a Python binding to LLVM for use in Numba. Numba previously relied on llvmpy.</description>
      <link>https://llvmlite.readthedocs.io</link>
      <comments>https://github.com/numba/llvmlite</comments>
      <guid>https://pypi.org/packages/source/l/llvmlite/llvmlite-0.50.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 14:26:37 GMT</pubDate>
      <source>https://llvmlite.readthedocs.io</source>
    </item>
    <item>
      <title>enkryptai-sdk 1.0.44 [linux-64, linux-aarch64, osx-arm64, win-64]</title>
      <description>enkryptai-sdk is the official Python client SDK for the Enkrypt AI platform. It provides guardrails (detect and block harmful or non-compliant model inputs/outputs), red teaming of LLM endpoints, AI proxying, and compliance scanning, talking to the hosted Enkrypt AI API. MIT covers the client SDK code only; using the platform itself requires an Enkrypt AI account.</description>
      <link>https://docs.enkryptai.com/</link>
      <comments>https://github.com/enkryptai/enkryptai-sdk</comments>
      <guid>https://pypi.org/packages/source/e/enkryptai_sdk/enkryptai_sdk-1.0.44.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 14:17:57 GMT</pubDate>
      <source>https://github.com/enkryptai/enkryptai-sdk</source>
    </item>
    <item>
      <title>python-discovery 1.6.1 [linux-64, linux-aarch64, noarch, osx-arm64, win-64]</title>
      <description>Python interpreter discovery locates Python interpreters installed on a system from various sources such as system packages, pyenv, mise, asdf, uv, or the Windows registry.</description>
      <link>https://python-discovery.readthedocs.io</link>
      <comments>https://github.com/tox-dev/python-discovery</comments>
      <guid>https://pypi.org/packages/source/p/python-discovery/python_discovery-1.6.1.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 13:39:21 GMT</pubDate>
      <source>https://github.com/tox-dev/python-discovery</source>
    </item>
    <item>
      <title>conda-build 26.9.1 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Conda-build contains commands and tools to allow you to build your own packages for conda.</description>
      <link>https://docs.conda.io/projects/conda-build/en/latest/</link>
      <comments>https://github.com/conda/conda-build</comments>
      <guid>https://github.com/conda/conda-build/releases/download/26.9.1/conda-build-26.9.1.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 13:24:17 GMT</pubDate>
      <source>https://github.com/conda/conda-build</source>
    </item>
    <item>
      <title>mlx-lm 0.32.0 [osx-arm64]</title>
      <description>MLX LM is a Python package for generating text and fine-tuning large language models on Apple silicon with MLX. Some key features include integration with the Hugging Face Hub to easily use thousands of LLMs with a single command, support for quantizing and uploading models to the Hugging Face Hub, low-rank and full model fine-tuning with support for quantized models, distributed inference and fine-tuning with mx.distributed</description>
      <link>https://github.com/ml-explore/mlx-lm</link>
      <comments>https://github.com/ml-explore/mlx-lm</comments>
      <pubDate>Mon, 05 Oct 2026 13:06:35 GMT</pubDate>
      <source>https://github.com/ml-explore/mlx-lm</source>
    </item>
    <item>
      <title>jupyter-builder-with-nodejs 1.2.3 [noarch]</title>
      <description>Build tools shared by JupyterLab and Jupyter Notebook extensions.</description>
      <link>https://jupyterlab.readthedocs.io</link>
      <comments>https://github.com/jupyterlab/jupyter-builder</comments>
      <guid>https://pypi.io/packages/source/j/jupyter-builder/jupyter_builder-1.2.3.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 12:48:08 GMT</pubDate>
      <source>https://jupyter.org</source>
    </item>
    <item>
      <title>groff 1.24.2 [linux-64, linux-aarch64, linux-ppc64le, osx-64, osx-arm64]</title>
      <description>The Groff package contains programs for processing and formatting text.</description>
      <link>https://www.gnu.org/software/groff/#documentation</link>
      <comments>https://git.savannah.gnu.org/cgit/groff.git</comments>
      <guid>https://ftp.gnu.org/gnu/groff/groff-1.24.2.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 10:13:53 GMT</pubDate>
      <source>https://www.gnu.org/software/groff/</source>
    </item>
    <item>
      <title>plotly 7.1.0 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, noarch, osx-64, osx-arm64, win-32, win-64]</title>
      <description>plotly.py is an interactive, open-source, and browser-based graphing library for Python. Built on top of plotly.js, plotly.py is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more.</description>
      <link>https://plotly.com/python</link>
      <comments>https://github.com/plotly/plotly.py</comments>
      <guid>https://github.com/plotly/plotly.py/archive/refs/tags/v7.1.0.tar.gz</guid>
      <pubDate>Mon, 05 Oct 2026 07:50:39 GMT</pubDate>
      <source>https://plotly.com/python</source>
    </item>
    <item>
      <title>cuda-pathfinder 1.8.3 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>Public API for loading NVIDIA Dynamic Libraries</description>
      <link>https://nvidia.github.io/cuda-python/cuda-pathfinder</link>
      <comments>https://github.com/NVIDIA/cuda-python/tree/main/cuda_pathfinder</comments>
      <guid>https://github.com/NVIDIA/cuda-python/releases/download/cuda-pathfinder-v1.8.3/cuda-python-cuda-pathfinder-v1.8.3.tar.gz</guid>
      <pubDate>Fri, 02 Oct 2026 18:46:44 GMT</pubDate>
      <source>https://nvidia.github.io/cuda-python/cuda-pathfinder</source>
    </item>
    <item>
      <title>conda 26.9.1 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Conda is an open source package management system and environment management system for installing multiple versions of software packages and their dependencies and switching easily between them. It works on Linux, OS X and Windows, and was created for Python programs but can package and distribute any software.</description>
      <link>https://docs.conda.io/projects/conda/en/stable/</link>
      <comments>https://github.com/conda/conda</comments>
      <guid>https://github.com/conda/conda/releases/download/26.9.1/conda-26.9.1.tar.gz</guid>
      <pubDate>Fri, 02 Oct 2026 17:41:14 GMT</pubDate>
      <source>https://docs.conda.io/</source>
    </item>
    <item>
      <title>cuda 13.4.2 [linux-64, linux-aarch64, noarch, win-64, win-arm64]</title>
      <description>Meta-package containing all the available packages required for native CUDA development</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Fri, 02 Oct 2026 16:13:18 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-toolkit 13.4.2 [linux-64, linux-aarch64, noarch, win-64, win-arm64]</title>
      <description>Meta-package containing all toolkit packages for CUDA development</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Fri, 02 Oct 2026 14:59:10 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-tools 13.4.2 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>Meta-package containing all CUDA command line and visual tools.</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Fri, 02 Oct 2026 14:39:26 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>proj 9.9.0 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64]</title>
      <description>PROJ is a generic coordinate transformation software that transforms geospatial coordinates from one coordinate reference system (CRS) to another. This includes cartographic projections as well as geodetic transformations.</description>
      <link>https://proj.org/index.html</link>
      <comments>https://github.com/OSGeo/PROJ</comments>
      <guid>https://download.osgeo.org/proj/proj-9.9.0.tar.gz</guid>
      <pubDate>Fri, 02 Oct 2026 11:14:05 GMT</pubDate>
      <source>https://proj.org</source>
    </item>
    <item>
      <title>whisper.cpp 1.9.4 [linux-64, linux-aarch64, osx-arm64, win-64, win-arm64]</title>
      <description>whisper.cpp is a high-performance inference of OpenAI's Whisper automatic speech recognition (ASR) model implemented in C/C++. It provides efficient speech-to-text transcription with support for multiple languages and hardware acceleration options including Metal (Apple Silicon), CUDA (NVIDIA GPUs), and optimized BLAS libraries (MKL, OpenBLAS, Accelerate).  Hardware acceleration is provided by the installed libllama variant, which ships the shared ggml library.</description>
      <link>https://github.com/ggml-org/whisper.cpp/blob/master/README.md</link>
      <comments>https://github.com/ggml-org/whisper.cpp</comments>
      <guid>https://github.com/ggml-org/whisper.cpp/archive/v1.9.4.tar.gz</guid>
      <pubDate>Thu, 01 Oct 2026 23:41:46 GMT</pubDate>
      <source>https://github.com/ggml-org/whisper.cpp</source>
    </item>
    <item>
      <title>python-freethreading 3.14.8 [noarch]</title>
      <description>Python is a widely used high-level, general-purpose, interpreted, dynamic programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java. The language provides constructs intended to enable clear programs on both a small and large scale.</description>
      <link>https://www.python.org/doc/versions/</link>
      <comments>https://devguide.python.org/</comments>
      <pubDate>Thu, 01 Oct 2026 20:50:07 GMT</pubDate>
      <source>https://www.python.org/</source>
    </item>
    <item>
      <title>python-jit 3.14.8 [noarch]</title>
      <description>Python is a widely used high-level, general-purpose, interpreted, dynamic programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java. The language provides constructs intended to enable clear programs on both a small and large scale.</description>
      <link>https://www.python.org/doc/versions/</link>
      <comments>https://devguide.python.org/</comments>
      <pubDate>Thu, 01 Oct 2026 20:44:35 GMT</pubDate>
      <source>https://www.python.org/</source>
    </item>
    <item>
      <title>python-gil 3.14.8 [noarch]</title>
      <description>Python is a widely used high-level, general-purpose, interpreted, dynamic programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java. The language provides constructs intended to enable clear programs on both a small and large scale.</description>
      <link>https://www.python.org/doc/versions/</link>
      <comments>https://devguide.python.org/</comments>
      <pubDate>Thu, 01 Oct 2026 20:44:30 GMT</pubDate>
      <source>https://www.python.org/</source>
    </item>
    <item>
      <title>cuda-runtime 13.4.2 [linux-64, linux-aarch64, noarch, win-64, win-arm64]</title>
      <description>Meta-package containing all runtime library packages.</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Thu, 01 Oct 2026 20:18:55 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-visual-tools 13.4.2 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>Contains the visual tools to debug and profile CUDA applications</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Thu, 01 Oct 2026 20:18:41 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-libraries-static 13.4.2 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>Meta-package containing all available library static packages.</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Thu, 01 Oct 2026 17:02:00 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-libraries-dev 13.4.2 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>Meta-package containing all available library development packages.</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Thu, 01 Oct 2026 16:55:11 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-libraries 13.4.2 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>Meta-package containing all available library runtime packages.</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Thu, 01 Oct 2026 16:47:23 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>python-tzdata 2026.4 [noarch]</title>
      <description>This is a Python package containing zic-compiled binaries for the IANA time zone database. It is intended to be a fallback for systems that do not have system time zone data installed (or don't have it installed in a standard location), as a part of PEP 615.</description>
      <link>https://tzdata.readthedocs.org</link>
      <comments>https://github.com/python/tzdata</comments>
      <guid>https://pypi.org/packages/source/t/tzdata/tzdata-2026.4.tar.gz</guid>
      <pubDate>Thu, 01 Oct 2026 14:14:42 GMT</pubDate>
      <source>https://github.com/python/tzdata</source>
    </item>
    <item>
      <title>cuda-minimal-build 13.4.2 [linux-64, linux-aarch64, noarch, win-64, win-arm64]</title>
      <description>Meta-package containing the minimal necessary to build basic CUDA apps.</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Thu, 01 Oct 2026 14:01:39 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>notebook 7.6.3 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64]</title>
      <description>The Jupyter notebook is a web-based notebook environment for interactive computing.</description>
      <link>https://jupyter-notebook.readthedocs.io</link>
      <comments>https://github.com/jupyter/notebook</comments>
      <guid>https://pypi.org/packages/source/n/notebook/notebook-7.6.3.tar.gz</guid>
      <pubDate>Thu, 01 Oct 2026 07:18:42 GMT</pubDate>
      <source>https://github.com/jupyter/notebook</source>
    </item>
    <item>
      <title>openjph 0.31.0 [linux-64, linux-aarch64, osx-arm64, win-64, win-arm64]</title>
      <description>Open source implementation of High-throughput JPEG2000 (HTJ2K).</description>
      <link>https://github.com/aous72/OpenJPH</link>
      <comments>https://github.com/aous72/OpenJPH</comments>
      <guid>https://github.com/aous72/openjph/archive/0.31.0.tar.gz</guid>
      <pubDate>Thu, 01 Oct 2026 00:49:12 GMT</pubDate>
      <source>https://github.com/aous72/OpenJPH</source>
    </item>
    <item>
      <title>requests-kerberos 0.15.0 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, noarch, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Requests is an HTTP library, written in Python, for human beings. This library adds optional Kerberos/GSSAPI authentication support and supports mutual authentication.</description>
      <link>https://pypi.org/project/requests-kerberos/</link>
      <comments>https://github.com/requests/requests-kerberos</comments>
      <guid>https://github.com/requests/requests-kerberos/archive/refs/tags/v0.15.0.tar.gz</guid>
      <pubDate>Thu, 01 Oct 2026 00:47:23 GMT</pubDate>
      <source>https://github.com/requests/requests-kerberos</source>
    </item>
    <item>
      <title>tifffile 2026.9.20 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, noarch, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Tifffile is a Python library to store NumPy arrays in TIFF (Tagged Image File Format) files, and read image and metadata from TIFF-like files used in bioimaging.</description>
      <link>https://github.com/cgohlke/tifffile/blob/master/README.rst</link>
      <comments>https://github.com/cgohlke/tifffile</comments>
      <guid>https://pypi.org/packages/source/t/tifffile/tifffile-2026.9.20.tar.gz</guid>
      <pubDate>Thu, 01 Oct 2026 00:46:44 GMT</pubDate>
      <source>https://github.com/cgohlke/tifffile</source>
    </item>
    <item>
      <title>echo 0.16.0 [linux-64, linux-aarch64, noarch, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>Echo is a small library for attaching callback functions to property state changes.</description>
      <link>https://echo.readthedocs.io</link>
      <comments>https://github.com/glue-viz/echo</comments>
      <guid>https://pypi.org/packages/source/e/echo/echo-0.16.0.tar.gz</guid>
      <pubDate>Thu, 01 Oct 2026 00:43:09 GMT</pubDate>
      <source>https://github.com/glue-viz/echo</source>
    </item>
    <item>
      <title>cuda-compiler 13.4.2 [linux-64, linux-aarch64, noarch, win-64, win-arm64]</title>
      <description>A meta-package containing tools to start developing and compiling a basic CUDA application.</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Wed, 30 Sep 2026 23:41:21 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-cccl_win-64 13.3.4.3.1 [noarch]</title>
      <description>CUDA C++ Core Libraries</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cccl/windows-x86_64/cccl-windows-x86_64-13.3.4.3.1-archive.zip</guid>
      <pubDate>Wed, 30 Sep 2026 23:40:26 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-cccl 13.3.4.3.1 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>CUDA C++ Core Libraries</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cccl/windows-arm64/cccl-windows-arm64-13.3.4.3.1-archive.zip</guid>
      <pubDate>Wed, 30 Sep 2026 23:40:02 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-command-line-tools 13.4.2 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>Meta-package containing the command line tools to debug CUDA applications</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_documentation/LICENSE.txt</guid>
      <pubDate>Wed, 30 Sep 2026 23:39:56 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-cccl_win-arm64 13.3.4.3.1 [noarch]</title>
      <description>CUDA C++ Core Libraries</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cccl/windows-arm64/cccl-windows-arm64-13.3.4.3.1-archive.zip</guid>
      <pubDate>Wed, 30 Sep 2026 23:39:32 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-cccl_linux-64 13.3.4.3.1 [noarch]</title>
      <description>CUDA C++ Core Libraries</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cccl/linux-x86_64/cccl-linux-x86_64-13.3.4.3.1-archive.tar.xz</guid>
      <pubDate>Wed, 30 Sep 2026 23:34:51 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-cccl_linux-aarch64 13.3.4.3.1 [noarch]</title>
      <description>CUDA C++ Core Libraries</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cccl/linux-sbsa/cccl-linux-sbsa-13.3.4.3.1-archive.tar.xz</guid>
      <pubDate>Wed, 30 Sep 2026 23:33:50 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>tiktoken 0.14.0 [linux-64, linux-aarch64, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>tiktoken is a fast BPE tokeniser for use with OpenAI's models.</description>
      <link>https://github.com/openai/tiktoken/blob/main/README.md</link>
      <comments>https://github.com/openai/tiktoken</comments>
      <guid>https://pypi.org/packages/source/t/tiktoken/tiktoken-0.14.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 23:28:25 GMT</pubDate>
      <source>https://github.com/openai/tiktoken</source>
    </item>
    <item>
      <title>passlib 1.7.4 [linux-32, linux-64, linux-aarch64, linux-ppc64le, noarch, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Passlib is a password hashing library for Python, which provides cross-platform implementations of over 30 password hashing algorithms, as well as a framework for managing existing password hashes. It's designed to be useful for a wide range of tasks, from verifying a hash found in /etc/shadow, to providing full-strength password hashing for multi-user applications.</description>
      <link>https://passlib.readthedocs.io</link>
      <comments>https://foss.heptapod.net/python-libs/passlib</comments>
      <guid>https://pypi.io/packages/source/p/passlib/passlib-1.7.4.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 23:27:33 GMT</pubDate>
      <source>https://foss.heptapod.net/python-libs/passlib</source>
    </item>
    <item>
      <title>anthropic 1.7.0 [linux-64, linux-aarch64, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>The Anthropic Python SDK is a library for accessing the anthropic API. It provides a simple and intuitive interface for making requests to the API and handling responses. The SDK is designed to be easy to use and integrate into your existing Python projects.</description>
      <link>https://platform.claude.com/docs/en/home</link>
      <comments>https://github.com/anthropics/anthropic-sdk-python</comments>
      <guid>https://pypi.org/packages/source/a/anthropic/anthropic-1.7.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 23:26:59 GMT</pubDate>
      <source>https://github.com/anthropics/anthropic-sdk-python</source>
    </item>
    <item>
      <title>pyspnego 0.12.1 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Library to handle SPNEGO (Negotiate, NTLM, Kerberos) and CredSSP authentication. Also includes a packet parser that can be used to decode raw NTLM/SPNEGO/Kerberos tokens into a human readable format.</description>
      <link>https://github.com/jborean93/pyspnego/blob/main/README.md</link>
      <comments>https://github.com/jborean93/pyspnego</comments>
      <guid>https://pypi.org/packages/source/p/pyspnego/pyspnego-0.12.1.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 23:22:20 GMT</pubDate>
      <source>https://github.com/jborean93/pyspnego</source>
    </item>
    <item>
      <title>openblas 0.3.31 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>OpenBLAS is based on GotoBLAS2 1.13 BSD version.</description>
      <link>https://www.openblas.net</link>
      <comments>https://github.com/xianyi/OpenBLAS</comments>
      <guid>https://github.com/OpenMathLib/OpenBLAS/archive/v0.3.31.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:29:44 GMT</pubDate>
      <source>https://www.openblas.net</source>
    </item>
    <item>
      <title>openblas-devel 0.3.31 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>OpenBLAS is based on GotoBLAS2 1.13 BSD version.</description>
      <link>https://www.openblas.net</link>
      <comments>https://github.com/xianyi/OpenBLAS</comments>
      <guid>https://github.com/OpenMathLib/OpenBLAS/archive/v0.3.31.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:29:41 GMT</pubDate>
      <source>https://www.openblas.net</source>
    </item>
    <item>
      <title>libopenblas 0.3.31 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>OpenBLAS is based on GotoBLAS2 1.13 BSD version.</description>
      <link>https://www.openblas.net</link>
      <comments>https://github.com/xianyi/OpenBLAS</comments>
      <guid>https://github.com/OpenMathLib/OpenBLAS/archive/v0.3.31.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:29:28 GMT</pubDate>
      <source>https://www.openblas.net</source>
    </item>
    <item>
      <title>awscrt 0.37.0 [linux-64, linux-aarch64, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>Python 3 bindings for the AWS Common Runtime.</description>
      <link>https://awslabs.github.io/aws-crt-python</link>
      <comments>https://github.com/awslabs/aws-crt-python</comments>
      <guid>https://pypi.org/packages/source/a/awscrt/awscrt-0.37.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:08:37 GMT</pubDate>
      <source>https://github.com/awslabs/aws-crt-python</source>
    </item>
    <item>
      <title>python-xxhash 4.0.1 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Python binding for xxHash which is an extremely fast hash algorithm, processing at RAM speed limits. Code is highly portable, and produces hashes identical across all platforms (little / big endian).</description>
      <link>https://github.com/ifduyue/python-xxhash</link>
      <comments>https://github.com/ifduyue/python-xxhash</comments>
      <guid>https://pypi.org/packages/source/x/xxhash/xxhash-4.0.1.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:08:20 GMT</pubDate>
      <source>https://github.com/ifduyue/python-xxhash</source>
    </item>
    <item>
      <title>cchardet 2.3.0 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>cChardet is high speed universal character encoding detector. - binding to uchardet.</description>
      <link>https://github.com/PyYoshi/cChardet</link>
      <comments>https://github.com/PyYoshi/cChardet</comments>
      <guid>https://pypi.org/packages/source/c/cchardet/cchardet-2.3.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:07:11 GMT</pubDate>
      <source>https://github.com/PyYoshi/cChardet</source>
    </item>
    <item>
      <title>pyjwt 2.15.1 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>PyJWT is a Python library which allows you to encode and decode JSON Web Tokens (JWT). JWT is an open, industry-standard (RFC 7519) for representing claims securely between two parties.</description>
      <link>https://pyjwt.readthedocs.io</link>
      <comments>https://github.com/jpadilla/pyjwt</comments>
      <guid>https://pypi.org/packages/source/p/pyjwt/pyjwt-2.15.1.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:07:05 GMT</pubDate>
      <source>https://github.com/jpadilla/pyjwt</source>
    </item>
    <item>
      <title>types-python-dateutil 2.9.0.20260807 [linux-64, linux-aarch64, osx-arm64, win-64, win-arm64]</title>
      <description>This is a PEP 561 type stub package for the python-dateutil package.</description>
      <link>https://github.com/python/typeshed/blob/main/README.md</link>
      <comments>https://github.com/python/typeshed/tree/main</comments>
      <guid>https://pypi.org/packages/source/t/types-python-dateutil/types_python_dateutil-2.9.0.20260807.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:04:08 GMT</pubDate>
      <source>https://github.com/python/typeshed</source>
    </item>
    <item>
      <title>fastsafetensors 0.4.0 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>fastsafetensors is an efficient safetensors loader that accelerates loading of large model weights. It supports Linux/CUDA (including GPU Direct Storage), ROCm, Windows, 3FS, and unified-memory systems. vLLM and SGLang expose a `--load-format fastsafetensors` option that uses this library to speed up model initialization.</description>
      <link>https://github.com/foundation-model-stack/fastsafetensors/tree/main/docs</link>
      <comments>https://github.com/foundation-model-stack/fastsafetensors</comments>
      <guid>https://github.com/foundation-model-stack/fastsafetensors/archive/refs/tags/0.4.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:03:28 GMT</pubDate>
      <source>https://github.com/foundation-model-stack/fastsafetensors</source>
    </item>
    <item>
      <title>types-pyyaml 6.0.12.20260815 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>This is a PEP 561 type stub package for the PyYaml package. It can be used by type-checking tools like mypy, pyright, pytype, PyCharm, etc. to check code that uses PyYaml.</description>
      <link>https://pyyaml.org/wiki/PyYAMLDocumentation</link>
      <comments>https://github.com/python/typeshed</comments>
      <guid>https://pypi.org/packages/source/t/types-PyYAML/types_pyyaml-6.0.12.20260815.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:02:58 GMT</pubDate>
      <source>https://github.com/python/typeshed</source>
    </item>
    <item>
      <title>pydata-sphinx-theme 0.20.0 [linux-64, linux-aarch64, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>A clean, three-column, Bootstrap-based Sphinx theme by and for the PyData community.</description>
      <link>https://github.com/pydata/pydata-sphinx-theme/blob/main/README.md</link>
      <comments>https://github.com/pydata/pydata-sphinx-theme</comments>
      <guid>https://pypi.org/packages/source/p/pydata-sphinx-theme/pydata_sphinx_theme-0.20.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:02:43 GMT</pubDate>
      <source>https://github.com/pydata/pydata-sphinx-theme</source>
    </item>
    <item>
      <title>joblib 1.6.0 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, noarch, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>A set of tools to provide lightweight pipelining in Python. In particular: transparent disk-caching of functions and lazy re-evaluation (memoize pattern), easy, simple parallel computing. Joblib is optimized to be fast and robust on large data in particular and has specific optimizations for numpy arrays.</description>
      <link>https://joblib.readthedocs.io</link>
      <comments>https://github.com/joblib/joblib</comments>
      <guid>https://pypi.org/packages/source/j/joblib/joblib-1.6.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:02:32 GMT</pubDate>
      <source>https://joblib.readthedocs.io</source>
    </item>
    <item>
      <title>boto3 1.43.68 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, noarch, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Boto3 makes it easy to integrate you Python application, library or script with AWS services. It allows Python developers to write softare that makes use of services like Amazon S3 and Amazon EC2.</description>
      <link>https://docs.aws.amazon.com/boto3/latest</link>
      <comments>https://github.com/boto/boto3</comments>
      <guid>https://github.com/boto/boto3/archive/refs/tags/1.43.68.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:02:28 GMT</pubDate>
      <source>https://aws.amazon.com/sdk-for-python</source>
    </item>
    <item>
      <title>cookiecutter 2.7.1 [linux-64, linux-aarch64, linux-s390x, noarch, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>Cookiecutter takes a template provided as a directory structure with template-files. Templates can be located in the filesystem, as a ZIP-file or on a VCS-Server (Git/Hg) like GitHub. It reads a settings file and prompts the user interactively whether or not to change the settings. Then it takes both and generates an output directory structure from it. Additionally the template can provide code (Python or shell-script) to be executed before and after generation (pre-gen- and post-gen-hooks).</description>
      <link>https://cookiecutter.readthedocs.io</link>
      <comments>https://github.com/cookiecutter/cookiecutter</comments>
      <guid>https://pypi.io/packages/source/c/cookiecutter/cookiecutter-2.7.1.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:02:06 GMT</pubDate>
      <source>https://github.com/cookiecutter/cookiecutter</source>
    </item>
    <item>
      <title>markdown 3.10.3 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>This is a Python implementation of John Gruber’s Markdown. It is almost completely compliant with the reference implementation, though there are a few very minor differences.</description>
      <link>https://python-markdown.github.io/</link>
      <comments>https://github.com/Python-Markdown/markdown</comments>
      <guid>https://pypi.org/packages/source/M/Markdown/markdown-3.10.3.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 22:01:27 GMT</pubDate>
      <source>https://github.com/Python-Markdown/markdown</source>
    </item>
    <item>
      <title>zeromq-static 4.3.5 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>The ZeroMQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. ZeroMQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.</description>
      <link>https://zeromq.org/get-started/</link>
      <comments>https://github.com/zeromq/libzmq</comments>
      <guid>https://github.com/zeromq/libzmq/releases/download/v4.3.5/zeromq-4.3.5.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 20:55:21 GMT</pubDate>
      <source>https://zeromq.org</source>
    </item>
    <item>
      <title>zeromq 4.3.5 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>The ZeroMQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. ZeroMQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.</description>
      <link>https://zeromq.org/get-started/</link>
      <comments>https://github.com/zeromq/libzmq</comments>
      <guid>https://github.com/zeromq/libzmq/releases/download/v4.3.5/zeromq-4.3.5.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 20:54:52 GMT</pubDate>
      <source>https://zeromq.org</source>
    </item>
    <item>
      <title>ls-hpack 2.3.5 [linux-64, linux-aarch64, osx-arm64, win-64, win-arm64]</title>
      <description>LS-HPACK provides functionality to encode and decode HTTP headers using HPACK compression mechanism specified in RFC 7541.</description>
      <link>https://github.com/litespeedtech/ls-hpack</link>
      <comments>https://github.com/litespeedtech/ls-hpack</comments>
      <guid>https://github.com/litespeedtech/ls-hpack/archive/refs/tags/v2.3.5.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 20:49:15 GMT</pubDate>
      <source>https://github.com/litespeedtech/ls-hpack</source>
    </item>
    <item>
      <title>azure-storage-common-cpp 12.14.0 [linux-64, linux-aarch64, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>Azure Storage is a Microsoft-managed service providing cloud storage that is highly available, secure, durable, scalable, and redundant. Azure Storage includes Azure Blobs (objects), Azure Data Lake Storage Gen2, Azure Files, and Azure Queues. The Azure Storage Common library provides infrastructure shared by the other Azure Storage client libraries.</description>
      <link>https://azure.github.io/azure-sdk-for-cpp</link>
      <comments>https://github.com/Azure/azure-sdk-for-cpp/tree/main/sdk/storage/azure-storage-common</comments>
      <guid>https://github.com/Azure/azure-sdk-for-cpp/archive/refs/tags/azure-storage-common_12.14.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 20:49:07 GMT</pubDate>
      <source>https://github.com/Azure/azure-sdk-for-cpp</source>
    </item>
    <item>
      <title>urllib3 2.8.0 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, noarch, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>urllib3 is a powerful, sanity-friendly HTTP client for Python. Much of the Python ecosystem already uses urllib3. urllib3 brings many critical features that are missing from the Python standard libraries, such as thread safety, connection pooling, client side ssl/tls verification, support for gzip and deflate encodings, HTTP and SOCKS proxy support, helpers for retrying requests and dealing with HTTP redirects.</description>
      <link>https://urllib3.readthedocs.io</link>
      <comments>https://github.com/urllib3/urllib3</comments>
      <guid>https://pypi.org/packages/source/u/urllib3/urllib3-2.8.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 20:46:34 GMT</pubDate>
      <source>https://urllib3.readthedocs.io</source>
    </item>
    <item>
      <title>perl-exporter 5.79 [linux-64, linux-aarch64, osx-arm64, win-64, win-arm64]</title>
      <description>The Exporter module implements an import method which allows a module to export functions and variables to its users' namespaces. Many modules use Exporter rather than implementing their own import method because Exporter provides a flexible interface with an implementation optimised for the common case.</description>
      <link>https://metacpan.org/pod/Exporter</link>
      <comments>https://github.com/Perl/perl5/tree/blead/dist/Exporter</comments>
      <guid>https://cpan.metacpan.org/authors/id/T/TO/TODDR/Exporter-5.79.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 20:30:09 GMT</pubDate>
      <source>https://metacpan.org/release/Exporter</source>
    </item>
    <item>
      <title>python_abi 3.15 [linux-64, linux-aarch64, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>Metapackage to select python implementation</description>
      <link>https://github.com/conda-forge/python_abi-feedstock</link>
      <comments>https://github.com/conda-forge/python_abi-feedstock</comments>
      <pubDate>Wed, 30 Sep 2026 20:27:59 GMT</pubDate>
      <source>https://github.com/conda-forge/python_abi-feedstock</source>
    </item>
    <item>
      <title>aws-sdk-cpp 1.11.895 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>The AWS SDK for C++ provides a modern C++ (version C++ 11 or later) interface for Amazon Web Services (AWS). It is meant to be performant and fully functioning with low- and high-level SDKs, while minimizing dependencies and providing platform portability (Windows, OSX, Linux, and mobile).</description>
      <link>https://docs.aws.amazon.com/sdk-for-cpp</link>
      <comments>https://github.com/aws/aws-sdk-cpp</comments>
      <guid>https://github.com/aws/aws-sdk-cpp/archive/1.11.774.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 18:56:43 GMT</pubDate>
      <source>https://github.com/aws/aws-sdk-cpp</source>
    </item>
    <item>
      <title>aws-crt-cpp 0.43.6 [linux-64, linux-aarch64, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>C++ wrapper around the aws-c-* libraries. Provides Cross-Platform Transport Protocols and SSL/TLS implementations for C++.</description>
      <link>https://awslabs.github.io/aws-crt-cpp</link>
      <comments>https://github.com/awslabs/aws-crt-cpp</comments>
      <guid>https://github.com/awslabs/aws-crt-cpp/archive/v0.43.6.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 18:33:46 GMT</pubDate>
      <source>https://github.com/awslabs/aws-crt-cpp</source>
    </item>
    <item>
      <title>aws-c-s3 1.2.0 [linux-64, linux-aarch64, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>The AWS-C-S3 library is an asynchronous AWS S3 client focused on maximizing throughput and network utilization.</description>
      <link>https://github.com/awslabs/aws-c-s3</link>
      <comments>https://github.com/awslabs/aws-c-s3</comments>
      <guid>https://github.com/awslabs/aws-c-s3/archive/v1.2.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 18:21:46 GMT</pubDate>
      <source>https://github.com/awslabs/aws-c-s3</source>
    </item>
    <item>
      <title>aws-c-auth 1.0.0 [linux-64, linux-aarch64, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>C99 library implementation of AWS client-side authentication: standard credentials providers and signing. From a cryptographic perspective, only functions with the suffix &quot;_constant_time&quot; should be considered constant time.</description>
      <link>https://github.com/awslabs/aws-c-auth</link>
      <comments>https://github.com/awslabs/aws-c-auth</comments>
      <guid>https://github.com/awslabs/aws-c-auth/archive/v1.0.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 17:57:01 GMT</pubDate>
      <source>https://github.com/awslabs/aws-c-auth</source>
    </item>
    <item>
      <title>aws-c-event-stream 1.0.0 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>C99 implementation of the vnd.amazon.eventstream content-type.</description>
      <link>https://github.com/awslabs/aws-c-event-stream</link>
      <comments>https://github.com/awslabs/aws-c-event-stream</comments>
      <guid>https://github.com/awslabs/aws-c-event-stream/archive/v1.0.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 17:44:42 GMT</pubDate>
      <source>https://github.com/awslabs/aws-c-event-stream</source>
    </item>
    <item>
      <title>cccl 3.4.3 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>CUDA C++ Core Libraries (CCCL) includes thrust, cub, and libcudacxx. These are header-only libraries.</description>
      <link>https://nvidia.github.io/cccl/</link>
      <comments>https://github.com/NVIDIA/cccl</comments>
      <guid>https://github.com/NVIDIA/cccl/archive/refs/tags/v3.4.3.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 17:36:04 GMT</pubDate>
      <source>https://github.com/NVIDIA/cccl</source>
    </item>
    <item>
      <title>aws-c-io 1.0.0 [linux-64, linux-aarch64, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>This is an event driven framework for implementing application protocols. It is built on top of cross-platform abstractions that allow you as a developer to think only about the state machine and API for your protocols. A typical use-case would be to write something like Http on top of asynchronous-io with TLS already baked in. All of the platform and security concerns are already handled for you.</description>
      <link>https://github.com/awslabs/aws-c-io</link>
      <comments>https://github.com/awslabs/aws-c-io</comments>
      <guid>https://github.com/awslabs/aws-c-io/archive/v1.0.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 17:28:10 GMT</pubDate>
      <source>https://github.com/awslabs/aws-c-io</source>
    </item>
    <item>
      <title>aws-c-compression 1.0.0 [linux-64, linux-aarch64, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>This is a cross-platform C99 implementation of compression algorithms such as gzip, and huffman encoding/decoding. Currently only huffman is implemented.</description>
      <link>https://github.com/awslabs/aws-c-compression</link>
      <comments>https://github.com/awslabs/aws-c-compression</comments>
      <guid>https://github.com/awslabs/aws-c-compression/archive/v1.0.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 17:15:58 GMT</pubDate>
      <source>https://github.com/awslabs/aws-c-compression</source>
    </item>
    <item>
      <title>aws-c-cal 1.0.0 [linux-64, linux-aarch64, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>AWS Crypto Abstraction Layer: Cross-Platform, C99 wrapper for cryptography primitives.</description>
      <link>https://github.com/awslabs/aws-c-cal</link>
      <comments>https://github.com/awslabs/aws-c-cal</comments>
      <guid>https://github.com/awslabs/aws-c-cal/archive/v1.0.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 17:13:53 GMT</pubDate>
      <source>https://github.com/awslabs/aws-c-cal</source>
    </item>
    <item>
      <title>aws-checksums 1.0.0 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Cross-Platform HW accelerated CRC32c and CRC32 with fallback to efficient SW implementations. C interface with language bindings for each of our SDKs.</description>
      <link>https://github.com/awslabs/aws-checksums</link>
      <comments>https://github.com/awslabs/aws-checksums</comments>
      <guid>https://github.com/awslabs/aws-checksums/archive/v1.0.0.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 17:10:06 GMT</pubDate>
      <source>https://github.com/awslabs/aws-checksums</source>
    </item>
    <item>
      <title>coin-or-osi 0.108.12 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-64, win-arm64]</title>
      <description>Osi (Open Solver Interface) provides an abstract base class to a generic linear programming (LP) solver, along with derived classes for specific solvers. Many applications may be able to use the Osi to insulate themselves from a specific LP solver. That is, programs written to the OSI standard may be linked to any solver with an OSI interface and should produce correct results. The OSI has been significantly extended compared to its first incarnation. Currently, the OSI supports linear programming solvers and has rudimentary support for integer programming. Among others the following operations are supported:    - creating the LP formulation;   - directly modifying the formulation by adding rows/columns;   - modifying the formulation by adding cutting planes provided by CGL;   - solving the formulation (and resolving after modifications);   - extracting solution information;   - invoking the underlying solver's branch-and-bound component.</description>
      <link>https://coin-or.github.io/Osi/Doxygen/</link>
      <comments>https://github.com/coin-or/Osi</comments>
      <guid>https://github.com/coin-or/Osi/archive/releases/0.108.12.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 17:09:21 GMT</pubDate>
      <source>https://github.com/coin-or/Osi</source>
    </item>
    <item>
      <title>aws-c-common 1.0.1 [linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>Core c99 package for AWS SDK for C. Includes cross-platform primitives, configuration, data structures, and error handling.</description>
      <link>https://github.com/awslabs/aws-c-common#readme</link>
      <comments>https://github.com/awslabs/aws-c-common</comments>
      <guid>https://github.com/awslabs/aws-c-common/archive/v1.0.1.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 16:58:44 GMT</pubDate>
      <source>https://github.com/awslabs/aws-c-common</source>
    </item>
    <item>
      <title>cuda-gdb 13.4.92 [linux-64, linux-aarch64]</title>
      <description>CUDA-GDB is the NVIDIA tool for debugging CUDA applications running on Linux. CUDA-GDB is an extension to the x86-64 port of GDB, the GNU Project debugger.</description>
      <link>https://docs.nvidia.com/cuda/cuda-gdb/index.html</link>
      <comments>https://github.com/NVIDIA/cuda-gdb</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_gdb/linux-sbsa/cuda_gdb-linux-sbsa-13.4.92-archive.tar.xz</guid>
      <pubDate>Wed, 30 Sep 2026 15:34:10 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-gdb-src 13.4.92 [linux-64, linux-aarch64]</title>
      <description>CUDA-GDB is the NVIDIA tool for debugging CUDA applications running on Linux. CUDA-GDB is an extension to the x86-64 port of GDB, the GNU Project debugger.</description>
      <link>https://docs.nvidia.com/cuda/cuda-gdb/index.html</link>
      <comments>https://github.com/NVIDIA/cuda-gdb</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_gdb/linux-sbsa/cuda_gdb-linux-sbsa-13.4.92-archive.tar.xz</guid>
      <pubDate>Wed, 30 Sep 2026 14:57:53 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>cuda-tileiras 13.4.92 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>With Tile IR, we introduce a new operation set and programming model to retain CUDA’s performance across architectures while regaining portability and improving productivity for developers using matrix operations on new architectures. We virtualize tensor-cores and their associated programming model to the point that we can innovate new approaches in hardware without invalidating investments in software.</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_tileiras/windows-arm64/cuda_tileiras-windows-arm64-13.4.92-archive.zip</guid>
      <pubDate>Wed, 30 Sep 2026 14:55:29 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>openssl 3.5.9 [linux-32, linux-64, linux-aarch64, linux-ppc64le, linux-s390x, osx-64, osx-arm64, win-32, win-64, win-arm64]</title>
      <description>OpenSSL is a robust, commercial-grade, full-featured Open Source Toolkit for the Transport Layer Security (TLS) protocol formerly known as the Secure Sockets Layer (SSL) protocol. The protocol implementation is based on a full-strength general purpose cryptographic library, which can also be used stand-alone.</description>
      <link>https://docs.openssl.org</link>
      <comments>https://github.com/openssl/openssl</comments>
      <guid>https://github.com/openssl/openssl/releases/download/openssl-3.5.9/openssl-3.5.9.tar.gz</guid>
      <pubDate>Wed, 30 Sep 2026 14:17:46 GMT</pubDate>
      <source>https://www.openssl.org</source>
    </item>
    <item>
      <title>cuda-cuobjdump 13.4.92 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>Extracts information from CUDA binary files and presents them in human readable format.</description>
      <link>https://docs.nvidia.com/cuda/index.html</link>
      <comments>https://docs.nvidia.com/cuda/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/cuda_cuobjdump/windows-arm64/cuda_cuobjdump-windows-arm64-13.4.92-archive.zip</guid>
      <pubDate>Wed, 30 Sep 2026 13:30:19 GMT</pubDate>
      <source>https://developer.nvidia.com/cuda-toolkit</source>
    </item>
    <item>
      <title>libcusolver-dev 12.3.4.7 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>cuSOLVER - Direct Linear Solvers on NVIDIA GPUs</description>
      <link>https://docs.nvidia.com/cuda/cusolver/index.html</link>
      <comments>https://docs.nvidia.com/cuda/cusolver/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/libcusolver/windows-arm64/libcusolver-windows-arm64-12.3.4.7-archive.zip</guid>
      <pubDate>Wed, 30 Sep 2026 13:29:08 GMT</pubDate>
      <source>https://developer.nvidia.com/cusolver</source>
    </item>
    <item>
      <title>libcusolver 12.3.4.7 [linux-64, linux-aarch64, win-64, win-arm64]</title>
      <description>cuSOLVER - Direct Linear Solvers on NVIDIA GPUs</description>
      <link>https://docs.nvidia.com/cuda/cusolver/</link>
      <comments>https://docs.nvidia.com/cuda/cusolver/</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/libcusolver/windows-arm64/libcusolver-windows-arm64-12.3.4.7-archive.zip</guid>
      <pubDate>Wed, 30 Sep 2026 13:28:37 GMT</pubDate>
      <source>https://developer.nvidia.com/cusolver</source>
    </item>
    <item>
      <title>libcusolver-static 12.3.4.7 [linux-64, linux-aarch64]</title>
      <description>cuSOLVER - Direct Linear Solvers on NVIDIA GPUs</description>
      <link>https://docs.nvidia.com/cuda/cusolver/index.html</link>
      <comments>https://docs.nvidia.com/cuda/cusolver/index.html</comments>
      <guid>https://developer.download.nvidia.com/compute/cuda/redist/libcusolver/linux-sbsa/libcusolver-linux-sbsa-12.3.4.7-archive.tar.xz</guid>
      <pubDate>Wed, 30 Sep 2026 13:26:27 GMT</pubDate>
      <source>https://developer.nvidia.com/cusolver</source>
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