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    <title>PyPI recent updates for turboloader</title>
    <link>https://pypi.org/project/turboloader/</link>
    <description>Recent updates to the Python Package Index for turboloader</description>
    <language>en</language>    <item>
      <title>2.25.0</title>
      <link>https://pypi.org/project/turboloader/2.25.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Wed, 11 Feb 2026 01:32:54 GMT</pubDate>
    </item>    <item>
      <title>2.23.0</title>
      <link>https://pypi.org/project/turboloader/2.23.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Fri, 19 Dec 2025 04:10:54 GMT</pubDate>
    </item>    <item>
      <title>2.22.0</title>
      <link>https://pypi.org/project/turboloader/2.22.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Fri, 19 Dec 2025 02:14:11 GMT</pubDate>
    </item>    <item>
      <title>2.21.0</title>
      <link>https://pypi.org/project/turboloader/2.21.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Fri, 19 Dec 2025 01:34:27 GMT</pubDate>
    </item>    <item>
      <title>2.20.0</title>
      <link>https://pypi.org/project/turboloader/2.20.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Fri, 19 Dec 2025 00:42:59 GMT</pubDate>
    </item>    <item>
      <title>2.19.0</title>
      <link>https://pypi.org/project/turboloader/2.19.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Thu, 18 Dec 2025 22:58:39 GMT</pubDate>
    </item>    <item>
      <title>2.18.0</title>
      <link>https://pypi.org/project/turboloader/2.18.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Thu, 18 Dec 2025 13:17:12 GMT</pubDate>
    </item>    <item>
      <title>2.17.0</title>
      <link>https://pypi.org/project/turboloader/2.17.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Thu, 18 Dec 2025 13:09:49 GMT</pubDate>
    </item>    <item>
      <title>2.16.0</title>
      <link>https://pypi.org/project/turboloader/2.16.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Thu, 18 Dec 2025 13:05:00 GMT</pubDate>
    </item>    <item>
      <title>2.15.0</title>
      <link>https://pypi.org/project/turboloader/2.15.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Thu, 18 Dec 2025 05:07:36 GMT</pubDate>
    </item>    <item>
      <title>2.14.0</title>
      <link>https://pypi.org/project/turboloader/2.14.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Thu, 18 Dec 2025 05:04:34 GMT</pubDate>
    </item>    <item>
      <title>2.13.0</title>
      <link>https://pypi.org/project/turboloader/2.13.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Thu, 18 Dec 2025 04:43:29 GMT</pubDate>
    </item>    <item>
      <title>2.12.0</title>
      <link>https://pypi.org/project/turboloader/2.12.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Wed, 17 Dec 2025 12:29:31 GMT</pubDate>
    </item>    <item>
      <title>2.11.0</title>
      <link>https://pypi.org/project/turboloader/2.11.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Wed, 17 Dec 2025 03:10:32 GMT</pubDate>
    </item>    <item>
      <title>2.10.0</title>
      <link>https://pypi.org/project/turboloader/2.10.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Wed, 17 Dec 2025 02:38:44 GMT</pubDate>
    </item>    <item>
      <title>2.9.0</title>
      <link>https://pypi.org/project/turboloader/2.9.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Tue, 16 Dec 2025 23:51:44 GMT</pubDate>
    </item>    <item>
      <title>2.8.0</title>
      <link>https://pypi.org/project/turboloader/2.8.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Wed, 03 Dec 2025 05:07:04 GMT</pubDate>
    </item>    <item>
      <title>2.7.0</title>
      <link>https://pypi.org/project/turboloader/2.7.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Tue, 02 Dec 2025 23:37:04 GMT</pubDate>
    </item>    <item>
      <title>2.6.0</title>
      <link>https://pypi.org/project/turboloader/2.6.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Tue, 02 Dec 2025 03:56:06 GMT</pubDate>
    </item>    <item>
      <title>2.5.0</title>
      <link>https://pypi.org/project/turboloader/2.5.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Tue, 02 Dec 2025 00:44:04 GMT</pubDate>
    </item>    <item>
      <title>2.4.0</title>
      <link>https://pypi.org/project/turboloader/2.4.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 20:21:30 GMT</pubDate>
    </item>    <item>
      <title>2.3.23</title>
      <link>https://pypi.org/project/turboloader/2.3.23/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 17:54:56 GMT</pubDate>
    </item>    <item>
      <title>2.3.22</title>
      <link>https://pypi.org/project/turboloader/2.3.22/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 17:35:50 GMT</pubDate>
    </item>    <item>
      <title>2.3.21</title>
      <link>https://pypi.org/project/turboloader/2.3.21/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 17:34:09 GMT</pubDate>
    </item>    <item>
      <title>2.3.20</title>
      <link>https://pypi.org/project/turboloader/2.3.20/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 17:29:26 GMT</pubDate>
    </item>    <item>
      <title>2.3.19</title>
      <link>https://pypi.org/project/turboloader/2.3.19/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 08:53:25 GMT</pubDate>
    </item>    <item>
      <title>2.3.18</title>
      <link>https://pypi.org/project/turboloader/2.3.18/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 08:46:18 GMT</pubDate>
    </item>    <item>
      <title>2.3.17</title>
      <link>https://pypi.org/project/turboloader/2.3.17/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 08:35:18 GMT</pubDate>
    </item>    <item>
      <title>2.3.16</title>
      <link>https://pypi.org/project/turboloader/2.3.16/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 08:29:50 GMT</pubDate>
    </item>    <item>
      <title>2.3.15</title>
      <link>https://pypi.org/project/turboloader/2.3.15/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 08:20:39 GMT</pubDate>
    </item>    <item>
      <title>2.3.14</title>
      <link>https://pypi.org/project/turboloader/2.3.14/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 08:16:11 GMT</pubDate>
    </item>    <item>
      <title>2.3.13</title>
      <link>https://pypi.org/project/turboloader/2.3.13/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 08:12:18 GMT</pubDate>
    </item>    <item>
      <title>2.3.12</title>
      <link>https://pypi.org/project/turboloader/2.3.12/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 07:08:46 GMT</pubDate>
    </item>    <item>
      <title>2.3.10</title>
      <link>https://pypi.org/project/turboloader/2.3.10/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++17 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 07:00:11 GMT</pubDate>
    </item>    <item>
      <title>2.3.6</title>
      <link>https://pypi.org/project/turboloader/2.3.6/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++20 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 06:35:46 GMT</pubDate>
    </item>    <item>
      <title>2.3.5</title>
      <link>https://pypi.org/project/turboloader/2.3.5/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++20 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 06:30:09 GMT</pubDate>
    </item>    <item>
      <title>2.3.4</title>
      <link>https://pypi.org/project/turboloader/2.3.4/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++20 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 06:22:19 GMT</pubDate>
    </item>    <item>
      <title>2.3.3</title>
      <link>https://pypi.org/project/turboloader/2.3.3/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++20 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 06:18:54 GMT</pubDate>
    </item>    <item>
      <title>2.3.2</title>
      <link>https://pypi.org/project/turboloader/2.3.2/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++20 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 06:09:59 GMT</pubDate>
    </item>    <item>
      <title>2.3.0</title>
      <link>https://pypi.org/project/turboloader/2.3.0/</link>
      <description>Production-ready ML data loading library with distributed training support, SIMD-accelerated transforms, pipe operator composition, HDF5/TFRecord/Zarr support, and GPU transforms. Built with C++20 for maximum performance.</description>
<author>arnav@example.com</author>      <pubDate>Mon, 01 Dec 2025 05:42:00 GMT</pubDate>
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