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    <title>PyPI recent updates for pytrendy</title>
    <link>https://pypi.org/project/pytrendy/</link>
    <description>Recent updates to the Python Package Index for pytrendy</description>
    <language>en</language>    <item>
      <title>1.2.0</title>
      <link>https://pypi.org/project/pytrendy/1.2.0/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 09 May 2026 10:47:59 GMT</pubDate>
    </item>    <item>
      <title>1.2.0.dev1</title>
      <link>https://pypi.org/project/pytrendy/1.2.0.dev1/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Wed, 06 May 2026 21:46:44 GMT</pubDate>
    </item>    <item>
      <title>1.1.11.dev4</title>
      <link>https://pypi.org/project/pytrendy/1.1.11.dev4/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Tue, 28 Apr 2026 08:00:55 GMT</pubDate>
    </item>    <item>
      <title>1.1.11.dev3</title>
      <link>https://pypi.org/project/pytrendy/1.1.11.dev3/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Mon, 20 Apr 2026 01:27:06 GMT</pubDate>
    </item>    <item>
      <title>1.1.11</title>
      <link>https://pypi.org/project/pytrendy/1.1.11/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Thu, 02 Apr 2026 07:32:59 GMT</pubDate>
    </item>    <item>
      <title>1.1.11.dev2</title>
      <link>https://pypi.org/project/pytrendy/1.1.11.dev2/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sun, 29 Mar 2026 22:14:03 GMT</pubDate>
    </item>    <item>
      <title>1.1.11.dev1</title>
      <link>https://pypi.org/project/pytrendy/1.1.11.dev1/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sun, 22 Mar 2026 15:07:20 GMT</pubDate>
    </item>    <item>
      <title>1.1.10</title>
      <link>https://pypi.org/project/pytrendy/1.1.10/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 21 Mar 2026 16:31:37 GMT</pubDate>
    </item>    <item>
      <title>1.1.9</title>
      <link>https://pypi.org/project/pytrendy/1.1.9/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 07 Feb 2026 18:47:14 GMT</pubDate>
    </item>    <item>
      <title>1.1.8</title>
      <link>https://pypi.org/project/pytrendy/1.1.8/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 15 Nov 2025 18:20:18 GMT</pubDate>
    </item>    <item>
      <title>1.1.7</title>
      <link>https://pypi.org/project/pytrendy/1.1.7/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 01 Nov 2025 18:06:03 GMT</pubDate>
    </item>    <item>
      <title>1.1.6</title>
      <link>https://pypi.org/project/pytrendy/1.1.6/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Thu, 23 Oct 2025 07:44:42 GMT</pubDate>
    </item>    <item>
      <title>1.1.5</title>
      <link>https://pypi.org/project/pytrendy/1.1.5/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Wed, 22 Oct 2025 08:07:45 GMT</pubDate>
    </item>    <item>
      <title>1.1.4</title>
      <link>https://pypi.org/project/pytrendy/1.1.4/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sun, 19 Oct 2025 09:11:57 GMT</pubDate>
    </item>    <item>
      <title>1.1.3</title>
      <link>https://pypi.org/project/pytrendy/1.1.3/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Thu, 16 Oct 2025 08:01:47 GMT</pubDate>
    </item>    <item>
      <title>1.1.2</title>
      <link>https://pypi.org/project/pytrendy/1.1.2/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Wed, 15 Oct 2025 11:38:43 GMT</pubDate>
    </item>    <item>
      <title>1.1.1</title>
      <link>https://pypi.org/project/pytrendy/1.1.1/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Wed, 15 Oct 2025 08:26:10 GMT</pubDate>
    </item>    <item>
      <title>1.0.8</title>
      <link>https://pypi.org/project/pytrendy/1.0.8/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Tue, 02 Sep 2025 20:33:09 GMT</pubDate>
    </item>    <item>
      <title>1.0.7</title>
      <link>https://pypi.org/project/pytrendy/1.0.7/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Mon, 01 Sep 2025 19:51:10 GMT</pubDate>
    </item>    <item>
      <title>1.0.6</title>
      <link>https://pypi.org/project/pytrendy/1.0.6/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Mon, 01 Sep 2025 10:25:32 GMT</pubDate>
    </item>    <item>
      <title>1.0.5</title>
      <link>https://pypi.org/project/pytrendy/1.0.5/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Mon, 01 Sep 2025 09:19:47 GMT</pubDate>
    </item>    <item>
      <title>1.0.4</title>
      <link>https://pypi.org/project/pytrendy/1.0.4/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Mon, 01 Sep 2025 09:15:27 GMT</pubDate>
    </item>    <item>
      <title>1.0.3</title>
      <link>https://pypi.org/project/pytrendy/1.0.3/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Mon, 01 Sep 2025 06:59:03 GMT</pubDate>
    </item>    <item>
      <title>1.0.2</title>
      <link>https://pypi.org/project/pytrendy/1.0.2/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Mon, 01 Sep 2025 06:31:48 GMT</pubDate>
    </item>    <item>
      <title>1.0.1</title>
      <link>https://pypi.org/project/pytrendy/1.0.1/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sun, 31 Aug 2025 08:46:26 GMT</pubDate>
    </item>    <item>
      <title>0.0.12</title>
      <link>https://pypi.org/project/pytrendy/0.0.12/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 30 Aug 2025 15:40:44 GMT</pubDate>
    </item>    <item>
      <title>0.0.11</title>
      <link>https://pypi.org/project/pytrendy/0.0.11/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 30 Aug 2025 13:47:26 GMT</pubDate>
    </item>    <item>
      <title>0.0.10</title>
      <link>https://pypi.org/project/pytrendy/0.0.10/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 30 Aug 2025 08:58:08 GMT</pubDate>
    </item>    <item>
      <title>0.0.9</title>
      <link>https://pypi.org/project/pytrendy/0.0.9/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 30 Aug 2025 08:54:53 GMT</pubDate>
    </item>    <item>
      <title>0.0.8</title>
      <link>https://pypi.org/project/pytrendy/0.0.8/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 30 Aug 2025 08:49:04 GMT</pubDate>
    </item>    <item>
      <title>0.0.7</title>
      <link>https://pypi.org/project/pytrendy/0.0.7/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 30 Aug 2025 08:32:45 GMT</pubDate>
    </item>    <item>
      <title>0.0.5</title>
      <link>https://pypi.org/project/pytrendy/0.0.5/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 30 Aug 2025 08:23:26 GMT</pubDate>
    </item>    <item>
      <title>0.0.4</title>
      <link>https://pypi.org/project/pytrendy/0.0.4/</link>
      <description>Trend Detection in Python. Applicable for real-world industry use cases in time series.</description>
<author>r.sammutbonnici@gmail.com</author>      <pubDate>Sat, 30 Aug 2025 08:16:17 GMT</pubDate>
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