This is an automated email from the ASF dual-hosted git repository.
github-bot pushed a commit to branch asf-staging
in repository https://gitbox.apache.org/repos/asf/datafusion-site.git
The following commit(s) were added to refs/heads/asf-staging by this push:
new d32b5fb Commit build products
d32b5fb is described below
commit d32b5fb81277f313f5ffddbd627751d3138868e9
Author: Build Pelican (action) <priv...@infra.apache.org>
AuthorDate: Sun Mar 30 22:14:38 2025 +0000
Commit build products
---
.../2025/02/07/datafusion-python-46.0.0/index.html | 41 ++++++++++++++++------
blog/feeds/all-en.atom.xml | 41 ++++++++++++++++------
blog/feeds/blog.atom.xml | 41 ++++++++++++++++------
blog/feeds/timsaucer.atom.xml | 41 ++++++++++++++++------
4 files changed, 120 insertions(+), 44 deletions(-)
diff --git a/blog/2025/02/07/datafusion-python-46.0.0/index.html
b/blog/2025/02/07/datafusion-python-46.0.0/index.html
index efb063e..e4ed091 100644
--- a/blog/2025/02/07/datafusion-python-46.0.0/index.html
+++ b/blog/2025/02/07/datafusion-python-46.0.0/index.html
@@ -67,10 +67,20 @@ blog post for <a
href="https://datafusion.apache.org/blog/2024/12/14/datafusion-
that can be found in the <a
href="https://github.com/apache/datafusion-python/tree/main/dev/changelog";>changelogs</a>.</p>
<p>We highly recommend reviewing the upstream <a
href="https://datafusion.apache.org/blog/2025/03/24/datafusion-46.0.0";>DataFusion
46.0.0</a> announcement.</p>
<h2>Easier file reading</h2>
-<p>https://github.com/apache/datafusion-python/pull/982</p>
+<p>In these releases we have introduced two new ways to more easily read files
into
+DataFrames.</p>
+<p><a href="https://github.com/apache/datafusion-python/pull/982";>PR 982</a>
introduced a series of easier read functions for Parquet, JSON, CSV, and
+AVRO files. This introduces a concept of a global context that is available by
+default when using these methods. Now instead of creating a default Session
+Context and then calling the read methods, you can simply import these read
+alternative methods and begin working with your DataFrames. Below is an
example of
+how easy to use this new approach is.</p>
<div class="codehilite"><pre><span></span><code><span class="kn">from</span>
<span class="nn">datafusion.io</span> <span class="kn">import</span> <span
class="n">read_parquet</span>
<span class="n">df</span> <span class="o">=</span> <span
class="n">read_parquet</span><span class="p">(</span><span
class="n">path</span><span class="o">=</span><span
class="s2">"./examples/tpch/data/customer.parquet"</span><span
class="p">)</span>
</code></pre></div>
+<p><a href="https://github.com/apache/datafusion-python/pull/980";>PR 980</a>
adds a method for setting up a session context to use URL tables. With
+this enabled, you can use a path to a local file as a table name. An example
+of how to use this is demonstrated in the following snippet.</p>
<div class="codehilite"><pre><span></span><code><span class="kn">import</span>
<span class="nn">datafusion</span>
<span class="n">ctx</span> <span class="o">=</span> <span
class="n">datafusion</span><span class="o">.</span><span
class="n">SessionContext</span><span class="p">()</span><span
class="o">.</span><span class="n">enable_url_table</span><span
class="p">()</span>
<span class="n">df</span> <span class="o">=</span> <span
class="n">ctx</span><span class="o">.</span><span class="n">table</span><span
class="p">(</span><span
class="s2">"./examples/tpch/data/customer.parquet"</span><span
class="p">)</span>
@@ -102,8 +112,18 @@ excellent compression scheme that balances speed and
compression ratio. Users ca
save their Parquet files uncompressed by passing in the appropriate value to
the
<code>compression</code> argument when calling
<code>DataFrame.write_parquet</code>.</p>
<h2>UDF Decorators</h2>
-<p>https://github.com/apache/datafusion-python/pull/1040
-https://github.com/apache/datafusion-python/pull/1061</p>
+<p>In <a href="https://github.com/apache/datafusion-python/pull/1040";>PR
1040</a> and <a href="https://github.com/apache/datafusion-python/pull/1061";>PR
1061</a> we add methods to make creating user defined functions
+easier and take advantage of Python decorators. With these PRs you can save a
step
+from defining a method and then defining a udf of that method. Instead you can
+simply add the appropriate <code>udf</code> decorator. Similar methods exist
for aggregate
+and window user defined functions.</p>
+<div class="codehilite"><pre><span></span><code><span
class="nd">@udf</span><span class="p">([</span><span class="n">pa</span><span
class="o">.</span><span class="n">int64</span><span class="p">(),</span> <span
class="n">pa</span><span class="o">.</span><span class="n">int64</span><span
class="p">()],</span> <span class="n">pa</span><span class="o">.</span><span
class="n">bool_</span><span class="p">(),</span> <span
class="s2">"stable"</span><span class="p">)</span>
+<span class="k">def</span> <span class="nf">my_custom_function</span><span
class="p">(</span>
+ <span class="n">age</span><span class="p">:</span> <span
class="n">pa</span><span class="o">.</span><span class="n">Array</span><span
class="p">,</span>
+ <span class="n">favorite_number</span><span class="p">:</span> <span
class="n">pa</span><span class="o">.</span><span class="n">Array</span><span
class="p">,</span>
+<span class="p">)</span> <span class="o">-></span> <span
class="n">pa</span><span class="o">.</span><span class="n">Array</span><span
class="p">:</span>
+ <span class="k">pass</span>
+</code></pre></div>
<h2><code>uv</code> package management</h2>
<p><a href="https://github.com/astral-sh/uv";>uv</a> is an extremely fast
Python package manager, written in Rust. In the previous version
of <code>datafusion-python</code> we had a combination of settings of PyPi and
Conda. Instead, we
@@ -111,12 +131,11 @@ switch to using <a
href="https://github.com/astral-sh/uv";>uv</a> is our primary
<p>For most users of DataFusion, this change will be transparent. You can
still install
via <code>pip</code> or <code>conda</code>. For developers, the instructions
in the repository have been updated.</p>
<h2><code>ruff</code> code cleanup</h2>
-<p>https://github.com/apache/datafusion-python/pull/1055
-https://github.com/apache/datafusion-python/pull/1062</p>
+<p>In <a href="https://github.com/apache/datafusion-python/pull/1055";>PR
1055</a> and <a href="https://github.com/apache/datafusion-python/pull/1062";>PR
1062</a> - TODO(tsaucer) </p>
<h2>Improved Jupyter Notebook rendering</h2>
-<p>https://github.com/apache/datafusion-python/pull/1036</p>
-<h2>Documentation</h2>
-<p>https://github.com/apache/datafusion-python/pull/1031/files</p>
+<p><a href="https://github.com/apache/datafusion-python/pull/1036";>PR 1036</a>
changed the way tables are rendered in jupyter notebooks - TODO(tsaucer)</p>
+<h2>Extensions Documentation</h2>
+<p>We have recently added <a
href="https://datafusion.apache.org/python/contributor-guide/ffi.html";>Extensions
Documentation</a> to the DataFusion Python website. - TODO(tsaucer)</p>
<h2>Migration Guide</h2>
<p>During the upgrade from <a
href="https://github.com/apache/datafusion/blob/main/dev/changelog/43.0.0.md";>DataFusion
43.0.0</a> to [DataFusion 44.0.0] as our upstream core
dependency, we discovered a few changes were necessary within our repository
and our
@@ -138,9 +157,9 @@ supported.</li>
</ul>
<h2>Coming Soon</h2>
<ul>
-<li>Reusable DataFusion UDFs</li>
-<li>contrib table providers</li>
-<li>catalog and schema providers</li>
+<li>Reusable DataFusion UDFs - TODO(tsaucer)</li>
+<li>contrib table providers - TODO(tsaucer)</li>
+<li>catalog and schema providers - TODO(tsaucer)</li>
</ul>
<h2>Appreciation</h2>
<p>TODO : UPDATE WITH LATEST LIST UP TO 46.0.0</p>
diff --git a/blog/feeds/all-en.atom.xml b/blog/feeds/all-en.atom.xml
index c9735df..5748f10 100644
--- a/blog/feeds/all-en.atom.xml
+++ b/blog/feeds/all-en.atom.xml
@@ -1278,10 +1278,20 @@ blog post for <a
href="https://datafusion.apache.org/blog/2024/12/14/datafusi
that can be found in the <a
href="https://github.com/apache/datafusion-python/tree/main/dev/changelog">changelogs</a>.</p>
<p>We highly recommend reviewing the upstream <a
href="https://datafusion.apache.org/blog/2025/03/24/datafusion-46.0.0">DataFusion
46.0.0</a> announcement.</p>
<h2>Easier file reading</h2>
-<p>https://github.com/apache/datafusion-python/pull/982</p>
+<p>In these releases we have introduced two new ways to more easily read
files into
+DataFrames.</p>
+<p><a
href="https://github.com/apache/datafusion-python/pull/982">PR 982</a>
introduced a series of easier read functions for Parquet, JSON, CSV, and
+AVRO files. This introduces a concept of a global context that is available by
+default when using these methods. Now instead of creating a default Session
+Context and then calling the read methods, you can simply import these read
+alternative methods and begin working with your DataFrames. Below is an
example of
+how easy to use this new approach is.</p>
<div
class="codehilite"><pre><span></span><code><span
class="kn">from</span> <span
class="nn">datafusion.io</span> <span
class="kn">import</span> <span
class="n">read_parquet</span>
<span class="n">df</span> <span class="o">=</span>
<span class="n">read_parquet</span><span
class="p">(</span><span class="n">path</span><span
class="o">=</span><span
class="s2">"./examples/tpch/data/customer.parquet"</span><span
class="p">)</span>
</code></pre></div>
+<p><a
href="https://github.com/apache/datafusion-python/pull/980">PR 980</a>
adds a method for setting up a session context to use URL tables. With
+this enabled, you can use a path to a local file as a table name. An example
+of how to use this is demonstrated in the following snippet.</p>
<div
class="codehilite"><pre><span></span><code><span
class="kn">import</span> <span class="nn">datafusion</span>
<span class="n">ctx</span> <span class="o">=</span>
<span class="n">datafusion</span><span
class="o">.</span><span
class="n">SessionContext</span><span
class="p">()</span><span class="o">.</span><span
class="n">enable_url_table</span><span class="p">()</span>
<span class="n">df</span> <span class="o">=</span>
<span class="n">ctx</span><span
class="o">.</span><span class="n">table</span><span
class="p">(</span><span
class="s2">"./examples/tpch/data/customer.parquet"</span><span
class="p">)</span>
@@ -1313,8 +1323,18 @@ excellent compression scheme that balances speed and
compression ratio. Users ca
save their Parquet files uncompressed by passing in the appropriate value to
the
<code>compression</code> argument when calling
<code>DataFrame.write_parquet</code>.</p>
<h2>UDF Decorators</h2>
-<p>https://github.com/apache/datafusion-python/pull/1040
-https://github.com/apache/datafusion-python/pull/1061</p>
+<p>In <a
href="https://github.com/apache/datafusion-python/pull/1040">PR
1040</a> and <a
href="https://github.com/apache/datafusion-python/pull/1061">PR
1061</a> we add methods to make creating user defined functions
+easier and take advantage of Python decorators. With these PRs you can save a
step
+from defining a method and then defining a udf of that method. Instead you can
+simply add the appropriate <code>udf</code> decorator. Similar
methods exist for aggregate
+and window user defined functions.</p>
+<div
class="codehilite"><pre><span></span><code><span
class="nd">@udf</span><span class="p">([</span><span
class="n">pa</span><span class="o">.</span><span
class="n">int64</span><span class="p">(),</span> <span
class="n">pa</span><span class="o">.</span><span
class="n">int64</span><span class="p">()],</span> <span
class="n">pa</spa [...]
+<span class="k">def</span> <span
class="nf">my_custom_function</span><span
class="p">(</span>
+ <span class="n">age</span><span class="p">:</span>
<span class="n">pa</span><span
class="o">.</span><span class="n">Array</span><span
class="p">,</span>
+ <span class="n">favorite_number</span><span
class="p">:</span> <span class="n">pa</span><span
class="o">.</span><span class="n">Array</span><span
class="p">,</span>
+<span class="p">)</span> <span
class="o">-&gt;</span> <span
class="n">pa</span><span class="o">.</span><span
class="n">Array</span><span class="p">:</span>
+ <span class="k">pass</span>
+</code></pre></div>
<h2><code>uv</code> package management</h2>
<p><a href="https://github.com/astral-sh/uv">uv</a> is an
extremely fast Python package manager, written in Rust. In the previous version
of <code>datafusion-python</code> we had a combination of settings
of PyPi and Conda. Instead, we
@@ -1322,12 +1342,11 @@ switch to using <a
href="https://github.com/astral-sh/uv">uv</a> is
<p>For most users of DataFusion, this change will be transparent. You
can still install
via <code>pip</code> or <code>conda</code>. For
developers, the instructions in the repository have been updated.</p>
<h2><code>ruff</code> code cleanup</h2>
-<p>https://github.com/apache/datafusion-python/pull/1055
-https://github.com/apache/datafusion-python/pull/1062</p>
+<p>In <a
href="https://github.com/apache/datafusion-python/pull/1055">PR
1055</a> and <a
href="https://github.com/apache/datafusion-python/pull/1062">PR
1062</a> - TODO(tsaucer) </p>
<h2>Improved Jupyter Notebook rendering</h2>
-<p>https://github.com/apache/datafusion-python/pull/1036</p>
-<h2>Documentation</h2>
-<p>https://github.com/apache/datafusion-python/pull/1031/files</p>
+<p><a
href="https://github.com/apache/datafusion-python/pull/1036">PR
1036</a> changed the way tables are rendered in jupyter notebooks -
TODO(tsaucer)</p>
+<h2>Extensions Documentation</h2>
+<p>We have recently added <a
href="https://datafusion.apache.org/python/contributor-guide/ffi.html">Extensions
Documentation</a> to the DataFusion Python website. -
TODO(tsaucer)</p>
<h2>Migration Guide</h2>
<p>During the upgrade from <a
href="https://github.com/apache/datafusion/blob/main/dev/changelog/43.0.0.md">DataFusion
43.0.0</a> to [DataFusion 44.0.0] as our upstream core
dependency, we discovered a few changes were necessary within our repository
and our
@@ -1349,9 +1368,9 @@ supported.</li>
</ul>
<h2>Coming Soon</h2>
<ul>
-<li>Reusable DataFusion UDFs</li>
-<li>contrib table providers</li>
-<li>catalog and schema providers</li>
+<li>Reusable DataFusion UDFs - TODO(tsaucer)</li>
+<li>contrib table providers - TODO(tsaucer)</li>
+<li>catalog and schema providers - TODO(tsaucer)</li>
</ul>
<h2>Appreciation</h2>
<p>TODO : UPDATE WITH LATEST LIST UP TO 46.0.0</p>
diff --git a/blog/feeds/blog.atom.xml b/blog/feeds/blog.atom.xml
index fb94fa3..138d1e3 100644
--- a/blog/feeds/blog.atom.xml
+++ b/blog/feeds/blog.atom.xml
@@ -1278,10 +1278,20 @@ blog post for <a
href="https://datafusion.apache.org/blog/2024/12/14/datafusi
that can be found in the <a
href="https://github.com/apache/datafusion-python/tree/main/dev/changelog">changelogs</a>.</p>
<p>We highly recommend reviewing the upstream <a
href="https://datafusion.apache.org/blog/2025/03/24/datafusion-46.0.0">DataFusion
46.0.0</a> announcement.</p>
<h2>Easier file reading</h2>
-<p>https://github.com/apache/datafusion-python/pull/982</p>
+<p>In these releases we have introduced two new ways to more easily read
files into
+DataFrames.</p>
+<p><a
href="https://github.com/apache/datafusion-python/pull/982">PR 982</a>
introduced a series of easier read functions for Parquet, JSON, CSV, and
+AVRO files. This introduces a concept of a global context that is available by
+default when using these methods. Now instead of creating a default Session
+Context and then calling the read methods, you can simply import these read
+alternative methods and begin working with your DataFrames. Below is an
example of
+how easy to use this new approach is.</p>
<div
class="codehilite"><pre><span></span><code><span
class="kn">from</span> <span
class="nn">datafusion.io</span> <span
class="kn">import</span> <span
class="n">read_parquet</span>
<span class="n">df</span> <span class="o">=</span>
<span class="n">read_parquet</span><span
class="p">(</span><span class="n">path</span><span
class="o">=</span><span
class="s2">"./examples/tpch/data/customer.parquet"</span><span
class="p">)</span>
</code></pre></div>
+<p><a
href="https://github.com/apache/datafusion-python/pull/980">PR 980</a>
adds a method for setting up a session context to use URL tables. With
+this enabled, you can use a path to a local file as a table name. An example
+of how to use this is demonstrated in the following snippet.</p>
<div
class="codehilite"><pre><span></span><code><span
class="kn">import</span> <span class="nn">datafusion</span>
<span class="n">ctx</span> <span class="o">=</span>
<span class="n">datafusion</span><span
class="o">.</span><span
class="n">SessionContext</span><span
class="p">()</span><span class="o">.</span><span
class="n">enable_url_table</span><span class="p">()</span>
<span class="n">df</span> <span class="o">=</span>
<span class="n">ctx</span><span
class="o">.</span><span class="n">table</span><span
class="p">(</span><span
class="s2">"./examples/tpch/data/customer.parquet"</span><span
class="p">)</span>
@@ -1313,8 +1323,18 @@ excellent compression scheme that balances speed and
compression ratio. Users ca
save their Parquet files uncompressed by passing in the appropriate value to
the
<code>compression</code> argument when calling
<code>DataFrame.write_parquet</code>.</p>
<h2>UDF Decorators</h2>
-<p>https://github.com/apache/datafusion-python/pull/1040
-https://github.com/apache/datafusion-python/pull/1061</p>
+<p>In <a
href="https://github.com/apache/datafusion-python/pull/1040">PR
1040</a> and <a
href="https://github.com/apache/datafusion-python/pull/1061">PR
1061</a> we add methods to make creating user defined functions
+easier and take advantage of Python decorators. With these PRs you can save a
step
+from defining a method and then defining a udf of that method. Instead you can
+simply add the appropriate <code>udf</code> decorator. Similar
methods exist for aggregate
+and window user defined functions.</p>
+<div
class="codehilite"><pre><span></span><code><span
class="nd">@udf</span><span class="p">([</span><span
class="n">pa</span><span class="o">.</span><span
class="n">int64</span><span class="p">(),</span> <span
class="n">pa</span><span class="o">.</span><span
class="n">int64</span><span class="p">()],</span> <span
class="n">pa</spa [...]
+<span class="k">def</span> <span
class="nf">my_custom_function</span><span
class="p">(</span>
+ <span class="n">age</span><span class="p">:</span>
<span class="n">pa</span><span
class="o">.</span><span class="n">Array</span><span
class="p">,</span>
+ <span class="n">favorite_number</span><span
class="p">:</span> <span class="n">pa</span><span
class="o">.</span><span class="n">Array</span><span
class="p">,</span>
+<span class="p">)</span> <span
class="o">-&gt;</span> <span
class="n">pa</span><span class="o">.</span><span
class="n">Array</span><span class="p">:</span>
+ <span class="k">pass</span>
+</code></pre></div>
<h2><code>uv</code> package management</h2>
<p><a href="https://github.com/astral-sh/uv">uv</a> is an
extremely fast Python package manager, written in Rust. In the previous version
of <code>datafusion-python</code> we had a combination of settings
of PyPi and Conda. Instead, we
@@ -1322,12 +1342,11 @@ switch to using <a
href="https://github.com/astral-sh/uv">uv</a> is
<p>For most users of DataFusion, this change will be transparent. You
can still install
via <code>pip</code> or <code>conda</code>. For
developers, the instructions in the repository have been updated.</p>
<h2><code>ruff</code> code cleanup</h2>
-<p>https://github.com/apache/datafusion-python/pull/1055
-https://github.com/apache/datafusion-python/pull/1062</p>
+<p>In <a
href="https://github.com/apache/datafusion-python/pull/1055">PR
1055</a> and <a
href="https://github.com/apache/datafusion-python/pull/1062">PR
1062</a> - TODO(tsaucer) </p>
<h2>Improved Jupyter Notebook rendering</h2>
-<p>https://github.com/apache/datafusion-python/pull/1036</p>
-<h2>Documentation</h2>
-<p>https://github.com/apache/datafusion-python/pull/1031/files</p>
+<p><a
href="https://github.com/apache/datafusion-python/pull/1036">PR
1036</a> changed the way tables are rendered in jupyter notebooks -
TODO(tsaucer)</p>
+<h2>Extensions Documentation</h2>
+<p>We have recently added <a
href="https://datafusion.apache.org/python/contributor-guide/ffi.html">Extensions
Documentation</a> to the DataFusion Python website. -
TODO(tsaucer)</p>
<h2>Migration Guide</h2>
<p>During the upgrade from <a
href="https://github.com/apache/datafusion/blob/main/dev/changelog/43.0.0.md">DataFusion
43.0.0</a> to [DataFusion 44.0.0] as our upstream core
dependency, we discovered a few changes were necessary within our repository
and our
@@ -1349,9 +1368,9 @@ supported.</li>
</ul>
<h2>Coming Soon</h2>
<ul>
-<li>Reusable DataFusion UDFs</li>
-<li>contrib table providers</li>
-<li>catalog and schema providers</li>
+<li>Reusable DataFusion UDFs - TODO(tsaucer)</li>
+<li>contrib table providers - TODO(tsaucer)</li>
+<li>catalog and schema providers - TODO(tsaucer)</li>
</ul>
<h2>Appreciation</h2>
<p>TODO : UPDATE WITH LATEST LIST UP TO 46.0.0</p>
diff --git a/blog/feeds/timsaucer.atom.xml b/blog/feeds/timsaucer.atom.xml
index 3dc0e18..2fb939b 100644
--- a/blog/feeds/timsaucer.atom.xml
+++ b/blog/feeds/timsaucer.atom.xml
@@ -44,10 +44,20 @@ blog post for <a
href="https://datafusion.apache.org/blog/2024/12/14/datafusi
that can be found in the <a
href="https://github.com/apache/datafusion-python/tree/main/dev/changelog">changelogs</a>.</p>
<p>We highly recommend reviewing the upstream <a
href="https://datafusion.apache.org/blog/2025/03/24/datafusion-46.0.0">DataFusion
46.0.0</a> announcement.</p>
<h2>Easier file reading</h2>
-<p>https://github.com/apache/datafusion-python/pull/982</p>
+<p>In these releases we have introduced two new ways to more easily read
files into
+DataFrames.</p>
+<p><a
href="https://github.com/apache/datafusion-python/pull/982">PR 982</a>
introduced a series of easier read functions for Parquet, JSON, CSV, and
+AVRO files. This introduces a concept of a global context that is available by
+default when using these methods. Now instead of creating a default Session
+Context and then calling the read methods, you can simply import these read
+alternative methods and begin working with your DataFrames. Below is an
example of
+how easy to use this new approach is.</p>
<div
class="codehilite"><pre><span></span><code><span
class="kn">from</span> <span
class="nn">datafusion.io</span> <span
class="kn">import</span> <span
class="n">read_parquet</span>
<span class="n">df</span> <span class="o">=</span>
<span class="n">read_parquet</span><span
class="p">(</span><span class="n">path</span><span
class="o">=</span><span
class="s2">"./examples/tpch/data/customer.parquet"</span><span
class="p">)</span>
</code></pre></div>
+<p><a
href="https://github.com/apache/datafusion-python/pull/980">PR 980</a>
adds a method for setting up a session context to use URL tables. With
+this enabled, you can use a path to a local file as a table name. An example
+of how to use this is demonstrated in the following snippet.</p>
<div
class="codehilite"><pre><span></span><code><span
class="kn">import</span> <span class="nn">datafusion</span>
<span class="n">ctx</span> <span class="o">=</span>
<span class="n">datafusion</span><span
class="o">.</span><span
class="n">SessionContext</span><span
class="p">()</span><span class="o">.</span><span
class="n">enable_url_table</span><span class="p">()</span>
<span class="n">df</span> <span class="o">=</span>
<span class="n">ctx</span><span
class="o">.</span><span class="n">table</span><span
class="p">(</span><span
class="s2">"./examples/tpch/data/customer.parquet"</span><span
class="p">)</span>
@@ -79,8 +89,18 @@ excellent compression scheme that balances speed and
compression ratio. Users ca
save their Parquet files uncompressed by passing in the appropriate value to
the
<code>compression</code> argument when calling
<code>DataFrame.write_parquet</code>.</p>
<h2>UDF Decorators</h2>
-<p>https://github.com/apache/datafusion-python/pull/1040
-https://github.com/apache/datafusion-python/pull/1061</p>
+<p>In <a
href="https://github.com/apache/datafusion-python/pull/1040">PR
1040</a> and <a
href="https://github.com/apache/datafusion-python/pull/1061">PR
1061</a> we add methods to make creating user defined functions
+easier and take advantage of Python decorators. With these PRs you can save a
step
+from defining a method and then defining a udf of that method. Instead you can
+simply add the appropriate <code>udf</code> decorator. Similar
methods exist for aggregate
+and window user defined functions.</p>
+<div
class="codehilite"><pre><span></span><code><span
class="nd">@udf</span><span class="p">([</span><span
class="n">pa</span><span class="o">.</span><span
class="n">int64</span><span class="p">(),</span> <span
class="n">pa</span><span class="o">.</span><span
class="n">int64</span><span class="p">()],</span> <span
class="n">pa</spa [...]
+<span class="k">def</span> <span
class="nf">my_custom_function</span><span
class="p">(</span>
+ <span class="n">age</span><span class="p">:</span>
<span class="n">pa</span><span
class="o">.</span><span class="n">Array</span><span
class="p">,</span>
+ <span class="n">favorite_number</span><span
class="p">:</span> <span class="n">pa</span><span
class="o">.</span><span class="n">Array</span><span
class="p">,</span>
+<span class="p">)</span> <span
class="o">-&gt;</span> <span
class="n">pa</span><span class="o">.</span><span
class="n">Array</span><span class="p">:</span>
+ <span class="k">pass</span>
+</code></pre></div>
<h2><code>uv</code> package management</h2>
<p><a href="https://github.com/astral-sh/uv">uv</a> is an
extremely fast Python package manager, written in Rust. In the previous version
of <code>datafusion-python</code> we had a combination of settings
of PyPi and Conda. Instead, we
@@ -88,12 +108,11 @@ switch to using <a
href="https://github.com/astral-sh/uv">uv</a> is
<p>For most users of DataFusion, this change will be transparent. You
can still install
via <code>pip</code> or <code>conda</code>. For
developers, the instructions in the repository have been updated.</p>
<h2><code>ruff</code> code cleanup</h2>
-<p>https://github.com/apache/datafusion-python/pull/1055
-https://github.com/apache/datafusion-python/pull/1062</p>
+<p>In <a
href="https://github.com/apache/datafusion-python/pull/1055">PR
1055</a> and <a
href="https://github.com/apache/datafusion-python/pull/1062">PR
1062</a> - TODO(tsaucer) </p>
<h2>Improved Jupyter Notebook rendering</h2>
-<p>https://github.com/apache/datafusion-python/pull/1036</p>
-<h2>Documentation</h2>
-<p>https://github.com/apache/datafusion-python/pull/1031/files</p>
+<p><a
href="https://github.com/apache/datafusion-python/pull/1036">PR
1036</a> changed the way tables are rendered in jupyter notebooks -
TODO(tsaucer)</p>
+<h2>Extensions Documentation</h2>
+<p>We have recently added <a
href="https://datafusion.apache.org/python/contributor-guide/ffi.html">Extensions
Documentation</a> to the DataFusion Python website. -
TODO(tsaucer)</p>
<h2>Migration Guide</h2>
<p>During the upgrade from <a
href="https://github.com/apache/datafusion/blob/main/dev/changelog/43.0.0.md">DataFusion
43.0.0</a> to [DataFusion 44.0.0] as our upstream core
dependency, we discovered a few changes were necessary within our repository
and our
@@ -115,9 +134,9 @@ supported.</li>
</ul>
<h2>Coming Soon</h2>
<ul>
-<li>Reusable DataFusion UDFs</li>
-<li>contrib table providers</li>
-<li>catalog and schema providers</li>
+<li>Reusable DataFusion UDFs - TODO(tsaucer)</li>
+<li>contrib table providers - TODO(tsaucer)</li>
+<li>catalog and schema providers - TODO(tsaucer)</li>
</ul>
<h2>Appreciation</h2>
<p>TODO : UPDATE WITH LATEST LIST UP TO 46.0.0</p>
---------------------------------------------------------------------
To unsubscribe, e-mail: commits-unsubscr...@datafusion.apache.org
For additional commands, e-mail: commits-h...@datafusion.apache.org
