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| <section id="python-extensions"> |
| <h1>Python Extensions<a class="headerlink" href="#python-extensions" title="Link to this heading">¶</a></h1> |
| <p>The DataFusion in Python project is designed to allow users to extend its functionality in a few core |
| areas. Ideally many users would like to package their extensions as a Python package and easily |
| integrate that package with this project. This page serves to describe some of the challenges we face |
| when doing these integrations and the approach our project uses.</p> |
| <section id="the-primary-issue"> |
| <h2>The Primary Issue<a class="headerlink" href="#the-primary-issue" title="Link to this heading">¶</a></h2> |
| <p>Suppose you wish to use DataFusion and you have a custom data source that can produce tables that |
| can then be queried against, similar to how you can register a <a class="reference internal" href="../user-guide/io/csv.html#io-csv"><span class="std std-ref">CSV</span></a> or |
| <a class="reference internal" href="../user-guide/io/parquet.html#io-parquet"><span class="std std-ref">Parquet</span></a> file. In DataFusion terminology, you likely want to implement a |
| <a class="reference internal" href="../user-guide/io/table_provider.html#io-custom-table-provider"><span class="std std-ref">Custom Table Provider</span></a>. In an effort to make your data source |
| as performant as possible and to utilize the features of DataFusion, you may decide to write |
| your source in Rust and then expose it through <a class="reference external" href="https://pyo3.rs">PyO3</a> as a Python library.</p> |
| <p>At first glance, it may appear the best way to do this is to add the <code class="docutils literal notranslate"><span class="pre">datafusion-python</span></code> |
| crate as a dependency, provide a <code class="docutils literal notranslate"><span class="pre">PyTable</span></code>, and then to register it with the |
| <code class="docutils literal notranslate"><span class="pre">SessionContext</span></code>. Unfortunately, this will not work.</p> |
| <p>When you produce your code as a Python library and it needs to interact with the DataFusion |
| library, at the lowest level they communicate through an Application Binary Interface (ABI). |
| The acronym sounds similar to API (Application Programming Interface), but it is distinctly |
| different.</p> |
| <p>The ABI sets the standard for how these libraries can share data and functions between each |
| other. One of the key differences between Rust and other programming languages is that Rust |
| does not have a stable ABI. What this means in practice is that if you compile a Rust library |
| with one version of the <code class="docutils literal notranslate"><span class="pre">rustc</span></code> compiler and I compile another library to interface with it |
| but I use a different version of the compiler, there is no guarantee the interface will be |
| the same.</p> |
| <p>In practice, this means that a Python library built with <code class="docutils literal notranslate"><span class="pre">datafusion-python</span></code> as a Rust |
| dependency will generally <strong>not</strong> be compatible with the DataFusion Python package, even |
| if they reference the same version of <code class="docutils literal notranslate"><span class="pre">datafusion-python</span></code>. If you attempt to do this, it may |
| work on your local computer if you have built both packages with the same optimizations. |
| This can sometimes lead to a false expectation that the code will work, but it frequently |
| breaks the moment you try to use your package against the released packages.</p> |
| <p>You can find more information about the Rust ABI in their |
| <a class="reference external" href="https://doc.rust-lang.org/reference/abi.html">online documentation</a>.</p> |
| </section> |
| <section id="the-ffi-approach"> |
| <h2>The FFI Approach<a class="headerlink" href="#the-ffi-approach" title="Link to this heading">¶</a></h2> |
| <p>Rust supports interacting with other programming languages through it’s Foreign Function |
| Interface (FFI). The advantage of using the FFI is that it enables you to write data structures |
| and functions that have a stable ABI. The allows you to use Rust code with C, Python, and |
| other languages. In fact, the <a class="reference external" href="https://pyo3.rs">PyO3</a> library uses the FFI to share data |
| and functions between Python and Rust.</p> |
| <p>The approach we are taking in the DataFusion in Python project is to incrementally expose |
| more portions of the DataFusion project via FFI interfaces. This allows users to write Rust |
| code that does <strong>not</strong> require the <code class="docutils literal notranslate"><span class="pre">datafusion-python</span></code> crate as a dependency, expose their |
| code in Python via PyO3, and have it interact with the DataFusion Python package.</p> |
| <p>Early adopters of this approach include <a class="reference external" href="https://delta-io.github.io/delta-rs/">delta-rs</a> |
| who has adapted their Table Provider for use in <code class="docutils literal notranslate"><span class="pre">`datafusion-python`</span></code> with only a few lines |
| of code. Also, the DataFusion Python project uses the existing definitions from |
| <a class="reference external" href="https://arrow.apache.org/docs/format/CStreamInterface.html">Apache Arrow CStream Interface</a> |
| to support importing <strong>and</strong> exporting tables. Any Python package that supports reading |
| the Arrow C Stream interface can work with DataFusion Python out of the box! You can read |
| more about working with Arrow sources in the <a class="reference internal" href="../user-guide/data-sources.html#user-guide-data-sources"><span class="std std-ref">Data Sources</span></a> |
| page.</p> |
| <p>To learn more about the Foreign Function Interface in Rust, the |
| <a class="reference external" href="https://doc.rust-lang.org/nomicon/ffi.html">Rustonomicon</a> is a good resource.</p> |
| </section> |
| <section id="inspiration-from-arrow"> |
| <h2>Inspiration from Arrow<a class="headerlink" href="#inspiration-from-arrow" title="Link to this heading">¶</a></h2> |
| <p>DataFusion is built upon <a class="reference external" href="https://arrow.apache.org/">Apache Arrow</a>. The canonical Python |
| Arrow implementation, <a class="reference external" href="https://arrow.apache.org/docs/python/index.html">pyarrow</a> provides |
| an excellent way to share Arrow data between Python projects without performing any copy |
| operations on the data. They do this by using a well defined set of interfaces. You can |
| find the details about their stream interface |
| <a class="reference external" href="https://arrow.apache.org/docs/format/CStreamInterface.html">here</a>. The |
| <a class="reference external" href="https://github.com/apache/arrow-rs">Rust Arrow Implementation</a> also supports these |
| <code class="docutils literal notranslate"><span class="pre">C</span></code> style definitions via the Foreign Function Interface.</p> |
| <p>In addition to using these interfaces to transfer Arrow data between libraries, <code class="docutils literal notranslate"><span class="pre">pyarrow</span></code> |
| goes one step further to make sharing the interfaces easier in Python. They do this |
| by exposing PyCapsules that contain the expected functionality.</p> |
| <p>You can learn more about PyCapsules from the official |
| <a class="reference external" href="https://docs.python.org/3/c-api/capsule.html">Python online documentation</a>. PyCapsules |
| have excellent support in PyO3 already. The |
| <a class="reference external" href="https://pyo3.rs/main/doc/pyo3/types/struct.pycapsule">PyO3 online documentation</a> is a good source |
| for more details on using PyCapsules in Rust.</p> |
| <p>Two lessons we leverage from the Arrow project in DataFusion Python are:</p> |
| <ul class="simple"> |
| <li><p>We reuse the existing Arrow FFI functionality wherever possible.</p></li> |
| <li><p>We expose PyCapsules that contain a FFI stable struct.</p></li> |
| </ul> |
| </section> |
| <section id="implementation-details"> |
| <h2>Implementation Details<a class="headerlink" href="#implementation-details" title="Link to this heading">¶</a></h2> |
| <p>The bulk of the code necessary to perform our FFI operations is in the upstream |
| <a class="reference external" href="https://datafusion.apache.org/">DataFusion</a> core repository. You can review the code and |
| documentation in the <a class="reference external" href="https://crates.io/crates/datafusion-ffi">datafusion-ffi</a> crate.</p> |
| <p>Our FFI implementation is narrowly focused at sharing data and functions with Rust backed |
| libraries. This allows us to use the <a class="reference external" href="https://crates.io/crates/abi_stable">abi_stable crate</a>. |
| This is an excellent crate that allows for easy conversion between Rust native types |
| and FFI-safe alternatives. For example, if you needed to pass a <code class="docutils literal notranslate"><span class="pre">Vec<String></span></code> via FFI, |
| you can simply convert it to a <code class="docutils literal notranslate"><span class="pre">RVec<RString></span></code> in an intuitive manner. It also supports |
| features like <code class="docutils literal notranslate"><span class="pre">RResult</span></code> and <code class="docutils literal notranslate"><span class="pre">ROption</span></code> that do not have an obvious translation to a |
| C equivalent.</p> |
| <p>The <a class="reference external" href="https://crates.io/crates/datafusion-ffi">datafusion-ffi</a> crate has been designed to make it easy to convert from DataFusion |
| traits into their FFI counterparts. For example, if you have defined a custom |
| <a class="reference external" href="https://docs.rs/datafusion/45.0.0/datafusion/catalog/trait.TableProvider.html">TableProvider</a> |
| and you want to create a sharable FFI counterpart, you could write:</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="kd">let</span><span class="w"> </span><span class="n">my_provider</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">MyTableProvider</span><span class="p">::</span><span class="n">default</span><span class="p">();</span> |
| <span class="kd">let</span><span class="w"> </span><span class="n">ffi_provider</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">FFI_TableProvider</span><span class="p">::</span><span class="n">new</span><span class="p">(</span><span class="n">Arc</span><span class="p">::</span><span class="n">new</span><span class="p">(</span><span class="n">my_provider</span><span class="p">),</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"> </span><span class="nb">None</span><span class="p">);</span> |
| </pre></div> |
| </div> |
| </section> |
| <section id="pyo3-class-mutability-guidelines"> |
| <span id="ffi-pyclass-mutability"></span><h2>PyO3 class mutability guidelines<a class="headerlink" href="#pyo3-class-mutability-guidelines" title="Link to this heading">¶</a></h2> |
| <p>PyO3 bindings should present immutable wrappers whenever a struct stores shared or |
| interior-mutable state. In practice this means that any <code class="docutils literal notranslate"><span class="pre">#[pyclass]</span></code> containing an |
| <code class="docutils literal notranslate"><span class="pre">Arc<RwLock<_>></span></code> or similar synchronized primitive must opt into <code class="docutils literal notranslate"><span class="pre">#[pyclass(frozen)]</span></code> |
| unless there is a compelling reason not to.</p> |
| <p>The <a class="reference internal" href="../autoapi/datafusion/index.html#module-datafusion" title="datafusion"><code class="xref py py-mod docutils literal notranslate"><span class="pre">datafusion</span></code></a> configuration helpers illustrate the preferred pattern. The |
| <code class="docutils literal notranslate"><span class="pre">PyConfig</span></code> class in <code class="file docutils literal notranslate"><span class="pre">src/config.rs</span></code> stores an <code class="docutils literal notranslate"><span class="pre">Arc<RwLock<ConfigOptions>></span></code> and is |
| explicitly frozen so callers interact with configuration state through provided methods |
| instead of mutating the container directly:</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="cp">#[pyclass(name = </span><span class="s">"Config"</span><span class="cp">, module = </span><span class="s">"datafusion"</span><span class="cp">, subclass, frozen)]</span> |
| <span class="cp">#[derive(Clone)]</span> |
| <span class="k">pub</span><span class="p">(</span><span class="k">crate</span><span class="p">)</span><span class="w"> </span><span class="k">struct</span><span class="w"> </span><span class="nc">PyConfig</span><span class="w"> </span><span class="p">{</span> |
| <span class="w"> </span><span class="n">config</span><span class="p">:</span><span class="w"> </span><span class="nc">Arc</span><span class="o"><</span><span class="n">RwLock</span><span class="o"><</span><span class="n">ConfigOptions</span><span class="o">>></span><span class="p">,</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| <p>The same approach applies to execution contexts. <code class="docutils literal notranslate"><span class="pre">PySessionContext</span></code> in |
| <code class="file docutils literal notranslate"><span class="pre">src/context.rs</span></code> stays frozen even though it shares mutable state internally via |
| <code class="docutils literal notranslate"><span class="pre">SessionContext</span></code>. This ensures PyO3 tracks borrows correctly while Python-facing APIs |
| clone the inner <code class="docutils literal notranslate"><span class="pre">SessionContext</span></code> or return new wrappers instead of mutating the |
| existing instance in place:</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="cp">#[pyclass(frozen, name = </span><span class="s">"SessionContext"</span><span class="cp">, module = </span><span class="s">"datafusion"</span><span class="cp">, subclass)]</span> |
| <span class="cp">#[derive(Clone)]</span> |
| <span class="k">pub</span><span class="w"> </span><span class="k">struct</span><span class="w"> </span><span class="nc">PySessionContext</span><span class="w"> </span><span class="p">{</span> |
| <span class="w"> </span><span class="k">pub</span><span class="w"> </span><span class="n">ctx</span><span class="p">:</span><span class="w"> </span><span class="nc">SessionContext</span><span class="p">,</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| <p>Occasionally a type must remain mutable—for example when PyO3 attribute setters need to |
| update fields directly. In these rare cases add an inline justification so reviewers and |
| future contributors understand why <code class="docutils literal notranslate"><span class="pre">frozen</span></code> is unsafe to enable. <code class="docutils literal notranslate"><span class="pre">DataTypeMap</span></code> in |
| <code class="file docutils literal notranslate"><span class="pre">src/common/data_type.rs</span></code> includes such a comment because PyO3 still needs to track |
| field updates:</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="c1">// TODO: This looks like this needs pyo3 tracking so leaving unfrozen for now</span> |
| <span class="cp">#[derive(Debug, Clone)]</span> |
| <span class="cp">#[pyclass(name = </span><span class="s">"DataTypeMap"</span><span class="cp">, module = </span><span class="s">"datafusion.common"</span><span class="cp">, subclass)]</span> |
| <span class="k">pub</span><span class="w"> </span><span class="k">struct</span><span class="w"> </span><span class="nc">DataTypeMap</span><span class="w"> </span><span class="p">{</span> |
| <span class="w"> </span><span class="cp">#[pyo3(get, set)]</span> |
| <span class="w"> </span><span class="k">pub</span><span class="w"> </span><span class="n">arrow_type</span><span class="p">:</span><span class="w"> </span><span class="nc">PyDataType</span><span class="p">,</span> |
| <span class="w"> </span><span class="cp">#[pyo3(get, set)]</span> |
| <span class="w"> </span><span class="k">pub</span><span class="w"> </span><span class="n">python_type</span><span class="p">:</span><span class="w"> </span><span class="nc">PythonType</span><span class="p">,</span> |
| <span class="w"> </span><span class="cp">#[pyo3(get, set)]</span> |
| <span class="w"> </span><span class="k">pub</span><span class="w"> </span><span class="n">sql_type</span><span class="p">:</span><span class="w"> </span><span class="nc">SqlType</span><span class="p">,</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| <p>When reviewers encounter a mutable <code class="docutils literal notranslate"><span class="pre">#[pyclass]</span></code> without a comment, they should request |
| an explanation or ask that <code class="docutils literal notranslate"><span class="pre">frozen</span></code> be added. Keeping these wrappers frozen by default |
| helps avoid subtle bugs stemming from PyO3’s interior mutability tracking.</p> |
| <p>If you were interfacing with a library that provided the above <code class="docutils literal notranslate"><span class="pre">FFI_TableProvider</span></code> and |
| you needed to turn it back into an <code class="docutils literal notranslate"><span class="pre">TableProvider</span></code>, you can turn it into a |
| <code class="docutils literal notranslate"><span class="pre">ForeignTableProvider</span></code> with implements the <code class="docutils literal notranslate"><span class="pre">TableProvider</span></code> trait.</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="kd">let</span><span class="w"> </span><span class="n">foreign_provider</span><span class="p">:</span><span class="w"> </span><span class="nc">ForeignTableProvider</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">ffi_provider</span><span class="p">.</span><span class="n">into</span><span class="p">();</span> |
| </pre></div> |
| </div> |
| <p>If you review the code in <a class="reference external" href="https://crates.io/crates/datafusion-ffi">datafusion-ffi</a> you will find that each of the traits we share |
| across the boundary has two portions, one with a <code class="docutils literal notranslate"><span class="pre">FFI_</span></code> prefix and one with a <code class="docutils literal notranslate"><span class="pre">Foreign</span></code> |
| prefix. This is used to distinguish which side of the FFI boundary that struct is |
| designed to be used on. The structures with the <code class="docutils literal notranslate"><span class="pre">FFI_</span></code> prefix are to be used on the |
| <strong>provider</strong> of the structure. In the example we’re showing, this means the code that has |
| written the underlying <code class="docutils literal notranslate"><span class="pre">TableProvider</span></code> implementation to access your custom data source. |
| The structures with the <code class="docutils literal notranslate"><span class="pre">Foreign</span></code> prefix are to be used by the receiver. In this case, |
| it is the <code class="docutils literal notranslate"><span class="pre">datafusion-python</span></code> library.</p> |
| <p>In order to share these FFI structures, we need to wrap them in some kind of Python object |
| that can be used to interface from one package to another. As described in the above |
| section on our inspiration from Arrow, we use <code class="docutils literal notranslate"><span class="pre">PyCapsule</span></code>. We can create a <code class="docutils literal notranslate"><span class="pre">PyCapsule</span></code> |
| for our provider thusly:</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="kd">let</span><span class="w"> </span><span class="n">name</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">CString</span><span class="p">::</span><span class="n">new</span><span class="p">(</span><span class="s">"datafusion_table_provider"</span><span class="p">)</span><span class="o">?</span><span class="p">;</span> |
| <span class="kd">let</span><span class="w"> </span><span class="n">my_capsule</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">PyCapsule</span><span class="p">::</span><span class="n">new_bound</span><span class="p">(</span><span class="n">py</span><span class="p">,</span><span class="w"> </span><span class="n">provider</span><span class="p">,</span><span class="w"> </span><span class="nb">Some</span><span class="p">(</span><span class="n">name</span><span class="p">))</span><span class="o">?</span><span class="p">;</span> |
| </pre></div> |
| </div> |
| <p>On the receiving side, turn this pycapsule object into the <code class="docutils literal notranslate"><span class="pre">FFI_TableProvider</span></code>, which |
| can then be turned into a <code class="docutils literal notranslate"><span class="pre">ForeignTableProvider</span></code> the associated code is:</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="kd">let</span><span class="w"> </span><span class="n">capsule</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">capsule</span><span class="p">.</span><span class="n">downcast</span><span class="p">::</span><span class="o"><</span><span class="n">PyCapsule</span><span class="o">></span><span class="p">()</span><span class="o">?</span><span class="p">;</span> |
| <span class="kd">let</span><span class="w"> </span><span class="n">provider</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="k">unsafe</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="n">capsule</span><span class="p">.</span><span class="n">reference</span><span class="p">::</span><span class="o"><</span><span class="n">FFI_TableProvider</span><span class="o">></span><span class="p">()</span><span class="w"> </span><span class="p">};</span> |
| </pre></div> |
| </div> |
| <p>By convention the <code class="docutils literal notranslate"><span class="pre">datafusion-python</span></code> library expects a Python object that has a |
| <code class="docutils literal notranslate"><span class="pre">TableProvider</span></code> PyCapsule to have this capsule accessible by calling a function named |
| <code class="docutils literal notranslate"><span class="pre">__datafusion_table_provider__</span></code>. You can see a complete working example of how to |
| share a <code class="docutils literal notranslate"><span class="pre">TableProvider</span></code> from one python library to DataFusion Python in the |
| <a class="reference external" href="https://github.com/apache/datafusion-python/tree/main/examples/datafusion-ffi-example">repository examples folder</a>.</p> |
| <p>This section has been written using <code class="docutils literal notranslate"><span class="pre">TableProvider</span></code> as an example. It is the first |
| extension that has been written using this approach and the most thoroughly implemented. |
| As we continue to expose more of the DataFusion features, we intend to follow this same |
| design pattern.</p> |
| </section> |
| <section id="alternative-approach"> |
| <h2>Alternative Approach<a class="headerlink" href="#alternative-approach" title="Link to this heading">¶</a></h2> |
| <p>Suppose you needed to expose some other features of DataFusion and you could not wait |
| for the upstream repository to implement the FFI approach we describe. In this case |
| you decide to create your dependency on the <code class="docutils literal notranslate"><span class="pre">datafusion-python</span></code> crate instead.</p> |
| <p>As we discussed, this is not guaranteed to work across different compiler versions and |
| optimization levels. If you wish to go down this route, there are two approaches we |
| have identified you can use.</p> |
| <ol class="arabic simple"> |
| <li><p>Re-export all of <code class="docutils literal notranslate"><span class="pre">datafusion-python</span></code> yourself with your extensions built in.</p></li> |
| <li><p>Carefully synchronize your software releases with the <code class="docutils literal notranslate"><span class="pre">datafusion-python</span></code> CI build |
| system so that your libraries use the exact same compiler, features, and |
| optimization level.</p></li> |
| </ol> |
| <p>We currently do not recommend either of these approaches as they are difficult to |
| maintain over a long period. Additionally, they require a tight version coupling |
| between libraries.</p> |
| </section> |
| <section id="status-of-work"> |
| <h2>Status of Work<a class="headerlink" href="#status-of-work" title="Link to this heading">¶</a></h2> |
| <p>At the time of this writing, the FFI features are under active development. To see |
| the latest status, we recommend reviewing the code in the <a class="reference external" href="https://crates.io/crates/datafusion-ffi">datafusion-ffi</a> crate.</p> |
| </section> |
| </section> |
| |
| |
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