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| <section id="why-ffi"> |
| <span id="extension-why-ffi"></span><h1>Why FFI<a class="headerlink" href="#why-ffi" 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 describes the problem that makes the obvious approach |
| fail, and the approach this project uses instead.</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 its 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. That 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, using a well defined set of interfaces — see |
| their <a class="reference external" href="https://arrow.apache.org/docs/format/CStreamInterface.html">stream interface</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. Beyond |
| transferring data, <code class="docutils literal notranslate"><span class="pre">pyarrow</span></code> goes one step further and makes the interfaces |
| themselves easy to share in Python, by exposing PyCapsules that contain the |
| expected functionality.</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 an FFI stable struct.</p></li> |
| </ul> |
| <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> |
| </section> |
| <section id="if-ffi-does-not-yet-cover-what-you-need"> |
| <h2>If FFI does not yet cover what you need<a class="headerlink" href="#if-ffi-does-not-yet-cover-what-you-need" title="Link to this heading">#</a></h2> |
| <div class="admonition note"> |
| <p class="admonition-title">Note</p> |
| <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> |
| <p>The better path is to open an issue describing what you need exposed. The FFI |
| surface in the <a class="reference external" href="https://crates.io/crates/datafusion-ffi">datafusion-ffi</a> crate grows in response to these.</p> |
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