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| <div class="section" id="feather-file-format"> |
| <span id="feather"></span><h1>Feather File Format<a class="headerlink" href="#feather-file-format" title="Permalink to this headline">¶</a></h1> |
| <p>Feather is a portable file format for storing Arrow tables or data frames (from |
| languages like Python or R) that utilizes the <a class="reference internal" href="ipc.html#ipc"><span class="std std-ref">Arrow IPC format</span></a> |
| internally. Feather was created early in the Arrow project as a proof of |
| concept for fast, language-agnostic data frame storage for Python (pandas) and |
| R. There are two file format versions for Feather:</p> |
| <ul class="simple"> |
| <li><p>Version 2 (V2), the default version, which is exactly represented as the |
| Arrow IPC file format on disk. V2 files support storing all Arrow data types |
| as well as compression with LZ4 or ZSTD. V2 was first made available in |
| Apache Arrow 0.17.0.</p></li> |
| <li><p>Version 1 (V1), a legacy version available starting in 2016, replaced by |
| V2. V1 files are distinct from Arrow IPC files and lack many features, such |
| as the ability to store all Arrow data types. V1 files also lack compression |
| support. We intend to maintain read support for V1 for the foreseeable |
| future.</p></li> |
| </ul> |
| <p>The <code class="docutils literal notranslate"><span class="pre">pyarrow.feather</span></code> module contains the read and write functions for the |
| format. <a class="reference internal" href="generated/pyarrow.feather.write_feather.html#pyarrow.feather.write_feather" title="pyarrow.feather.write_feather"><code class="xref py py-func docutils literal notranslate"><span class="pre">write_feather()</span></code></a> accepts either a |
| <a class="reference internal" href="generated/pyarrow.Table.html#pyarrow.Table" title="pyarrow.Table"><code class="xref py py-class docutils literal notranslate"><span class="pre">Table</span></code></a> or <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code> object:</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">pyarrow.feather</span> <span class="kn">as</span> <span class="nn">feather</span> |
| <span class="n">feather</span><span class="o">.</span><span class="n">write_feather</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="s1">'/path/to/file'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p><a class="reference internal" href="generated/pyarrow.feather.read_feather.html#pyarrow.feather.read_feather" title="pyarrow.feather.read_feather"><code class="xref py py-func docutils literal notranslate"><span class="pre">read_feather()</span></code></a> reads a Feather file as a |
| <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code>. <a class="reference internal" href="generated/pyarrow.feather.read_table.html#pyarrow.feather.read_table" title="pyarrow.feather.read_table"><code class="xref py py-func docutils literal notranslate"><span class="pre">read_table()</span></code></a> reads a Feather file |
| as a <a class="reference internal" href="generated/pyarrow.Table.html#pyarrow.Table" title="pyarrow.Table"><code class="xref py py-class docutils literal notranslate"><span class="pre">Table</span></code></a>. Internally, <a class="reference internal" href="generated/pyarrow.feather.read_feather.html#pyarrow.feather.read_feather" title="pyarrow.feather.read_feather"><code class="xref py py-func docutils literal notranslate"><span class="pre">read_feather()</span></code></a> |
| simply calls <a class="reference internal" href="generated/pyarrow.feather.read_table.html#pyarrow.feather.read_table" title="pyarrow.feather.read_table"><code class="xref py py-func docutils literal notranslate"><span class="pre">read_table()</span></code></a> and the result is converted to |
| pandas:</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Result is pandas.DataFrame</span> |
| <span class="n">read_df</span> <span class="o">=</span> <span class="n">feather</span><span class="o">.</span><span class="n">read_feather</span><span class="p">(</span><span class="s1">'/path/to/file'</span><span class="p">)</span> |
| |
| <span class="c1"># Result is pyarrow.Table</span> |
| <span class="n">read_arrow</span> <span class="o">=</span> <span class="n">feather</span><span class="o">.</span><span class="n">read_table</span><span class="p">(</span><span class="s1">'/path/to/file'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>These functions can read and write with file-paths or file-like objects. For |
| example:</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">'/path/to/file'</span><span class="p">,</span> <span class="s1">'wb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span> |
| <span class="n">feather</span><span class="o">.</span><span class="n">write_feather</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span> |
| |
| <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">'/path/to/file'</span><span class="p">,</span> <span class="s1">'rb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span> |
| <span class="n">read_df</span> <span class="o">=</span> <span class="n">feather</span><span class="o">.</span><span class="n">read_feather</span><span class="p">(</span><span class="n">f</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>A file input to <code class="docutils literal notranslate"><span class="pre">read_feather</span></code> must support seeking.</p> |
| <div class="section" id="using-compression"> |
| <h2>Using Compression<a class="headerlink" href="#using-compression" title="Permalink to this headline">¶</a></h2> |
| <p>As of Apache Arrow version 0.17.0, Feather V2 files (the default version) |
| support two fast compression libraries, LZ4 (using the frame format) and |
| ZSTD. LZ4 is used by default if it is available (which it should be if you |
| obtained pyarrow through a normal package manager):</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Uses LZ4 by default</span> |
| <span class="n">feather</span><span class="o">.</span><span class="n">write_feather</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">file_path</span><span class="p">)</span> |
| |
| <span class="c1"># Use LZ4 explicitly</span> |
| <span class="n">feather</span><span class="o">.</span><span class="n">write_feather</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">file_path</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'lz4'</span><span class="p">)</span> |
| |
| <span class="c1"># Use ZSTD</span> |
| <span class="n">feather</span><span class="o">.</span><span class="n">write_feather</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">file_path</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'zstd'</span><span class="p">)</span> |
| |
| <span class="c1"># Do not compress</span> |
| <span class="n">feather</span><span class="o">.</span><span class="n">write_feather</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">file_path</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'uncompressed'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Note that the default LZ4 compression generally yields much smaller files |
| without sacrificing much read or write performance. In some instances, |
| LZ4-compressed files may be faster to read and write than uncompressed due to |
| reduced disk IO requirements.</p> |
| </div> |
| <div class="section" id="writing-version-1-v1-files"> |
| <h2>Writing Version 1 (V1) Files<a class="headerlink" href="#writing-version-1-v1-files" title="Permalink to this headline">¶</a></h2> |
| <p>For compatibility with libraries without support for Version 2 files, you can |
| write the version 1 format by passing <code class="docutils literal notranslate"><span class="pre">version=1</span></code> to <code class="docutils literal notranslate"><span class="pre">write_feather</span></code>. We |
| intend to maintain read support for V1 for the foreseeable future.</p> |
| </div> |
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