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<title>Common Python API — Scalable Vector Search 0.0.1 documentation</title>
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<section id="common-python-api">
<span id="python-common"></span><h1>Common Python API<a class="headerlink" href="#common-python-api" title="Link to this heading"></a></h1>
<section id="memory-allocators">
<h2>Memory Allocators<a class="headerlink" href="#memory-allocators" title="Link to this heading"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="svs.DRAM">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">svs.</span></span><span class="sig-name descname"><span class="pre">DRAM</span></span><a class="headerlink" href="#svs.DRAM" title="Link to this definition"></a></dt>
<dd><p>Small class for an allocator capable of using huge pages. Prioritizes page use in the order:
1~GiB, 2~MiB, 4~KiB. See <a class="reference internal" href="../performance/hugepages.html#hugepages"><span class="std std-ref">Huge Pages</span></a> for more information on what huge pages are
and how to allocate them on your system.</p>
</dd></dl>
</section>
<section id="enums">
<h2>Enums<a class="headerlink" href="#enums" title="Link to this heading"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="svs.DistanceType">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">svs.</span></span><span class="sig-name descname"><span class="pre">DistanceType</span></span><a class="headerlink" href="#svs.DistanceType" title="Link to this definition"></a></dt>
<dd><p>Select which distance function to use</p>
<p>Members:</p>
<blockquote>
<div><p>L2 : Euclidean Distance (minimize)</p>
<p>MIP : Maximum Inner Product (maximize)</p>
<p>Cosine : Cosine similarity (maximize)</p>
</div></blockquote>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="svs.DataType">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">svs.</span></span><span class="sig-name descname"><span class="pre">DataType</span></span><a class="headerlink" href="#svs.DataType" title="Link to this definition"></a></dt>
<dd><p>Datatype Selector</p>
<p>Members:</p>
<blockquote>
<div><p>uint8 : 8-bit unsigned integer.</p>
<p>uint16 : 16-bit unsigned integer.</p>
<p>uint32 : 32-bit unsigned integer.</p>
<p>uint64 : 64-bit unsigned integer.</p>
<p>int8 : 8-bit signed integer.</p>
<p>int16 : 16-bit signed integer.</p>
<p>int32 : 32-bit signed integer.</p>
<p>int64 : 64-bit signed integer.</p>
<p>float16 : 16-bit IEEE floating point.</p>
<p>float32 : 32-bit IEEE floating point.</p>
<p>float64 : 64-bit IEEE floating point.</p>
</div></blockquote>
</dd></dl>
</section>
<section id="helper-functions">
<span id="python-common-helpers"></span><h2>Helper Functions<a class="headerlink" href="#helper-functions" title="Link to this heading"></a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="svs.read_vecs">
<span class="sig-prename descclassname"><span class="pre">svs.</span></span><span class="sig-name descname"><span class="pre">read_vecs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#svs.read_vecs" title="Link to this definition"></a></dt>
<dd><p>Read a file in the <cite>bvecs/fvecs/ivecs</cite> format and return a NumPy array with the results.</p>
<p>The data type of the returned array is determined by the file extension with the
following mapping:</p>
<ul class="simple">
<li><p><cite>bvecs</cite>: 8-bit unsigned integers.</p></li>
<li><p><cite>fvecs</cite>: 32-bit floating point numbers.</p></li>
<li><p><cite>ivecs</cite>: 32-bit signed integers.</p></li>
</ul>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>filename</strong> (<em>str</em>) – The file to read.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Numpy array with the results.</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="svs.write_vecs">
<span class="sig-prename descclassname"><span class="pre">svs.</span></span><span class="sig-name descname"><span class="pre">write_vecs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_check</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#svs.write_vecs" title="Link to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>array</strong> (<em>array</em>) – The raw array to save.</p></li>
<li><p><strong>filename</strong> (<em>str</em>) – The file where the results will be saved.</p></li>
<li><p><strong>skip_check</strong> (<em>bool</em>) – <p>Be default, this function will check if the file extension for the vecs
file is appropriate for the given array (see list below).</p>
<p>Passing <cite>skip_check = True</cite> overrides this logic and forces creation of the
file.</p>
</p></li>
</ul>
</dd>
</dl>
<dl class="simple">
<dt>Result:</dt><dd><p>The array is saved to the requested file.</p>
</dd>
</dl>
<p>File extention to array element type:</p>
<blockquote>
<div><ul class="simple">
<li><p>fvecs: np.float32</p></li>
<li><p>hvecs: np.float16</p></li>
<li><p>ivecs: np.uint32</p></li>
<li><p>bvecs: np.uint8</p></li>
</ul>
</div></blockquote>
</dd></dl>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>The user must specify the file extension corresponding to the desired file format in the <code class="docutils literal notranslate"><span class="pre">filename</span></code> argument of
<a class="reference internal" href="#svs.write_vecs" title="svs.write_vecs"><code class="xref py py-func docutils literal notranslate"><span class="pre">svs.write_vecs()</span></code></a>.</p>
</div>
<dl class="py function">
<dt class="sig sig-object py" id="svs.read_svs">
<span class="sig-prename descclassname"><span class="pre">svs.</span></span><span class="sig-name descname"><span class="pre">read_svs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype=<class</span> <span class="pre">'numpy.float32'></span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#svs.read_svs" title="Link to this definition"></a></dt>
<dd><p>Read the svs native data file as a numpy array.
<em>Note</em>: As of no, now type checking is performed. Make sure the requested type actually
matches the contents of the file.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>filename</strong> (<em>str</em>) – The file to read.</p></li>
<li><p><strong>dtype</strong> – The data type of the encoded vectors in the file.</p></li>
</ul>
</dd>
</dl>
<dl class="simple">
<dt>Result:</dt><dd><p>A numpy matrix with the results.</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="svs.convert_fvecs_to_float16">
<span class="sig-prename descclassname"><span class="pre">svs.</span></span><span class="sig-name descname"><span class="pre">convert_fvecs_to_float16</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">source_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">destination_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="headerlink" href="#svs.convert_fvecs_to_float16" title="Link to this definition"></a></dt>
<dd><p>Convert the <cite>fvecs</cite> file on disk with 32-bit floating point entries to a <cite>fvecs</cite> file with
16-bit floating point entries.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>source_file</strong> – The source file path to convert.</p></li>
<li><p><strong>destination_file</strong> – The destination file to generate.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="svs.generate_test_dataset">
<span class="sig-prename descclassname"><span class="pre">svs.</span></span><span class="sig-name descname"><span class="pre">generate_test_dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">nvectors</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nqueries</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ndims</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">directory</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_seed=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">query_seed=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_threads=1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_neighbors=100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance=<DistanceType.L2:</span> <span class="pre">0></span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#svs.generate_test_dataset" title="Link to this definition"></a></dt>
<dd><p>Generate a sample dataset consisting of the base data, queries, and groundtruth all in
the standard <code class="docutils literal notranslate"><span class="pre">*vecs</span></code> form.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>nvectors</strong> (<em>int</em>) – The number of base vectors in the generated dataset.</p></li>
<li><p><strong>nqueries</strong> (<em>int</em>) – The number of query vectors in the generated dataset.</p></li>
<li><p><strong>ndims</strong> (<em>int</em>) – The number of dimensions per vector in the dataset.</p></li>
<li><p><strong>directory</strong> (<em>str</em>) – The directory in which to generate the dataset.</p></li>
<li><p><strong>data_seed</strong> (<em>optional</em>) – The seed to use for random number generation in the dataset.</p></li>
<li><p><strong>query_seed</strong> (<em>optional</em>) – The seed to use for random number generation for the queries.</p></li>
<li><p><strong>num_threads</strong> (<em>optional</em>) – Number of threads to use to generate the groundtruth.</p></li>
<li><p><strong>num_neighbors</strong> (<em>int</em>) – The number of neighbors to compute for the groundtruth.</p></li>
<li><p><strong>distance</strong> (<em>optional</em>) – The distance metric to use for groundtruth generation.</p></li>
</ul>
</dd>
</dl>
<p>Creates <code class="docutils literal notranslate"><span class="pre">directory</span></code> if it didn’t already exist. The following files are generated:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">$(directory)/data.fvecs</span></code>: The dataset encoded using float32 in as fvecs.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">$(directory)/queries.fvecs</span></code>: The queries encoded using float32 as fvecs.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">$(directory)/groundtruth.ivecs</span></code>: The computed <code class="docutils literal notranslate"><span class="pre">num_neighbors</span></code> nearest
neighbors of the queries in the dataset with respect to the provided distance.</p></li>
</ul>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="svs.convert_vecs_to_svs">
<span class="sig-prename descclassname"><span class="pre">svs.</span></span><span class="sig-name descname"><span class="pre">convert_vecs_to_svs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">vecs_file:</span> <span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">svs_file:</span> <span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">svs::python.DataType</span> <span class="pre">=</span> <span class="pre"><DataType.float32:</span> <span class="pre">9></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="headerlink" href="#svs.convert_vecs_to_svs" title="Link to this definition"></a></dt>
<dd><p>Convert the vecs file (containing the specified element types) to the svs native format.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>vecs_file</strong> – The source [f/h/i/b]vecs file.</p></li>
<li><p><strong>svs_file</strong> – The destination native file.</p></li>
<li><p><strong>dtype</strong> – The svs.DataType of the vecs file. Supported types: (float32, float16, uint32, and uint8).</p></li>
</ul>
</dd>
</dl>
<p>File extension type map:</p>
<ul class="simple">
<li><p>fvecs = svs.DataType.float32</p></li>
<li><p>hvecs = svs.DataType.float16</p></li>
<li><p>ivecs = svs.DataType.uint32</p></li>
<li><p>bvecs = svs.DataType.uint8</p></li>
</ul>
</dd></dl>
</section>
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