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datamol.utils.html
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Cluster Molecules
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datamol.fragment
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datamol.scaffold
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datamol.actions
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datamol.molar
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datamol.utils
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datamol.utils
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Parallelization helpers
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parallelized()
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JobRunner
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Filesystem related utility functions
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get_extension()
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exists()
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is_file()
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is_dir()
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get_protocol()
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is_local_path()
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join()
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get_size()
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<h1 id="datamolutils"><code>datamol.utils</code><a class="headerlink" href="#datamolutils" title="Permanent link">¶</a></h1>
<h2 id="parallelization-helpers">Parallelization helpers<a class="headerlink" href="#parallelization-helpers" title="Permanent link">¶</a></h2>
<div class="doc doc-object doc-function">
<h4 id="datamol.utils.jobs.parallelized" class="doc doc-heading">
<code class="highlight language-python"><span class="n">parallelized</span><span class="p">(</span><span class="n">fn</span><span class="p">,</span> <span class="n">inputs_list</span><span class="p">,</span> <span class="n">scheduler</span><span class="o">=</span><span class="s1">'processes'</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">progress</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">arg_type</span><span class="o">=</span><span class="s1">'arg'</span><span class="p">,</span> <span class="n">tqdm_kwargs</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">job_kwargs</span><span class="p">)</span></code>
<a href="#datamol.utils.jobs.parallelized" class="headerlink" title="Permanent link">¶</a></h4>
<div class="doc doc-contents first">
<p>Run a function in parallel.</p>
<p><strong>Parameters:</strong></p>
<table>
<thead>
<tr>
<th>Name</th>
<th>Type</th>
<th>Description</th>
<th>Default</th>
</tr>
</thead>
<tbody>
<tr>
<td><code>fn</code></td>
<td><code>Callable</code></td>
<td><p>The function to run in parallel.</p></td>
<td><em>required</em></td>
</tr>
<tr>
<td><code>inputs_list</code></td>
<td><code>Iterable[Any]</code></td>
<td><p>List of inputs to pass to <code>fn</code>.</p></td>
<td><em>required</em></td>
</tr>
<tr>
<td><code>scheduler</code></td>
<td><code>str</code></td>
<td><p>Choose between ["processes", "threads"]. Defaults
to None which uses the default joblib "loky" scheduler.</p></td>
<td><code>'processes'</code></td>
</tr>
<tr>
<td><code>n_jobs</code></td>
<td><code>Optional[int]</code></td>
<td><p>Number of process. Use 0 or None to force sequential.
Use -1 to use all the available processors. For details see
<a href="https://joblib.readthedocs.io/en/latest/parallel.html#parallel-reference-documentation">https://joblib.readthedocs.io/en/latest/parallel.html#parallel-reference-documentation</a></p></td>
<td><code>-1</code></td>
</tr>
<tr>
<td><code>batch_size</code></td>
<td><code>int</code></td>
<td><p>Whether to automatically batch <code>inputs_list</code>. You should only use it when the length
of <code>inputs_list</code> is very large (>100k elements). The length of <code>inputs_list</code> must also be
defined.</p></td>
<td><code>None</code></td>
</tr>
<tr>
<td><code>progress</code></td>
<td><code>bool</code></td>
<td><p>Display a progress bar. Defaults to False.</p></td>
<td><code>False</code></td>
</tr>
<tr>
<td><code>arg_type</code></td>
<td><code>str</code></td>
<td><p>One of ["arg", "args", "kwargs]:
- "arg": the input is passed as an argument: <code>fn(arg)</code> (default).
- "args": the input is passed as a list: <code>fn(*args)</code>.
- "kwargs": the input is passed as a map: <code>fn(**kwargs)</code>.</p></td>
<td><code>'arg'</code></td>
</tr>
<tr>
<td><code>tqdm_kwargs</code></td>
<td><code>dict</code></td>
<td><p>Any additional arguments supported by the <code>tqdm</code> progress bar.</p></td>
<td><code>None</code></td>
</tr>
<tr>
<td><code>job_kwargs</code></td>
<td></td>
<td><p>Any additional arguments supported by <code>joblib.Parallel</code>.</p></td>
<td><code>{}</code></td>
</tr>
</tbody>
</table>
<p><strong>Returns:</strong></p>
<table>
<thead>
<tr>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr>
<td><code>Sequence[Optional[Any]]</code></td>
<td><p>The results of the execution as a list.</p></td>
</tr>
</tbody>
</table>
<details class="quote">
<summary>Source code in <code>datamol/utils/jobs.py</code></summary>
<div class="highlight"><pre><span></span><code><span class="k">def</span> <span class="nf">parallelized</span><span class="p">(</span>
<span class="n">fn</span><span class="p">:</span> <span class="n">Callable</span><span class="p">,</span>
<span class="n">inputs_list</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="n">Any</span><span class="p">],</span>
<span class="n">scheduler</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"processes"</span><span class="p">,</span>
<span class="n">n_jobs</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
<span class="n">batch_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">progress</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
<span class="n">arg_type</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"arg"</span><span class="p">,</span>
<span class="n">tqdm_kwargs</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="o">**</span><span class="n">job_kwargs</span><span class="p">,</span>
<span class="p">)</span> <span class="o">-></span> <span class="n">Sequence</span><span class="p">[</span><span class="n">Optional</span><span class="p">[</span><span class="n">Any</span><span class="p">]]:</span>
<span class="sd">"""Run a function in parallel.</span>
<span class="sd"> Args:</span>
<span class="sd"> fn: The function to run in parallel.</span>
<span class="sd"> inputs_list: List of inputs to pass to `fn`.</span>
<span class="sd"> scheduler: Choose between ["processes", "threads"]. Defaults</span>
<span class="sd"> to None which uses the default joblib "loky" scheduler.</span>
<span class="sd"> n_jobs: Number of process. Use 0 or None to force sequential.</span>
<span class="sd"> Use -1 to use all the available processors. For details see</span>
<span class="sd"> https://joblib.readthedocs.io/en/latest/parallel.html#parallel-reference-documentation</span>