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  <div class="section" id="api">
<span id="id1"></span><h1>API<a class="headerlink" href="#api" title="Permalink to this headline"></a></h1>
<p><strong>Client</strong></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client" title="distributed.client.Client"><code class="xref py py-obj docutils literal"><span class="pre">Client</span></code></a>([address,&nbsp;loop,&nbsp;timeout,&nbsp;…])</td>
<td>Connect to and drive computation on a distributed Dask cluster</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.call_stack" title="distributed.client.Client.call_stack"><code class="xref py py-obj docutils literal"><span class="pre">Client.call_stack</span></code></a>([futures,&nbsp;keys])</td>
<td>The actively running call stack of all relevant keys</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.cancel" title="distributed.client.Client.cancel"><code class="xref py py-obj docutils literal"><span class="pre">Client.cancel</span></code></a>(futures[,&nbsp;asynchronous,&nbsp;force])</td>
<td>Cancel running futures</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.close" title="distributed.client.Client.close"><code class="xref py py-obj docutils literal"><span class="pre">Client.close</span></code></a>([timeout])</td>
<td>Close this client</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.compute" title="distributed.client.Client.compute"><code class="xref py py-obj docutils literal"><span class="pre">Client.compute</span></code></a>(collections[,&nbsp;sync,&nbsp;…])</td>
<td>Compute dask collections on cluster</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.gather" title="distributed.client.Client.gather"><code class="xref py py-obj docutils literal"><span class="pre">Client.gather</span></code></a>(futures[,&nbsp;errors,&nbsp;maxsize,&nbsp;…])</td>
<td>Gather futures from distributed memory</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.get" title="distributed.client.Client.get"><code class="xref py py-obj docutils literal"><span class="pre">Client.get</span></code></a>(dsk,&nbsp;keys[,&nbsp;restrictions,&nbsp;…])</td>
<td>Compute dask graph</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.get_dataset" title="distributed.client.Client.get_dataset"><code class="xref py py-obj docutils literal"><span class="pre">Client.get_dataset</span></code></a>(name,&nbsp;**kwargs)</td>
<td>Get named dataset from the scheduler</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.get_executor" title="distributed.client.Client.get_executor"><code class="xref py py-obj docutils literal"><span class="pre">Client.get_executor</span></code></a>(**kwargs)</td>
<td>Return a concurrent.futures Executor for submitting tasks on this Client.</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.get_metadata" title="distributed.client.Client.get_metadata"><code class="xref py py-obj docutils literal"><span class="pre">Client.get_metadata</span></code></a>(keys[,&nbsp;default])</td>
<td>Get arbitrary metadata from scheduler</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.get_scheduler_logs" title="distributed.client.Client.get_scheduler_logs"><code class="xref py py-obj docutils literal"><span class="pre">Client.get_scheduler_logs</span></code></a>([n])</td>
<td>Get logs from scheduler</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.get_worker_logs" title="distributed.client.Client.get_worker_logs"><code class="xref py py-obj docutils literal"><span class="pre">Client.get_worker_logs</span></code></a>([n,&nbsp;workers])</td>
<td>Get logs from workers</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.has_what" title="distributed.client.Client.has_what"><code class="xref py py-obj docutils literal"><span class="pre">Client.has_what</span></code></a>([workers])</td>
<td>Which keys are held by which workers</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.list_datasets" title="distributed.client.Client.list_datasets"><code class="xref py py-obj docutils literal"><span class="pre">Client.list_datasets</span></code></a>(**kwargs)</td>
<td>List named datasets available on the scheduler</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.map" title="distributed.client.Client.map"><code class="xref py py-obj docutils literal"><span class="pre">Client.map</span></code></a>(func,&nbsp;*iterables,&nbsp;**kwargs)</td>
<td>Map a function on a sequence of arguments</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.ncores" title="distributed.client.Client.ncores"><code class="xref py py-obj docutils literal"><span class="pre">Client.ncores</span></code></a>([workers])</td>
<td>The number of threads/cores available on each worker node</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.persist" title="distributed.client.Client.persist"><code class="xref py py-obj docutils literal"><span class="pre">Client.persist</span></code></a>(collections[,&nbsp;…])</td>
<td>Persist dask collections on cluster</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.publish_dataset" title="distributed.client.Client.publish_dataset"><code class="xref py py-obj docutils literal"><span class="pre">Client.publish_dataset</span></code></a>(**kwargs)</td>
<td>Publish named datasets to scheduler</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.profile" title="distributed.client.Client.profile"><code class="xref py py-obj docutils literal"><span class="pre">Client.profile</span></code></a>([key,&nbsp;start,&nbsp;stop,&nbsp;workers,&nbsp;…])</td>
<td>Collect statistical profiling information about recent work</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.rebalance" title="distributed.client.Client.rebalance"><code class="xref py py-obj docutils literal"><span class="pre">Client.rebalance</span></code></a>([futures,&nbsp;workers])</td>
<td>Rebalance data within network</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.replicate" title="distributed.client.Client.replicate"><code class="xref py py-obj docutils literal"><span class="pre">Client.replicate</span></code></a>(futures[,&nbsp;n,&nbsp;workers,&nbsp;…])</td>
<td>Set replication of futures within network</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.restart" title="distributed.client.Client.restart"><code class="xref py py-obj docutils literal"><span class="pre">Client.restart</span></code></a>(**kwargs)</td>
<td>Restart the distributed network</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.run" title="distributed.client.Client.run"><code class="xref py py-obj docutils literal"><span class="pre">Client.run</span></code></a>(function,&nbsp;*args,&nbsp;**kwargs)</td>
<td>Run a function on all workers outside of task scheduling system</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.run_on_scheduler" title="distributed.client.Client.run_on_scheduler"><code class="xref py py-obj docutils literal"><span class="pre">Client.run_on_scheduler</span></code></a>(function,&nbsp;*args,&nbsp;…)</td>
<td>Run a function on the scheduler process</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.scatter" title="distributed.client.Client.scatter"><code class="xref py py-obj docutils literal"><span class="pre">Client.scatter</span></code></a>(data[,&nbsp;workers,&nbsp;broadcast,&nbsp;…])</td>
<td>Scatter data into distributed memory</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.scheduler_info" title="distributed.client.Client.scheduler_info"><code class="xref py py-obj docutils literal"><span class="pre">Client.scheduler_info</span></code></a>(**kwargs)</td>
<td>Basic information about the workers in the cluster</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.set_metadata" title="distributed.client.Client.set_metadata"><code class="xref py py-obj docutils literal"><span class="pre">Client.set_metadata</span></code></a>(key,&nbsp;value)</td>
<td>Set arbitrary metadata in the scheduler</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.start_ipython_workers" title="distributed.client.Client.start_ipython_workers"><code class="xref py py-obj docutils literal"><span class="pre">Client.start_ipython_workers</span></code></a>([workers,&nbsp;…])</td>
<td>Start IPython kernels on workers</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.start_ipython_scheduler" title="distributed.client.Client.start_ipython_scheduler"><code class="xref py py-obj docutils literal"><span class="pre">Client.start_ipython_scheduler</span></code></a>([magic_name,&nbsp;…])</td>
<td>Start IPython kernel on the scheduler</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.submit" title="distributed.client.Client.submit"><code class="xref py py-obj docutils literal"><span class="pre">Client.submit</span></code></a>(func,&nbsp;*args,&nbsp;**kwargs)</td>
<td>Submit a function application to the scheduler</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.unpublish_dataset" title="distributed.client.Client.unpublish_dataset"><code class="xref py py-obj docutils literal"><span class="pre">Client.unpublish_dataset</span></code></a>(name,&nbsp;**kwargs)</td>
<td>Remove named datasets from scheduler</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Client.upload_file" title="distributed.client.Client.upload_file"><code class="xref py py-obj docutils literal"><span class="pre">Client.upload_file</span></code></a>(filename,&nbsp;**kwargs)</td>
<td>Upload local package to workers</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Client.who_has" title="distributed.client.Client.who_has"><code class="xref py py-obj docutils literal"><span class="pre">Client.who_has</span></code></a>([futures])</td>
<td>The workers storing each future’s data</td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><a class="reference internal" href="#distributed.worker_client" title="distributed.worker_client"><code class="xref py py-obj docutils literal"><span class="pre">worker_client</span></code></a>([timeout,&nbsp;separate_thread])</td>
<td>Get client for this thread</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.get_worker" title="distributed.get_worker"><code class="xref py py-obj docutils literal"><span class="pre">get_worker</span></code></a>()</td>
<td>Get the worker currently running this task</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.get_client" title="distributed.get_client"><code class="xref py py-obj docutils literal"><span class="pre">get_client</span></code></a>([address,&nbsp;timeout])</td>
<td>Get a client while within a task</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.secede" title="distributed.secede"><code class="xref py py-obj docutils literal"><span class="pre">secede</span></code></a>()</td>
<td>Have this task secede from the worker’s thread pool</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.rejoin" title="distributed.rejoin"><code class="xref py py-obj docutils literal"><span class="pre">rejoin</span></code></a>()</td>
<td>Have this thread rejoin the ThreadPoolExecutor</td>
</tr>
<tr class="row-even"><td><code class="xref py py-obj docutils literal"><span class="pre">Reschedule</span></code></td>
<td>Reschedule this task</td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><a class="reference internal" href="#distributed.recreate_exceptions.ReplayExceptionClient.get_futures_error" title="distributed.recreate_exceptions.ReplayExceptionClient.get_futures_error"><code class="xref py py-obj docutils literal"><span class="pre">ReplayExceptionClient.get_futures_error</span></code></a>(future)</td>
<td>Ask the scheduler details of the sub-task of the given failed future</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.recreate_exceptions.ReplayExceptionClient.recreate_error_locally" title="distributed.recreate_exceptions.ReplayExceptionClient.recreate_error_locally"><code class="xref py py-obj docutils literal"><span class="pre">ReplayExceptionClient.recreate_error_locally</span></code></a>(future)</td>
<td>For a failed calculation, perform the blamed task locally for debugging.</td>
</tr>
</tbody>
</table>
<p><strong>Future</strong></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Future" title="distributed.client.Future"><code class="xref py py-obj docutils literal"><span class="pre">Future</span></code></a>(key[,&nbsp;client,&nbsp;inform,&nbsp;state])</td>
<td>A remotely running computation</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Future.add_done_callback" title="distributed.client.Future.add_done_callback"><code class="xref py py-obj docutils literal"><span class="pre">Future.add_done_callback</span></code></a>(fn)</td>
<td>Call callback on future when callback has finished</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Future.cancel" title="distributed.client.Future.cancel"><code class="xref py py-obj docutils literal"><span class="pre">Future.cancel</span></code></a>(**kwargs)</td>
<td>Cancel request to run this future</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Future.cancelled" title="distributed.client.Future.cancelled"><code class="xref py py-obj docutils literal"><span class="pre">Future.cancelled</span></code></a>()</td>
<td>Returns True if the future has been cancelled</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Future.done" title="distributed.client.Future.done"><code class="xref py py-obj docutils literal"><span class="pre">Future.done</span></code></a>()</td>
<td>Is the computation complete?</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Future.exception" title="distributed.client.Future.exception"><code class="xref py py-obj docutils literal"><span class="pre">Future.exception</span></code></a>([timeout])</td>
<td>Return the exception of a failed task</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#distributed.client.Future.result" title="distributed.client.Future.result"><code class="xref py py-obj docutils literal"><span class="pre">Future.result</span></code></a>([timeout])</td>
<td>Wait until computation completes, gather result to local process.</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.client.Future.traceback" title="distributed.client.Future.traceback"><code class="xref py py-obj docutils literal"><span class="pre">Future.traceback</span></code></a>([timeout])</td>
<td>Return the traceback of a failed task</td>
</tr>
</tbody>
</table>
<p><strong>Client Coordination</strong></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><code class="xref py py-obj docutils literal"><span class="pre">Lock</span></code>([name,&nbsp;client])</td>
<td>Distributed Centralized Lock</td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><a class="reference internal" href="#distributed.Queue" title="distributed.Queue"><code class="xref py py-obj docutils literal"><span class="pre">Queue</span></code></a>([name,&nbsp;client,&nbsp;maxsize])</td>
<td>Distributed Queue</td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><a class="reference internal" href="#distributed.Variable" title="distributed.Variable"><code class="xref py py-obj docutils literal"><span class="pre">Variable</span></code></a>([name,&nbsp;client,&nbsp;maxsize])</td>
<td>Distributed Global Variable</td>
</tr>
</tbody>
</table>
<p><strong>Other</strong></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><code class="xref py py-obj docutils literal"><span class="pre">as_completed</span></code>([futures,&nbsp;loop,&nbsp;with_results])</td>
<td>Return futures in the order in which they complete</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#distributed.diagnostics.progress" title="distributed.diagnostics.progress"><code class="xref py py-obj docutils literal"><span class="pre">distributed.diagnostics.progress</span></code></a>(*futures,&nbsp;…)</td>
<td>Track progress of futures</td>
</tr>
<tr class="row-odd"><td><code class="xref py py-obj docutils literal"><span class="pre">wait</span></code>(fs[,&nbsp;timeout,&nbsp;return_when])</td>
<td>Wait until all futures are complete</td>
</tr>
<tr class="row-even"><td><code class="xref py py-obj docutils literal"><span class="pre">fire_and_forget</span></code>(obj)</td>
<td>Run tasks at least once, even if we release the futures</td>
</tr>
</tbody>
</table>
<div class="section" id="asynchronous-methods">
<h2>Asynchronous methods<a class="headerlink" href="#asynchronous-methods" title="Permalink to this headline"></a></h2>
<p>Most methods and functions can be used equally well within a blocking or
asynchronous environment using Tornado coroutines.  If used within a Tornado
IOLoop then you should yield or await otherwise blocking operations
appropriately.</p>
<p>You must tell the client that you intend to use it within an asynchronous
environment by passing the <code class="docutils literal"><span class="pre">asynchronous=True</span></code> keyword</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="c1"># blocking</span>
<span class="n">client</span> <span class="o">=</span> <span class="n">Client</span><span class="p">()</span>
<span class="n">future</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">)</span>  <span class="c1"># immediate, no blocking/async difference</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">gather</span><span class="p">(</span><span class="n">future</span><span class="p">)</span>  <span class="c1"># blocking</span>

<span class="c1"># asynchronous Python 2/3</span>
<span class="n">client</span> <span class="o">=</span> <span class="k">yield</span> <span class="n">Client</span><span class="p">(</span><span class="n">asynchronous</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="n">future</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">)</span>  <span class="c1"># immediate, no blocking/async difference</span>
<span class="n">result</span> <span class="o">=</span> <span class="k">yield</span> <span class="n">client</span><span class="o">.</span><span class="n">gather</span><span class="p">(</span><span class="n">future</span><span class="p">)</span>  <span class="c1"># non-blocking/asynchronous</span>

<span class="c1"># asynchronous Python 3</span>
<span class="n">client</span> <span class="o">=</span> <span class="n">await</span> <span class="n">Client</span><span class="p">(</span><span class="n">asynchronous</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="n">future</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">)</span>  <span class="c1"># immediate, no blocking/async difference</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">await</span> <span class="n">client</span><span class="o">.</span><span class="n">gather</span><span class="p">(</span><span class="n">future</span><span class="p">)</span>  <span class="c1"># non-blocking/asynchronous</span>
</pre></div>
</div>
<p>The asynchronous variants must be run within a Tornado coroutine.  See the
<a class="reference internal" href="asynchronous.html"><span class="doc">Asynchronous</span></a> documentation for more information.</p>
</div>
<div class="section" id="client">
<h2>Client<a class="headerlink" href="#client" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="distributed.client.Client">
<em class="property">class </em><code class="descclassname">distributed.client.</code><code class="descname">Client</code><span class="sig-paren">(</span><em>address=None</em>, <em>loop=None</em>, <em>timeout=5</em>, <em>set_as_default=True</em>, <em>scheduler_file=None</em>, <em>security=None</em>, <em>asynchronous=False</em>, <em>name=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client" title="Permalink to this definition"></a></dt>
<dd><p>Connect to and drive computation on a distributed Dask cluster</p>
<p>The Client connects users to a dask.distributed compute cluster.  It
provides an asynchronous user interface around functions and futures.  This
class resembles executors in <code class="docutils literal"><span class="pre">concurrent.futures</span></code> but also allows
<code class="docutils literal"><span class="pre">Future</span></code> objects within <code class="docutils literal"><span class="pre">submit/map</span></code> calls.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>address: string, or Cluster</strong></p>
<blockquote>
<div><p>This can be the address of a <code class="docutils literal"><span class="pre">Scheduler</span></code> server like a string
<code class="docutils literal"><span class="pre">'127.0.0.1:8786'</span></code> or a cluster object like <code class="docutils literal"><span class="pre">LocalCluster()</span></code></p>
</div></blockquote>
<p><strong>timeout: int</strong></p>
<blockquote>
<div><p>Timeout duration for initial connection to the scheduler</p>
</div></blockquote>
<p><strong>set_as_default: bool (True)</strong></p>
<blockquote>
<div><p>Claim this scheduler as the global dask scheduler</p>
</div></blockquote>
<p><strong>scheduler_file: string (optional)</strong></p>
<blockquote>
<div><p>Path to a file with scheduler information if available</p>
</div></blockquote>
<p><strong>security: (optional)</strong></p>
<blockquote>
<div><p>Optional security information</p>
</div></blockquote>
<p><strong>asynchronous: bool (False by default)</strong></p>
<blockquote>
<div><p>Set to True if this client will be used within a Tornado event loop</p>
</div></blockquote>
<p><strong>name: string (optional)</strong></p>
<blockquote class="last">
<div><p>Gives the client a name that will be included in logs generated on
the scheduler for matters relating to this client</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="scheduling-state.html#distributed.scheduler.Scheduler" title="distributed.scheduler.Scheduler"><code class="xref py py-obj docutils literal"><span class="pre">distributed.scheduler.Scheduler</span></code></a></dt>
<dd>Internal scheduler</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<p>Provide cluster’s scheduler node address on initialization:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span> <span class="o">=</span> <span class="n">Client</span><span class="p">(</span><span class="s1">&#39;127.0.0.1:8786&#39;</span><span class="p">)</span>  
</pre></div>
</div>
<p>Use <code class="docutils literal"><span class="pre">submit</span></code> method to send individual computations to the cluster</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">b</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">20</span><span class="p">)</span>  
</pre></div>
</div>
<p>Continue using submit or map on results to build up larger computations</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>  
</pre></div>
</div>
<p>Gather results with the <code class="docutils literal"><span class="pre">gather</span></code> method.</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">gather</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>  
<span class="go">33</span>
</pre></div>
</div>
<dl class="attribute">
<dt id="distributed.client.Client.asynchronous">
<code class="descname">asynchronous</code><a class="headerlink" href="#distributed.client.Client.asynchronous" title="Permalink to this definition"></a></dt>
<dd><p>Are we running in the event loop?</p>
<p>This is true if the user signaled that we might be when creating the
client as in the following:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">client</span> <span class="o">=</span> <span class="n">Client</span><span class="p">(</span><span class="n">asynchronous</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
</pre></div>
</div>
<p>However, we override this expectation if we can definitively tell that
we are running from a thread that is not the event loop.  This is
common when calling get_client() from within a worker task.  Even
though the client was originally created in asynchronous mode we may
find ourselves in contexts when it is better to operate synchronously.</p>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.call_stack">
<code class="descname">call_stack</code><span class="sig-paren">(</span><em>futures=None</em>, <em>keys=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.call_stack"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.call_stack" title="Permalink to this definition"></a></dt>
<dd><p>The actively running call stack of all relevant keys</p>
<p>You can specify data of interest either by providing futures or
collections in the <code class="docutils literal"><span class="pre">futures=</span></code> keyword or a list of explicit keys in
the <code class="docutils literal"><span class="pre">keys=</span></code> keyword.  If neither are provided then all call stacks
will be returned.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>futures: list (optional)</strong></p>
<blockquote>
<div><p>List of futures, defaults to all data</p>
</div></blockquote>
<p><strong>keys: list (optional)</strong></p>
<blockquote class="last">
<div><p>List of key names, defaults to all data</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span> <span class="o">=</span> <span class="n">dd</span><span class="o">.</span><span class="n">read_parquet</span><span class="p">(</span><span class="o">...</span><span class="p">)</span><span class="o">.</span><span class="n">persist</span><span class="p">()</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">call_stack</span><span class="p">(</span><span class="n">df</span><span class="p">)</span>  <span class="c1"># call on collections</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">call_stack</span><span class="p">()</span>  <span class="c1"># Or call with no arguments for all activity  </span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.cancel">
<code class="descname">cancel</code><span class="sig-paren">(</span><em>futures</em>, <em>asynchronous=None</em>, <em>force=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.cancel"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.cancel" title="Permalink to this definition"></a></dt>
<dd><p>Cancel running futures</p>
<p>This stops future tasks from being scheduled if they have not yet run
and deletes them if they have already run.  After calling, this result
and all dependent results will no longer be accessible</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>futures: list of Futures</strong></p>
<p><strong>force: boolean (False)</strong></p>
<blockquote class="last">
<div><p>Cancel this future even if other clients desire it</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.close">
<code class="descname">close</code><span class="sig-paren">(</span><em>timeout=10</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.close"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.close" title="Permalink to this definition"></a></dt>
<dd><p>Close this client</p>
<p>Clients will also close automatically when your Python session ends</p>
<p>If you started a client without arguments like <code class="docutils literal"><span class="pre">Client()</span></code> then this
will also close the local cluster that was started at the same time.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.restart" title="distributed.client.Client.restart"><code class="xref py py-obj docutils literal"><span class="pre">Client.restart</span></code></a></p>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.compute">
<code class="descname">compute</code><span class="sig-paren">(</span><em>collections</em>, <em>sync=False</em>, <em>optimize_graph=True</em>, <em>workers=None</em>, <em>allow_other_workers=False</em>, <em>resources=None</em>, <em>retries=0</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.compute"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.compute" title="Permalink to this definition"></a></dt>
<dd><p>Compute dask collections on cluster</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>collections: iterable of dask objects or single dask object</strong></p>
<blockquote>
<div><p>Collections like dask.array or dataframe or dask.value objects</p>
</div></blockquote>
<p><strong>sync: bool (optional)</strong></p>
<blockquote>
<div><p>Returns Futures if False (default) or concrete values if True</p>
</div></blockquote>
<p><strong>optimize_graph: bool</strong></p>
<blockquote>
<div><p>Whether or not to optimize the underlying graphs</p>
</div></blockquote>
<p><strong>workers: str, list, dict</strong></p>
<blockquote>
<div><p>Which workers can run which parts of the computation
If a string a list then the output collections will run on the listed</p>
<blockquote>
<div><p>workers, but other sub-computations can run anywhere</p>
</div></blockquote>
<dl class="docutils">
<dt>If a dict then keys should be (tuples of) collections and values</dt>
<dd><p class="first last">should be addresses or lists.</p>
</dd>
</dl>
</div></blockquote>
<p><strong>allow_other_workers: bool, list</strong></p>
<blockquote>
<div><p>If True then all restrictions in workers= are considered loose
If a list then only the keys for the listed collections are loose</p>
</div></blockquote>
<p><strong>retries: int (default to 0)</strong></p>
<blockquote>
<div><p>Number of allowed automatic retries if computing a result fails</p>
</div></blockquote>
<p><strong>**kwargs:</strong></p>
<blockquote>
<div><p>Options to pass to the graph optimize calls</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">List of Futures if input is a sequence, or a single future otherwise</p>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.get" title="distributed.client.Client.get"><code class="xref py py-obj docutils literal"><span class="pre">Client.get</span></code></a></dt>
<dd>Normal synchronous dask.get function</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">dask</span> <span class="k">import</span> <span class="n">delayed</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">operator</span> <span class="k">import</span> <span class="n">add</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">delayed</span><span class="p">(</span><span class="n">add</span><span class="p">)(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">delayed</span><span class="p">(</span><span class="n">add</span><span class="p">)(</span><span class="n">x</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">xx</span><span class="p">,</span> <span class="n">yy</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">compute</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">xx</span>  
<span class="go">&lt;Future: status: finished, key: add-8f6e709446674bad78ea8aeecfee188e&gt;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">xx</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>  
<span class="go">3</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">yy</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>  
<span class="go">6</span>
</pre></div>
</div>
<p>Also support single arguments</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">xx</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">compute</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>  
</pre></div>
</div>
</dd></dl>

<dl class="classmethod">
<dt id="distributed.client.Client.current">
<em class="property">classmethod </em><code class="descname">current</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.current"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.current" title="Permalink to this definition"></a></dt>
<dd><p>Return global client if one exists, otherwise raise ValueError</p>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.gather">
<code class="descname">gather</code><span class="sig-paren">(</span><em>futures</em>, <em>errors='raise'</em>, <em>maxsize=0</em>, <em>direct=None</em>, <em>asynchronous=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.gather"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.gather" title="Permalink to this definition"></a></dt>
<dd><p>Gather futures from distributed memory</p>
<p>Accepts a future, nested container of futures, iterator, or queue.
The return type will match the input type.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>futures: Collection of futures</strong></p>
<blockquote>
<div><p>This can be a possibly nested collection of Future objects.
Collections can be lists, sets, iterators, queues or dictionaries</p>
</div></blockquote>
<p><strong>errors: string</strong></p>
<blockquote>
<div><p>Either ‘raise’ or ‘skip’ if we should raise if a future has erred
or skip its inclusion in the output collection</p>
</div></blockquote>
<p><strong>maxsize: int</strong></p>
<blockquote>
<div><p>If the input is a queue then this produces an output queue with a
maximum size.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">results: a collection of the same type as the input, but now with</p>
<p class="last">gathered results rather than futures</p>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.scatter" title="distributed.client.Client.scatter"><code class="xref py py-obj docutils literal"><span class="pre">Client.scatter</span></code></a></dt>
<dd>Send data out to cluster</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">operator</span> <span class="k">import</span> <span class="n">add</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span> <span class="o">=</span> <span class="n">Client</span><span class="p">(</span><span class="s1">&#39;127.0.0.1:8787&#39;</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">gather</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>  
<span class="go">3</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">gather</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="p">[</span><span class="n">x</span><span class="p">],</span> <span class="n">x</span><span class="p">])</span>  <span class="c1"># support lists and dicts </span>
<span class="go">[3, [3], 3]</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">seq</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">gather</span><span class="p">(</span><span class="nb">iter</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">x</span><span class="p">]))</span>  <span class="c1"># support iterators </span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">next</span><span class="p">(</span><span class="n">seq</span><span class="p">)</span>  
<span class="go">3</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.get">
<code class="descname">get</code><span class="sig-paren">(</span><em>dsk</em>, <em>keys</em>, <em>restrictions=None</em>, <em>loose_restrictions=None</em>, <em>resources=None</em>, <em>sync=True</em>, <em>asynchronous=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.get"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.get" title="Permalink to this definition"></a></dt>
<dd><p>Compute dask graph</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>dsk: dict</strong></p>
<p><strong>keys: object, or nested lists of objects</strong></p>
<p><strong>restrictions: dict (optional)</strong></p>
<blockquote>
<div><p>A mapping of {key: {set of worker hostnames}} that restricts where
jobs can take place</p>
</div></blockquote>
<p><strong>sync: bool (optional)</strong></p>
<blockquote class="last">
<div><p>Returns Futures if False or concrete values if True (default).</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.compute" title="distributed.client.Client.compute"><code class="xref py py-obj docutils literal"><span class="pre">Client.compute</span></code></a></dt>
<dd>Compute asynchronous collections</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">operator</span> <span class="k">import</span> <span class="n">add</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span> <span class="o">=</span> <span class="n">Client</span><span class="p">(</span><span class="s1">&#39;127.0.0.1:8787&#39;</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">get</span><span class="p">({</span><span class="s1">&#39;x&#39;</span><span class="p">:</span> <span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)},</span> <span class="s1">&#39;x&#39;</span><span class="p">)</span>  
<span class="go">3</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.get_dataset">
<code class="descname">get_dataset</code><span class="sig-paren">(</span><em>name</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.get_dataset"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.get_dataset" title="Permalink to this definition"></a></dt>
<dd><p>Get named dataset from the scheduler</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.publish_dataset" title="distributed.client.Client.publish_dataset"><code class="xref py py-obj docutils literal"><span class="pre">Client.publish_dataset</span></code></a>, <a class="reference internal" href="#distributed.client.Client.list_datasets" title="distributed.client.Client.list_datasets"><code class="xref py py-obj docutils literal"><span class="pre">Client.list_datasets</span></code></a></p>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.get_executor">
<code class="descname">get_executor</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.get_executor"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.get_executor" title="Permalink to this definition"></a></dt>
<dd><p>Return a concurrent.futures Executor for submitting tasks
on this Client.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>**kwargs:</strong></p>
<blockquote>
<div><p>Any submit()- or map()- compatible arguments, such as
<cite>workers</cite> or <cite>resources</cite>.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">An Executor object that’s fully compatible with the concurrent.futures</p>
<p class="last">API.</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.get_metadata">
<code class="descname">get_metadata</code><span class="sig-paren">(</span><em>keys</em>, <em>default='__no_default__'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.get_metadata"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.get_metadata" title="Permalink to this definition"></a></dt>
<dd><p>Get arbitrary metadata from scheduler</p>
<p>See set_metadata for the full docstring with examples</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.set_metadata" title="distributed.client.Client.set_metadata"><code class="xref py py-obj docutils literal"><span class="pre">Client.set_metadata</span></code></a></p>
</div>
</dd></dl>

<dl class="classmethod">
<dt id="distributed.client.Client.get_restrictions">
<em class="property">classmethod </em><code class="descname">get_restrictions</code><span class="sig-paren">(</span><em>collections</em>, <em>workers</em>, <em>allow_other_workers</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.get_restrictions"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.get_restrictions" title="Permalink to this definition"></a></dt>
<dd><p>Get restrictions from inputs to compute/persist</p>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.get_scheduler_logs">
<code class="descname">get_scheduler_logs</code><span class="sig-paren">(</span><em>n=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.get_scheduler_logs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.get_scheduler_logs" title="Permalink to this definition"></a></dt>
<dd><p>Get logs from scheduler</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>n: int</strong></p>
<blockquote>
<div><p>Number of logs to retrive.  Maxes out at 10000 by default,
confiruable in config.yaml::log-length</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">Logs in reversed order (newest first)</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.get_versions">
<code class="descname">get_versions</code><span class="sig-paren">(</span><em>check=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.get_versions"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.get_versions" title="Permalink to this definition"></a></dt>
<dd><p>Return version info for the scheduler, all workers and myself</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>check</strong> : boolean, default False</p>
<blockquote class="last">
<div><p>raise ValueError if all required &amp; optional packages
do not match</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">get_versions</span><span class="p">()</span>  
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.get_worker_logs">
<code class="descname">get_worker_logs</code><span class="sig-paren">(</span><em>n=None</em>, <em>workers=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.get_worker_logs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.get_worker_logs" title="Permalink to this definition"></a></dt>
<dd><p>Get logs from workers</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>n: int</strong></p>
<blockquote>
<div><p>Number of logs to retrive.  Maxes out at 10000 by default,
confiruable in config.yaml::log-length</p>
</div></blockquote>
<p><strong>workers: iterable</strong></p>
<blockquote>
<div><p>List of worker addresses to retrive.  Gets all workers by default.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">Dictionary mapping worker address to logs.</p>
<p class="last">Logs are returned in reversed order (newest first)</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.has_what">
<code class="descname">has_what</code><span class="sig-paren">(</span><em>workers=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.has_what"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.has_what" title="Permalink to this definition"></a></dt>
<dd><p>Which keys are held by which workers</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>workers: list (optional)</strong></p>
<blockquote class="last">
<div><p>A list of worker addresses, defaults to all</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.who_has" title="distributed.client.Client.who_has"><code class="xref py py-obj docutils literal"><span class="pre">Client.who_has</span></code></a>, <a class="reference internal" href="#distributed.client.Client.ncores" title="distributed.client.Client.ncores"><code class="xref py py-obj docutils literal"><span class="pre">Client.ncores</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">inc</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">wait</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">has_what</span><span class="p">()</span>  
<span class="go">{&#39;192.168.1.141:46784&#39;: [&#39;inc-1c8dd6be1c21646c71f76c16d09304ea&#39;,</span>
<span class="go">                         &#39;inc-fd65c238a7ea60f6a01bf4c8a5fcf44b&#39;,</span>
<span class="go">                         &#39;inc-1e297fc27658d7b67b3a758f16bcf47a&#39;]}</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.list_datasets">
<code class="descname">list_datasets</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.list_datasets"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.list_datasets" title="Permalink to this definition"></a></dt>
<dd><p>List named datasets available on the scheduler</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.publish_dataset" title="distributed.client.Client.publish_dataset"><code class="xref py py-obj docutils literal"><span class="pre">Client.publish_dataset</span></code></a>, <a class="reference internal" href="#distributed.client.Client.get_dataset" title="distributed.client.Client.get_dataset"><code class="xref py py-obj docutils literal"><span class="pre">Client.get_dataset</span></code></a></p>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.map">
<code class="descname">map</code><span class="sig-paren">(</span><em>func</em>, <em>*iterables</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.map"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.map" title="Permalink to this definition"></a></dt>
<dd><p>Map a function on a sequence of arguments</p>
<p>Arguments can be normal objects or Futures</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>func: callable</strong></p>
<p><strong>iterables: Iterables, Iterators, or Queues</strong></p>
<p><strong>key: str, list</strong></p>
<blockquote>
<div><p>Prefix for task names if string.  Explicit names if list.</p>
</div></blockquote>
<p><strong>pure: bool (defaults to True)</strong></p>
<blockquote>
<div><p>Whether or not the function is pure.  Set <code class="docutils literal"><span class="pre">pure=False</span></code> for
impure functions like <code class="docutils literal"><span class="pre">np.random.random</span></code>.</p>
</div></blockquote>
<p><strong>workers: set, iterable of sets</strong></p>
<blockquote>
<div><p>A set of worker hostnames on which computations may be performed.
Leave empty to default to all workers (common case)</p>
</div></blockquote>
<p><strong>retries: int (default to 0)</strong></p>
<blockquote>
<div><p>Number of allowed automatic retries if a task fails</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">List, iterator, or Queue of futures, depending on the type of the</p>
<p class="last">inputs.</p>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.submit" title="distributed.client.Client.submit"><code class="xref py py-obj docutils literal"><span class="pre">Client.submit</span></code></a></dt>
<dd>Submit a single function</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">L</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">sequence</span><span class="p">)</span>  
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.nbytes">
<code class="descname">nbytes</code><span class="sig-paren">(</span><em>keys=None</em>, <em>summary=True</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.nbytes"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.nbytes" title="Permalink to this definition"></a></dt>
<dd><p>The bytes taken up by each key on the cluster</p>
<p>This is as measured by <code class="docutils literal"><span class="pre">sys.getsizeof</span></code> which may not accurately
reflect the true cost.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>keys: list (optional)</strong></p>
<blockquote>
<div><p>A list of keys, defaults to all keys</p>
</div></blockquote>
<p><strong>summary: boolean, (optional)</strong></p>
<blockquote class="last">
<div><p>Summarize keys into key types</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.who_has" title="distributed.client.Client.who_has"><code class="xref py py-obj docutils literal"><span class="pre">Client.who_has</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">inc</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">nbytes</span><span class="p">(</span><span class="n">summary</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>  
<span class="go">{&#39;inc-1c8dd6be1c21646c71f76c16d09304ea&#39;: 28,</span>
<span class="go"> &#39;inc-1e297fc27658d7b67b3a758f16bcf47a&#39;: 28,</span>
<span class="go"> &#39;inc-fd65c238a7ea60f6a01bf4c8a5fcf44b&#39;: 28}</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">nbytes</span><span class="p">(</span><span class="n">summary</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>  
<span class="go">{&#39;inc&#39;: 84}</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.ncores">
<code class="descname">ncores</code><span class="sig-paren">(</span><em>workers=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.ncores"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.ncores" title="Permalink to this definition"></a></dt>
<dd><p>The number of threads/cores available on each worker node</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>workers: list (optional)</strong></p>
<blockquote class="last">
<div><p>A list of workers that we care about specifically.
Leave empty to receive information about all workers.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.who_has" title="distributed.client.Client.who_has"><code class="xref py py-obj docutils literal"><span class="pre">Client.who_has</span></code></a>, <a class="reference internal" href="#distributed.client.Client.has_what" title="distributed.client.Client.has_what"><code class="xref py py-obj docutils literal"><span class="pre">Client.has_what</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">ncores</span><span class="p">()</span>  
<span class="go">{&#39;192.168.1.141:46784&#39;: 8,</span>
<span class="go"> &#39;192.167.1.142:47548&#39;: 8,</span>
<span class="go"> &#39;192.167.1.143:47329&#39;: 8,</span>
<span class="go"> &#39;192.167.1.144:37297&#39;: 8}</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.normalize_collection">
<code class="descname">normalize_collection</code><span class="sig-paren">(</span><em>collection</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.normalize_collection"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.normalize_collection" title="Permalink to this definition"></a></dt>
<dd><p>Replace collection’s tasks by already existing futures if they exist</p>
<p>This normalizes the tasks within a collections task graph against the
known futures within the scheduler.  It returns a copy of the
collection with a task graph that includes the overlapping futures.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.persist" title="distributed.client.Client.persist"><code class="xref py py-obj docutils literal"><span class="pre">Client.persist</span></code></a></dt>
<dd>trigger computation of collection’s tasks</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">__dask_graph__</span><span class="p">())</span>  <span class="c1"># x is a dask collection with 100 tasks  </span>
<span class="go">100</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">set</span><span class="p">(</span><span class="n">client</span><span class="o">.</span><span class="n">futures</span><span class="p">)</span><span class="o">.</span><span class="n">intersection</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">__dask_graph__</span><span class="p">())</span>  <span class="c1"># some overlap exists  </span>
<span class="go">10</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">normalize_collection</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">__dask_graph__</span><span class="p">())</span>  <span class="c1"># smaller computational graph  </span>
<span class="go">20</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.persist">
<code class="descname">persist</code><span class="sig-paren">(</span><em>collections</em>, <em>optimize_graph=True</em>, <em>workers=None</em>, <em>allow_other_workers=None</em>, <em>resources=None</em>, <em>retries=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.persist"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.persist" title="Permalink to this definition"></a></dt>
<dd><p>Persist dask collections on cluster</p>
<p>Starts computation of the collection on the cluster in the background.
Provides a new dask collection that is semantically identical to the
previous one, but now based off of futures currently in execution.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>collections: sequence or single dask object</strong></p>
<blockquote>
<div><p>Collections like dask.array or dataframe or dask.value objects</p>
</div></blockquote>
<p><strong>optimize_graph: bool</strong></p>
<blockquote>
<div><p>Whether or not to optimize the underlying graphs</p>
</div></blockquote>
<p><strong>workers: str, list, dict</strong></p>
<blockquote>
<div><p>Which workers can run which parts of the computation
If a string a list then the output collections will run on the listed</p>
<blockquote>
<div><p>workers, but other sub-computations can run anywhere</p>
</div></blockquote>
<dl class="docutils">
<dt>If a dict then keys should be (tuples of) collections and values</dt>
<dd><p class="first last">should be addresses or lists.</p>
</dd>
</dl>
</div></blockquote>
<p><strong>allow_other_workers: bool, list</strong></p>
<blockquote>
<div><p>If True then all restrictions in workers= are considered loose
If a list then only the keys for the listed collections are loose</p>
</div></blockquote>
<p><strong>retries: int (default to 0)</strong></p>
<blockquote>
<div><p>Number of allowed automatic retries if computing a result fails</p>
</div></blockquote>
<p><strong>kwargs:</strong></p>
<blockquote>
<div><p>Options to pass to the graph optimize calls</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">List of collections, or single collection, depending on type of input.</p>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.compute" title="distributed.client.Client.compute"><code class="xref py py-obj docutils literal"><span class="pre">Client.compute</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">xx</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">persist</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">xx</span><span class="p">,</span> <span class="n">yy</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">persist</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">])</span>  
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.processing">
<code class="descname">processing</code><span class="sig-paren">(</span><em>workers=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.processing"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.processing" title="Permalink to this definition"></a></dt>
<dd><p>The tasks currently running on each worker</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>workers: list (optional)</strong></p>
<blockquote class="last">
<div><p>A list of worker addresses, defaults to all</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.stacks" title="distributed.client.Client.stacks"><code class="xref py py-obj docutils literal"><span class="pre">Client.stacks</span></code></a>, <a class="reference internal" href="#distributed.client.Client.who_has" title="distributed.client.Client.who_has"><code class="xref py py-obj docutils literal"><span class="pre">Client.who_has</span></code></a>, <a class="reference internal" href="#distributed.client.Client.has_what" title="distributed.client.Client.has_what"><code class="xref py py-obj docutils literal"><span class="pre">Client.has_what</span></code></a>, <a class="reference internal" href="#distributed.client.Client.ncores" title="distributed.client.Client.ncores"><code class="xref py py-obj docutils literal"><span class="pre">Client.ncores</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">inc</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">processing</span><span class="p">()</span>  
<span class="go">{&#39;192.168.1.141:46784&#39;: [&#39;inc-1c8dd6be1c21646c71f76c16d09304ea&#39;,</span>
<span class="go">                         &#39;inc-fd65c238a7ea60f6a01bf4c8a5fcf44b&#39;,</span>
<span class="go">                         &#39;inc-1e297fc27658d7b67b3a758f16bcf47a&#39;]}</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.profile">
<code class="descname">profile</code><span class="sig-paren">(</span><em>key=None</em>, <em>start=None</em>, <em>stop=None</em>, <em>workers=None</em>, <em>merge_workers=True</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.profile"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.profile" title="Permalink to this definition"></a></dt>
<dd><p>Collect statistical profiling information about recent work</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>key: str</strong></p>
<blockquote>
<div><p>Key prefix to select, this is typically a function name like ‘inc’
Leave as None to collect all data</p>
</div></blockquote>
<p><strong>start: time</strong></p>
<p><strong>stop: time</strong></p>
<p><strong>workers: list</strong></p>
<blockquote class="last">
<div><p>List of workers to restrict profile information</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">profile</span><span class="p">()</span>  <span class="c1"># call on collections</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.publish_dataset">
<code class="descname">publish_dataset</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.publish_dataset"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.publish_dataset" title="Permalink to this definition"></a></dt>
<dd><p>Publish named datasets to scheduler</p>
<p>This stores a named reference to a dask collection or list of futures
on the scheduler.  These references are available to other Clients
which can download the collection or futures with <code class="docutils literal"><span class="pre">get_dataset</span></code>.</p>
<p>Datasets are not immediately computed.  You may wish to call
<code class="docutils literal"><span class="pre">Client.persist</span></code> prior to publishing a dataset.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>kwargs: dict</strong></p>
<blockquote>
<div><p>named collections to publish on the scheduler</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">None</p>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.list_datasets" title="distributed.client.Client.list_datasets"><code class="xref py py-obj docutils literal"><span class="pre">Client.list_datasets</span></code></a>, <a class="reference internal" href="#distributed.client.Client.get_dataset" title="distributed.client.Client.get_dataset"><code class="xref py py-obj docutils literal"><span class="pre">Client.get_dataset</span></code></a>, <a class="reference internal" href="#distributed.client.Client.unpublish_dataset" title="distributed.client.Client.unpublish_dataset"><code class="xref py py-obj docutils literal"><span class="pre">Client.unpublish_dataset</span></code></a>, <a class="reference internal" href="#distributed.client.Client.persist" title="distributed.client.Client.persist"><code class="xref py py-obj docutils literal"><span class="pre">Client.persist</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<p>Publishing client:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span> <span class="o">=</span> <span class="n">dd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;s3://...&#39;</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">df</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">persist</span><span class="p">(</span><span class="n">df</span><span class="p">)</span> 
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">publish_dataset</span><span class="p">(</span><span class="n">my_dataset</span><span class="o">=</span><span class="n">df</span><span class="p">)</span>  
</pre></div>
</div>
<p>Receiving client:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">list_datasets</span><span class="p">()</span>  
<span class="go">[&#39;my_dataset&#39;]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">df2</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">get_dataset</span><span class="p">(</span><span class="s1">&#39;my_dataset&#39;</span><span class="p">)</span>  
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.rebalance">
<code class="descname">rebalance</code><span class="sig-paren">(</span><em>futures=None</em>, <em>workers=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.rebalance"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.rebalance" title="Permalink to this definition"></a></dt>
<dd><p>Rebalance data within network</p>
<p>Move data between workers to roughly balance memory burden.  This
either affects a subset of the keys/workers or the entire network,
depending on keyword arguments.</p>
<p>This operation is generally not well tested against normal operation of
the scheduler.  It it not recommended to use it while waiting on
computations.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>futures: list, optional</strong></p>
<blockquote>
<div><p>A list of futures to balance, defaults all data</p>
</div></blockquote>
<p><strong>workers: list, optional</strong></p>
<blockquote class="last">
<div><p>A list of workers on which to balance, defaults to all workers</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.replicate">
<code class="descname">replicate</code><span class="sig-paren">(</span><em>futures</em>, <em>n=None</em>, <em>workers=None</em>, <em>branching_factor=2</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.replicate"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.replicate" title="Permalink to this definition"></a></dt>
<dd><p>Set replication of futures within network</p>
<p>Copy data onto many workers.  This helps to broadcast frequently
accessed data and it helps to improve resilience.</p>
<p>This performs a tree copy of the data throughout the network
individually on each piece of data.  This operation blocks until
complete.  It does not guarantee replication of data to future workers.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>futures: list of futures</strong></p>
<blockquote>
<div><p>Futures we wish to replicate</p>
</div></blockquote>
<p><strong>n: int, optional</strong></p>
<blockquote>
<div><p>Number of processes on the cluster on which to replicate the data.
Defaults to all.</p>
</div></blockquote>
<p><strong>workers: list of worker addresses</strong></p>
<blockquote>
<div><p>Workers on which we want to restrict the replication.
Defaults to all.</p>
</div></blockquote>
<p><strong>branching_factor: int, optional</strong></p>
<blockquote class="last">
<div><p>The number of workers that can copy data in each generation</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.rebalance" title="distributed.client.Client.rebalance"><code class="xref py py-obj docutils literal"><span class="pre">Client.rebalance</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">replicate</span><span class="p">([</span><span class="n">x</span><span class="p">])</span>  <span class="c1"># send to all workers  </span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">replicate</span><span class="p">([</span><span class="n">x</span><span class="p">],</span> <span class="n">n</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>  <span class="c1"># send to three workers  </span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">replicate</span><span class="p">([</span><span class="n">x</span><span class="p">],</span> <span class="n">workers</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;alice&#39;</span><span class="p">,</span> <span class="s1">&#39;bob&#39;</span><span class="p">])</span>  <span class="c1"># send to specific  </span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">replicate</span><span class="p">([</span><span class="n">x</span><span class="p">],</span> <span class="n">n</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">workers</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;alice&#39;</span><span class="p">,</span> <span class="s1">&#39;bob&#39;</span><span class="p">])</span>  <span class="c1"># send to one of specific workers  </span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">replicate</span><span class="p">([</span><span class="n">x</span><span class="p">],</span> <span class="n">n</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>  <span class="c1"># reduce replications </span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.restart">
<code class="descname">restart</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.restart"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.restart" title="Permalink to this definition"></a></dt>
<dd><p>Restart the distributed network</p>
<p>This kills all active work, deletes all data on the network, and
restarts the worker processes.</p>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.run">
<code class="descname">run</code><span class="sig-paren">(</span><em>function</em>, <em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.run"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.run" title="Permalink to this definition"></a></dt>
<dd><p>Run a function on all workers outside of task scheduling system</p>
<p>This calls a function on all currently known workers immediately,
blocks until those results come back, and returns the results
asynchronously as a dictionary keyed by worker address.  This method
if generally used for side effects, such and collecting diagnostic
information or installing libraries.</p>
<p>If your function takes an input argument named <code class="docutils literal"><span class="pre">dask_worker</span></code> then
that variable will be populated with the worker itself.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>function: callable</strong></p>
<p><strong>*args: arguments for remote function</strong></p>
<p><strong>**kwargs: keyword arguments for remote function</strong></p>
<p><strong>workers: list</strong></p>
<blockquote class="last">
<div><p>Workers on which to run the function. Defaults to all known workers.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">getpid</span><span class="p">)</span>  
<span class="go">{&#39;192.168.0.100:9000&#39;: 1234,</span>
<span class="go"> &#39;192.168.0.101:9000&#39;: 4321,</span>
<span class="go"> &#39;192.168.0.102:9000&#39;: 5555}</span>
</pre></div>
</div>
<p>Restrict computation to particular workers with the <code class="docutils literal"><span class="pre">workers=</span></code>
keyword argument.</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">getpid</span><span class="p">,</span> <span class="n">workers</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;192.168.0.100:9000&#39;</span><span class="p">,</span>
<span class="gp">... </span>                          <span class="s1">&#39;192.168.0.101:9000&#39;</span><span class="p">])</span>  
<span class="go">{&#39;192.168.0.100:9000&#39;: 1234,</span>
<span class="go"> &#39;192.168.0.101:9000&#39;: 4321}</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">get_status</span><span class="p">(</span><span class="n">dask_worker</span><span class="p">):</span>
<span class="gp">... </span>    <span class="k">return</span> <span class="n">dask_worker</span><span class="o">.</span><span class="n">status</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">get_hostname</span><span class="p">)</span>  
<span class="go">{&#39;192.168.0.100:9000&#39;: &#39;running&#39;,</span>
<span class="go"> &#39;192.168.0.101:9000&#39;: &#39;running}</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.run_coroutine">
<code class="descname">run_coroutine</code><span class="sig-paren">(</span><em>function</em>, <em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.run_coroutine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.run_coroutine" title="Permalink to this definition"></a></dt>
<dd><p>Spawn a coroutine on all workers.</p>
<p>This spaws a coroutine on all currently known workers and then waits
for the coroutine on each worker.  The coroutines’ results are returned
as a dictionary keyed by worker address.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>function: a coroutine function</strong></p>
<blockquote>
<div><dl class="docutils">
<dt>(typically a function wrapped in gen.coroutine or</dt>
<dd><p class="first last">a Python 3.5+ async function)</p>
</dd>
</dl>
</div></blockquote>
<p><strong>*args: arguments for remote function</strong></p>
<p><strong>**kwargs: keyword arguments for remote function</strong></p>
<p><strong>wait: boolean (default True)</strong></p>
<blockquote>
<div><p>Whether to wait for coroutines to end.</p>
</div></blockquote>
<p><strong>workers: list</strong></p>
<blockquote class="last">
<div><p>Workers on which to run the function. Defaults to all known workers.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.run_on_scheduler">
<code class="descname">run_on_scheduler</code><span class="sig-paren">(</span><em>function</em>, <em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.run_on_scheduler"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.run_on_scheduler" title="Permalink to this definition"></a></dt>
<dd><p>Run a function on the scheduler process</p>
<p>This is typically used for live debugging.  The function should take a
keyword argument <code class="docutils literal"><span class="pre">dask_scheduler=</span></code>, which will be given the scheduler
object itself.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.run" title="distributed.client.Client.run"><code class="xref py py-obj docutils literal"><span class="pre">Client.run</span></code></a></dt>
<dd>Run a function on all workers</dd>
<dt><a class="reference internal" href="#distributed.client.Client.start_ipython_scheduler" title="distributed.client.Client.start_ipython_scheduler"><code class="xref py py-obj docutils literal"><span class="pre">Client.start_ipython_scheduler</span></code></a></dt>
<dd>Start an IPython session on scheduler</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">get_number_of_tasks</span><span class="p">(</span><span class="n">dask_scheduler</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="gp">... </span>    <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="n">dask_scheduler</span><span class="o">.</span><span class="n">task_state</span><span class="p">)</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">run_on_scheduler</span><span class="p">(</span><span class="n">get_number_of_tasks</span><span class="p">)</span>  
<span class="go">100</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.scatter">
<code class="descname">scatter</code><span class="sig-paren">(</span><em>data</em>, <em>workers=None</em>, <em>broadcast=False</em>, <em>direct=None</em>, <em>hash=True</em>, <em>maxsize=0</em>, <em>timeout=3</em>, <em>asynchronous=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.scatter"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.scatter" title="Permalink to this definition"></a></dt>
<dd><p>Scatter data into distributed memory</p>
<p>This moves data from the local client process into the workers of the
distributed scheduler.  Note that it is often better to submit jobs to
your workers to have them load the data rather than loading data
locally and then scattering it out to them.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>data: list, iterator, dict, Queue, or object</strong></p>
<blockquote>
<div><p>Data to scatter out to workers.  Output type matches input type.</p>
</div></blockquote>
<p><strong>workers: list of tuples (optional)</strong></p>
<blockquote>
<div><p>Optionally constrain locations of data.
Specify workers as hostname/port pairs, e.g. <code class="docutils literal"><span class="pre">('127.0.0.1',</span> <span class="pre">8787)</span></code>.</p>
</div></blockquote>
<p><strong>broadcast: bool (defaults to False)</strong></p>
<blockquote>
<div><p>Whether to send each data element to all workers.
By default we round-robin based on number of cores.</p>
</div></blockquote>
<p><strong>direct: bool (defaults to automatically check)</strong></p>
<blockquote>
<div><p>Send data directly to workers, bypassing the central scheduler
This avoids burdening the scheduler but assumes that the client is
able to talk directly with the workers.</p>
</div></blockquote>
<p><strong>maxsize: int (optional)</strong></p>
<blockquote>
<div><p>Maximum size of queue if using queues, 0 implies infinite</p>
</div></blockquote>
<p><strong>hash: bool (optional)</strong></p>
<blockquote>
<div><p>Whether or not to hash data to determine key.
If False then this uses a random key</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">List, dict, iterator, or queue of futures matching the type of input.</p>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.gather" title="distributed.client.Client.gather"><code class="xref py py-obj docutils literal"><span class="pre">Client.gather</span></code></a></dt>
<dd>Gather data back to local process</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span> <span class="o">=</span> <span class="n">Client</span><span class="p">(</span><span class="s1">&#39;127.0.0.1:8787&#39;</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> 
<span class="go">&lt;Future: status: finished, key: c0a8a20f903a4915b94db8de3ea63195&gt;</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">scatter</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>  
<span class="go">[&lt;Future: status: finished, key: c0a8a20f903a4915b94db8de3ea63195&gt;,</span>
<span class="go"> &lt;Future: status: finished, key: 58e78e1b34eb49a68c65b54815d1b158&gt;,</span>
<span class="go"> &lt;Future: status: finished, key: d3395e15f605bc35ab1bac6341a285e2&gt;]</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">scatter</span><span class="p">({</span><span class="s1">&#39;x&#39;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s1">&#39;y&#39;</span><span class="p">:</span> <span class="mi">2</span><span class="p">,</span> <span class="s1">&#39;z&#39;</span><span class="p">:</span> <span class="mi">3</span><span class="p">})</span>  
<span class="go">{&#39;x&#39;: &lt;Future: status: finished, key: x&gt;,</span>
<span class="go"> &#39;y&#39;: &lt;Future: status: finished, key: y&gt;,</span>
<span class="go"> &#39;z&#39;: &lt;Future: status: finished, key: z&gt;}</span>
</pre></div>
</div>
<p>Constrain location of data to subset of workers</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">scatter</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="n">workers</span><span class="o">=</span><span class="p">[(</span><span class="s1">&#39;hostname&#39;</span><span class="p">,</span> <span class="mi">8788</span><span class="p">)])</span>   
</pre></div>
</div>
<p>Handle streaming sequences of data with iterators or queues</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">seq</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="nb">iter</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]))</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="nb">next</span><span class="p">(</span><span class="n">seq</span><span class="p">)</span>  
<span class="go">&lt;Future: status: finished, key: c0a8a20f903a4915b94db8de3ea63195&gt;,</span>
</pre></div>
</div>
<p>Broadcast data to all workers</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="p">[</span><span class="n">future</span><span class="p">]</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">scatter</span><span class="p">([</span><span class="n">element</span><span class="p">],</span> <span class="n">broadcast</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>  
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.scheduler_info">
<code class="descname">scheduler_info</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.scheduler_info"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.scheduler_info" title="Permalink to this definition"></a></dt>
<dd><p>Basic information about the workers in the cluster</p>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">scheduler_info</span><span class="p">()</span>  
<span class="go">{&#39;id&#39;: &#39;2de2b6da-69ee-11e6-ab6a-e82aea155996&#39;,</span>
<span class="go"> &#39;services&#39;: {},</span>
<span class="go"> &#39;type&#39;: &#39;Scheduler&#39;,</span>
<span class="go"> &#39;workers&#39;: {&#39;127.0.0.1:40575&#39;: {&#39;active&#39;: 0,</span>
<span class="go">                                 &#39;last-seen&#39;: 1472038237.4845693,</span>
<span class="go">                                 &#39;name&#39;: &#39;127.0.0.1:40575&#39;,</span>
<span class="go">                                 &#39;services&#39;: {},</span>
<span class="go">                                 &#39;stored&#39;: 0,</span>
<span class="go">                                 &#39;time-delay&#39;: 0.0061032772064208984}}}</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.set_metadata">
<code class="descname">set_metadata</code><span class="sig-paren">(</span><em>key</em>, <em>value</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.set_metadata"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.set_metadata" title="Permalink to this definition"></a></dt>
<dd><p>Set arbitrary metadata in the scheduler</p>
<p>This allows you to store small amounts of data on the central scheduler
process for administrative purposes.  Data should be msgpack
serializable (ints, strings, lists, dicts)</p>
<p>If the key corresponds to a task then that key will be cleaned up when
the task is forgotten by the scheduler.</p>
<p>If the key is a list then it will be assumed that you want to index
into a nested dictionary structure using those keys.  For example if
you call the following:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">set_metadata</span><span class="p">([</span><span class="s1">&#39;a&#39;</span><span class="p">,</span> <span class="s1">&#39;b&#39;</span><span class="p">,</span> <span class="s1">&#39;c&#39;</span><span class="p">],</span> <span class="mi">123</span><span class="p">)</span>
</pre></div>
</div>
<p>Then this is the same as setting</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">scheduler</span><span class="o">.</span><span class="n">task_metadata</span><span class="p">[</span><span class="s1">&#39;a&#39;</span><span class="p">][</span><span class="s1">&#39;b&#39;</span><span class="p">][</span><span class="s1">&#39;c&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">123</span>
</pre></div>
</div>
<p>The lower level dictionaries will be created on demand.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.get_metadata" title="distributed.client.Client.get_metadata"><code class="xref py py-obj docutils literal"><span class="pre">get_metadata</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">set_metadata</span><span class="p">(</span><span class="s1">&#39;x&#39;</span><span class="p">,</span> <span class="mi">123</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">get_metadata</span><span class="p">(</span><span class="s1">&#39;x&#39;</span><span class="p">)</span>  
<span class="go">123</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">set_metadata</span><span class="p">([</span><span class="s1">&#39;x&#39;</span><span class="p">,</span> <span class="s1">&#39;y&#39;</span><span class="p">],</span> <span class="mi">123</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">get_metadata</span><span class="p">(</span><span class="s1">&#39;x&#39;</span><span class="p">)</span>  
<span class="go">{&#39;y&#39;: 123}</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">set_metadata</span><span class="p">([</span><span class="s1">&#39;x&#39;</span><span class="p">,</span> <span class="s1">&#39;w&#39;</span><span class="p">,</span> <span class="s1">&#39;z&#39;</span><span class="p">],</span> <span class="mi">456</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">get_metadata</span><span class="p">(</span><span class="s1">&#39;x&#39;</span><span class="p">)</span>  
<span class="go">{&#39;y&#39;: 123, &#39;w&#39;: {&#39;z&#39;: 456}}</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">get_metadata</span><span class="p">([</span><span class="s1">&#39;x&#39;</span><span class="p">,</span> <span class="s1">&#39;w&#39;</span><span class="p">])</span>  
<span class="go">{&#39;z&#39;: 456}</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.shutdown">
<code class="descname">shutdown</code><span class="sig-paren">(</span><em>timeout=10</em><span class="sig-paren">)</span><a class="headerlink" href="#distributed.client.Client.shutdown" title="Permalink to this definition"></a></dt>
<dd><p>Close this client</p>
<p>Clients will also close automatically when your Python session ends</p>
<p>If you started a client without arguments like <code class="docutils literal"><span class="pre">Client()</span></code> then this
will also close the local cluster that was started at the same time.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.restart" title="distributed.client.Client.restart"><code class="xref py py-obj docutils literal"><span class="pre">Client.restart</span></code></a></p>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.stacks">
<code class="descname">stacks</code><span class="sig-paren">(</span><em>workers=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.stacks"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.stacks" title="Permalink to this definition"></a></dt>
<dd><p>The task queues on each worker</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>workers: list (optional)</strong></p>
<blockquote class="last">
<div><p>A list of worker addresses, defaults to all</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.processing" title="distributed.client.Client.processing"><code class="xref py py-obj docutils literal"><span class="pre">Client.processing</span></code></a>, <a class="reference internal" href="#distributed.client.Client.who_has" title="distributed.client.Client.who_has"><code class="xref py py-obj docutils literal"><span class="pre">Client.who_has</span></code></a>, <a class="reference internal" href="#distributed.client.Client.has_what" title="distributed.client.Client.has_what"><code class="xref py py-obj docutils literal"><span class="pre">Client.has_what</span></code></a>, <a class="reference internal" href="#distributed.client.Client.ncores" title="distributed.client.Client.ncores"><code class="xref py py-obj docutils literal"><span class="pre">Client.ncores</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">inc</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">stacks</span><span class="p">()</span>  
<span class="go">{&#39;192.168.1.141:46784&#39;: [&#39;inc-1c8dd6be1c21646c71f76c16d09304ea&#39;,</span>
<span class="go">                         &#39;inc-fd65c238a7ea60f6a01bf4c8a5fcf44b&#39;,</span>
<span class="go">                         &#39;inc-1e297fc27658d7b67b3a758f16bcf47a&#39;]}</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.start">
<code class="descname">start</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.start"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.start" title="Permalink to this definition"></a></dt>
<dd><p>Start scheduler running in separate thread</p>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.start_ipython_scheduler">
<code class="descname">start_ipython_scheduler</code><span class="sig-paren">(</span><em>magic_name='scheduler_if_ipython'</em>, <em>qtconsole=False</em>, <em>qtconsole_args=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.start_ipython_scheduler"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.start_ipython_scheduler" title="Permalink to this definition"></a></dt>
<dd><p>Start IPython kernel on the scheduler</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>magic_name: str or None (optional)</strong></p>
<blockquote>
<div><p>If defined, register IPython magic with this name for
executing code on the scheduler.
If not defined, register %scheduler magic if IPython is running.</p>
</div></blockquote>
<p><strong>qtconsole: bool (optional)</strong></p>
<blockquote>
<div><p>If True, launch a Jupyter QtConsole connected to the worker(s).</p>
</div></blockquote>
<p><strong>qtconsole_args: list(str) (optional)</strong></p>
<blockquote>
<div><p>Additional arguments to pass to the qtconsole on startup.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">connection_info: dict</p>
<blockquote class="last">
<div><p>connection_info dict containing info necessary
to connect Jupyter clients to the scheduler.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.start_ipython_workers" title="distributed.client.Client.start_ipython_workers"><code class="xref py py-obj docutils literal"><span class="pre">Client.start_ipython_workers</span></code></a></dt>
<dd>Start IPython on the workers</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">start_ipython_scheduler</span><span class="p">()</span> 
<span class="gp">&gt;&gt;&gt; </span><span class="o">%</span><span class="n">scheduler</span> <span class="n">scheduler</span><span class="o">.</span><span class="n">processing</span>  
<span class="go">{&#39;127.0.0.1:3595&#39;: {&#39;inc-1&#39;, &#39;inc-2&#39;},</span>
<span class="go"> &#39;127.0.0.1:53589&#39;: {&#39;inc-2&#39;, &#39;add-5&#39;}}</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">start_ipython_scheduler</span><span class="p">(</span><span class="n">qtconsole</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> 
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.start_ipython_workers">
<code class="descname">start_ipython_workers</code><span class="sig-paren">(</span><em>workers=None</em>, <em>magic_names=False</em>, <em>qtconsole=False</em>, <em>qtconsole_args=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.start_ipython_workers"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.start_ipython_workers" title="Permalink to this definition"></a></dt>
<dd><p>Start IPython kernels on workers</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>workers: list (optional)</strong></p>
<blockquote>
<div><p>A list of worker addresses, defaults to all</p>
</div></blockquote>
<p><strong>magic_names: str or list(str) (optional)</strong></p>
<blockquote>
<div><p>If defined, register IPython magics with these names for
executing code on the workers.  If string has asterix then expand
asterix into 0, 1, …, n for n workers</p>
</div></blockquote>
<p><strong>qtconsole: bool (optional)</strong></p>
<blockquote>
<div><p>If True, launch a Jupyter QtConsole connected to the worker(s).</p>
</div></blockquote>
<p><strong>qtconsole_args: list(str) (optional)</strong></p>
<blockquote>
<div><p>Additional arguments to pass to the qtconsole on startup.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">iter_connection_info: list</p>
<blockquote class="last">
<div><p>List of connection_info dicts containing info necessary
to connect Jupyter clients to the workers.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.start_ipython_scheduler" title="distributed.client.Client.start_ipython_scheduler"><code class="xref py py-obj docutils literal"><span class="pre">Client.start_ipython_scheduler</span></code></a></dt>
<dd>start ipython on the scheduler</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">info</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">start_ipython_workers</span><span class="p">()</span> 
<span class="gp">&gt;&gt;&gt; </span><span class="o">%</span><span class="n">remote</span> <span class="n">info</span><span class="p">[</span><span class="s1">&#39;192.168.1.101:5752&#39;</span><span class="p">]</span> <span class="n">worker</span><span class="o">.</span><span class="n">data</span>  
<span class="go">{&#39;x&#39;: 1, &#39;y&#39;: 100}</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">start_ipython_workers</span><span class="p">(</span><span class="s1">&#39;192.168.1.101:5752&#39;</span><span class="p">,</span> <span class="n">magic_names</span><span class="o">=</span><span class="s1">&#39;w&#39;</span><span class="p">)</span> 
<span class="gp">&gt;&gt;&gt; </span><span class="o">%</span><span class="n">w</span> <span class="n">worker</span><span class="o">.</span><span class="n">data</span>  
<span class="go">{&#39;x&#39;: 1, &#39;y&#39;: 100}</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">start_ipython_workers</span><span class="p">(</span><span class="s1">&#39;192.168.1.101:5752&#39;</span><span class="p">,</span> <span class="n">qtconsole</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> 
</pre></div>
</div>
<p>Add asterix * in magic names to add one magic per worker</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">start_ipython_workers</span><span class="p">(</span><span class="n">magic_names</span><span class="o">=</span><span class="s1">&#39;w_*&#39;</span><span class="p">)</span> 
<span class="gp">&gt;&gt;&gt; </span><span class="o">%</span><span class="n">w_0</span> <span class="n">worker</span><span class="o">.</span><span class="n">data</span>  
<span class="go">{&#39;x&#39;: 1, &#39;y&#39;: 100}</span>
<span class="gp">&gt;&gt;&gt; </span><span class="o">%</span><span class="n">w_1</span> <span class="n">worker</span><span class="o">.</span><span class="n">data</span>  
<span class="go">{&#39;z&#39;: 5}</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.submit">
<code class="descname">submit</code><span class="sig-paren">(</span><em>func</em>, <em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.submit"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.submit" title="Permalink to this definition"></a></dt>
<dd><p>Submit a function application to the scheduler</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>func: callable</strong></p>
<p><strong>*args:</strong></p>
<p><strong>**kwargs:</strong></p>
<p><strong>pure: bool (defaults to True)</strong></p>
<blockquote>
<div><p>Whether or not the function is pure.  Set <code class="docutils literal"><span class="pre">pure=False</span></code> for
impure functions like <code class="docutils literal"><span class="pre">np.random.random</span></code>.</p>
</div></blockquote>
<p><strong>workers: set, iterable of sets</strong></p>
<blockquote>
<div><p>A set of worker hostnames on which computations may be performed.
Leave empty to default to all workers (common case)</p>
</div></blockquote>
<p><strong>key: str</strong></p>
<blockquote>
<div><p>Unique identifier for the task.  Defaults to function-name and hash</p>
</div></blockquote>
<p><strong>allow_other_workers: bool (defaults to False)</strong></p>
<blockquote>
<div><p>Used with <cite>workers</cite>. Inidicates whether or not the computations
may be performed on workers that are not in the <cite>workers</cite> set(s).</p>
</div></blockquote>
<p><strong>retries: int (default to 0)</strong></p>
<blockquote>
<div><p>Number of allowed automatic retries if the task fails</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">Future</p>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client.map" title="distributed.client.Client.map"><code class="xref py py-obj docutils literal"><span class="pre">Client.map</span></code></a></dt>
<dd>Submit on many arguments at once</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>  
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.unpublish_dataset">
<code class="descname">unpublish_dataset</code><span class="sig-paren">(</span><em>name</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.unpublish_dataset"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.unpublish_dataset" title="Permalink to this definition"></a></dt>
<dd><p>Remove named datasets from scheduler</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.publish_dataset" title="distributed.client.Client.publish_dataset"><code class="xref py py-obj docutils literal"><span class="pre">Client.publish_dataset</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">list_datasets</span><span class="p">()</span>  
<span class="go">[&#39;my_dataset&#39;]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">unpublish_datasets</span><span class="p">(</span><span class="s1">&#39;my_dataset&#39;</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">list_datasets</span><span class="p">()</span>  
<span class="go">[]</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.upload_file">
<code class="descname">upload_file</code><span class="sig-paren">(</span><em>filename</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.upload_file"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.upload_file" title="Permalink to this definition"></a></dt>
<dd><p>Upload local package to workers</p>
<p>This sends a local file up to all worker nodes.  This file is placed
into a temporary directory on Python’s system path so any .py, .pyc, .egg
or .zip  files will be importable.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>filename: string</strong></p>
<blockquote class="last">
<div><p>Filename of .py, .pyc, .egg or .zip file to send to workers</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">client</span><span class="o">.</span><span class="n">upload_file</span><span class="p">(</span><span class="s1">&#39;mylibrary.egg&#39;</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">mylibrary</span> <span class="k">import</span> <span class="n">myfunc</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">L</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">myfunc</span><span class="p">,</span> <span class="n">seq</span><span class="p">)</span>  
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Client.who_has">
<code class="descname">who_has</code><span class="sig-paren">(</span><em>futures=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Client.who_has"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Client.who_has" title="Permalink to this definition"></a></dt>
<dd><p>The workers storing each future’s data</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>futures: list (optional)</strong></p>
<blockquote class="last">
<div><p>A list of futures, defaults to all data</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.has_what" title="distributed.client.Client.has_what"><code class="xref py py-obj docutils literal"><span class="pre">Client.has_what</span></code></a>, <a class="reference internal" href="#distributed.client.Client.ncores" title="distributed.client.Client.ncores"><code class="xref py py-obj docutils literal"><span class="pre">Client.ncores</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">inc</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">wait</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">who_has</span><span class="p">()</span>  
<span class="go">{&#39;inc-1c8dd6be1c21646c71f76c16d09304ea&#39;: [&#39;192.168.1.141:46784&#39;],</span>
<span class="go"> &#39;inc-1e297fc27658d7b67b3a758f16bcf47a&#39;: [&#39;192.168.1.141:46784&#39;],</span>
<span class="go"> &#39;inc-fd65c238a7ea60f6a01bf4c8a5fcf44b&#39;: [&#39;192.168.1.141:46784&#39;]}</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">who_has</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">])</span>  
<span class="go">{&#39;inc-1c8dd6be1c21646c71f76c16d09304ea&#39;: [&#39;192.168.1.141:46784&#39;],</span>
<span class="go"> &#39;inc-1e297fc27658d7b67b3a758f16bcf47a&#39;: [&#39;192.168.1.141:46784&#39;]}</span>
</pre></div>
</div>
</dd></dl>

</dd></dl>

<dl class="class">
<dt id="distributed.recreate_exceptions.ReplayExceptionClient">
<em class="property">class </em><code class="descclassname">distributed.recreate_exceptions.</code><code class="descname">ReplayExceptionClient</code><span class="sig-paren">(</span><em>client</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/recreate_exceptions.html#ReplayExceptionClient"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.recreate_exceptions.ReplayExceptionClient" title="Permalink to this definition"></a></dt>
<dd><p>A plugin for the client allowing replay of remote exceptions locally</p>
<p>Adds the following methods (and their async variants)to the given client:</p>
<ul class="simple">
<li><code class="docutils literal"><span class="pre">recreate_error_locally</span></code>: main user method</li>
<li><dl class="first docutils">
<dt><code class="docutils literal"><span class="pre">get_futures_error</span></code>: gets the task, its details and dependencies,</dt>
<dd>responsible for failure of the given future.</dd>
</dl>
</li>
</ul>
<dl class="method">
<dt id="distributed.recreate_exceptions.ReplayExceptionClient.get_futures_error">
<code class="descname">get_futures_error</code><span class="sig-paren">(</span><em>future</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/recreate_exceptions.html#ReplayExceptionClient.get_futures_error"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.recreate_exceptions.ReplayExceptionClient.get_futures_error" title="Permalink to this definition"></a></dt>
<dd><p>Ask the scheduler details of the sub-task of the given failed future</p>
<p>When a future evaluates to a status of “error”, i.e., an exception
was raised in a task within its graph, we an get information from
the scheduler. This function gets the details of the specific task
that raised the exception and led to the error, but does not fetch
data from the cluster or execute the function.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>future</strong> : future that failed, having <code class="docutils literal"><span class="pre">status==&quot;error&quot;</span></code>, typically</p>
<blockquote>
<div><p>after an attempt to <code class="docutils literal"><span class="pre">gather()</span></code> shows a stack-stace.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">Tuple:</p>
<ul class="last simple">
<li>the function that raised an exception</li>
<li>argument list (a tuple), may include values and keys</li>
<li>keyword arguments (a dictionary), may include values and keys</li>
<li>list of keys that the function requires to be fetched to run</li>
</ul>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.recreate_exceptions.ReplayExceptionClient.recreate_error_locally" title="distributed.recreate_exceptions.ReplayExceptionClient.recreate_error_locally"><code class="xref py py-obj docutils literal"><span class="pre">ReplayExceptionClient.recreate_error_locally</span></code></a></p>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.recreate_exceptions.ReplayExceptionClient.recreate_error_locally">
<code class="descname">recreate_error_locally</code><span class="sig-paren">(</span><em>future</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/recreate_exceptions.html#ReplayExceptionClient.recreate_error_locally"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.recreate_exceptions.ReplayExceptionClient.recreate_error_locally" title="Permalink to this definition"></a></dt>
<dd><p>For a failed calculation, perform the blamed task locally for debugging.</p>
<p>This operation should be performed after a future (result of <code class="docutils literal"><span class="pre">gather</span></code>,
<code class="docutils literal"><span class="pre">compute</span></code>, etc) comes back with a status of “error”, if the stack-
trace is not informative enough to diagnose the problem. The specific
task (part of the graph pointing to the future) responsible for the
error will be fetched from the scheduler, together with the values of
its inputs. The function will then be executed, so that <code class="docutils literal"><span class="pre">pdb</span></code> can
be used for debugging.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>future</strong> : future or collection that failed</p>
<blockquote>
<div><p>The same thing as was given to <code class="docutils literal"><span class="pre">gather</span></code>, but came back with
an exception/stack-trace. Can also be a (persisted) dask collection
containing any errored futures.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">Nothing; the function runs and should raise an exception, allowing</p>
<p class="last">the debugger to run.</p>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">future</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">div</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>         
<span class="gp">&gt;&gt;&gt; </span><span class="n">future</span><span class="o">.</span><span class="n">status</span>                        
<span class="go">&#39;error&#39;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">recreate_error_locally</span><span class="p">(</span><span class="n">future</span><span class="p">)</span>     
<span class="go">ZeroDivisionError: division by zero</span>
</pre></div>
</div>
<p>If you’re in IPython you might take this opportunity to use pdb</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="o">%</span><span class="n">pdb</span>                                 
<span class="go">Automatic pdb calling has been turned ON</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">recreate_error_locally</span><span class="p">(</span><span class="n">future</span><span class="p">)</span>     
<span class="go">ZeroDivisionError: division by zero</span>
<span class="go">      1 def div(x, y):</span>
<span class="go">----&gt; 2     return x / y</span>
<span class="go">ipdb&gt;</span>
</pre></div>
</div>
</dd></dl>

</dd></dl>

</div>
<div class="section" id="future">
<h2>Future<a class="headerlink" href="#future" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="distributed.client.Future">
<em class="property">class </em><code class="descclassname">distributed.client.</code><code class="descname">Future</code><span class="sig-paren">(</span><em>key</em>, <em>client=None</em>, <em>inform=True</em>, <em>state=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Future"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Future" title="Permalink to this definition"></a></dt>
<dd><p>A remotely running computation</p>
<p>A Future is a local proxy to a result running on a remote worker.  A user
manages future objects in the local Python process to determine what
happens in the larger cluster.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>key: str, or tuple</strong></p>
<blockquote>
<div><p>Key of remote data to which this future refers</p>
</div></blockquote>
<p><strong>client: Client</strong></p>
<blockquote>
<div><p>Client that should own this future.  Defaults to _get_global_client()</p>
</div></blockquote>
<p><strong>inform: bool</strong></p>
<blockquote class="last">
<div><p>Do we inform the scheduler that we need an update on this future</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client" title="distributed.client.Client"><code class="xref py py-obj docutils literal"><span class="pre">Client</span></code></a></dt>
<dd>Creates futures</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<p>Futures typically emerge from Client computations</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">my_future</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>  
</pre></div>
</div>
<p>We can track the progress and results of a future</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">my_future</span>  
<span class="go">&lt;Future: status: finished, key: add-8f6e709446674bad78ea8aeecfee188e&gt;</span>
</pre></div>
</div>
<p>We can get the result or the exception and traceback from the future</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">my_future</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>  
</pre></div>
</div>
<dl class="method">
<dt id="distributed.client.Future.add_done_callback">
<code class="descname">add_done_callback</code><span class="sig-paren">(</span><em>fn</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Future.add_done_callback"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Future.add_done_callback" title="Permalink to this definition"></a></dt>
<dd><p>Call callback on future when callback has finished</p>
<p>The callback <code class="docutils literal"><span class="pre">fn</span></code> should take the future as its only argument.  This
will be called regardless of if the future completes successfully,
errs, or is cancelled</p>
<p>The callback is executed in a separate thread.</p>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Future.cancel">
<code class="descname">cancel</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Future.cancel"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Future.cancel" title="Permalink to this definition"></a></dt>
<dd><p>Cancel request to run this future</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Client.cancel" title="distributed.client.Client.cancel"><code class="xref py py-obj docutils literal"><span class="pre">Client.cancel</span></code></a></p>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Future.cancelled">
<code class="descname">cancelled</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Future.cancelled"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Future.cancelled" title="Permalink to this definition"></a></dt>
<dd><p>Returns True if the future has been cancelled</p>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Future.done">
<code class="descname">done</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Future.done"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Future.done" title="Permalink to this definition"></a></dt>
<dd><p>Is the computation complete?</p>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Future.exception">
<code class="descname">exception</code><span class="sig-paren">(</span><em>timeout=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Future.exception"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Future.exception" title="Permalink to this definition"></a></dt>
<dd><p>Return the exception of a failed task</p>
<p>If <em>timeout</em> seconds are elapsed before returning, a TimeoutError
is raised.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Future.traceback" title="distributed.client.Future.traceback"><code class="xref py py-obj docutils literal"><span class="pre">Future.traceback</span></code></a></p>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Future.result">
<code class="descname">result</code><span class="sig-paren">(</span><em>timeout=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Future.result"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Future.result" title="Permalink to this definition"></a></dt>
<dd><p>Wait until computation completes, gather result to local process.</p>
<p>If <em>timeout</em> seconds are elapsed before returning, a TimeoutError
is raised.</p>
</dd></dl>

<dl class="method">
<dt id="distributed.client.Future.traceback">
<code class="descname">traceback</code><span class="sig-paren">(</span><em>timeout=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#Future.traceback"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.Future.traceback" title="Permalink to this definition"></a></dt>
<dd><p>Return the traceback of a failed task</p>
<p>This returns a traceback object.  You can inspect this object using the
<code class="docutils literal"><span class="pre">traceback</span></code> module.  Alternatively if you call <code class="docutils literal"><span class="pre">future.result()</span></code>
this traceback will accompany the raised exception.</p>
<p>If <em>timeout</em> seconds are elapsed before returning, a TimeoutError
is raised.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.client.Future.exception" title="distributed.client.Future.exception"><code class="xref py py-obj docutils literal"><span class="pre">Future.exception</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">traceback</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">tb</span> <span class="o">=</span> <span class="n">future</span><span class="o">.</span><span class="n">traceback</span><span class="p">()</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">traceback</span><span class="o">.</span><span class="n">export_tb</span><span class="p">(</span><span class="n">tb</span><span class="p">)</span>  
<span class="go">[...]</span>
</pre></div>
</div>
</dd></dl>

</dd></dl>

</div>
<div class="section" id="other">
<h2>Other<a class="headerlink" href="#other" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt id="distributed.client.as_completed">
<code class="descclassname">distributed.client.</code><code class="descname">as_completed</code><span class="sig-paren">(</span><em>futures=None</em>, <em>loop=None</em>, <em>with_results=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#as_completed"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.as_completed" title="Permalink to this definition"></a></dt>
<dd><p>Return futures in the order in which they complete</p>
<p>This returns an iterator that yields the input future objects in the order
in which they complete.  Calling <code class="docutils literal"><span class="pre">next</span></code> on the iterator will block until
the next future completes, irrespective of order.</p>
<p>Additionally, you can also add more futures to this object during
computation with the <code class="docutils literal"><span class="pre">.add</span></code> method</p>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">inc</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="k">for</span> <span class="n">future</span> <span class="ow">in</span> <span class="n">as_completed</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span><span class="p">]):</span>  
<span class="gp">... </span>    <span class="nb">print</span><span class="p">(</span><span class="n">future</span><span class="o">.</span><span class="n">result</span><span class="p">())</span>  
<span class="go">3</span>
<span class="go">2</span>
<span class="go">4</span>
</pre></div>
</div>
<p>Add more futures during computation</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">inc</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">ac</span> <span class="o">=</span> <span class="n">as_completed</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span><span class="p">])</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="k">for</span> <span class="n">future</span> <span class="ow">in</span> <span class="n">ac</span><span class="p">:</span>  
<span class="gp">... </span>    <span class="nb">print</span><span class="p">(</span><span class="n">future</span><span class="o">.</span><span class="n">result</span><span class="p">())</span>  
<span class="gp">... </span>    <span class="k">if</span> <span class="n">random</span><span class="o">.</span><span class="n">random</span><span class="p">()</span> <span class="o">&lt;</span> <span class="mf">0.5</span><span class="p">:</span>  
<span class="gp">... </span>        <span class="n">ac</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">double</span><span class="p">,</span> <span class="n">future</span><span class="p">))</span>  
<span class="go">4</span>
<span class="go">2</span>
<span class="go">8</span>
<span class="go">3</span>
<span class="go">6</span>
<span class="go">12</span>
<span class="go">24</span>
</pre></div>
</div>
<p>Optionally wait until the result has been gathered as well</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">ac</span> <span class="o">=</span> <span class="n">as_completed</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span><span class="p">],</span> <span class="n">with_results</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="k">for</span> <span class="n">future</span><span class="p">,</span> <span class="n">result</span> <span class="ow">in</span> <span class="n">ac</span><span class="p">:</span>  
<span class="gp">... </span>    <span class="nb">print</span><span class="p">(</span><span class="n">result</span><span class="p">)</span>  
<span class="go">2</span>
<span class="go">4</span>
<span class="go">3</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="distributed.diagnostics.progress">
<code class="descclassname">distributed.diagnostics.</code><code class="descname">progress</code><span class="sig-paren">(</span><em>*futures</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/diagnostics/progressbar.html#progress"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.diagnostics.progress" title="Permalink to this definition"></a></dt>
<dd><p>Track progress of futures</p>
<p>This operates differently in the notebook and the console</p>
<ul class="simple">
<li>Notebook:  This returns immediately, leaving an IPython widget on screen</li>
<li>Console:  This blocks until the computation completes</li>
</ul>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>futures: Futures</strong></p>
<blockquote>
<div><p>A list of futures or keys to track</p>
</div></blockquote>
<p><strong>notebook: bool (optional)</strong></p>
<blockquote>
<div><p>Running in the notebook or not (defaults to guess)</p>
</div></blockquote>
<p><strong>multi: bool (optional)</strong></p>
<blockquote>
<div><p>Track different functions independently (defaults to True)</p>
</div></blockquote>
<p><strong>complete: bool (optional)</strong></p>
<blockquote class="last">
<div><p>Track all keys (True) or only keys that have not yet run (False)
(defaults to True)</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Notes</p>
<p>In the notebook, the output of <cite>progress</cite> must be the last statement
in the cell. Typically, this means calling <cite>progress</cite> at the end of a
cell.</p>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">progress</span><span class="p">(</span><span class="n">futures</span><span class="p">)</span>  
<span class="go">[########################################] | 100% Completed |  1.7s</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="distributed.client.wait">
<code class="descclassname">distributed.client.</code><code class="descname">wait</code><span class="sig-paren">(</span><em>fs</em>, <em>timeout=None</em>, <em>return_when='ALL_COMPLETED'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/client.html#wait"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.client.wait" title="Permalink to this definition"></a></dt>
<dd><p>Wait until all futures are complete</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>fs: list of futures</strong></p>
<p><strong>timeout: number, optional</strong></p>
<blockquote>
<div><p>Time in seconds after which to raise a gen.TimeoutError</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">Named tuple of completed, not completed</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="distributed.worker_client">
<code class="descclassname">distributed.</code><code class="descname">worker_client</code><span class="sig-paren">(</span><em>timeout=3</em>, <em>separate_thread=True</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/worker_client.html#worker_client"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.worker_client" title="Permalink to this definition"></a></dt>
<dd><p>Get client for this thread</p>
<p>This context manager is intended to be called within functions that we run
on workers.  When run as a context manager it delivers a client
<code class="docutils literal"><span class="pre">Client</span></code> object that can submit other tasks directly from that worker.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>timeout: Number</strong></p>
<blockquote>
<div><p>Timeout after which to err</p>
</div></blockquote>
<p><strong>separate_thread: bool, optional</strong></p>
<blockquote class="last">
<div><p>Whether to run this function outside of the normal thread pool
defaults to True</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.get_worker" title="distributed.get_worker"><code class="xref py py-obj docutils literal"><span class="pre">get_worker</span></code></a>, <a class="reference internal" href="#distributed.get_client" title="distributed.get_client"><code class="xref py py-obj docutils literal"><span class="pre">get_client</span></code></a>, <a class="reference internal" href="#distributed.secede" title="distributed.secede"><code class="xref py py-obj docutils literal"><span class="pre">secede</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">func</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
<span class="gp">... </span>    <span class="k">with</span> <span class="n">worker_client</span><span class="p">()</span> <span class="k">as</span> <span class="n">c</span><span class="p">:</span>  <span class="c1"># connect from worker back to scheduler</span>
<span class="gp">... </span>        <span class="n">a</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">inc</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span>     <span class="c1"># this task can submit more tasks</span>
<span class="gp">... </span>        <span class="n">b</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">dec</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span>
<span class="gp">... </span>        <span class="n">result</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">gather</span><span class="p">([</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">])</span>  <span class="c1"># and gather results</span>
<span class="gp">... </span>    <span class="k">return</span> <span class="n">result</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">future</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>  <span class="c1"># submit func(1) on cluster</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="distributed.get_worker">
<code class="descclassname">distributed.</code><code class="descname">get_worker</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/worker.html#get_worker"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.get_worker" title="Permalink to this definition"></a></dt>
<dd><p>Get the worker currently running this task</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.get_client" title="distributed.get_client"><code class="xref py py-obj docutils literal"><span class="pre">get_client</span></code></a>, <a class="reference internal" href="#distributed.worker_client" title="distributed.worker_client"><code class="xref py py-obj docutils literal"><span class="pre">worker_client</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">f</span><span class="p">():</span>
<span class="gp">... </span>    <span class="n">worker</span> <span class="o">=</span> <span class="n">get_worker</span><span class="p">()</span>  <span class="c1"># The worker on which this task is running</span>
<span class="gp">... </span>    <span class="k">return</span> <span class="n">worker</span><span class="o">.</span><span class="n">address</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">future</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">future</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>  
<span class="go">&#39;tcp://127.0.0.1:47373&#39;</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="distributed.get_client">
<code class="descclassname">distributed.</code><code class="descname">get_client</code><span class="sig-paren">(</span><em>address=None</em>, <em>timeout=3</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/worker.html#get_client"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.get_client" title="Permalink to this definition"></a></dt>
<dd><p>Get a client while within a task</p>
<p>This client connects to the same scheduler to which the worker is connected</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.get_worker" title="distributed.get_worker"><code class="xref py py-obj docutils literal"><span class="pre">get_worker</span></code></a>, <a class="reference internal" href="#distributed.worker_client" title="distributed.worker_client"><code class="xref py py-obj docutils literal"><span class="pre">worker_client</span></code></a>, <a class="reference internal" href="#distributed.secede" title="distributed.secede"><code class="xref py py-obj docutils literal"><span class="pre">secede</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">f</span><span class="p">():</span>
<span class="gp">... </span>    <span class="n">client</span> <span class="o">=</span> <span class="n">get_client</span><span class="p">()</span>
<span class="gp">... </span>    <span class="n">futures</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="nb">range</span><span class="p">(</span><span class="mi">10</span><span class="p">))</span>  <span class="c1"># spawn many tasks</span>
<span class="gp">... </span>    <span class="n">results</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">gather</span><span class="p">(</span><span class="n">futures</span><span class="p">)</span>
<span class="gp">... </span>    <span class="k">return</span> <span class="nb">sum</span><span class="p">(</span><span class="n">results</span><span class="p">)</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">future</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">future</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>  
<span class="go">55</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="distributed.secede">
<code class="descclassname">distributed.</code><code class="descname">secede</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/worker.html#secede"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.secede" title="Permalink to this definition"></a></dt>
<dd><p>Have this task secede from the worker’s thread pool</p>
<p>This opens up a new scheduling slot and a new thread for a new task. This
enables the client to schedule tasks on this node, which is
especially useful while waiting for other jobs to finish (e.g., with
<code class="docutils literal"><span class="pre">client.gather</span></code>).</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.get_client" title="distributed.get_client"><code class="xref py py-obj docutils literal"><span class="pre">get_client</span></code></a>, <a class="reference internal" href="#distributed.get_worker" title="distributed.get_worker"><code class="xref py py-obj docutils literal"><span class="pre">get_worker</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">mytask</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
<span class="gp">... </span>    <span class="c1"># do some work</span>
<span class="gp">... </span>    <span class="n">client</span> <span class="o">=</span> <span class="n">get_client</span><span class="p">()</span>
<span class="gp">... </span>    <span class="n">futures</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>  <span class="c1"># do some remote work</span>
<span class="gp">... </span>    <span class="n">secede</span><span class="p">()</span>  <span class="c1"># while that work happens, remove ourself from the pool</span>
<span class="gp">... </span>    <span class="k">return</span> <span class="n">client</span><span class="o">.</span><span class="n">gather</span><span class="p">(</span><span class="n">futures</span><span class="p">)</span>  <span class="c1"># return gathered results</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="distributed.rejoin">
<code class="descclassname">distributed.</code><code class="descname">rejoin</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/threadpoolexecutor.html#rejoin"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.rejoin" title="Permalink to this definition"></a></dt>
<dd><p>Have this thread rejoin the ThreadPoolExecutor</p>
<p>This will block until a new slot opens up in the executor.  The next thread
to finish a task will leave the pool to allow this one to join.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.secede" title="distributed.secede"><code class="xref py py-obj docutils literal"><span class="pre">secede</span></code></a></dt>
<dd>leave the thread pool</dd>
</dl>
</div>
</dd></dl>

<dl class="class">
<dt id="distributed.Queue">
<em class="property">class </em><code class="descclassname">distributed.</code><code class="descname">Queue</code><span class="sig-paren">(</span><em>name=None</em>, <em>client=None</em>, <em>maxsize=0</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/queues.html#Queue"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.Queue" title="Permalink to this definition"></a></dt>
<dd><p>Distributed Queue</p>
<p>This allows multiple clients to share futures or small bits of data between
each other with a multi-producer/multi-consumer queue.  All metadata is
sequentialized through the scheduler.</p>
<p>Elements of the Queue must be either Futures or msgpack-encodable data
(ints, strings, lists, dicts).  All data is sent through the scheduler so
it is wise not to send large objects.  To share large objects scatter the
data and share the future instead.</p>
<div class="admonition warning">
<p class="first admonition-title">Warning</p>
<p class="last">This object is experimental and has known issues in Python 2</p>
</div>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.Variable" title="distributed.Variable"><code class="xref py py-obj docutils literal"><span class="pre">Variable</span></code></a></dt>
<dd>shared variable between clients</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">dask.distributed</span> <span class="k">import</span> <span class="n">Client</span><span class="p">,</span> <span class="n">Queue</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">client</span> <span class="o">=</span> <span class="n">Client</span><span class="p">()</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">queue</span> <span class="o">=</span> <span class="n">Queue</span><span class="p">(</span><span class="s1">&#39;x&#39;</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">future</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">queue</span><span class="o">.</span><span class="n">put</span><span class="p">(</span><span class="n">future</span><span class="p">)</span>  
</pre></div>
</div>
<dl class="method">
<dt id="distributed.Queue.get">
<code class="descname">get</code><span class="sig-paren">(</span><em>timeout=None</em>, <em>batch=False</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/queues.html#Queue.get"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.Queue.get" title="Permalink to this definition"></a></dt>
<dd><p>Get data from the queue</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>timeout: Number (optional)</strong></p>
<blockquote>
<div><p>Time in seconds to wait before timing out</p>
</div></blockquote>
<p><strong>batch: boolean, int (optional)</strong></p>
<blockquote class="last">
<div><p>If True then return all elements currently waiting in the queue.
If an integer than return that many elements from the queue
If False (default) then return one item at a time</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="method">
<dt id="distributed.Queue.put">
<code class="descname">put</code><span class="sig-paren">(</span><em>value</em>, <em>timeout=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/queues.html#Queue.put"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.Queue.put" title="Permalink to this definition"></a></dt>
<dd><p>Put data into the queue</p>
</dd></dl>

<dl class="method">
<dt id="distributed.Queue.qsize">
<code class="descname">qsize</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/queues.html#Queue.qsize"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.Queue.qsize" title="Permalink to this definition"></a></dt>
<dd><p>Current number of elements in the queue</p>
</dd></dl>

</dd></dl>

<dl class="class">
<dt id="distributed.Variable">
<em class="property">class </em><code class="descclassname">distributed.</code><code class="descname">Variable</code><span class="sig-paren">(</span><em>name=None</em>, <em>client=None</em>, <em>maxsize=0</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/variable.html#Variable"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.Variable" title="Permalink to this definition"></a></dt>
<dd><p>Distributed Global Variable</p>
<p>This allows multiple clients to share futures and data between each other
with a single mutable variable.  All metadata is sequentialized through the
scheduler.  Race conditions can occur.</p>
<p>Values must be either Futures or msgpack-encodable data (ints, lists,
strings, etc..)  All data will be kept and sent through the scheduler, so
it is wise not to send too much.  If you want to share a large amount of
data then <code class="docutils literal"><span class="pre">scatter</span></code> it and share the future instead.</p>
<div class="admonition warning">
<p class="first admonition-title">Warning</p>
<p class="last">This object is experimental and has known issues in Python 2</p>
</div>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.Queue" title="distributed.Queue"><code class="xref py py-obj docutils literal"><span class="pre">Queue</span></code></a></dt>
<dd>shared multi-producer/multi-consumer queue between clients</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">dask.distributed</span> <span class="k">import</span> <span class="n">Client</span><span class="p">,</span> <span class="n">Variable</span> 
<span class="gp">&gt;&gt;&gt; </span><span class="n">client</span> <span class="o">=</span> <span class="n">Client</span><span class="p">()</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">Variable</span><span class="p">(</span><span class="s1">&#39;x&#39;</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">set</span><span class="p">(</span><span class="mi">123</span><span class="p">)</span>  <span class="c1"># docttest: +SKIP</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">get</span><span class="p">()</span>  <span class="c1"># docttest: +SKIP</span>
<span class="go">123</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">future</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">set</span><span class="p">(</span><span class="n">future</span><span class="p">)</span>  
</pre></div>
</div>
<dl class="method">
<dt id="distributed.Variable.delete">
<code class="descname">delete</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/variable.html#Variable.delete"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.Variable.delete" title="Permalink to this definition"></a></dt>
<dd><p>Delete this variable</p>
<p>Caution, this affects all clients currently pointing to this variable.</p>
</dd></dl>

<dl class="method">
<dt id="distributed.Variable.get">
<code class="descname">get</code><span class="sig-paren">(</span><em>timeout=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/variable.html#Variable.get"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.Variable.get" title="Permalink to this definition"></a></dt>
<dd><p>Get the value of this variable</p>
</dd></dl>

<dl class="method">
<dt id="distributed.Variable.set">
<code class="descname">set</code><span class="sig-paren">(</span><em>value</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/variable.html#Variable.set"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.Variable.set" title="Permalink to this definition"></a></dt>
<dd><p>Set the value of this variable</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>value: Future or object</strong></p>
<blockquote class="last">
<div><p>Must be either a Future or a msgpack-encodable value</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
</dd></dl>

</dd></dl>

</div>
<div class="section" id="asyncio-client">
<h2>Asyncio Client<a class="headerlink" href="#asyncio-client" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="distributed.asyncio.AioClient">
<em class="property">class </em><code class="descclassname">distributed.asyncio.</code><code class="descname">AioClient</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/asyncio.html#AioClient"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.asyncio.AioClient" title="Permalink to this definition"></a></dt>
<dd><p>Connect to and drive computation on a distributed Dask cluster</p>
<p>This class provides an asyncio compatible async/await interface for
dask.distributed.</p>
<p>The Client connects users to a dask.distributed compute cluster. It
provides an asynchronous user interface around functions and futures.
This class resembles executors in <code class="docutils literal"><span class="pre">concurrent.futures</span></code> but also
allows <code class="docutils literal"><span class="pre">Future</span></code> objects within <code class="docutils literal"><span class="pre">submit/map</span></code> calls.</p>
<p>AioClient is an <strong>experimental</strong> interface for distributed and may
disappear without warning!</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>address: string, or Cluster</strong></p>
<blockquote class="last">
<div><p>This can be the address of a <code class="docutils literal"><span class="pre">Scheduler</span></code> server like a string
<code class="docutils literal"><span class="pre">'127.0.0.1:8786'</span></code> or a cluster object like <code class="docutils literal"><span class="pre">LocalCluster()</span></code></p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="#distributed.client.Client" title="distributed.client.Client"><code class="xref py py-obj docutils literal"><span class="pre">distributed.client.Client</span></code></a></dt>
<dd>Blocking Client</dd>
<dt><a class="reference internal" href="scheduling-state.html#distributed.scheduler.Scheduler" title="distributed.scheduler.Scheduler"><code class="xref py py-obj docutils literal"><span class="pre">distributed.scheduler.Scheduler</span></code></a></dt>
<dd>Internal scheduler</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<p>Provide cluster’s scheduler address on initialization:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">client</span> <span class="o">=</span> <span class="n">AioClient</span><span class="p">(</span><span class="s1">&#39;127.0.0.1:8786&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Start the client:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="k">async</span> <span class="k">def</span> <span class="nf">start_the_client</span><span class="p">():</span>
    <span class="n">client</span> <span class="o">=</span> <span class="k">await</span> <span class="n">AioClient</span><span class="p">()</span>

    <span class="c1"># Use the client....</span>

    <span class="k">await</span> <span class="n">client</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
</pre></div>
</div>
<p>An <code class="docutils literal"><span class="pre">async</span> <span class="pre">with</span></code> statement is a more convenient way to start and shut down
the client:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="k">async</span> <span class="k">def</span> <span class="nf">start_the_client</span><span class="p">():</span>
    <span class="k">async</span> <span class="k">with</span> <span class="n">AioClient</span><span class="p">()</span> <span class="k">as</span> <span class="n">client</span><span class="p">:</span>
        <span class="c1"># Use the client within this block.</span>
        <span class="k">pass</span>
</pre></div>
</div>
<p>Use the <code class="docutils literal"><span class="pre">submit</span></code> method to send individual computations to the cluster,
and await the returned future to retrieve the result:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="k">async</span> <span class="k">def</span> <span class="nf">add_two_numbers</span><span class="p">():</span>
    <span class="k">async</span> <span class="k">with</span> <span class="n">AioClient</span><span class="p">()</span> <span class="k">as</span> <span class="n">client</span><span class="p">:</span>
        <span class="n">a</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
        <span class="n">result</span> <span class="o">=</span> <span class="k">await</span> <span class="n">a</span>
</pre></div>
</div>
<p>Continue using submit or map on results to build up larger computations,
and gather results with the <code class="docutils literal"><span class="pre">gather</span></code> method:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="k">async</span> <span class="k">def</span> <span class="nf">gather_some_results</span><span class="p">():</span>
    <span class="k">async</span> <span class="k">with</span> <span class="n">AioClient</span><span class="p">()</span> <span class="k">as</span> <span class="n">client</span><span class="p">:</span>
        <span class="n">a</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
        <span class="n">b</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">20</span><span class="p">)</span>
        <span class="n">c</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>
        <span class="n">result</span> <span class="o">=</span> <span class="k">await</span> <span class="n">client</span><span class="o">.</span><span class="n">gather</span><span class="p">([</span><span class="n">c</span><span class="p">])</span>
</pre></div>
</div>
<dl class="method">
<dt id="distributed.asyncio.AioClient.close">
<code class="descname">close</code><span class="sig-paren">(</span><em>timeout=10</em><span class="sig-paren">)</span><a class="headerlink" href="#distributed.asyncio.AioClient.close" title="Permalink to this definition"></a></dt>
<dd><p>Close this client</p>
<p>Clients will also close automatically when your Python session ends</p>
<p>If you started a client without arguments like <code class="docutils literal"><span class="pre">Client()</span></code> then this
will also close the local cluster that was started at the same time.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><code class="xref py py-obj docutils literal"><span class="pre">Client.restart</span></code></p>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.asyncio.AioClient.get">
<code class="descname">get</code><span class="sig-paren">(</span><em>dsk</em>, <em>keys</em>, <em>restrictions=None</em>, <em>loose_restrictions=None</em>, <em>resources=None</em>, <em>sync=True</em>, <em>asynchronous=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#distributed.asyncio.AioClient.get" title="Permalink to this definition"></a></dt>
<dd><p>Compute dask graph</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>dsk: dict</strong></p>
<p><strong>keys: object, or nested lists of objects</strong></p>
<p><strong>restrictions: dict (optional)</strong></p>
<blockquote>
<div><p>A mapping of {key: {set of worker hostnames}} that restricts where
jobs can take place</p>
</div></blockquote>
<p><strong>sync: bool (optional)</strong></p>
<blockquote class="last">
<div><p>Returns Futures if False or concrete values if True (default).</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><code class="xref py py-obj docutils literal"><span class="pre">Client.compute</span></code></dt>
<dd>Compute asynchronous collections</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">operator</span> <span class="k">import</span> <span class="n">add</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span> <span class="o">=</span> <span class="n">Client</span><span class="p">(</span><span class="s1">&#39;127.0.0.1:8787&#39;</span><span class="p">)</span>  
<span class="gp">&gt;&gt;&gt; </span><span class="n">c</span><span class="o">.</span><span class="n">get</span><span class="p">({</span><span class="s1">&#39;x&#39;</span><span class="p">:</span> <span class="p">(</span><span class="n">add</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)},</span> <span class="s1">&#39;x&#39;</span><span class="p">)</span>  
<span class="go">3</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="distributed.asyncio.AioClient.shutdown">
<code class="descname">shutdown</code><span class="sig-paren">(</span><em>timeout=10</em><span class="sig-paren">)</span><a class="headerlink" href="#distributed.asyncio.AioClient.shutdown" title="Permalink to this definition"></a></dt>
<dd><p>Close this client</p>
<p>Clients will also close automatically when your Python session ends</p>
<p>If you started a client without arguments like <code class="docutils literal"><span class="pre">Client()</span></code> then this
will also close the local cluster that was started at the same time.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><code class="xref py py-obj docutils literal"><span class="pre">Client.restart</span></code></p>
</div>
</dd></dl>

</dd></dl>

</div>
<div class="section" id="adaptive">
<h2>Adaptive<a class="headerlink" href="#adaptive" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="distributed.deploy.Adaptive">
<em class="property">class </em><code class="descclassname">distributed.deploy.</code><code class="descname">Adaptive</code><span class="sig-paren">(</span><em>scheduler</em>, <em>cluster</em>, <em>interval=1000</em>, <em>startup_cost=1</em>, <em>scale_factor=2</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/deploy/adaptive.html#Adaptive"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.deploy.Adaptive" title="Permalink to this definition"></a></dt>
<dd><p>Adaptively allocate workers based on scheduler load.  A superclass.</p>
<p>Contains logic to dynamically resize a Dask cluster based on current use.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>scheduler: distributed.Scheduler</strong></p>
<p><strong>cluster: object</strong></p>
<blockquote>
<div><p>Must have scale_up and scale_down methods/coroutines</p>
</div></blockquote>
<p><strong>startup_cost</strong> : int, default 1</p>
<blockquote>
<div><p>Factor representing how costly it is to start an additional worker.
Affects quickly to adapt to high tasks per worker loads</p>
</div></blockquote>
<p><strong>scale_factor</strong> : int, default 2</p>
<blockquote class="last">
<div><p>Factor to scale by when it’s determined additional workers are needed</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Notes</p>
<p>Subclasses can override <a class="reference internal" href="#distributed.deploy.Adaptive.should_scale_up" title="distributed.deploy.Adaptive.should_scale_up"><code class="xref py py-meth docutils literal"><span class="pre">Adaptive.should_scale_up()</span></code></a> and
<a class="reference internal" href="#distributed.deploy.Adaptive.should_scale_down" title="distributed.deploy.Adaptive.should_scale_down"><code class="xref py py-meth docutils literal"><span class="pre">Adaptive.should_scale_down()</span></code></a> to control when the cluster should be
resized. The default implementation checks if there are too many tasks
per worker or too little memory available (see <a class="reference internal" href="#distributed.deploy.Adaptive.needs_cpu" title="distributed.deploy.Adaptive.needs_cpu"><code class="xref py py-meth docutils literal"><span class="pre">Adaptive.needs_cpu()</span></code></a>
and <a class="reference internal" href="#distributed.deploy.Adaptive.needs_memory" title="distributed.deploy.Adaptive.needs_memory"><code class="xref py py-meth docutils literal"><span class="pre">Adaptive.needs_memory()</span></code></a>).</p>
<p><a class="reference internal" href="#distributed.deploy.Adaptive.get_scale_up_kwargs" title="distributed.deploy.Adaptive.get_scale_up_kwargs"><code class="xref py py-meth docutils literal"><span class="pre">Adaptive.get_scale_up_kwargs()</span></code></a> method controls the arguments passed to
the cluster’s <code class="docutils literal"><span class="pre">scale_up</span></code> method.</p>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">class</span> <span class="nc">MyCluster</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="gp">... </span>    <span class="k">def</span> <span class="nf">scale_up</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span>
<span class="gp">... </span>        <span class="sd">&quot;&quot;&quot; Bring worker count up to n &quot;&quot;&quot;</span>
<span class="gp">... </span>    <span class="k">def</span> <span class="nf">scale_down</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">workers</span><span class="p">):</span>
<span class="gp">... </span>       <span class="sd">&quot;&quot;&quot; Remove worker addresses from cluster &quot;&quot;&quot;</span>
</pre></div>
</div>
<dl class="method">
<dt id="distributed.deploy.Adaptive.get_scale_up_kwargs">
<code class="descname">get_scale_up_kwargs</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/deploy/adaptive.html#Adaptive.get_scale_up_kwargs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.deploy.Adaptive.get_scale_up_kwargs" title="Permalink to this definition"></a></dt>
<dd><p>Get the arguments to be passed to <code class="docutils literal"><span class="pre">self.cluster.scale_up</span></code>.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><code class="xref py py-obj docutils literal"><span class="pre">LocalCluster.scale_up</span></code></p>
</div>
<p class="rubric">Notes</p>
<p>By default the desired number of total workers is returned (<code class="docutils literal"><span class="pre">n</span></code>).
Subclasses should ensure that the return dictionary includes a key-
value pair for <code class="docutils literal"><span class="pre">n</span></code>, either by implementing it or by calling the
parent’s <code class="docutils literal"><span class="pre">get_scale_up_kwargs</span></code>.</p>
</dd></dl>

<dl class="method">
<dt id="distributed.deploy.Adaptive.needs_cpu">
<code class="descname">needs_cpu</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/deploy/adaptive.html#Adaptive.needs_cpu"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.deploy.Adaptive.needs_cpu" title="Permalink to this definition"></a></dt>
<dd><p>Check if the cluster is CPU constrained (too many tasks per core)</p>
<p class="rubric">Notes</p>
<p>Returns <code class="docutils literal"><span class="pre">True</span></code> if the occupancy per core is some factor larger
than <code class="docutils literal"><span class="pre">startup_cost</span></code>.</p>
</dd></dl>

<dl class="method">
<dt id="distributed.deploy.Adaptive.needs_memory">
<code class="descname">needs_memory</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/deploy/adaptive.html#Adaptive.needs_memory"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.deploy.Adaptive.needs_memory" title="Permalink to this definition"></a></dt>
<dd><p>Check if the cluster is RAM constrained</p>
<p class="rubric">Notes</p>
<p>Returns <code class="docutils literal"><span class="pre">True</span></code> if  the required bytes in distributed memory is some
factor larger than the actual distributed memory available.</p>
</dd></dl>

<dl class="method">
<dt id="distributed.deploy.Adaptive.should_scale_down">
<code class="descname">should_scale_down</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/deploy/adaptive.html#Adaptive.should_scale_down"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.deploy.Adaptive.should_scale_down" title="Permalink to this definition"></a></dt>
<dd><p>Determine whether any workers should potentially be removed from
the cluster.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>scale_down</strong> : bool</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><code class="xref py py-obj docutils literal"><span class="pre">Scheduler.workers_to_close</span></code></p>
</div>
<p class="rubric">Notes</p>
<p><code class="docutils literal"><span class="pre">Adaptive.should_scale_down</span></code> always returns True, so we will always
attempt to remove workers as determined by
<code class="docutils literal"><span class="pre">Scheduler.workers_to_close</span></code>.</p>
</dd></dl>

<dl class="method">
<dt id="distributed.deploy.Adaptive.should_scale_up">
<code class="descname">should_scale_up</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/distributed/deploy/adaptive.html#Adaptive.should_scale_up"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#distributed.deploy.Adaptive.should_scale_up" title="Permalink to this definition"></a></dt>
<dd><p>Determine whether additional workers should be added to the cluster</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>scale_up</strong> : bool</p>
<p>Notes</p>
<p>Additional workers are added whenever</p>
<ol class="last arabic simple">
<li>There are unrunnable tasks and no workers</li>
<li>The cluster is CPU constrained</li>
<li>The cluster is RAM constrained</li>
</ol>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#distributed.deploy.Adaptive.needs_cpu" title="distributed.deploy.Adaptive.needs_cpu"><code class="xref py py-obj docutils literal"><span class="pre">needs_cpu</span></code></a>, <a class="reference internal" href="#distributed.deploy.Adaptive.needs_memory" title="distributed.deploy.Adaptive.needs_memory"><code class="xref py py-obj docutils literal"><span class="pre">needs_memory</span></code></a></p>
</div>
</dd></dl>

</dd></dl>

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