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        <p class="developmentversion">
        This document is for Celery's development version, which can be
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    <div class="section" id="canvas-building-workflows">
<span id="guide-canvas"></span><h1>Canvas: Building Workflows<a class="headerlink" href="#canvas-building-workflows" title="Permalink to this headline">¶</a></h1>
<div class="contents local topic" id="contents">
<ul class="simple">
<li><a class="reference internal" href="#subtasks" id="id2">Subtasks</a><ul>
<li><a class="reference internal" href="#callbacks" id="id3">Callbacks</a></li>
</ul>
</li>
<li><a class="reference internal" href="#groups" id="id4">Groups</a><ul>
<li><a class="reference internal" href="#group-results" id="id5">Group Results</a></li>
</ul>
</li>
<li><a class="reference internal" href="#chords" id="id6">Chords</a><ul>
<li><a class="reference internal" href="#important-notes" id="id7">Important Notes</a></li>
</ul>
</li>
</ul>
</div>
<div class="section" id="subtasks">
<span id="canvas-subtasks"></span><h2><a class="toc-backref" href="#id2">Subtasks</a><a class="headerlink" href="#subtasks" title="Permalink to this headline">¶</a></h2>
<p class="versionadded">
<span class="versionmodified">New in version 2.0.</span></p>
<p>The <a class="reference internal" href="../reference/celery.html#celery.subtask" title="celery.subtask"><tt class="xref py py-class docutils literal"><span class="pre">subtask</span></tt></a> type is used to wrap the arguments and
execution options for a single task invocation:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="kn">from</span> <span class="nn">celery</span> <span class="kn">import</span> <span class="n">subtask</span>

<span class="n">subtask</span><span class="p">(</span><span class="n">task_name_or_cls</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">,</span> <span class="n">options</span><span class="p">)</span>
</pre></div>
</div>
<p>For convenience every task also has a shortcut to create subtasks:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">task</span><span class="o">.</span><span class="n">subtask</span><span class="p">(</span><span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">,</span> <span class="n">options</span><span class="p">)</span>
</pre></div>
</div>
<p><a class="reference internal" href="../reference/celery.html#celery.subtask" title="celery.subtask"><tt class="xref py py-class docutils literal"><span class="pre">subtask</span></tt></a> is actually a <a class="reference external" href="http://docs.python.org/dev/library/stdtypes.html#dict" title="(in Python v3.3)"><tt class="xref py py-class docutils literal"><span class="pre">dict</span></tt></a> subclass,
which means it can be serialized with JSON or other encodings that doesn&#8217;t
support complex Python objects.</p>
<p>Also it can be regarded as a type, as the following usage works:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="n">s</span> <span class="o">=</span> <span class="n">subtask</span><span class="p">(</span><span class="s">&quot;tasks.add&quot;</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="n">kwargs</span><span class="o">=</span><span class="p">{})</span>

<span class="gp">&gt;&gt;&gt; </span><span class="n">subtask</span><span class="p">(</span><span class="nb">dict</span><span class="p">(</span><span class="n">s</span><span class="p">))</span>  <span class="c"># coerce dict into subtask</span>
</pre></div>
</div>
<p>This makes it excellent as a means to pass callbacks around to tasks.</p>
<div class="section" id="callbacks">
<span id="canvas-callbacks"></span><h3><a class="toc-backref" href="#id3">Callbacks</a><a class="headerlink" href="#callbacks" title="Permalink to this headline">¶</a></h3>
<p>Callbacks can be added to any task using the <tt class="docutils literal"><span class="pre">link</span></tt> argument
to <tt class="docutils literal"><span class="pre">apply_async</span></tt>:</p>
<blockquote>
<div>add.apply_async((2, 2), link=other_task.subtask())</div></blockquote>
<p>The callback will only be applied if the task exited successfully,
and it will be applied with the return value of the parent task as argument.</p>
<p>The best thing is that any arguments you add to <cite>subtask</cite>,
will be prepended to the arguments specified by the subtask itself!</p>
<p>If you have the subtask:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">(</span><span class="n">args</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="p">))</span>
</pre></div>
</div>
<p><cite>subtask.delay(result)</cite> becomes:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="n">add</span><span class="o">.</span><span class="n">apply_async</span><span class="p">(</span><span class="n">args</span><span class="o">=</span><span class="p">(</span><span class="n">result</span><span class="p">,</span> <span class="mi">10</span><span class="p">))</span>
</pre></div>
</div>
<p>...</p>
<p>Now let&#8217;s call our <tt class="docutils literal"><span class="pre">add</span></tt> task with a callback using partial
arguments:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="n">add</span><span class="o">.</span><span class="n">apply_async</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="n">link</span><span class="o">=</span><span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">((</span><span class="mi">8</span><span class="p">,</span> <span class="p">)))</span>
</pre></div>
</div>
<p>As expected this will first launch one task calculating <img class="math" src="../_images/math/2da3a5ecd44fdb54a9a30c87a48a5b1638c139b0.png" alt="2 + 2"/>, then
another task calculating <img class="math" src="../_images/math/c67562ae31bb2d1017a9b0240c012edc474851c3.png" alt="4 + 8"/>.</p>
</div>
</div>
<div class="section" id="groups">
<span id="canvas-group"></span><h2><a class="toc-backref" href="#id4">Groups</a><a class="headerlink" href="#groups" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="../reference/celery.html#celery.group" title="celery.group"><tt class="xref py py-class docutils literal"><span class="pre">group</span></tt></a> enables easy invocation of several
tasks at once, and is then able to join the results in the same order as the
tasks were invoked.</p>
<p><tt class="docutils literal"><span class="pre">group</span></tt> takes a list of <a class="reference internal" href="../reference/celery.html#celery.subtask" title="celery.subtask"><tt class="xref py py-class docutils literal"><span class="pre">subtask</span></tt></a>&#8216;s:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">celery</span> <span class="kn">import</span> <span class="n">group</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">tasks</span> <span class="kn">import</span> <span class="n">add</span>

<span class="gp">&gt;&gt;&gt; </span><span class="n">job</span> <span class="o">=</span> <span class="n">group</span><span class="p">([</span>
<span class="gp">... </span>            <span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)),</span>
<span class="gp">... </span>            <span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">((</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)),</span>
<span class="gp">... </span>            <span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">((</span><span class="mi">8</span><span class="p">,</span> <span class="mi">8</span><span class="p">)),</span>
<span class="gp">... </span>            <span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">((</span><span class="mi">16</span><span class="p">,</span> <span class="mi">16</span><span class="p">)),</span>
<span class="gp">... </span>            <span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">((</span><span class="mi">32</span><span class="p">,</span> <span class="mi">32</span><span class="p">)),</span>
<span class="gp">... </span><span class="p">])</span>

<span class="gp">&gt;&gt;&gt; </span><span class="n">result</span> <span class="o">=</span> <span class="n">job</span><span class="o">.</span><span class="n">apply_async</span><span class="p">()</span>

<span class="gp">&gt;&gt;&gt; </span><span class="n">result</span><span class="o">.</span><span class="n">ready</span><span class="p">()</span>  <span class="c"># have all subtasks completed?</span>
<span class="go">True</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">result</span><span class="o">.</span><span class="n">successful</span><span class="p">()</span> <span class="c"># were all subtasks successful?</span>
<span class="go">True</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">result</span><span class="o">.</span><span class="n">join</span><span class="p">()</span>
<span class="go">[4, 8, 16, 32, 64]</span>
</pre></div>
</div>
<p>The first argument can alternatively be an iterator, like:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="n">group</span><span class="p">(</span><span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">((</span><span class="n">i</span><span class="p">,</span> <span class="n">i</span><span class="p">))</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">))</span>
</pre></div>
</div>
<div class="section" id="group-results">
<span id="canvas-group-results"></span><h3><a class="toc-backref" href="#id5">Group Results</a><a class="headerlink" href="#group-results" title="Permalink to this headline">¶</a></h3>
<p>When a  <a class="reference internal" href="../reference/celery.html#celery.group" title="celery.group"><tt class="xref py py-class docutils literal"><span class="pre">group</span></tt></a> is applied it returns a
<a class="reference internal" href="../reference/celery.result.html#celery.result.GroupResult" title="celery.result.GroupResult"><tt class="xref py py-class docutils literal"><span class="pre">GroupResult</span></tt></a> object.</p>
<p><a class="reference internal" href="../reference/celery.result.html#celery.result.GroupResult" title="celery.result.GroupResult"><tt class="xref py py-class docutils literal"><span class="pre">GroupResult</span></tt></a> takes a list of
<a class="reference internal" href="../reference/celery.result.html#celery.result.AsyncResult" title="celery.result.AsyncResult"><tt class="xref py py-class docutils literal"><span class="pre">AsyncResult</span></tt></a> instances and operates on them as if it was a
single task.</p>
<p>It supports the following operations:</p>
<ul>
<li><p class="first"><tt class="xref py py-meth docutils literal"><span class="pre">successful()</span></tt></p>
<blockquote>
<div><p>Returns <tt class="xref py py-const docutils literal"><span class="pre">True</span></tt> if all of the subtasks finished
successfully (e.g. did not raise an exception).</p>
</div></blockquote>
</li>
<li><p class="first"><tt class="xref py py-meth docutils literal"><span class="pre">failed()</span></tt></p>
<blockquote>
<div><p>Returns <tt class="xref py py-const docutils literal"><span class="pre">True</span></tt> if any of the subtasks failed.</p>
</div></blockquote>
</li>
<li><p class="first"><tt class="xref py py-meth docutils literal"><span class="pre">waiting()</span></tt></p>
<blockquote>
<div><p>Returns <tt class="xref py py-const docutils literal"><span class="pre">True</span></tt> if any of the subtasks
is not ready yet.</p>
</div></blockquote>
</li>
<li><p class="first"><tt class="xref py py-meth docutils literal"><span class="pre">ready()</span></tt></p>
<blockquote>
<div><p>Return <tt class="xref py py-const docutils literal"><span class="pre">True</span></tt> if all of the subtasks
are ready.</p>
</div></blockquote>
</li>
<li><p class="first"><tt class="xref py py-meth docutils literal"><span class="pre">completed_count()</span></tt></p>
<blockquote>
<div><p>Returns the number of completed subtasks.</p>
</div></blockquote>
</li>
<li><p class="first"><tt class="xref py py-meth docutils literal"><span class="pre">revoke()</span></tt></p>
<blockquote>
<div><p>Revokes all of the subtasks.</p>
</div></blockquote>
</li>
<li><p class="first"><tt class="xref py py-meth docutils literal"><span class="pre">iterate()</span></tt></p>
<blockquote>
<div><p>Iterates over the return values of the subtasks
as they finish, one by one.</p>
</div></blockquote>
</li>
<li><p class="first"><tt class="xref py py-meth docutils literal"><span class="pre">join()</span></tt></p>
<blockquote>
<div><p>Gather the results for all of the subtasks
and return a list with them ordered by the order of which they
were called.</p>
</div></blockquote>
</li>
</ul>
</div>
</div>
<div class="section" id="chords">
<span id="id1"></span><h2><a class="toc-backref" href="#id6">Chords</a><a class="headerlink" href="#chords" title="Permalink to this headline">¶</a></h2>
<p class="versionadded">
<span class="versionmodified">New in version 2.3.</span></p>
<p>A chord is a task that only executes after all of the tasks in a taskset has
finished executing.</p>
<p>Let&#8217;s calculate the sum of the expression
<img class="math" src="../_images/math/c9bf2df3c397d6399241c37fc9887ca50bc8fa09.png" alt="1 + 1 + 2 + 2 + 3 + 3 ... n + n"/> up to a hundred digits.</p>
<p>First we need two tasks, <tt class="xref py py-func docutils literal"><span class="pre">add()</span></tt> and <tt class="xref py py-func docutils literal"><span class="pre">tsum()</span></tt> (<a class="reference external" href="http://docs.python.org/dev/library/functions.html#sum" title="(in Python v3.3)"><tt class="xref py py-func docutils literal"><span class="pre">sum()</span></tt></a> is
already a standard function):</p>
<div class="highlight-python"><div class="highlight"><pre><span class="nd">@celery.task</span><span class="p">()</span>
<span class="k">def</span> <span class="nf">add</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="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="n">y</span>

<span class="nd">@celery.task</span><span class="p">()</span>
<span class="k">def</span> <span class="nf">tsum</span><span class="p">(</span><span class="n">numbers</span><span class="p">):</span>
    <span class="k">return</span> <span class="nb">sum</span><span class="p">(</span><span class="n">numbers</span><span class="p">)</span>
</pre></div>
</div>
<p>Now we can use a chord to calculate each addition step in parallel, and then
get the sum of the resulting numbers:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">celery</span> <span class="kn">import</span> <span class="n">chord</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">tasks</span> <span class="kn">import</span> <span class="n">add</span><span class="p">,</span> <span class="n">tsum</span>

<span class="gp">&gt;&gt;&gt; </span><span class="n">chord</span><span class="p">(</span><span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">((</span><span class="n">i</span><span class="p">,</span> <span class="n">i</span><span class="p">))</span>
<span class="gp">... </span>    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">xrange</span><span class="p">(</span><span class="mi">100</span><span class="p">))(</span><span class="n">tsum</span><span class="o">.</span><span class="n">subtask</span><span class="p">())</span><span class="o">.</span><span class="n">get</span><span class="p">()</span>
<span class="go">9900</span>
</pre></div>
</div>
<p>This is obviously a very contrived example, the overhead of messaging and
synchronization makes this a lot slower than its Python counterpart:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="nb">sum</span><span class="p">(</span><span class="n">i</span> <span class="o">+</span> <span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">xrange</span><span class="p">(</span><span class="mi">100</span><span class="p">))</span>
</pre></div>
</div>
<p>The synchronization step is costly, so you should avoid using chords as much
as possible. Still, the chord is a powerful primitive to have in your toolbox
as synchronization is a required step for many parallel algorithms.</p>
<p>Let&#8217;s break the chord expression down:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="n">callback</span> <span class="o">=</span> <span class="n">tsum</span><span class="o">.</span><span class="n">subtask</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">header</span> <span class="o">=</span> <span class="p">[</span><span class="n">add</span><span class="o">.</span><span class="n">subtask</span><span class="p">((</span><span class="n">i</span><span class="p">,</span> <span class="n">i</span><span class="p">))</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">xrange</span><span class="p">(</span><span class="mi">100</span><span class="p">)]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">result</span> <span class="o">=</span> <span class="n">chord</span><span class="p">(</span><span class="n">header</span><span class="p">)(</span><span class="n">callback</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">result</span><span class="o">.</span><span class="n">get</span><span class="p">()</span>
<span class="go">9900</span>
</pre></div>
</div>
<p>Remember, the callback can only be executed after all of the tasks in the
header has returned.  Each step in the header is executed as a task, in
parallel, possibly on different nodes.  The callback is then applied with
the return value of each task in the header.  The task id returned by
<tt class="xref py py-meth docutils literal"><span class="pre">chord()</span></tt> is the id of the callback, so you can wait for it to complete
and get the final return value (but remember to <a class="reference internal" href="tasks.html#task-synchronous-subtasks"><em>never have a task wait
for other tasks</em></a>)</p>
<div class="section" id="important-notes">
<span id="chord-important-notes"></span><h3><a class="toc-backref" href="#id7">Important Notes</a><a class="headerlink" href="#important-notes" title="Permalink to this headline">¶</a></h3>
<p>By default the synchronization step is implemented by having a recurring task
poll the completion of the taskset every second, applying the subtask when
ready.</p>
<p>Example implementation:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="k">def</span> <span class="nf">unlock_chord</span><span class="p">(</span><span class="n">taskset</span><span class="p">,</span> <span class="n">callback</span><span class="p">,</span> <span class="n">interval</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">max_retries</span><span class="o">=</span><span class="bp">None</span><span class="p">):</span>
    <span class="k">if</span> <span class="n">taskset</span><span class="o">.</span><span class="n">ready</span><span class="p">():</span>
        <span class="k">return</span> <span class="n">subtask</span><span class="p">(</span><span class="n">callback</span><span class="p">)</span><span class="o">.</span><span class="n">delay</span><span class="p">(</span><span class="n">taskset</span><span class="o">.</span><span class="n">join</span><span class="p">())</span>
    <span class="k">raise</span> <span class="n">unlock_chord</span><span class="o">.</span><span class="n">retry</span><span class="p">(</span><span class="n">countdown</span><span class="o">=</span><span class="n">interval</span><span class="p">,</span> <span class="n">max_retries</span><span class="o">=</span><span class="n">max_retries</span><span class="p">)</span>
</pre></div>
</div>
<p>This is used by all result backends except Redis and Memcached, which increment a
counter after each task in the header, then applying the callback when the
counter exceeds the number of tasks in the set. <em>Note:</em> chords do not properly
work with Redis before version 2.2; you will need to upgrade to at least 2.2 to
use them.</p>
<p>The Redis and Memcached approach is a much better solution, but not easily
implemented in other backends (suggestions welcome!).</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p>If you are using chords with the Redis result backend and also overriding
the <tt class="xref py py-meth docutils literal"><span class="pre">Task.after_return()</span></tt> method, you need to make sure to call the
super method or else the chord callback will not be applied.</p>
<div class="last highlight-python"><div class="highlight"><pre><span class="k">def</span> <span class="nf">after_return</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
    <span class="n">do_something</span><span class="p">()</span>
    <span class="nb">super</span><span class="p">(</span><span class="n">MyTask</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">after_return</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</pre></div>
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