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<div class="section" id="module-apache_beam.runners.interactive.interactive_beam">
<span id="apache-beam-runners-interactive-interactive-beam-module"></span><h1>apache_beam.runners.interactive.interactive_beam module<a class="headerlink" href="#module-apache_beam.runners.interactive.interactive_beam" title="Permalink to this headline"></a></h1>
<p>Module of Interactive Beam features that can be used in notebook.</p>
<p>The purpose of the module is to reduce the learning curve of Interactive Beam
users, provide a single place for importing and add sugar syntax for all
Interactive Beam components. It gives users capability to interact with existing
environment/session/context for Interactive Beam and visualize PCollections as
bounded dataset. In the meantime, it hides the interactivity implementation
from users so that users can focus on developing Beam pipeline without worrying
about how hidden states in the interactive session are managed.</p>
<p>Note: If you want backward-compatibility, only invoke interfaces provided by
this module in your notebook or application code.</p>
<dl class="class">
<dt id="apache_beam.runners.interactive.interactive_beam.Options">
<em class="property">class </em><code class="descclassname">apache_beam.runners.interactive.interactive_beam.</code><code class="descname">Options</code><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#Options"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Options" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="apache_beam.runners.interactive.options.interactive_options.html#apache_beam.runners.interactive.options.interactive_options.InteractiveOptions" title="apache_beam.runners.interactive.options.interactive_options.InteractiveOptions"><code class="xref py py-class docutils literal notranslate"><span class="pre">apache_beam.runners.interactive.options.interactive_options.InteractiveOptions</span></code></a></p>
<p>Options that guide how Interactive Beam works.</p>
<dl class="attribute">
<dt id="apache_beam.runners.interactive.interactive_beam.Options.enable_recording_replay">
<code class="descname">enable_recording_replay</code><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Options.enable_recording_replay" title="Permalink to this definition"></a></dt>
<dd><p>Whether replayable source data recorded should be replayed for multiple
PCollection evaluations and pipeline runs as long as the data recorded is
still valid.</p>
</dd></dl>
<dl class="attribute">
<dt id="apache_beam.runners.interactive.interactive_beam.Options.recordable_sources">
<code class="descname">recordable_sources</code><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Options.recordable_sources" title="Permalink to this definition"></a></dt>
<dd><p>Interactive Beam automatically records data from sources in this set.</p>
</dd></dl>
<dl class="attribute">
<dt id="apache_beam.runners.interactive.interactive_beam.Options.recording_duration">
<code class="descname">recording_duration</code><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Options.recording_duration" title="Permalink to this definition"></a></dt>
<dd><p>The data recording of sources ends as soon as the background source
recording job has run for this long.</p>
</dd></dl>
<dl class="attribute">
<dt id="apache_beam.runners.interactive.interactive_beam.Options.recording_size_limit">
<code class="descname">recording_size_limit</code><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Options.recording_size_limit" title="Permalink to this definition"></a></dt>
<dd><p>The data recording of sources ends as soon as the size (in bytes) of data
recorded from recordable sources reaches the limit.</p>
</dd></dl>
<dl class="attribute">
<dt id="apache_beam.runners.interactive.interactive_beam.Options.display_timestamp_format">
<code class="descname">display_timestamp_format</code><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Options.display_timestamp_format" title="Permalink to this definition"></a></dt>
<dd><p>The format in which timestamps are displayed.</p>
<p>Default is ‘%Y-%m-%d %H:%M:%S.%f%z’, e.g. 2020-02-01 15:05:06.000015-08:00.</p>
</dd></dl>
<dl class="attribute">
<dt id="apache_beam.runners.interactive.interactive_beam.Options.display_timezone">
<code class="descname">display_timezone</code><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Options.display_timezone" title="Permalink to this definition"></a></dt>
<dd><p>The timezone in which timestamps are displayed.</p>
<p>Defaults to local timezone.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="apache_beam.runners.interactive.interactive_beam.Recordings">
<em class="property">class </em><code class="descclassname">apache_beam.runners.interactive.interactive_beam.</code><code class="descname">Recordings</code><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#Recordings"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Recordings" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.9)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
<p>An introspection interface for recordings for pipelines.</p>
<p>When a user materializes a PCollection onto disk (eg. ib.show) for a streaming
pipeline, a background source recording job is started. This job pulls data
from all defined unbounded sources for that PCollection’s pipeline. The
following methods allow for introspection into that background recording job.</p>
<dl class="method">
<dt id="apache_beam.runners.interactive.interactive_beam.Recordings.describe">
<code class="descname">describe</code><span class="sig-paren">(</span><em>pipeline=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#Recordings.describe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Recordings.describe" title="Permalink to this definition"></a></dt>
<dd><p>Returns a description of all the recordings for the given pipeline.</p>
<p>If no pipeline is given then this returns a dictionary of descriptions for
all pipelines.</p>
</dd></dl>
<dl class="method">
<dt id="apache_beam.runners.interactive.interactive_beam.Recordings.clear">
<code class="descname">clear</code><span class="sig-paren">(</span><em>pipeline</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#Recordings.clear"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Recordings.clear" title="Permalink to this definition"></a></dt>
<dd><p>Clears all recordings of the given pipeline. Returns True if cleared.</p>
</dd></dl>
<dl class="method">
<dt id="apache_beam.runners.interactive.interactive_beam.Recordings.stop">
<code class="descname">stop</code><span class="sig-paren">(</span><em>pipeline</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#Recordings.stop"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Recordings.stop" title="Permalink to this definition"></a></dt>
<dd><p>Stops the background source recording of the given pipeline.</p>
</dd></dl>
<dl class="method">
<dt id="apache_beam.runners.interactive.interactive_beam.Recordings.record">
<code class="descname">record</code><span class="sig-paren">(</span><em>pipeline</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#Recordings.record"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.Recordings.record" title="Permalink to this definition"></a></dt>
<dd><p>Starts a background source recording job for the given pipeline. Returns
True if the recording job was started.</p>
</dd></dl>
</dd></dl>
<dl class="function">
<dt id="apache_beam.runners.interactive.interactive_beam.watch">
<code class="descclassname">apache_beam.runners.interactive.interactive_beam.</code><code class="descname">watch</code><span class="sig-paren">(</span><em>watchable</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#watch"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.watch" title="Permalink to this definition"></a></dt>
<dd><p>Monitors a watchable.</p>
<p>This allows Interactive Beam to implicitly pass on the information about the
location of your pipeline definition.</p>
<p>Current implementation mainly watches for PCollection variables defined in
user code. A watchable can be a dictionary of variable metadata such as
locals(), a str name of a module, a module object or an instance of a class.
The variable can come from any scope even local variables in a method of a
class defined in a module.</p>
<blockquote>
<div><p>Below are all valid:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">watch</span><span class="p">(</span><span class="n">__main__</span><span class="p">)</span> <span class="c1"># if import __main__ is already invoked</span>
<span class="n">watch</span><span class="p">(</span><span class="s1">&#39;__main__&#39;</span><span class="p">)</span> <span class="c1"># does not require invoking import __main__ beforehand</span>
<span class="n">watch</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="c1"># inside a class</span>
<span class="n">watch</span><span class="p">(</span><span class="n">SomeInstance</span><span class="p">())</span> <span class="c1"># an instance of a class</span>
<span class="n">watch</span><span class="p">(</span><span class="nb">locals</span><span class="p">())</span> <span class="c1"># inside a function, watching local variables within</span>
</pre></div>
</div>
</div></blockquote>
<p>If you write a Beam pipeline in the __main__ module directly, since the
__main__ module is always watched, you don’t have to instruct Interactive
Beam. If your Beam pipeline is defined in some module other than __main__,
such as inside a class function or a unit test, you can watch() the scope.</p>
<blockquote>
<div><p>For example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">Foo</span><span class="p">(</span><span class="nb">object</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">run_pipeline</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">with</span> <span class="n">beam</span><span class="o">.</span><span class="n">Pipeline</span><span class="p">()</span> <span class="k">as</span> <span class="n">p</span><span class="p">:</span>
<span class="n">init_pcoll</span> <span class="o">=</span> <span class="n">p</span> <span class="o">|</span> <span class="s1">&#39;Init Create&#39;</span> <span class="o">&gt;&gt;</span> <span class="n">beam</span><span class="o">.</span><span class="n">Create</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="n">watch</span><span class="p">(</span><span class="nb">locals</span><span class="p">())</span>
<span class="k">return</span> <span class="n">init_pcoll</span>
<span class="n">init_pcoll</span> <span class="o">=</span> <span class="n">Foo</span><span class="p">()</span><span class="o">.</span><span class="n">run_pipeline</span><span class="p">()</span>
</pre></div>
</div>
<p>Interactive Beam caches init_pcoll for the first run.</p>
<p>Then you can use:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">show</span><span class="p">(</span><span class="n">init_pcoll</span><span class="p">)</span>
</pre></div>
</div>
<p>To visualize data from init_pcoll once the pipeline is executed.</p>
</div></blockquote>
</dd></dl>
<dl class="function">
<dt id="apache_beam.runners.interactive.interactive_beam.show">
<code class="descclassname">apache_beam.runners.interactive.interactive_beam.</code><code class="descname">show</code><span class="sig-paren">(</span><em>*pcolls</em>, <em>include_window_info=False</em>, <em>visualize_data=False</em>, <em>n='inf'</em>, <em>duration='inf'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#show"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.show" title="Permalink to this definition"></a></dt>
<dd><p>Shows given PCollections in an interactive exploratory way if used within
a notebook, or prints a heading sampled data if used within an ipython shell.
Noop if used in a non-interactive environment.</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"><ul class="first last simple">
<li><strong>include_window_info</strong> – (optional) if True, windowing information of the
data will be visualized too. Default is false.</li>
<li><strong>visualize_data</strong> – (optional) by default, the visualization contains data
tables rendering data from given pcolls separately as if they are
converted into dataframes. If visualize_data is True, there will be a
more dive-in widget and statistically overview widget of the data.
Otherwise, those 2 data visualization widgets will not be displayed.</li>
<li><strong>n</strong> – (optional) max number of elements to visualize. Default ‘inf’.</li>
<li><strong>duration</strong> – (optional) max duration of elements to read in integer seconds or
a string duration. Default ‘inf’.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p>The given pcolls can be dictionary of PCollections (as values), or iterable
of PCollections or plain PCollection values.</p>
<p>The user can specify either the max number of elements with <cite>n</cite> to read
or the maximum duration of elements to read with <cite>duration</cite>. When a limiter is
not supplied, it is assumed to be infinite.</p>
<p>By default, the visualization contains data tables rendering data from given
pcolls separately as if they are converted into dataframes. If visualize_data
is True, there will be a more dive-in widget and statistically overview widget
of the data. Otherwise, those 2 data visualization widgets will not be
displayed.</p>
<p>Ad hoc builds a pipeline fragment including only transforms that are
necessary to produce data for given PCollections pcolls, runs the pipeline
fragment to compute data for those pcolls and then visualizes the data.</p>
<p>The function is always blocking. If used within a notebook, the data
visualized might be dynamically updated before the function returns as more
and more data could getting processed and emitted when the pipeline fragment
is being executed. If used within an ipython shell, there will be no dynamic
plotting but a static plotting in the end of pipeline fragment execution.</p>
<p>The PCollections given must belong to the same pipeline.</p>
<blockquote>
<div><p>For example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">p</span> <span class="o">=</span> <span class="n">beam</span><span class="o">.</span><span class="n">Pipeline</span><span class="p">(</span><span class="n">InteractiveRunner</span><span class="p">())</span>
<span class="n">init</span> <span class="o">=</span> <span class="n">p</span> <span class="o">|</span> <span class="s1">&#39;Init&#39;</span> <span class="o">&gt;&gt;</span> <span class="n">beam</span><span class="o">.</span><span class="n">Create</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1000</span><span class="p">))</span>
<span class="n">square</span> <span class="o">=</span> <span class="n">init</span> <span class="o">|</span> <span class="s1">&#39;Square&#39;</span> <span class="o">&gt;&gt;</span> <span class="n">beam</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="n">x</span><span class="p">)</span>
<span class="n">cube</span> <span class="o">=</span> <span class="n">init</span> <span class="o">|</span> <span class="s1">&#39;Cube&#39;</span> <span class="o">&gt;&gt;</span> <span class="n">beam</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">3</span><span class="p">)</span>
<span class="c1"># Below builds a pipeline fragment from the defined pipeline `p` that</span>
<span class="c1"># contains only applied transforms of `Init` and `Square`. Then the</span>
<span class="c1"># interactive runner runs the pipeline fragment implicitly to compute data</span>
<span class="c1"># represented by PCollection `square` and visualizes it.</span>
<span class="n">show</span><span class="p">(</span><span class="n">square</span><span class="p">)</span>
<span class="c1"># This is equivalent to `show(square)` because `square` depends on `init`</span>
<span class="c1"># and `init` is included in the pipeline fragment and computed anyway.</span>
<span class="n">show</span><span class="p">(</span><span class="n">init</span><span class="p">,</span> <span class="n">square</span><span class="p">)</span>
<span class="c1"># Below is similar to running `p.run()`. It computes data for both</span>
<span class="c1"># PCollection `square` and PCollection `cube`, then visualizes them.</span>
<span class="n">show</span><span class="p">(</span><span class="n">square</span><span class="p">,</span> <span class="n">cube</span><span class="p">)</span>
</pre></div>
</div>
</div></blockquote>
</dd></dl>
<dl class="function">
<dt id="apache_beam.runners.interactive.interactive_beam.collect">
<code class="descclassname">apache_beam.runners.interactive.interactive_beam.</code><code class="descname">collect</code><span class="sig-paren">(</span><em>pcoll</em>, <em>n='inf'</em>, <em>duration='inf'</em>, <em>include_window_info=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#collect"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.collect" title="Permalink to this definition"></a></dt>
<dd><p>Materializes the elements from a PCollection into a Dataframe.</p>
<p>This reads each element from file and reads only the amount that it needs
into memory. The user can specify either the max number of elements to read
or the maximum duration of elements to read. When a limiter is not supplied,
it is assumed to be infinite.</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"><ul class="first last simple">
<li><strong>n</strong> – (optional) max number of elements to visualize. Default ‘inf’.</li>
<li><strong>duration</strong> – (optional) max duration of elements to read in integer seconds or
a string duration. Default ‘inf’.</li>
<li><strong>include_window_info</strong> – (optional) if True, appends the windowing information
to each row. Default False.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p>For example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">p</span> <span class="o">=</span> <span class="n">beam</span><span class="o">.</span><span class="n">Pipeline</span><span class="p">(</span><span class="n">InteractiveRunner</span><span class="p">())</span>
<span class="n">init</span> <span class="o">=</span> <span class="n">p</span> <span class="o">|</span> <span class="s1">&#39;Init&#39;</span> <span class="o">&gt;&gt;</span> <span class="n">beam</span><span class="o">.</span><span class="n">Create</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="n">square</span> <span class="o">=</span> <span class="n">init</span> <span class="o">|</span> <span class="s1">&#39;Square&#39;</span> <span class="o">&gt;&gt;</span> <span class="n">beam</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="n">x</span><span class="p">)</span>
<span class="c1"># Run the pipeline and bring the PCollection into memory as a Dataframe.</span>
<span class="n">in_memory_square</span> <span class="o">=</span> <span class="n">head</span><span class="p">(</span><span class="n">square</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="function">
<dt id="apache_beam.runners.interactive.interactive_beam.show_graph">
<code class="descclassname">apache_beam.runners.interactive.interactive_beam.</code><code class="descname">show_graph</code><span class="sig-paren">(</span><em>pipeline</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#show_graph"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.show_graph" title="Permalink to this definition"></a></dt>
<dd><p>Shows the current pipeline shape of a given Beam pipeline as a DAG.</p>
</dd></dl>
<dl class="function">
<dt id="apache_beam.runners.interactive.interactive_beam.evict_recorded_data">
<code class="descclassname">apache_beam.runners.interactive.interactive_beam.</code><code class="descname">evict_recorded_data</code><span class="sig-paren">(</span><em>pipeline=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/runners/interactive/interactive_beam.html#evict_recorded_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.runners.interactive.interactive_beam.evict_recorded_data" title="Permalink to this definition"></a></dt>
<dd><p>Forcefully evicts all recorded replayable data for the given pipeline. If
no pipeline is specified, evicts for all user defined pipelines.</p>
<p>Once invoked, Interactive Beam will record new data based on the guidance of
options the next time it evaluates/visualizes PCollections or runs pipelines.</p>
</dd></dl>
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