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<h1>Source code for apache_beam.runners.runner</h1><div class="highlight"><pre>
<span></span><span class="c1">#</span>
<span class="c1"># Licensed to the Apache Software Foundation (ASF) under one or more</span>
<span class="c1"># contributor license agreements. See the NOTICE file distributed with</span>
<span class="c1"># this work for additional information regarding copyright ownership.</span>
<span class="c1"># The ASF licenses this file to You under the Apache License, Version 2.0</span>
<span class="c1"># (the &quot;License&quot;); you may not use this file except in compliance with</span>
<span class="c1"># the License. You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1"># Unless required by applicable law or agreed to in writing, software</span>
<span class="c1"># distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c1"># See the License for the specific language governing permissions and</span>
<span class="c1"># limitations under the License.</span>
<span class="c1">#</span>
<span class="sd">&quot;&quot;&quot;PipelineRunner, an abstract base runner object.&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">__future__</span> <span class="k">import</span> <span class="n">absolute_import</span>
<span class="kn">import</span> <span class="nn">logging</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">shelve</span>
<span class="kn">import</span> <span class="nn">shutil</span>
<span class="kn">import</span> <span class="nn">tempfile</span>
<span class="kn">from</span> <span class="nn">builtins</span> <span class="k">import</span> <span class="nb">object</span>
<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;PipelineRunner&#39;</span><span class="p">,</span> <span class="s1">&#39;PipelineState&#39;</span><span class="p">,</span> <span class="s1">&#39;PipelineResult&#39;</span><span class="p">]</span>
<span class="k">def</span> <span class="nf">_get_runner_map</span><span class="p">(</span><span class="n">runner_names</span><span class="p">,</span> <span class="n">module_path</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Create a map of runner name in lower case to full import path to the</span>
<span class="sd"> runner class.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="p">{</span><span class="n">runner_name</span><span class="o">.</span><span class="n">lower</span><span class="p">():</span> <span class="n">module_path</span> <span class="o">+</span> <span class="n">runner_name</span>
<span class="k">for</span> <span class="n">runner_name</span> <span class="ow">in</span> <span class="n">runner_names</span><span class="p">}</span>
<span class="n">_DIRECT_RUNNER_PATH</span> <span class="o">=</span> <span class="s1">&#39;apache_beam.runners.direct.direct_runner.&#39;</span>
<span class="n">_DATAFLOW_RUNNER_PATH</span> <span class="o">=</span> <span class="p">(</span>
<span class="s1">&#39;apache_beam.runners.dataflow.dataflow_runner.&#39;</span><span class="p">)</span>
<span class="n">_TEST_RUNNER_PATH</span> <span class="o">=</span> <span class="s1">&#39;apache_beam.runners.test.&#39;</span>
<span class="n">_PYTHON_RPC_DIRECT_RUNNER</span> <span class="o">=</span> <span class="p">(</span>
<span class="s1">&#39;apache_beam.runners.experimental.python_rpc_direct.&#39;</span>
<span class="s1">&#39;python_rpc_direct_runner.&#39;</span><span class="p">)</span>
<span class="n">_PORTABLE_RUNNER_PATH</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;apache_beam.runners.portability.portable_runner.&#39;</span><span class="p">)</span>
<span class="n">_KNOWN_PYTHON_RPC_DIRECT_RUNNER</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;PythonRPCDirectRunner&#39;</span><span class="p">,)</span>
<span class="n">_KNOWN_DIRECT_RUNNERS</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;DirectRunner&#39;</span><span class="p">,</span> <span class="s1">&#39;BundleBasedDirectRunner&#39;</span><span class="p">,</span>
<span class="s1">&#39;SwitchingDirectRunner&#39;</span><span class="p">)</span>
<span class="n">_KNOWN_DATAFLOW_RUNNERS</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;DataflowRunner&#39;</span><span class="p">,)</span>
<span class="n">_KNOWN_TEST_RUNNERS</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;TestDataflowRunner&#39;</span><span class="p">,</span> <span class="s1">&#39;TestDirectRunner&#39;</span><span class="p">)</span>
<span class="n">_KNOWN_PORTABLE_RUNNERS</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;PortableRunner&#39;</span><span class="p">,)</span>
<span class="n">_RUNNER_MAP</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">_RUNNER_MAP</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">_get_runner_map</span><span class="p">(</span><span class="n">_KNOWN_DIRECT_RUNNERS</span><span class="p">,</span>
<span class="n">_DIRECT_RUNNER_PATH</span><span class="p">))</span>
<span class="n">_RUNNER_MAP</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">_get_runner_map</span><span class="p">(</span><span class="n">_KNOWN_DATAFLOW_RUNNERS</span><span class="p">,</span>
<span class="n">_DATAFLOW_RUNNER_PATH</span><span class="p">))</span>
<span class="n">_RUNNER_MAP</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">_get_runner_map</span><span class="p">(</span><span class="n">_KNOWN_PYTHON_RPC_DIRECT_RUNNER</span><span class="p">,</span>
<span class="n">_PYTHON_RPC_DIRECT_RUNNER</span><span class="p">))</span>
<span class="n">_RUNNER_MAP</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">_get_runner_map</span><span class="p">(</span><span class="n">_KNOWN_TEST_RUNNERS</span><span class="p">,</span>
<span class="n">_TEST_RUNNER_PATH</span><span class="p">))</span>
<span class="n">_RUNNER_MAP</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">_get_runner_map</span><span class="p">(</span><span class="n">_KNOWN_PORTABLE_RUNNERS</span><span class="p">,</span>
<span class="n">_PORTABLE_RUNNER_PATH</span><span class="p">))</span>
<span class="n">_ALL_KNOWN_RUNNERS</span> <span class="o">=</span> <span class="p">(</span>
<span class="n">_KNOWN_DIRECT_RUNNERS</span> <span class="o">+</span> <span class="n">_KNOWN_DATAFLOW_RUNNERS</span> <span class="o">+</span> <span class="n">_KNOWN_TEST_RUNNERS</span> <span class="o">+</span>
<span class="n">_KNOWN_PORTABLE_RUNNERS</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">create_runner</span><span class="p">(</span><span class="n">runner_name</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;For internal use only; no backwards-compatibility guarantees.</span>
<span class="sd"> Creates a runner instance from a runner class name.</span>
<span class="sd"> Args:</span>
<span class="sd"> runner_name: Name of the pipeline runner. Possible values are listed in</span>
<span class="sd"> _RUNNER_MAP above.</span>
<span class="sd"> Returns:</span>
<span class="sd"> A runner object.</span>
<span class="sd"> Raises:</span>
<span class="sd"> RuntimeError: if an invalid runner name is used.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># Get the qualified runner name by using the lower case runner name. If that</span>
<span class="c1"># fails try appending the name with &#39;runner&#39; and check if it matches.</span>
<span class="c1"># If that also fails, use the given runner name as is.</span>
<span class="n">runner_name</span> <span class="o">=</span> <span class="n">_RUNNER_MAP</span><span class="o">.</span><span class="n">get</span><span class="p">(</span>
<span class="n">runner_name</span><span class="o">.</span><span class="n">lower</span><span class="p">(),</span>
<span class="n">_RUNNER_MAP</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">runner_name</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span> <span class="o">+</span> <span class="s1">&#39;runner&#39;</span><span class="p">,</span> <span class="n">runner_name</span><span class="p">))</span>
<span class="k">if</span> <span class="s1">&#39;.&#39;</span> <span class="ow">in</span> <span class="n">runner_name</span><span class="p">:</span>
<span class="n">module</span><span class="p">,</span> <span class="n">runner</span> <span class="o">=</span> <span class="n">runner_name</span><span class="o">.</span><span class="n">rsplit</span><span class="p">(</span><span class="s1">&#39;.&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">try</span><span class="p">:</span>
<span class="k">return</span> <span class="nb">getattr</span><span class="p">(</span><span class="nb">__import__</span><span class="p">(</span><span class="n">module</span><span class="p">,</span> <span class="p">{},</span> <span class="p">{},</span> <span class="p">[</span><span class="n">runner</span><span class="p">],</span> <span class="mi">0</span><span class="p">),</span> <span class="n">runner</span><span class="p">)()</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="k">if</span> <span class="n">runner_name</span> <span class="ow">in</span> <span class="n">_KNOWN_DATAFLOW_RUNNERS</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ImportError</span><span class="p">(</span>
<span class="s1">&#39;Google Cloud Dataflow runner not available, &#39;</span>
<span class="s1">&#39;please install apache_beam[gcp]&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="s1">&#39;Unexpected pipeline runner: </span><span class="si">%s</span><span class="s1">. Valid values are </span><span class="si">%s</span><span class="s1"> &#39;</span>
<span class="s1">&#39;or the fully qualified name of a PipelineRunner subclass.&#39;</span> <span class="o">%</span> <span class="p">(</span>
<span class="n">runner_name</span><span class="p">,</span> <span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">_ALL_KNOWN_RUNNERS</span><span class="p">)))</span>
<div class="viewcode-block" id="PipelineRunner"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineRunner">[docs]</a><span class="k">class</span> <span class="nc">PipelineRunner</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;A runner of a pipeline object.</span>
<span class="sd"> The base runner provides a run() method for visiting every node in the</span>
<span class="sd"> pipeline&#39;s DAG and executing the transforms computing the PValue in the node.</span>
<span class="sd"> A custom runner will typically provide implementations for some of the</span>
<span class="sd"> transform methods (ParDo, GroupByKey, Create, etc.). It may also</span>
<span class="sd"> provide a new implementation for clear_pvalue(), which is used to wipe out</span>
<span class="sd"> materialized values in order to reduce footprint.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<div class="viewcode-block" id="PipelineRunner.run"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineRunner.run">[docs]</a> <span class="k">def</span> <span class="nf">run</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">transform</span><span class="p">,</span> <span class="n">options</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Run the given transform or callable with this runner.</span>
<span class="sd"> Blocks until the pipeline is complete. See also `PipelineRunner.run_async`.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">result</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">run_async</span><span class="p">(</span><span class="n">transform</span><span class="p">,</span> <span class="n">options</span><span class="p">)</span>
<span class="n">result</span><span class="o">.</span><span class="n">wait_until_finish</span><span class="p">()</span>
<span class="k">return</span> <span class="n">result</span></div>
<div class="viewcode-block" id="PipelineRunner.run_async"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineRunner.run_async">[docs]</a> <span class="k">def</span> <span class="nf">run_async</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">transform</span><span class="p">,</span> <span class="n">options</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Run the given transform or callable with this runner.</span>
<span class="sd"> May return immediately, executing the pipeline in the background.</span>
<span class="sd"> The returned result object can be queried for progress, and</span>
<span class="sd"> `wait_until_finish` may be called to block until completion.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># Imported here to avoid circular dependencies.</span>
<span class="c1"># pylint: disable=wrong-import-order, wrong-import-position</span>
<span class="kn">from</span> <span class="nn">apache_beam</span> <span class="k">import</span> <span class="n">PTransform</span>
<span class="kn">from</span> <span class="nn">apache_beam.pvalue</span> <span class="k">import</span> <span class="n">PBegin</span>
<span class="kn">from</span> <span class="nn">apache_beam.pipeline</span> <span class="k">import</span> <span class="n">Pipeline</span>
<span class="n">p</span> <span class="o">=</span> <span class="n">Pipeline</span><span class="p">(</span><span class="n">runner</span><span class="o">=</span><span class="bp">self</span><span class="p">,</span> <span class="n">options</span><span class="o">=</span><span class="n">options</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">transform</span><span class="p">,</span> <span class="n">PTransform</span><span class="p">):</span>
<span class="n">p</span> <span class="o">|</span> <span class="n">transform</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">transform</span><span class="p">(</span><span class="n">PBegin</span><span class="p">(</span><span class="n">p</span><span class="p">))</span>
<span class="k">return</span> <span class="n">p</span><span class="o">.</span><span class="n">run</span><span class="p">()</span></div>
<div class="viewcode-block" id="PipelineRunner.run_pipeline"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineRunner.run_pipeline">[docs]</a> <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="n">pipeline</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Execute the entire pipeline or the sub-DAG reachable from a node.</span>
<span class="sd"> Runners should override this method.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># Imported here to avoid circular dependencies.</span>
<span class="c1"># pylint: disable=wrong-import-order, wrong-import-position</span>
<span class="kn">from</span> <span class="nn">apache_beam.pipeline</span> <span class="k">import</span> <span class="n">PipelineVisitor</span>
<span class="k">class</span> <span class="nc">RunVisitor</span><span class="p">(</span><span class="n">PipelineVisitor</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">runner</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">runner</span> <span class="o">=</span> <span class="n">runner</span>
<span class="k">def</span> <span class="nf">visit_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">transform_node</span><span class="p">):</span>
<span class="k">try</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">runner</span><span class="o">.</span><span class="n">run_transform</span><span class="p">(</span><span class="n">transform_node</span><span class="p">)</span>
<span class="k">except</span><span class="p">:</span>
<span class="n">logging</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="s1">&#39;Error while visiting </span><span class="si">%s</span><span class="s1">&#39;</span><span class="p">,</span> <span class="n">transform_node</span><span class="o">.</span><span class="n">full_label</span><span class="p">)</span>
<span class="k">raise</span>
<span class="n">pipeline</span><span class="o">.</span><span class="n">visit</span><span class="p">(</span><span class="n">RunVisitor</span><span class="p">(</span><span class="bp">self</span><span class="p">))</span></div>
<div class="viewcode-block" id="PipelineRunner.apply"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineRunner.apply">[docs]</a> <span class="k">def</span> <span class="nf">apply</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">transform</span><span class="p">,</span> <span class="nb">input</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Runner callback for a pipeline.apply call.</span>
<span class="sd"> Args:</span>
<span class="sd"> transform: the transform to apply.</span>
<span class="sd"> input: transform&#39;s input (typically a PCollection).</span>
<span class="sd"> A concrete implementation of the Runner class may want to do custom</span>
<span class="sd"> pipeline construction for a given transform. To override the behavior</span>
<span class="sd"> for a transform class Xyz, implement an apply_Xyz method with this same</span>
<span class="sd"> signature.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">for</span> <span class="bp">cls</span> <span class="ow">in</span> <span class="n">transform</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="n">mro</span><span class="p">():</span>
<span class="n">m</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;apply_</span><span class="si">%s</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="bp">cls</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="k">if</span> <span class="n">m</span><span class="p">:</span>
<span class="k">return</span> <span class="n">m</span><span class="p">(</span><span class="n">transform</span><span class="p">,</span> <span class="nb">input</span><span class="p">)</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span>
<span class="s1">&#39;Execution of [</span><span class="si">%s</span><span class="s1">] not implemented in runner </span><span class="si">%s</span><span class="s1">.&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">transform</span><span class="p">,</span> <span class="bp">self</span><span class="p">))</span></div>
<div class="viewcode-block" id="PipelineRunner.apply_PTransform"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineRunner.apply_PTransform">[docs]</a> <span class="k">def</span> <span class="nf">apply_PTransform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">transform</span><span class="p">,</span> <span class="nb">input</span><span class="p">):</span>
<span class="c1"># The base case of apply is to call the transform&#39;s expand.</span>
<span class="k">return</span> <span class="n">transform</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="nb">input</span><span class="p">)</span></div>
<div class="viewcode-block" id="PipelineRunner.run_transform"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineRunner.run_transform">[docs]</a> <span class="k">def</span> <span class="nf">run_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">transform_node</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Runner callback for a pipeline.run call.</span>
<span class="sd"> Args:</span>
<span class="sd"> transform_node: transform node for the transform to run.</span>
<span class="sd"> A concrete implementation of the Runner class must implement run_Abc for</span>
<span class="sd"> some class Abc in the method resolution order for every non-composite</span>
<span class="sd"> transform Xyz in the pipeline.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">for</span> <span class="bp">cls</span> <span class="ow">in</span> <span class="n">transform_node</span><span class="o">.</span><span class="n">transform</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="n">mro</span><span class="p">():</span>
<span class="n">m</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;run_</span><span class="si">%s</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="bp">cls</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="k">if</span> <span class="n">m</span><span class="p">:</span>
<span class="k">return</span> <span class="n">m</span><span class="p">(</span><span class="n">transform_node</span><span class="p">)</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span>
<span class="s1">&#39;Execution of [</span><span class="si">%s</span><span class="s1">] not implemented in runner </span><span class="si">%s</span><span class="s1">.&#39;</span> <span class="o">%</span> <span class="p">(</span>
<span class="n">transform_node</span><span class="o">.</span><span class="n">transform</span><span class="p">,</span> <span class="bp">self</span><span class="p">))</span></div></div>
<span class="k">class</span> <span class="nc">PValueCache</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;For internal use only; no backwards-compatibility guarantees.</span>
<span class="sd"> Local cache for arbitrary information computed for PValue objects.&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">use_disk_backed_cache</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
<span class="c1"># Cache of values computed while a runner executes a pipeline. This is a</span>
<span class="c1"># dictionary of PValues and their computed values. Note that in principle</span>
<span class="c1"># the runner could contain PValues from several pipelines without clashes</span>
<span class="c1"># since a PValue is associated with one and only one pipeline. The keys of</span>
<span class="c1"># the dictionary are tuple of PValue instance addresses obtained using id()</span>
<span class="c1"># and tag names converted to strings.</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_use_disk_backed_cache</span> <span class="o">=</span> <span class="n">use_disk_backed_cache</span>
<span class="k">if</span> <span class="n">use_disk_backed_cache</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_tempdir</span> <span class="o">=</span> <span class="n">tempfile</span><span class="o">.</span><span class="n">mkdtemp</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_cache</span> <span class="o">=</span> <span class="n">shelve</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_tempdir</span><span class="p">,</span> <span class="s1">&#39;shelve&#39;</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_cache</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">def</span> <span class="nf">__del__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_use_disk_backed_cache</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_cache</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
<span class="n">shutil</span><span class="o">.</span><span class="n">rmtree</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_tempdir</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_cache</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">to_cache_key</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">transform</span><span class="p">,</span> <span class="n">tag</span><span class="p">):</span>
<span class="k">return</span> <span class="n">transform</span><span class="o">.</span><span class="n">full_label</span><span class="p">,</span> <span class="n">tag</span>
<span class="k">def</span> <span class="nf">_ensure_pvalue_has_real_producer</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pvalue</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Ensure the passed-in PValue has the real_producer attribute.</span>
<span class="sd"> Args:</span>
<span class="sd"> pvalue: A PValue instance whose cached value is requested.</span>
<span class="sd"> During the runner&#39;s execution only the results of the primitive transforms</span>
<span class="sd"> are cached. Whenever we are looking for a PValue that is the output of a</span>
<span class="sd"> composite transform we need to find the output of its rightmost transform</span>
<span class="sd"> part.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">pvalue</span><span class="p">,</span> <span class="s1">&#39;real_producer&#39;</span><span class="p">):</span>
<span class="n">real_producer</span> <span class="o">=</span> <span class="n">pvalue</span><span class="o">.</span><span class="n">producer</span>
<span class="k">while</span> <span class="n">real_producer</span><span class="o">.</span><span class="n">parts</span><span class="p">:</span>
<span class="n">real_producer</span> <span class="o">=</span> <span class="n">real_producer</span><span class="o">.</span><span class="n">parts</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
<span class="n">pvalue</span><span class="o">.</span><span class="n">real_producer</span> <span class="o">=</span> <span class="n">real_producer</span>
<span class="k">def</span> <span class="nf">is_cached</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pobj</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">apache_beam.pipeline</span> <span class="k">import</span> <span class="n">AppliedPTransform</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">pobj</span><span class="p">,</span> <span class="n">AppliedPTransform</span><span class="p">):</span>
<span class="n">transform</span> <span class="o">=</span> <span class="n">pobj</span>
<span class="n">tag</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_ensure_pvalue_has_real_producer</span><span class="p">(</span><span class="n">pobj</span><span class="p">)</span>
<span class="n">transform</span> <span class="o">=</span> <span class="n">pobj</span><span class="o">.</span><span class="n">real_producer</span>
<span class="n">tag</span> <span class="o">=</span> <span class="n">pobj</span><span class="o">.</span><span class="n">tag</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_cache_key</span><span class="p">(</span><span class="n">transform</span><span class="p">,</span> <span class="n">tag</span><span class="p">)</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_cache</span>
<span class="k">def</span> <span class="nf">cache_output</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">transform</span><span class="p">,</span> <span class="n">tag_or_value</span><span class="p">,</span> <span class="n">value</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="k">if</span> <span class="n">value</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">value</span> <span class="o">=</span> <span class="n">tag_or_value</span>
<span class="n">tag</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">tag</span> <span class="o">=</span> <span class="n">tag_or_value</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_cache</span><span class="p">[</span>
<span class="bp">self</span><span class="o">.</span><span class="n">to_cache_key</span><span class="p">(</span><span class="n">transform</span><span class="p">,</span> <span class="n">tag</span><span class="p">)]</span> <span class="o">=</span> <span class="n">value</span>
<span class="k">def</span> <span class="nf">get_pvalue</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pvalue</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Gets the value associated with a PValue from the cache.&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_ensure_pvalue_has_real_producer</span><span class="p">(</span><span class="n">pvalue</span><span class="p">)</span>
<span class="k">try</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_cache</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">key</span><span class="p">(</span><span class="n">pvalue</span><span class="p">)]</span>
<span class="k">except</span> <span class="ne">KeyError</span><span class="p">:</span>
<span class="k">if</span> <span class="p">(</span><span class="n">pvalue</span><span class="o">.</span><span class="n">tag</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_cache_key</span><span class="p">(</span><span class="n">pvalue</span><span class="o">.</span><span class="n">real_producer</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_cache</span><span class="p">):</span>
<span class="c1"># This is an undeclared, empty output of a DoFn executed</span>
<span class="c1"># in the local runner before this output was referenced.</span>
<span class="k">return</span> <span class="p">[]</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span>
<span class="k">def</span> <span class="nf">get_unwindowed_pvalue</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pvalue</span><span class="p">):</span>
<span class="k">return</span> <span class="p">[</span><span class="n">v</span><span class="o">.</span><span class="n">value</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_pvalue</span><span class="p">(</span><span class="n">pvalue</span><span class="p">)]</span>
<span class="k">def</span> <span class="nf">clear_pvalue</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pvalue</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Removes a PValue from the cache.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_cached</span><span class="p">(</span><span class="n">pvalue</span><span class="p">):</span>
<span class="k">del</span> <span class="bp">self</span><span class="o">.</span><span class="n">_cache</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">key</span><span class="p">(</span><span class="n">pvalue</span><span class="p">)]</span>
<span class="k">def</span> <span class="nf">key</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pobj</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_ensure_pvalue_has_real_producer</span><span class="p">(</span><span class="n">pobj</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_cache_key</span><span class="p">(</span><span class="n">pobj</span><span class="o">.</span><span class="n">real_producer</span><span class="p">,</span> <span class="n">pobj</span><span class="o">.</span><span class="n">tag</span><span class="p">)</span>
<div class="viewcode-block" id="PipelineState"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineState">[docs]</a><span class="k">class</span> <span class="nc">PipelineState</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;State of the Pipeline, as returned by :attr:`PipelineResult.state`.</span>
<span class="sd"> This is meant to be the union of all the states any runner can put a</span>
<span class="sd"> pipeline in. Currently, it represents the values of the dataflow</span>
<span class="sd"> API JobState enum.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">UNKNOWN</span> <span class="o">=</span> <span class="s1">&#39;UNKNOWN&#39;</span> <span class="c1"># not specified</span>
<span class="n">STARTING</span> <span class="o">=</span> <span class="s1">&#39;STARTING&#39;</span> <span class="c1"># not yet started</span>
<span class="n">STOPPED</span> <span class="o">=</span> <span class="s1">&#39;STOPPED&#39;</span> <span class="c1"># paused or not yet started</span>
<span class="n">RUNNING</span> <span class="o">=</span> <span class="s1">&#39;RUNNING&#39;</span> <span class="c1"># currently running</span>
<span class="n">DONE</span> <span class="o">=</span> <span class="s1">&#39;DONE&#39;</span> <span class="c1"># successfully completed (terminal state)</span>
<span class="n">FAILED</span> <span class="o">=</span> <span class="s1">&#39;FAILED&#39;</span> <span class="c1"># failed (terminal state)</span>
<span class="n">CANCELLED</span> <span class="o">=</span> <span class="s1">&#39;CANCELLED&#39;</span> <span class="c1"># explicitly cancelled (terminal state)</span>
<span class="n">UPDATED</span> <span class="o">=</span> <span class="s1">&#39;UPDATED&#39;</span> <span class="c1"># replaced by another job (terminal state)</span>
<span class="n">DRAINING</span> <span class="o">=</span> <span class="s1">&#39;DRAINING&#39;</span> <span class="c1"># still processing, no longer reading data</span>
<span class="n">DRAINED</span> <span class="o">=</span> <span class="s1">&#39;DRAINED&#39;</span> <span class="c1"># draining completed (terminal state)</span>
<span class="n">PENDING</span> <span class="o">=</span> <span class="s1">&#39;PENDING&#39;</span> <span class="c1"># the job has been created but is not yet running.</span>
<span class="n">CANCELLING</span> <span class="o">=</span> <span class="s1">&#39;CANCELLING&#39;</span> <span class="c1"># job has been explicitly cancelled and is</span>
<span class="c1"># in the process of stopping</span>
<div class="viewcode-block" id="PipelineState.is_terminal"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineState.is_terminal">[docs]</a> <span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">is_terminal</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">state</span><span class="p">):</span>
<span class="k">return</span> <span class="n">state</span> <span class="ow">in</span> <span class="p">[</span><span class="bp">cls</span><span class="o">.</span><span class="n">STOPPED</span><span class="p">,</span> <span class="bp">cls</span><span class="o">.</span><span class="n">DONE</span><span class="p">,</span> <span class="bp">cls</span><span class="o">.</span><span class="n">FAILED</span><span class="p">,</span> <span class="bp">cls</span><span class="o">.</span><span class="n">CANCELLED</span><span class="p">,</span>
<span class="bp">cls</span><span class="o">.</span><span class="n">UPDATED</span><span class="p">,</span> <span class="bp">cls</span><span class="o">.</span><span class="n">DRAINED</span><span class="p">]</span></div></div>
<div class="viewcode-block" id="PipelineResult"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineResult">[docs]</a><span class="k">class</span> <span class="nc">PipelineResult</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;A :class:`PipelineResult` provides access to info about a pipeline.&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_state</span> <span class="o">=</span> <span class="n">state</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">state</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Return the current state of the pipeline execution.&quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_state</span>
<div class="viewcode-block" id="PipelineResult.wait_until_finish"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineResult.wait_until_finish">[docs]</a> <span class="k">def</span> <span class="nf">wait_until_finish</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">duration</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Waits until the pipeline finishes and returns the final status.</span>
<span class="sd"> Args:</span>
<span class="sd"> duration (int): The time to wait (in milliseconds) for job to finish.</span>
<span class="sd"> If it is set to :data:`None`, it will wait indefinitely until the job</span>
<span class="sd"> is finished.</span>
<span class="sd"> Raises:</span>
<span class="sd"> ~exceptions.IOError: If there is a persistent problem getting job</span>
<span class="sd"> information.</span>
<span class="sd"> ~exceptions.NotImplementedError: If the runner does not support this</span>
<span class="sd"> operation.</span>
<span class="sd"> Returns:</span>
<span class="sd"> The final state of the pipeline, or :data:`None` on timeout.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span></div>
<div class="viewcode-block" id="PipelineResult.cancel"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineResult.cancel">[docs]</a> <span class="k">def</span> <span class="nf">cancel</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Cancels the pipeline execution.</span>
<span class="sd"> Raises:</span>
<span class="sd"> ~exceptions.IOError: If there is a persistent problem getting job</span>
<span class="sd"> information.</span>
<span class="sd"> ~exceptions.NotImplementedError: If the runner does not support this</span>
<span class="sd"> operation.</span>
<span class="sd"> Returns:</span>
<span class="sd"> The final state of the pipeline.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span></div>
<div class="viewcode-block" id="PipelineResult.metrics"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineResult.metrics">[docs]</a> <span class="k">def</span> <span class="nf">metrics</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Returns :class:`~apache_beam.metrics.metric.MetricResults` object to</span>
<span class="sd"> query metrics from the runner.</span>
<span class="sd"> Raises:</span>
<span class="sd"> ~exceptions.NotImplementedError: If the runner does not support this</span>
<span class="sd"> operation.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span></div>
<span class="c1"># pylint: disable=unused-argument</span>
<div class="viewcode-block" id="PipelineResult.aggregated_values"><a class="viewcode-back" href="../../../apache_beam.runners.runner.html#apache_beam.runners.runner.PipelineResult.aggregated_values">[docs]</a> <span class="k">def</span> <span class="nf">aggregated_values</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">aggregator_or_name</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Return a dict of step names to values of the Aggregator.&quot;&quot;&quot;</span>
<span class="n">logging</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">%s</span><span class="s1"> does not implement aggregated_values&#39;</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span>
<span class="k">return</span> <span class="p">{}</span></div></div>
</pre></div>
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