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<blockquote>
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<div class="section" id="building-a-running-pipeline">
<h1>Building a Running Pipeline<a class="headerlink" href="#building-a-running-pipeline" title="Permalink to this heading"></a></h1>
<p>Lets look at another example: we need to get some data from a file which is hosted online and insert it into our local database. We also need to look at removing duplicate rows while inserting.</p>
<div class="section" id="initial-setup">
<h2>Initial setup<a class="headerlink" href="#initial-setup" title="Permalink to this heading"></a></h2>
<p>We need to have Docker installed as we will be using the <a class="reference internal" href="../howto/docker-compose/index.html"><span class="doc">Running Airflow in Docker</span></a> procedure for this example.
The steps below should be sufficient, but see the quick-start documentation for full instructions.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1"># Download the docker-compose.yaml file</span>
curl -LfO <span class="s1">&#39;https://airflow.apache.org/docs/apache-airflow/stable/docker-compose.yaml&#39;</span>
<span class="c1"># Make expected directories and set an expected environment variable</span>
mkdir -p ./dags ./logs ./plugins
<span class="nb">echo</span> -e <span class="s2">&quot;AIRFLOW_UID=</span><span class="k">$(</span>id -u<span class="k">)</span><span class="s2">&quot;</span> &gt; .env
<span class="c1"># Initialize the database</span>
docker-compose up airflow-init
<span class="c1"># Start up all services</span>
docker-compose up
</pre></div>
</div>
<p>After all services have started up, the web UI will be available at: <code class="docutils literal notranslate"><span class="pre">http://localhost:8080</span></code>. The default account has the username <code class="docutils literal notranslate"><span class="pre">airflow</span></code> and the password <code class="docutils literal notranslate"><span class="pre">airflow</span></code>.</p>
<p>We will also need to create a <a class="reference external" href="https://airflow.apache.org/docs/apache-airflow/stable/concepts/connections.html">connection</a> to the postgres db. To create one via the web UI, from the “Admin” menu, select “Connections”, then click the Plus sign to “Add a new record” to the list of connections.</p>
<p>Fill in the fields as shown below. Note the Connection Id value, which we’ll pass as a parameter for the <code class="docutils literal notranslate"><span class="pre">postgres_conn_id</span></code> kwarg.</p>
<ul class="simple">
<li><p>Connection Id: tutorial_pg_conn</p></li>
<li><p>Connection Type: postgres</p></li>
<li><p>Host: postgres</p></li>
<li><p>Schema: airflow</p></li>
<li><p>Login: airflow</p></li>
<li><p>Password: airflow</p></li>
<li><p>Port: 5432</p></li>
</ul>
<p>Test your connection and if the test is successful, save your connection.</p>
</div>
<div class="section" id="table-creation-tasks">
<h2>Table Creation Tasks<a class="headerlink" href="#table-creation-tasks" title="Permalink to this heading"></a></h2>
<p>We can use the <a class="reference external" href="https://airflow.apache.org/docs/apache-airflow-providers-postgres/stable/operators/postgres_operator_howto_guide.html#creating-a-postgres-database-table">PostgresOperator</a> to define tasks that create tables in our postgres db.</p>
<p>We’ll create one table to facilitate data cleaning steps (<code class="docutils literal notranslate"><span class="pre">employees_temp</span></code>) and another table to store our cleaned data (<code class="docutils literal notranslate"><span class="pre">employees</span></code>).</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">airflow.providers.postgres.operators.postgres</span> <span class="kn">import</span> <span class="n">PostgresOperator</span>
<span class="n">create_employees_table</span> <span class="o">=</span> <span class="n">PostgresOperator</span><span class="p">(</span>
<span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;create_employees_table&quot;</span><span class="p">,</span>
<span class="n">postgres_conn_id</span><span class="o">=</span><span class="s2">&quot;tutorial_pg_conn&quot;</span><span class="p">,</span>
<span class="n">sql</span><span class="o">=</span><span class="s2">&quot;&quot;&quot;</span>
<span class="s2"> CREATE TABLE IF NOT EXISTS employees (</span>
<span class="s2"> &quot;Serial Number&quot; NUMERIC PRIMARY KEY,</span>
<span class="s2"> &quot;Company Name&quot; TEXT,</span>
<span class="s2"> &quot;Employee Markme&quot; TEXT,</span>
<span class="s2"> &quot;Description&quot; TEXT,</span>
<span class="s2"> &quot;Leave&quot; INTEGER</span>
<span class="s2"> );&quot;&quot;&quot;</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">create_employees_temp_table</span> <span class="o">=</span> <span class="n">PostgresOperator</span><span class="p">(</span>
<span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;create_employees_temp_table&quot;</span><span class="p">,</span>
<span class="n">postgres_conn_id</span><span class="o">=</span><span class="s2">&quot;tutorial_pg_conn&quot;</span><span class="p">,</span>
<span class="n">sql</span><span class="o">=</span><span class="s2">&quot;&quot;&quot;</span>
<span class="s2"> DROP TABLE IF EXISTS employees_temp;</span>
<span class="s2"> CREATE TABLE employees_temp (</span>
<span class="s2"> &quot;Serial Number&quot; NUMERIC PRIMARY KEY,</span>
<span class="s2"> &quot;Company Name&quot; TEXT,</span>
<span class="s2"> &quot;Employee Markme&quot; TEXT,</span>
<span class="s2"> &quot;Description&quot; TEXT,</span>
<span class="s2"> &quot;Leave&quot; INTEGER</span>
<span class="s2"> );&quot;&quot;&quot;</span><span class="p">,</span>
<span class="p">)</span>
</pre></div>
</div>
</div>
<div class="section" id="optional-using-sql-from-files">
<h2>Optional: Using SQL From Files<a class="headerlink" href="#optional-using-sql-from-files" title="Permalink to this heading"></a></h2>
<p>If you want to abstract these sql statements out of your DAG, you can move the statements sql files somewhere within the <code class="docutils literal notranslate"><span class="pre">dags/</span></code> directory and pass the sql file_path (relative to <code class="docutils literal notranslate"><span class="pre">dags/</span></code>) to the <code class="docutils literal notranslate"><span class="pre">sql</span></code> kwarg. For <code class="docutils literal notranslate"><span class="pre">employees</span></code> for example, create a <code class="docutils literal notranslate"><span class="pre">sql</span></code> directory in <code class="docutils literal notranslate"><span class="pre">dags/</span></code>, put <code class="docutils literal notranslate"><span class="pre">employees</span></code> DDL in <code class="docutils literal notranslate"><span class="pre">dags/sql/employees_schema.sql</span></code>, and modify the PostgresOperator() to:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_employees_table</span> <span class="o">=</span> <span class="n">PostgresOperator</span><span class="p">(</span>
<span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;create_employees_table&quot;</span><span class="p">,</span>
<span class="n">postgres_conn_id</span><span class="o">=</span><span class="s2">&quot;tutorial_pg_conn&quot;</span><span class="p">,</span>
<span class="n">sql</span><span class="o">=</span><span class="s2">&quot;sql/employees_schema.sql&quot;</span><span class="p">,</span>
<span class="p">)</span>
</pre></div>
</div>
<p>and repeat for the <code class="docutils literal notranslate"><span class="pre">employees_temp</span></code> table.</p>
</div>
<div class="section" id="data-retrieval-task">
<h2>Data Retrieval Task<a class="headerlink" href="#data-retrieval-task" title="Permalink to this heading"></a></h2>
<p>Here we retrieve data, save it to a file on our Airflow instance, and load the data from that file into an intermediate table where we can execute data cleaning steps.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">requests</span>
<span class="kn">from</span> <span class="nn">airflow.decorators</span> <span class="kn">import</span> <span class="n">task</span>
<span class="kn">from</span> <span class="nn">airflow.providers.postgres.hooks.postgres</span> <span class="kn">import</span> <span class="n">PostgresHook</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<span class="c1"># NOTE: configure this as appropriate for your airflow environment</span>
<span class="n">data_path</span> <span class="o">=</span> <span class="s2">&quot;/opt/airflow/dags/files/employees.csv&quot;</span>
<span class="n">os</span><span class="o">.</span><span class="n">makedirs</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">dirname</span><span class="p">(</span><span class="n">data_path</span><span class="p">),</span> <span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">url</span> <span class="o">=</span> <span class="s2">&quot;https://raw.githubusercontent.com/apache/airflow/main/docs/apache-airflow/tutorial/pipeline_example.csv&quot;</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="o">.</span><span class="n">request</span><span class="p">(</span><span class="s2">&quot;GET&quot;</span><span class="p">,</span> <span class="n">url</span><span class="p">)</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">data_path</span><span class="p">,</span> <span class="s2">&quot;w&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">file</span><span class="p">:</span>
<span class="n">file</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">response</span><span class="o">.</span><span class="n">text</span><span class="p">)</span>
<span class="n">postgres_hook</span> <span class="o">=</span> <span class="n">PostgresHook</span><span class="p">(</span><span class="n">postgres_conn_id</span><span class="o">=</span><span class="s2">&quot;tutorial_pg_conn&quot;</span><span class="p">)</span>
<span class="n">conn</span> <span class="o">=</span> <span class="n">postgres_hook</span><span class="o">.</span><span class="n">get_conn</span><span class="p">()</span>
<span class="n">cur</span> <span class="o">=</span> <span class="n">conn</span><span class="o">.</span><span class="n">cursor</span><span class="p">()</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">data_path</span><span class="p">,</span> <span class="s2">&quot;r&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">file</span><span class="p">:</span>
<span class="n">cur</span><span class="o">.</span><span class="n">copy_expert</span><span class="p">(</span>
<span class="s2">&quot;COPY employees_temp FROM STDIN WITH CSV HEADER DELIMITER AS &#39;,&#39; QUOTE &#39;</span><span class="se">\&quot;</span><span class="s2">&#39;&quot;</span><span class="p">,</span>
<span class="n">file</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">conn</span><span class="o">.</span><span class="n">commit</span><span class="p">()</span>
</pre></div>
</div>
</div>
<div class="section" id="data-merge-task">
<h2>Data Merge Task<a class="headerlink" href="#data-merge-task" title="Permalink to this heading"></a></h2>
<p>Here we select completely unique records from the retrieved data, then we check to see if any employee <code class="docutils literal notranslate"><span class="pre">Serial</span> <span class="pre">Numbers</span></code> are already in the database (if they are, we update those records with the new data).</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">airflow.decorators</span> <span class="kn">import</span> <span class="n">task</span>
<span class="kn">from</span> <span class="nn">airflow.providers.postgres.hooks.postgres</span> <span class="kn">import</span> <span class="n">PostgresHook</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">merge_data</span><span class="p">():</span>
<span class="n">query</span> <span class="o">=</span> <span class="s2">&quot;&quot;&quot;</span>
<span class="s2"> INSERT INTO employees</span>
<span class="s2"> SELECT *</span>
<span class="s2"> FROM (</span>
<span class="s2"> SELECT DISTINCT *</span>
<span class="s2"> FROM employees_temp</span>
<span class="s2"> )</span>
<span class="s2"> ON CONFLICT (&quot;Serial Number&quot;) DO UPDATE</span>
<span class="s2"> SET &quot;Serial Number&quot; = excluded.&quot;Serial Number&quot;;</span>
<span class="s2"> &quot;&quot;&quot;</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">postgres_hook</span> <span class="o">=</span> <span class="n">PostgresHook</span><span class="p">(</span><span class="n">postgres_conn_id</span><span class="o">=</span><span class="s2">&quot;tutorial_pg_conn&quot;</span><span class="p">)</span>
<span class="n">conn</span> <span class="o">=</span> <span class="n">postgres_hook</span><span class="o">.</span><span class="n">get_conn</span><span class="p">()</span>
<span class="n">cur</span> <span class="o">=</span> <span class="n">conn</span><span class="o">.</span><span class="n">cursor</span><span class="p">()</span>
<span class="n">cur</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>
<span class="n">conn</span><span class="o">.</span><span class="n">commit</span><span class="p">()</span>
<span class="k">return</span> <span class="mi">0</span>
<span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
<span class="k">return</span> <span class="mi">1</span>
</pre></div>
</div>
</div>
<div class="section" id="completing-our-dag">
<h2>Completing our DAG<a class="headerlink" href="#completing-our-dag" title="Permalink to this heading"></a></h2>
<p>We’ve developed our tasks, now we need to wrap them in a DAG, which enables us to define when and how tasks should run, and state any dependencies that tasks have on other tasks. The DAG below is configured to:</p>
<ul class="simple">
<li><p>run every day at midnight starting on Jan 1, 2021,</p></li>
<li><p>only run once in the event that days are missed, and</p></li>
<li><p>timeout after 60 minutes</p></li>
</ul>
<p>And from the last line in the definition of the <code class="docutils literal notranslate"><span class="pre">process-employees</span></code> DAG, we see:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[</span><span class="n">create_employees_table</span><span class="p">,</span> <span class="n">create_employees_temp_table</span><span class="p">]</span> <span class="o">&gt;&gt;</span> <span class="n">get_data</span><span class="p">()</span> <span class="o">&gt;&gt;</span> <span class="n">merge_data</span><span class="p">()</span>
</pre></div>
</div>
<ul class="simple">
<li><p>the <code class="docutils literal notranslate"><span class="pre">merge_data()</span></code> task depends on the <code class="docutils literal notranslate"><span class="pre">get_data()</span></code> task,</p></li>
<li><p>the <code class="docutils literal notranslate"><span class="pre">get_data()</span></code> depends on both the <code class="docutils literal notranslate"><span class="pre">create_employees_table</span></code> and <code class="docutils literal notranslate"><span class="pre">create_employees_temp_table</span></code> tasks, and</p></li>
<li><p>the <code class="docutils literal notranslate"><span class="pre">create_employees_table</span></code> and <code class="docutils literal notranslate"><span class="pre">create_employees_temp_table</span></code> tasks can run independently.</p></li>
</ul>
<p>Putting all of the pieces together, we have our completed DAG.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">datetime</span>
<span class="kn">import</span> <span class="nn">pendulum</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">requests</span>
<span class="kn">from</span> <span class="nn">airflow.decorators</span> <span class="kn">import</span> <span class="n">dag</span><span class="p">,</span> <span class="n">task</span>
<span class="kn">from</span> <span class="nn">airflow.providers.postgres.hooks.postgres</span> <span class="kn">import</span> <span class="n">PostgresHook</span>
<span class="kn">from</span> <span class="nn">airflow.providers.postgres.operators.postgres</span> <span class="kn">import</span> <span class="n">PostgresOperator</span>
<span class="nd">@dag</span><span class="p">(</span>
<span class="n">dag_id</span><span class="o">=</span><span class="s2">&quot;process-employees&quot;</span><span class="p">,</span>
<span class="n">schedule_interval</span><span class="o">=</span><span class="s2">&quot;0 0 * * *&quot;</span><span class="p">,</span>
<span class="n">start_date</span><span class="o">=</span><span class="n">pendulum</span><span class="o">.</span><span class="n">datetime</span><span class="p">(</span><span class="mi">2021</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">tz</span><span class="o">=</span><span class="s2">&quot;UTC&quot;</span><span class="p">),</span>
<span class="n">catchup</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="n">dagrun_timeout</span><span class="o">=</span><span class="n">datetime</span><span class="o">.</span><span class="n">timedelta</span><span class="p">(</span><span class="n">minutes</span><span class="o">=</span><span class="mi">60</span><span class="p">),</span>
<span class="p">)</span>
<span class="k">def</span> <span class="nf">ProcessEmployees</span><span class="p">():</span>
<span class="n">create_employees_table</span> <span class="o">=</span> <span class="n">PostgresOperator</span><span class="p">(</span>
<span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;create_employees_table&quot;</span><span class="p">,</span>
<span class="n">postgres_conn_id</span><span class="o">=</span><span class="s2">&quot;tutorial_pg_conn&quot;</span><span class="p">,</span>
<span class="n">sql</span><span class="o">=</span><span class="s2">&quot;&quot;&quot;</span>
<span class="s2"> CREATE TABLE IF NOT EXISTS employees (</span>
<span class="s2"> &quot;Serial Number&quot; NUMERIC PRIMARY KEY,</span>
<span class="s2"> &quot;Company Name&quot; TEXT,</span>
<span class="s2"> &quot;Employee Markme&quot; TEXT,</span>
<span class="s2"> &quot;Description&quot; TEXT,</span>
<span class="s2"> &quot;Leave&quot; INTEGER</span>
<span class="s2"> );&quot;&quot;&quot;</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">create_employees_temp_table</span> <span class="o">=</span> <span class="n">PostgresOperator</span><span class="p">(</span>
<span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;create_employees_temp_table&quot;</span><span class="p">,</span>
<span class="n">postgres_conn_id</span><span class="o">=</span><span class="s2">&quot;tutorial_pg_conn&quot;</span><span class="p">,</span>
<span class="n">sql</span><span class="o">=</span><span class="s2">&quot;&quot;&quot;</span>
<span class="s2"> DROP TABLE IF EXISTS employees_temp;</span>
<span class="s2"> CREATE TABLE employees_temp (</span>
<span class="s2"> &quot;Serial Number&quot; NUMERIC PRIMARY KEY,</span>
<span class="s2"> &quot;Company Name&quot; TEXT,</span>
<span class="s2"> &quot;Employee Markme&quot; TEXT,</span>
<span class="s2"> &quot;Description&quot; TEXT,</span>
<span class="s2"> &quot;Leave&quot; INTEGER</span>
<span class="s2"> );&quot;&quot;&quot;</span><span class="p">,</span>
<span class="p">)</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<span class="c1"># NOTE: configure this as appropriate for your airflow environment</span>
<span class="n">data_path</span> <span class="o">=</span> <span class="s2">&quot;/opt/airflow/dags/files/employees.csv&quot;</span>
<span class="n">os</span><span class="o">.</span><span class="n">makedirs</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">dirname</span><span class="p">(</span><span class="n">data_path</span><span class="p">),</span> <span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">url</span> <span class="o">=</span> <span class="s2">&quot;https://raw.githubusercontent.com/apache/airflow/main/docs/apache-airflow/tutorial/pipeline_example.csv&quot;</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="o">.</span><span class="n">request</span><span class="p">(</span><span class="s2">&quot;GET&quot;</span><span class="p">,</span> <span class="n">url</span><span class="p">)</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">data_path</span><span class="p">,</span> <span class="s2">&quot;w&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">file</span><span class="p">:</span>
<span class="n">file</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">response</span><span class="o">.</span><span class="n">text</span><span class="p">)</span>
<span class="n">postgres_hook</span> <span class="o">=</span> <span class="n">PostgresHook</span><span class="p">(</span><span class="n">postgres_conn_id</span><span class="o">=</span><span class="s2">&quot;tutorial_pg_conn&quot;</span><span class="p">)</span>
<span class="n">conn</span> <span class="o">=</span> <span class="n">postgres_hook</span><span class="o">.</span><span class="n">get_conn</span><span class="p">()</span>
<span class="n">cur</span> <span class="o">=</span> <span class="n">conn</span><span class="o">.</span><span class="n">cursor</span><span class="p">()</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">data_path</span><span class="p">,</span> <span class="s2">&quot;r&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">file</span><span class="p">:</span>
<span class="n">cur</span><span class="o">.</span><span class="n">copy_expert</span><span class="p">(</span>
<span class="s2">&quot;COPY employees_temp FROM STDIN WITH CSV HEADER DELIMITER AS &#39;,&#39; QUOTE &#39;</span><span class="se">\&quot;</span><span class="s2">&#39;&quot;</span><span class="p">,</span>
<span class="n">file</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">conn</span><span class="o">.</span><span class="n">commit</span><span class="p">()</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">merge_data</span><span class="p">():</span>
<span class="n">query</span> <span class="o">=</span> <span class="s2">&quot;&quot;&quot;</span>
<span class="s2"> INSERT INTO employees</span>
<span class="s2"> SELECT *</span>
<span class="s2"> FROM (</span>
<span class="s2"> SELECT DISTINCT *</span>
<span class="s2"> FROM employees_temp</span>
<span class="s2"> )</span>
<span class="s2"> ON CONFLICT (&quot;Serial Number&quot;) DO UPDATE</span>
<span class="s2"> SET &quot;Serial Number&quot; = excluded.&quot;Serial Number&quot;;</span>
<span class="s2"> &quot;&quot;&quot;</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">postgres_hook</span> <span class="o">=</span> <span class="n">PostgresHook</span><span class="p">(</span><span class="n">postgres_conn_id</span><span class="o">=</span><span class="s2">&quot;tutorial_pg_conn&quot;</span><span class="p">)</span>
<span class="n">conn</span> <span class="o">=</span> <span class="n">postgres_hook</span><span class="o">.</span><span class="n">get_conn</span><span class="p">()</span>
<span class="n">cur</span> <span class="o">=</span> <span class="n">conn</span><span class="o">.</span><span class="n">cursor</span><span class="p">()</span>
<span class="n">cur</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>
<span class="n">conn</span><span class="o">.</span><span class="n">commit</span><span class="p">()</span>
<span class="k">return</span> <span class="mi">0</span>
<span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
<span class="k">return</span> <span class="mi">1</span>
<span class="p">[</span><span class="n">create_employees_table</span><span class="p">,</span> <span class="n">create_employees_temp_table</span><span class="p">]</span> <span class="o">&gt;&gt;</span> <span class="n">get_data</span><span class="p">()</span> <span class="o">&gt;&gt;</span> <span class="n">merge_data</span><span class="p">()</span>
<span class="n">dag</span> <span class="o">=</span> <span class="n">ProcessEmployees</span><span class="p">()</span>
</pre></div>
</div>
<p>Save this code to a python file in the <code class="docutils literal notranslate"><span class="pre">/dags</span></code> folder (e.g. <code class="docutils literal notranslate"><span class="pre">dags/process-employees.py</span></code>) and (after a <a class="reference external" href="https://airflow.apache.org/docs/apache-airflow/stable/configurations-ref.html#dag-dir-list-interval">brief delay</a>), the <code class="docutils literal notranslate"><span class="pre">process-employees</span></code> DAG will be included in the list of available DAGs on the web UI.</p>
<img alt="../_images/tutorial-pipeline-1.png" src="../_images/tutorial-pipeline-1.png" />
<p>You can trigger the <code class="docutils literal notranslate"><span class="pre">process-employees</span></code> DAG by unpausing it (via the slider on the left end) and running it (via the Run button under <strong>Actions</strong>).</p>
<img alt="../_images/tutorial-pipeline-2.png" src="../_images/tutorial-pipeline-2.png" />
<p>In the <code class="docutils literal notranslate"><span class="pre">process-employees</span></code> DAG’s <strong>Grid</strong> view, we see all that all tasks ran successfully in all executed runs. Success!</p>
</div>
<div class="section" id="what-s-next">
<h2>What’s Next?<a class="headerlink" href="#what-s-next" title="Permalink to this heading"></a></h2>
<p>You now have a pipeline running inside Airflow using Docker Compose. Here are a few things you might want to do next:</p>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<ul class="simple">
<li><p>Take an in-depth tour of the UI - click all the things! see what they do!</p></li>
<li><p>Keep reading the docs
- Review the <a class="reference internal" href="../howto/index.html"><span class="doc">how-to guides</span></a>, which include a guide for writing your own operator
- Review the <a class="reference internal" href="../cli-and-env-variables-ref.html#cli"><span class="std std-ref">Command Line Interface Reference</span></a>
- Review the <a class="reference internal" href="../python-api-ref.html#pythonapi-operators"><span class="std std-ref">List of operators</span></a>
- Review the <a class="reference external" href="https://jinja.palletsprojects.com/en/2.11.x/templates/#macros" title="(in Jinja v2.11.x)"><span class="xref std std-ref">Macros reference</span></a></p></li>
<li><p>Write your first pipeline</p></li>
</ul>
</div>
</div>
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