[GitHub] r39132 closed pull request #3834: [AIRFLOW-2965] CLI tool to show the next execution datetime

[GitBox <gi...@apache.org>]

r39132 closed pull request #3834: [AIRFLOW-2965] CLI tool to show the next execution datetime
URL: https://github.com/apache/incubator-airflow/pull/3834
 
 
   

This is a PR merged from a forked repository.
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diff --git a/airflow/bin/cli.py b/airflow/bin/cli.py
index e22427cf40..c38116e6c0 100644
--- a/airflow/bin/cli.py
+++ b/airflow/bin/cli.py
@@ -551,6 +551,31 @@ def dag_state(args):
     print(dr[0].state if len(dr) > 0 else None)
 
 
+@cli_utils.action_logging
+def next_execution(args):
+    """
+    Returns the next execution datetime of a DAG at the command line.
+    >>> airflow next_execution tutorial
+    2018-08-31 10:38:00
+    """
+    dag = get_dag(args)
+
+    if dag.is_paused:
+        print("[INFO] Please be reminded this DAG is PAUSED now.")
+
+    if dag.latest_execution_date:
+        next_execution_dttm = dag.following_schedule(dag.latest_execution_date)
+
+        if next_execution_dttm is None:
+            print("[WARN] No following schedule can be found. " +
+                  "This DAG may have schedule interval '@once' or `None`.")
+
+        print(next_execution_dttm)
+    else:
+        print("[WARN] Only applicable when there is execution record found for the DAG.")
+        print(None)
+
+
 @cli_utils.action_logging
 def list_dags(args):
     dagbag = DagBag(process_subdir(args.subdir))
@@ -1986,6 +2011,11 @@ class CLIFactory(object):
             'func': sync_perm,
             'help': "Update existing role's permissions.",
             'args': tuple(),
+        },
+        {
+            'func': next_execution,
+            'help': "Get the next execution datetime of a DAG.",
+            'args': ('dag_id', 'subdir')
         }
     )
     subparsers_dict = {sp['func'].__name__: sp for sp in subparsers}
diff --git a/tests/cli/test_cli.py b/tests/cli/test_cli.py
index 616b9a0f16..93ec0576e6 100644
--- a/tests/cli/test_cli.py
+++ b/tests/cli/test_cli.py
@@ -20,9 +20,12 @@
 
 import unittest
 
+from datetime import datetime, timedelta, time
 from mock import patch, Mock, MagicMock
 from time import sleep
 import psutil
+import pytz
+import subprocess
 from argparse import Namespace
 from airflow import settings
 from airflow.bin.cli import get_num_ready_workers_running, run, get_dag
@@ -165,3 +168,80 @@ def test_local_run(self):
             ti.refresh_from_db()
             state = ti.current_state()
             self.assertEqual(state, State.SUCCESS)
+
+    def test_next_execution(self):
+        # A scaffolding function
+        def reset_dr_db(dag_id):
+            session = Session()
+            dr = session.query(models.DagRun).filter_by(dag_id=dag_id)
+            dr.delete()
+            session.commit()
+            session.close()
+
+        EXAMPLE_DAGS_FOLDER = os.path.join(
+            os.path.dirname(
+                os.path.dirname(
+                    os.path.dirname(os.path.realpath(__file__))
+                )
+            ),
+            "airflow/example_dags"
+        )
+
+        dagbag = models.DagBag(dag_folder=EXAMPLE_DAGS_FOLDER,
+                               include_examples=False)
+        dag_ids = ['example_bash_operator',  # schedule_interval is '0 0 * * *'
+                   'latest_only',  # schedule_interval is timedelta(hours=4)
+                   'example_python_operator',  # schedule_interval=None
+                   'example_xcom']  # schedule_interval="@once"
+
+        # The details below is determined by the schedule_interval of example DAGs
+        now = timezone.utcnow()
+        next_execution_time_for_dag1 = pytz.utc.localize(
+            datetime.combine(
+                now.date() + timedelta(days=1),
+                time(0)
+            )
+        )
+        next_execution_time_for_dag2 = now + timedelta(hours=4)
+        expected_output = [str(next_execution_time_for_dag1),
+                           str(next_execution_time_for_dag2),
+                           "None",
+                           "None"]
+
+        for i in range(len(dag_ids)):
+            dag_id = dag_ids[i]
+
+            # Clear dag run so no execution history fo each DAG
+            reset_dr_db(dag_id)
+
+            p = subprocess.Popen(["airflow", "next_execution", dag_id,
+                                  "--subdir", EXAMPLE_DAGS_FOLDER],
+                                 stdout=subprocess.PIPE)
+            p.wait()
+            stdout = []
+            for line in p.stdout:
+                stdout.append(str(line.decode("utf-8").rstrip()))
+
+            # `next_execution` function is inapplicable if no execution record found
+            # It prints `None` in such cases
+            self.assertEqual(stdout[-1], "None")
+
+            dag = dagbag.dags[dag_id]
+            # Create a DagRun for each DAG, to prepare for next step
+            dag.create_dagrun(
+                run_id='manual__' + now.isoformat(),
+                execution_date=now,
+                start_date=now,
+                state=State.FAILED
+            )
+
+            p = subprocess.Popen(["airflow", "next_execution", dag_id,
+                                  "--subdir", EXAMPLE_DAGS_FOLDER],
+                                 stdout=subprocess.PIPE)
+            p.wait()
+            stdout = []
+            for line in p.stdout:
+                stdout.append(str(line.decode("utf-8").rstrip()))
+            self.assertEqual(stdout[-1], expected_output[i])
+
+            reset_dr_db(dag_id)


 

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