Non-zero exit code for client on errors

gordo_components/cli/client.py

@@ -2,6 +2,7 @@
 
 import os
 import typing
+import sys
 import json
 from datetime import datetime
 from pprint import pprint
@@ -108,20 +109,20 @@ def predict(
 
     # Loop over all error messages for each result and log them
     click.secho(f"\n{'-' * 20} Summary of failed predictions (if any) {'-' * 20}")
+    exit_code = 0
     for (_name, _df, error_messages) in predictions:
         for err_msg in error_messages:
+            # Any error message indicates we encountered at least one error
+            exit_code = 1
             click.secho(err_msg, fg="red")
 
     # Shall we write the predictions out?
     if output_dir is not None:
-        for (
-            name,
-            prediction_df,
-            _err_msgs,
-        ) in predictions:  # [(name: str, predictions: pd.DataFrame), ...]
+        for (name, prediction_df, _err_msgs) in predictions:
             prediction_df.to_csv(
                 os.path.join(output_dir, f"{name}.csv.gz"), compression="gzip"
             )
+    sys.exit(exit_code)
 
 
 @click.command("metadata")

tests/gordo_components/client/test_client.py

@@ -3,6 +3,7 @@
 import os
 import tempfile
 import json
+import logging
 from dateutil.parser import isoparse  # type: ignore
 
 import aiohttp
@@ -331,6 +332,49 @@ def test_client_cli_predict(
         )
 
 
+@pytest.mark.parametrize(
+    "should_fail,start_date,end_date",
+    [
+        (True, "1888-01-01T00:00:00Z", "1888-02-01T01:00:00Z"),  # Fail on bad dates
+        (False, "2016-01-01T00:00:00Z", "2016-01-01T01:00:00Z"),  # pass on good dates
+    ],
+)
+def test_client_cli_predict_non_zero_exit(
+    should_fail, start_date, end_date, caplog, influxdb, watchman_service
+):
+    """
+    Test ability for client to get predictions via CLI
+    """
+    runner = CliRunner()
+
+    # Should fail requesting dates which clearly don't exist.
+    args = [
+        "client",
+        "--metadata",
+        "key,value",
+        "--project",
+        tu.GORDO_PROJECT,
+        "predict",
+        start_date,
+        end_date,
+    ]
+
+    data_provider = providers.InfluxDataProvider(
+        measurement=tu.INFLUXDB_MEASUREMENT, value_name="Value", uri=tu.INFLUXDB_URI
+    )
+
+    args.extend(["--data-provider", json.dumps(data_provider.to_dict())])
+
+    # Run without any error
+    with caplog.at_level(logging.CRITICAL):
+        out = runner.invoke(cli.gordo, args=args)
+
+    if should_fail:
+        assert out.exit_code != 0, f"{out.output}"
+    else:
+        assert out.exit_code == 0, f"{out.output}"
+
+
 @pytest.mark.parametrize(
     "config",
     (