Merge branch 'master' into issue693-sar_backscatter-get-coefficients-…

…from-schema

CHANGELOG.md

@@ -9,6 +9,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Added `show_error_logs` argument to `cube.execute_batch()`/`job.start_and_wait()`/... to toggle the automatic printing of error logs on failure ([#505](https://github.com/Open-EO/openeo-python-client/issues/505))
+
 ### Changed
 
 ### Removed

docs/batch_jobs.rst

@@ -292,8 +292,8 @@ When using
 :py:meth:`job.start_and_wait() <openeo.rest.job.BatchJob.start_and_wait>`
 or :py:meth:`cube.execute_batch() <openeo.rest.datacube.DataCube.execute_batch>`
 to run a batch job and it fails,
-the openEO Python client library will automatically
-print the batch job logs and instructions to help with further investigation:
+the openEO Python client library will print (by default)
+the batch job's error logs and instructions to help with further investigation:
 
 .. code-block:: pycon
 

openeo/extra/job_management/__init__.py

@@ -658,16 +658,25 @@ def on_job_cancel(self, job: BatchJob, row):
 
     def _cancel_prolonged_job(self, job: BatchJob, row):
         """Cancel the job if it has been running for too long."""
-        job_running_start_time = rfc3339.parse_datetime(row["running_start_time"], with_timezone=True)
-        elapsed = datetime.datetime.now(tz=datetime.timezone.utc) - job_running_start_time
-        if elapsed > self._cancel_running_job_after:
-            try:
+        try:
+            # Ensure running start time is valid
+            job_running_start_time = rfc3339.parse_datetime(row.get("running_start_time"), with_timezone=True)
+
+            # Parse the current time into a datetime object with timezone info
+            current_time = rfc3339.parse_datetime(rfc3339.utcnow(), with_timezone=True)
+
+            # Calculate the elapsed time between job start and now
+            elapsed = current_time - job_running_start_time
+
+            if elapsed > self._cancel_running_job_after:
+
                 _log.info(
                     f"Cancelling long-running job {job.job_id} (after {elapsed}, running since {job_running_start_time})"
                 )
                 job.stop()
-            except OpenEoApiError as e:
-                _log.error(f"Failed to cancel long-running job {job.job_id}: {e}")
+
+        except Exception as e:
+            _log.error(f"Unexpected error while handling job {job.job_id}: {e}")
 
     def get_job_dir(self, job_id: str) -> Path:
         """Path to directory where job metadata, results and error logs are be saved."""
@@ -728,6 +737,13 @@ def _track_statuses(self, job_db: JobDatabaseInterface, stats: Optional[dict] =
                     self.on_job_cancel(the_job, active.loc[i])
 
                 if self._cancel_running_job_after and new_status == "running":
+                    if  (not active.loc[i, "running_start_time"] or pd.isna(active.loc[i, "running_start_time"])):
+                        _log.warning(
+                            f"Unknown 'running_start_time' for running job {job_id}. Using current time as an approximation."
+                            )
+                        stats["job started running"] += 1
+                        active.loc[i, "running_start_time"] = rfc3339.utcnow()
+
                     self._cancel_prolonged_job(the_job, active.loc[i])
 
                 active.loc[i, "status"] = new_status

openeo/rest/connection.py

@@ -84,6 +84,7 @@
     ContextTimer,
     LazyLoadCache,
     dict_no_none,
+    ensure_dir,
     ensure_list,
     load_json_resource,
     repr_truncate,
@@ -1771,7 +1772,9 @@ def download(
         )
 
         if outputfile is not None:
-            with Path(outputfile).open(mode="wb") as f:
+            target = Path(outputfile)
+            ensure_dir(target.parent)
+            with target.open(mode="wb") as f:
                 for chunk in response.iter_content(chunk_size=chunk_size):
                     f.write(chunk)
         else:

openeo/rest/datacube.py

@@ -2484,6 +2484,7 @@ def execute_batch(
         job_options: Optional[dict] = None,
         validate: Optional[bool] = None,
         auto_add_save_result: bool = True,
+        show_error_logs: bool = True,
         # TODO: deprecate `format_options` as keyword arguments
         **format_options,
     ) -> BatchJob:
@@ -2501,12 +2502,16 @@ def execute_batch(
         :param validate: Optional toggle to enable/prevent validation of the process graphs before execution
             (overruling the connection's ``auto_validate`` setting).
         :param auto_add_save_result: Automatically add a ``save_result`` node to the process graph if there is none yet.
+        :param show_error_logs: whether to automatically print error logs when the batch job failed.
 
         .. versionchanged:: 0.32.0
             Added ``auto_add_save_result`` option
 
         .. versionadded:: 0.36.0
             Added argument ``additional``.
+
+        .. versionchanged:: 0.37.0
+            Added argument ``show_error_logs``.
         """
         # TODO: start showing deprecation warnings about these inconsistent argument names
         if "format" in format_options and not out_format:
@@ -2536,7 +2541,10 @@ def execute_batch(
         )
         return job.run_synchronous(
             outputfile=outputfile,
-            print=print, max_poll_interval=max_poll_interval, connection_retry_interval=connection_retry_interval
+            print=print,
+            max_poll_interval=max_poll_interval,
+            connection_retry_interval=connection_retry_interval,
+            show_error_logs=show_error_logs,
         )
 
     def create_job(

openeo/rest/job.py

@@ -235,20 +235,43 @@ def logs(
         return VisualList("logs", data=entries)
 
     def run_synchronous(
-            self, outputfile: Union[str, Path, None] = None,
-            print=print, max_poll_interval=60, connection_retry_interval=30
+        self,
+        outputfile: Union[str, Path, None] = None,
+        print=print,
+        max_poll_interval=60,
+        connection_retry_interval=30,
+        show_error_logs: bool = True,
     ) -> BatchJob:
-        """Start the job, wait for it to finish and download result"""
+        """
+        Start the job, wait for it to finish and download result
+
+        :param outputfile: The path of a file to which a result can be written
+        :param print: print/logging function to show progress/status
+        :param max_poll_interval: maximum number of seconds to sleep between status polls
+        :param connection_retry_interval: how long to wait when status poll failed due to connection issue
+        :param show_error_logs: whether to automatically print error logs when the batch job failed.
+
+        .. versionchanged:: 0.37.0
+            Added argument ``show_error_logs``.
+        """
         self.start_and_wait(
-            print=print, max_poll_interval=max_poll_interval, connection_retry_interval=connection_retry_interval
+            print=print,
+            max_poll_interval=max_poll_interval,
+            connection_retry_interval=connection_retry_interval,
+            show_error_logs=show_error_logs,
         )
         # TODO #135 support multi file result sets too?
         if outputfile is not None:
             self.download_result(outputfile)
         return self
 
     def start_and_wait(
-            self, print=print, max_poll_interval: int = 60, connection_retry_interval: int = 30, soft_error_max=10
+        self,
+        print=print,
+        max_poll_interval: int = 60,
+        connection_retry_interval: int = 30,
+        soft_error_max=10,
+        show_error_logs: bool = True,
     ) -> BatchJob:
         """
         Start the batch job, poll its status and wait till it finishes (or fails)
@@ -257,7 +280,10 @@ def start_and_wait(
         :param max_poll_interval: maximum number of seconds to sleep between status polls
         :param connection_retry_interval: how long to wait when status poll failed due to connection issue
         :param soft_error_max: maximum number of soft errors (e.g. temporary connection glitches) to allow
-        :return:
+        :param show_error_logs: whether to automatically print error logs when the batch job failed.
+
+        .. versionchanged:: 0.37.0
+            Added argument ``show_error_logs``.
         """
         # TODO rename `connection_retry_interval` to something more generic?
         start_time = time.time()
@@ -314,13 +340,13 @@ def soft_error(message: str):
             poll_interval = min(1.25 * poll_interval, max_poll_interval)
 
         if status != "finished":
-            # TODO: allow to disable this printing logs (e.g. in non-interactive contexts)?
             # TODO: render logs jupyter-aware in a notebook context?
-            print(f"Your batch job {self.job_id!r} failed. Error logs:")
-            print(self.logs(level=logging.ERROR))
-            print(
-                f"Full logs can be inspected in an openEO (web) editor or with `connection.job({self.job_id!r}).logs()`."
-            )
+            if show_error_logs:
+                print(f"Your batch job {self.job_id!r} failed. Error logs:")
+                print(self.logs(level=logging.ERROR))
+                print(
+                    f"Full logs can be inspected in an openEO (web) editor or with `connection.job({self.job_id!r}).logs()`."
+                )
             raise JobFailedException(
                 f"Batch job {self.job_id!r} didn't finish successfully. Status: {status} (after {elapsed()}).",
                 job=self,

openeo/rest/mlmodel.py

@@ -71,12 +71,13 @@ def execute_batch(
         connection_retry_interval=30,
         additional: Optional[dict] = None,
         job_options: Optional[dict] = None,
+        show_error_logs: bool = True,
     ) -> BatchJob:
         """
         Evaluate the process graph by creating a batch job, and retrieving the results when it is finished.
         This method is mostly recommended if the batch job is expected to run in a reasonable amount of time.
 
-        For very long running jobs, you probably do not want to keep the client running.
+        For very long-running jobs, you probably do not want to keep the client running.
 
         :param job_options:
         :param outputfile: The path of a file to which a result can be written
@@ -85,9 +86,13 @@ def execute_batch(
         :param additional: additional (top-level) properties to set in the request body
         :param job_options: dictionary of job options to pass to the backend
             (under top-level property "job_options")
+        :param show_error_logs: whether to automatically print error logs when the batch job failed.
 
         .. versionadded:: 0.36.0
             Added argument ``additional``.
+
+        .. versionchanged:: 0.37.0
+            Added argument ``show_error_logs``.
         """
         job = self.create_job(
             title=title,
@@ -100,7 +105,10 @@ def execute_batch(
         return job.run_synchronous(
             # TODO #135 support multi file result sets too
             outputfile=outputfile,
-            print=print, max_poll_interval=max_poll_interval, connection_retry_interval=connection_retry_interval
+            print=print,
+            max_poll_interval=max_poll_interval,
+            connection_retry_interval=connection_retry_interval,
+            show_error_logs=show_error_logs,
         )
 
     def create_job(

openeo/rest/vectorcube.py

@@ -259,6 +259,7 @@ def execute_batch(
         job_options: Optional[dict] = None,
         validate: Optional[bool] = None,
         auto_add_save_result: bool = True,
+        show_error_logs: bool = True,
         # TODO: avoid using kwargs as format options
         **format_options,
     ) -> BatchJob:
@@ -277,6 +278,7 @@ def execute_batch(
         :param validate: Optional toggle to enable/prevent validation of the process graphs before execution
             (overruling the connection's ``auto_validate`` setting).
         :param auto_add_save_result: Automatically add a ``save_result`` node to the process graph if there is none yet.
+        :param show_error_logs: whether to automatically print error logs when the batch job failed.
 
         .. versionchanged:: 0.21.0
             When not specified explicitly, output format is guessed from output file extension.
@@ -286,6 +288,9 @@ def execute_batch(
 
         .. versionadded:: 0.36.0
             Added argument ``additional``.
+
+        .. versionchanged:: 0.37.0
+            Added argument ``show_error_logs``.
         """
         cube = self
         if auto_add_save_result:
@@ -310,7 +315,10 @@ def execute_batch(
         return job.run_synchronous(
             # TODO #135 support multi file result sets too
             outputfile=outputfile,
-            print=print, max_poll_interval=max_poll_interval, connection_retry_interval=connection_retry_interval
+            print=print,
+            max_poll_interval=max_poll_interval,
+            connection_retry_interval=connection_retry_interval,
+            show_error_logs=show_error_logs,
         )
 
     def create_job(

setup.py

@@ -22,6 +22,7 @@
     "mock",
     "requests-mock>=1.8.0",
     "httpretty>=1.1.4",
+    "urllib3<2.3.0",  # httpretty doesn't work properly with urllib3>=2.3.0. See #700 and https://github.com/gabrielfalcao/HTTPretty/issues/484
     "netCDF4>=1.7.0",
     "matplotlib",  # TODO: eliminate matplotlib as test dependency
     "geopandas",

tests/extra/job_management/test_job_management.py

@@ -7,6 +7,7 @@
 from time import sleep
 from typing import Callable, Union
 from unittest import mock
+import datetime
 
 import dirty_equals
 import geopandas
@@ -554,6 +555,7 @@ def start_job(row, connection_provider, connection, **kwargs):
                 12 * 60 * 60,
                 "finished",
             ),
+
         ],
     )
     def test_automatic_cancel_of_too_long_running_jobs(
@@ -645,6 +647,80 @@ def test_status_logging(self, tmp_path, job_manager, job_manager_root_dir, sleep
         assert needle.search(caplog.text)
 
 
+    @pytest.mark.parametrize(
+    ["create_time", "start_time", "running_start_time", "end_time", "end_status", "cancel_after_seconds"],
+    [
+        # Scenario 1: Missing running_start_time (None)
+        (
+            "2024-09-01T09:00:00Z",  # Job creation time
+            "2024-09-01T09:00:00Z",  # Job start time (should be 1 hour after create_time)
+            None,                     # Missing running_start_time
+            "2024-09-01T20:00:00Z",  # Job end time
+            "finished",               # Job final status
+            6 * 60 * 60,              # Cancel after 6 hours
+        ),
+        # Scenario 2: NaN running_start_time
+        (
+            "2024-09-01T09:00:00Z",
+            "2024-09-01T09:00:00Z",
+            float("nan"),             # NaN running_start_time
+            "2024-09-01T20:00:00Z",  # Job end time
+            "finished",               # Job final status
+            6 * 60 * 60,              # Cancel after 6 hours
+        ),
+    ]
+    )
+    def test_ensure_running_start_time_is_datetime(
+        self,
+        tmp_path,
+        time_machine,
+        create_time,
+        start_time,
+        running_start_time,
+        end_time,
+        end_status,
+        cancel_after_seconds,
+        dummy_backend_foo,
+        job_manager_root_dir,
+    ):
+        def get_status(job_id, current_status):
+            if rfc3339.utcnow() < start_time:
+                return "queued"
+            elif rfc3339.utcnow() < end_time:
+                return "running"
+            return end_status
+
+        # Set the job status updater function for the mock backend
+        dummy_backend_foo.job_status_updater = get_status
+
+        job_manager = MultiBackendJobManager(
+            root_dir=job_manager_root_dir, cancel_running_job_after=cancel_after_seconds
+        )
+        job_manager.add_backend("foo", connection=dummy_backend_foo.connection)
+
+        # Create a DataFrame representing the job database
+        df = pd.DataFrame({
+            "year": [2024],
+            "running_start_time": [running_start_time],  # Initial running_start_time
+        })
+
+        # Move the time machine to the job creation time
+        time_machine.move_to(create_time)
+
+        job_db_path = tmp_path / "jobs.csv"
+
+        # Mock sleep() to skip one hour at a time instead of actually sleeping
+        with mock.patch.object(openeo.extra.job_management.time, "sleep", new=lambda s: time_machine.shift(60 * 60)):
+            job_manager.run_jobs(df=df, start_job=self._create_year_job, job_db=job_db_path)
+
+        final_df = CsvJobDatabase(job_db_path).read()
+
+        # Validate running_start_time is a valid datetime object
+        filled_running_start_time = final_df.iloc[0]["running_start_time"]
+        assert isinstance(rfc3339.parse_datetime(filled_running_start_time), datetime.datetime)
+
+
+
 JOB_DB_DF_BASICS = pd.DataFrame(
     {
         "numbers": [3, 2, 1],