prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Fix lost runs in `CronTriggerTimetable`
  closes: #27399
  
  Fix lost runs in `CronTriggerTimetable` by resetting seconds and microseconds in `start_time_candidates`.
  <!--
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   or more contributor license agreements.  See the NOTICE file
   distributed with this work for additional information
   regarding copyright ownership.  The ASF licenses this file
   to you under the Apache License, Version 2.0 (the
   "License"); you may not use this file except in compliance
   with the License.  You may obtain a copy of the License at
  
     http://www.apache.org/licenses/LICENSE-2.0
  
   Unless required by applicable law or agreed to in writing,
   software distributed under the License is distributed on an
   "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
   KIND, either express or implied.  See the License for the
   specific language governing permissions and limitations
   under the License.
   -->
  
  <!--
  Thank you for contributing! Please make sure that your code changes
  are covered with tests. And in case of new features or big changes
  remember to adjust the documentation.
  
  Feel free to ping committers for the review!
  
  In case of an existing issue, reference it using one of the following:
  
  closes: #ISSUE
  related: #ISSUE
  
  How to write a good git commit message:
  http://chris.beams.io/posts/git-commit/
  -->
  
  
  
  <!-- Please keep an empty line above the dashes. -->
  ---
  **^ Add meaningful description above**
  
  Read the **[Pull Request Guidelines](https://github.com/apache/airflow/blob/main/CONTRIBUTING.rst#pull-request-guidelines)** for more information.
  In case of fundamental code changes, an Airflow Improvement Proposal ([AIP](https://cwiki.apache.org/confluence/display/AIRFLOW/Airflow+Improvement+Proposals)) is needed.
  In case of a new dependency, check compliance with the [ASF 3rd Party License Policy](https://www.apache.org/legal/resolved.html#category-x).
  In case of backwards incompatible changes please leave a note in a newsfragment file, named `{pr_number}.significant.rst` or `{issue_number}.significant.rst`, in [newsfragments](https://github.com/apache/airflow/tree/main/newsfragments).
  
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `airflow/timetables/trigger.py`
  Content:
  ```
  1 # Licensed to the Apache Software Foundation (ASF) under one
  2 # or more contributor license agreements.  See the NOTICE file
  3 # distributed with this work for additional information
  4 # regarding copyright ownership.  The ASF licenses this file
  5 # to you under the Apache License, Version 2.0 (the
  6 # "License"); you may not use this file except in compliance
  7 # with the License.  You may obtain a copy of the License at
  8 #
  9 #   http://www.apache.org/licenses/LICENSE-2.0
  10 #
  11 # Unless required by applicable law or agreed to in writing,
  12 # software distributed under the License is distributed on an
  13 # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  14 # KIND, either express or implied.  See the License for the
  15 # specific language governing permissions and limitations
  16 # under the License.
  17 from __future__ import annotations
  18 
  19 import datetime
  20 from typing import Any
  21 
  22 from dateutil.relativedelta import relativedelta
  23 from pendulum import DateTime
  24 from pendulum.tz.timezone import Timezone
  25 
  26 from airflow.timetables._cron import CronMixin
  27 from airflow.timetables.base import DagRunInfo, DataInterval, TimeRestriction, Timetable
  28 
  29 
  30 class CronTriggerTimetable(CronMixin, Timetable):
  31     """Timetable that triggers DAG runs according to a cron expression.
  32 
  33     This is different from ``CronDataIntervalTimetable``, where the cron
  34     expression specifies the *data interval* of a DAG run. With this timetable,
  35     the data intervals are specified independently from the cron expression.
  36     Also for the same reason, this timetable kicks off a DAG run immediately at
  37     the start of the period (similar to POSIX cron), instead of needing to wait
  38     for one data interval to pass.
  39 
  40     Don't pass ``@once`` in here; use ``OnceTimetable`` instead.
  41     """
  42 
  43     def __init__(
  44         self,
  45         cron: str,
  46         *,
  47         timezone: str | Timezone,
  48         interval: datetime.timedelta | relativedelta = datetime.timedelta(),
  49     ) -> None:
  50         super().__init__(cron, timezone)
  51         self._interval = interval
  52 
  53     @classmethod
  54     def deserialize(cls, data: dict[str, Any]) -> Timetable:
  55         from airflow.serialization.serialized_objects import decode_relativedelta, decode_timezone
  56 
  57         interval: datetime.timedelta | relativedelta
  58         if isinstance(data["interval"], dict):
  59             interval = decode_relativedelta(data["interval"])
  60         else:
  61             interval = datetime.timedelta(seconds=data["interval"])
  62         return cls(data["expression"], timezone=decode_timezone(data["timezone"]), interval=interval)
  63 
  64     def serialize(self) -> dict[str, Any]:
  65         from airflow.serialization.serialized_objects import encode_relativedelta, encode_timezone
  66 
  67         interval: float | dict[str, Any]
  68         if isinstance(self._interval, datetime.timedelta):
  69             interval = self._interval.total_seconds()
  70         else:
  71             interval = encode_relativedelta(self._interval)
  72         timezone = encode_timezone(self._timezone)
  73         return {"expression": self._expression, "timezone": timezone, "interval": interval}
  74 
  75     def infer_manual_data_interval(self, *, run_after: DateTime) -> DataInterval:
  76         return DataInterval(run_after - self._interval, run_after)
  77 
  78     def next_dagrun_info(
  79         self,
  80         *,
  81         last_automated_data_interval: DataInterval | None,
  82         restriction: TimeRestriction,
  83     ) -> DagRunInfo | None:
  84         if restriction.catchup:
  85             if last_automated_data_interval is not None:
  86                 next_start_time = self._get_next(last_automated_data_interval.end)
  87             elif restriction.earliest is None:
  88                 return None  # Don't know where to catch up from, give up.
  89             else:
  90                 next_start_time = self._align_to_next(restriction.earliest)
  91         else:
  92             start_time_candidates = [self._align_to_next(DateTime.utcnow())]
  93             if last_automated_data_interval is not None:
  94                 start_time_candidates.append(self._get_next(last_automated_data_interval.end))
  95             if restriction.earliest is not None:
  96                 start_time_candidates.append(self._align_to_next(restriction.earliest))
  97             next_start_time = max(start_time_candidates)
  98         if restriction.latest is not None and restriction.latest < next_start_time:
  99             return None
  100         return DagRunInfo.interval(next_start_time - self._interval, next_start_time)
  101
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/airflow/timetables/trigger.py b/airflow/timetables/trigger.py
  --- a/airflow/timetables/trigger.py
  +++ b/airflow/timetables/trigger.py
  @@ -89,7 +89,7 @@
               else:
                   next_start_time = self._align_to_next(restriction.earliest)
           else:
  -            start_time_candidates = [self._align_to_next(DateTime.utcnow())]
  +            start_time_candidates = [self._align_to_prev(DateTime.utcnow())]
               if last_automated_data_interval is not None:
                   start_time_candidates.append(self._get_next(last_automated_data_interval.end))
               if restriction.earliest is not None:
  
verification_info: {"golden_diff": "diff --git a/airflow/timetables/trigger.py b/airflow/timetables/trigger.py\n--- a/airflow/timetables/trigger.py\n+++ b/airflow/timetables/trigger.py\n@@ -89,7 +89,7 @@\n             else:\n                 next_start_time = self._align_to_next(restriction.earliest)\n         else:\n-            start_time_candidates = [self._align_to_next(DateTime.utcnow())]\n+            start_time_candidates = [self._align_to_prev(DateTime.utcnow())]\n             if last_automated_data_interval is not None:\n                 start_time_candidates.append(self._get_next(last_automated_data_interval.end))\n             if restriction.earliest is not None:\n", "issue": "Fix lost runs in `CronTriggerTimetable`\ncloses: #27399\r\n\r\nFix lost runs in `CronTriggerTimetable` by resetting seconds and microseconds in `start_time_candidates`.\r\n<!--\r\n Licensed to the Apache Software Foundation (ASF) under one\r\n or more contributor license agreements.  See the NOTICE file\r\n distributed with this work for additional information\r\n regarding copyright ownership.  The ASF licenses this file\r\n to you under the Apache License, Version 2.0 (the\r\n \"License\"); you may not use this file except in compliance\r\n with the License.  You may obtain a copy of the License at\r\n\r\n   http://www.apache.org/licenses/LICENSE-2.0\r\n\r\n Unless required by applicable law or agreed to in writing,\r\n software distributed under the License is distributed on an\r\n \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\r\n KIND, either express or implied.  See the License for the\r\n specific language governing permissions and limitations\r\n under the License.\r\n -->\r\n\r\n<!--\r\nThank you for contributing! Please make sure that your code changes\r\nare covered with tests. And in case of new features or big changes\r\nremember to adjust the documentation.\r\n\r\nFeel free to ping committers for the review!\r\n\r\nIn case of an existing issue, reference it using one of the following:\r\n\r\ncloses: #ISSUE\r\nrelated: #ISSUE\r\n\r\nHow to write a good git commit message:\r\nhttp://chris.beams.io/posts/git-commit/\r\n-->\r\n\r\n\r\n\r\n<!-- Please keep an empty line above the dashes. -->\r\n---\r\n**^ Add meaningful description above**\r\n\r\nRead the **[Pull Request Guidelines](https://github.com/apache/airflow/blob/main/CONTRIBUTING.rst#pull-request-guidelines)** for more information.\r\nIn case of fundamental code changes, an Airflow Improvement Proposal ([AIP](https://cwiki.apache.org/confluence/display/AIRFLOW/Airflow+Improvement+Proposals)) is needed.\r\nIn case of a new dependency, check compliance with the [ASF 3rd Party License Policy](https://www.apache.org/legal/resolved.html#category-x).\r\nIn case of backwards incompatible changes please leave a note in a newsfragment file, named `{pr_number}.significant.rst` or `{issue_number}.significant.rst`, in [newsfragments](https://github.com/apache/airflow/tree/main/newsfragments).\r\n\n", "before_files": [{"content": "# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements.  See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership.  The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); you may not use this file except in compliance\n# with the License.  You may obtain a copy of the License at\n#\n#   http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing,\n# software distributed under the License is distributed on an\n# \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n# KIND, either express or implied.  See the License for the\n# specific language governing permissions and limitations\n# under the License.\nfrom __future__ import annotations\n\nimport datetime\nfrom typing import Any\n\nfrom dateutil.relativedelta import relativedelta\nfrom pendulum import DateTime\nfrom pendulum.tz.timezone import Timezone\n\nfrom airflow.timetables._cron import CronMixin\nfrom airflow.timetables.base import DagRunInfo, DataInterval, TimeRestriction, Timetable\n\n\nclass CronTriggerTimetable(CronMixin, Timetable):\n    \"\"\"Timetable that triggers DAG runs according to a cron expression.\n\n    This is different from ``CronDataIntervalTimetable``, where the cron\n    expression specifies the *data interval* of a DAG run. With this timetable,\n    the data intervals are specified independently from the cron expression.\n    Also for the same reason, this timetable kicks off a DAG run immediately at\n    the start of the period (similar to POSIX cron), instead of needing to wait\n    for one data interval to pass.\n\n    Don't pass ``@once`` in here; use ``OnceTimetable`` instead.\n    \"\"\"\n\n    def __init__(\n        self,\n        cron: str,\n        *,\n        timezone: str | Timezone,\n        interval: datetime.timedelta | relativedelta = datetime.timedelta(),\n    ) -> None:\n        super().__init__(cron, timezone)\n        self._interval = interval\n\n    @classmethod\n    def deserialize(cls, data: dict[str, Any]) -> Timetable:\n        from airflow.serialization.serialized_objects import decode_relativedelta, decode_timezone\n\n        interval: datetime.timedelta | relativedelta\n        if isinstance(data[\"interval\"], dict):\n            interval = decode_relativedelta(data[\"interval\"])\n        else:\n            interval = datetime.timedelta(seconds=data[\"interval\"])\n        return cls(data[\"expression\"], timezone=decode_timezone(data[\"timezone\"]), interval=interval)\n\n    def serialize(self) -> dict[str, Any]:\n        from airflow.serialization.serialized_objects import encode_relativedelta, encode_timezone\n\n        interval: float | dict[str, Any]\n        if isinstance(self._interval, datetime.timedelta):\n            interval = self._interval.total_seconds()\n        else:\n            interval = encode_relativedelta(self._interval)\n        timezone = encode_timezone(self._timezone)\n        return {\"expression\": self._expression, \"timezone\": timezone, \"interval\": interval}\n\n    def infer_manual_data_interval(self, *, run_after: DateTime) -> DataInterval:\n        return DataInterval(run_after - self._interval, run_after)\n\n    def next_dagrun_info(\n        self,\n        *,\n        last_automated_data_interval: DataInterval | None,\n        restriction: TimeRestriction,\n    ) -> DagRunInfo | None:\n        if restriction.catchup:\n            if last_automated_data_interval is not None:\n                next_start_time = self._get_next(last_automated_data_interval.end)\n            elif restriction.earliest is None:\n                return None  # Don't know where to catch up from, give up.\n            else:\n                next_start_time = self._align_to_next(restriction.earliest)\n        else:\n            start_time_candidates = [self._align_to_next(DateTime.utcnow())]\n            if last_automated_data_interval is not None:\n                start_time_candidates.append(self._get_next(last_automated_data_interval.end))\n            if restriction.earliest is not None:\n                start_time_candidates.append(self._align_to_next(restriction.earliest))\n            next_start_time = max(start_time_candidates)\n        if restriction.latest is not None and restriction.latest < next_start_time:\n            return None\n        return DagRunInfo.interval(next_start_time - self._interval, next_start_time)\n", "path": "airflow/timetables/trigger.py"}], "after_files": [{"content": "# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements.  See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership.  The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); you may not use this file except in compliance\n# with the License.  You may obtain a copy of the License at\n#\n#   http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing,\n# software distributed under the License is distributed on an\n# \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n# KIND, either express or implied.  See the License for the\n# specific language governing permissions and limitations\n# under the License.\nfrom __future__ import annotations\n\nimport datetime\nfrom typing import Any\n\nfrom dateutil.relativedelta import relativedelta\nfrom pendulum import DateTime\nfrom pendulum.tz.timezone import Timezone\n\nfrom airflow.timetables._cron import CronMixin\nfrom airflow.timetables.base import DagRunInfo, DataInterval, TimeRestriction, Timetable\n\n\nclass CronTriggerTimetable(CronMixin, Timetable):\n    \"\"\"Timetable that triggers DAG runs according to a cron expression.\n\n    This is different from ``CronDataIntervalTimetable``, where the cron\n    expression specifies the *data interval* of a DAG run. With this timetable,\n    the data intervals are specified independently from the cron expression.\n    Also for the same reason, this timetable kicks off a DAG run immediately at\n    the start of the period (similar to POSIX cron), instead of needing to wait\n    for one data interval to pass.\n\n    Don't pass ``@once`` in here; use ``OnceTimetable`` instead.\n    \"\"\"\n\n    def __init__(\n        self,\n        cron: str,\n        *,\n        timezone: str | Timezone,\n        interval: datetime.timedelta | relativedelta = datetime.timedelta(),\n    ) -> None:\n        super().__init__(cron, timezone)\n        self._interval = interval\n\n    @classmethod\n    def deserialize(cls, data: dict[str, Any]) -> Timetable:\n        from airflow.serialization.serialized_objects import decode_relativedelta, decode_timezone\n\n        interval: datetime.timedelta | relativedelta\n        if isinstance(data[\"interval\"], dict):\n            interval = decode_relativedelta(data[\"interval\"])\n        else:\n            interval = datetime.timedelta(seconds=data[\"interval\"])\n        return cls(data[\"expression\"], timezone=decode_timezone(data[\"timezone\"]), interval=interval)\n\n    def serialize(self) -> dict[str, Any]:\n        from airflow.serialization.serialized_objects import encode_relativedelta, encode_timezone\n\n        interval: float | dict[str, Any]\n        if isinstance(self._interval, datetime.timedelta):\n            interval = self._interval.total_seconds()\n        else:\n            interval = encode_relativedelta(self._interval)\n        timezone = encode_timezone(self._timezone)\n        return {\"expression\": self._expression, \"timezone\": timezone, \"interval\": interval}\n\n    def infer_manual_data_interval(self, *, run_after: DateTime) -> DataInterval:\n        return DataInterval(run_after - self._interval, run_after)\n\n    def next_dagrun_info(\n        self,\n        *,\n        last_automated_data_interval: DataInterval | None,\n        restriction: TimeRestriction,\n    ) -> DagRunInfo | None:\n        if restriction.catchup:\n            if last_automated_data_interval is not None:\n                next_start_time = self._get_next(last_automated_data_interval.end)\n            elif restriction.earliest is None:\n                return None  # Don't know where to catch up from, give up.\n            else:\n                next_start_time = self._align_to_next(restriction.earliest)\n        else:\n            start_time_candidates = [self._align_to_prev(DateTime.utcnow())]\n            if last_automated_data_interval is not None:\n                start_time_candidates.append(self._get_next(last_automated_data_interval.end))\n            if restriction.earliest is not None:\n                start_time_candidates.append(self._align_to_next(restriction.earliest))\n            next_start_time = max(start_time_candidates)\n        if restriction.latest is not None and restriction.latest < next_start_time:\n            return None\n        return DagRunInfo.interval(next_start_time - self._interval, next_start_time)\n", "path": "airflow/timetables/trigger.py"}]}