import functools
import logging
from contextlib import ExitStack
from datetime import datetime
from typing import (
TYPE_CHECKING,
Any,
Callable,
Iterator,
Mapping,
NamedTuple,
Optional,
Sequence,
Set,
Union,
cast,
overload,
)
import pendulum
from typing_extensions import TypeAlias
import dagster._check as check
from dagster._annotations import deprecated_param, public
from dagster._core.definitions.instigation_logger import InstigationLogger
from dagster._core.definitions.resource_annotation import get_resource_args
from dagster._core.definitions.scoped_resources_builder import (
Resources,
ScopedResourcesBuilder,
)
from dagster._core.errors import (
DagsterInvalidDefinitionError,
DagsterInvariantViolationError,
RunStatusSensorExecutionError,
user_code_error_boundary,
)
from dagster._core.event_api import (
RunStatusChangeEventType,
RunStatusChangeRecordsFilter,
)
from dagster._core.events import (
PIPELINE_RUN_STATUS_TO_EVENT_TYPE,
DagsterEvent,
DagsterEventType,
)
from dagster._core.instance import DagsterInstance
from dagster._core.storage.dagster_run import DagsterRun, DagsterRunStatus, RunsFilter
from dagster._serdes import (
serialize_value,
whitelist_for_serdes,
)
from dagster._serdes.errors import DeserializationError
from dagster._serdes.serdes import deserialize_value
from dagster._seven import JSONDecodeError
from dagster._utils import utc_datetime_from_timestamp
from dagster._utils.error import serializable_error_info_from_exc_info
from dagster._utils.warnings import normalize_renamed_param
from .graph_definition import GraphDefinition
from .job_definition import JobDefinition
from .sensor_definition import (
DagsterRunReaction,
DefaultSensorStatus,
RawSensorEvaluationFunctionReturn,
RunRequest,
SensorDefinition,
SensorEvaluationContext,
SensorResult,
SensorType,
SkipReason,
get_context_param_name,
get_or_create_sensor_context,
validate_and_get_resource_dict,
)
from .target import ExecutableDefinition
from .unresolved_asset_job_definition import UnresolvedAssetJobDefinition
if TYPE_CHECKING:
from dagster._core.definitions.resource_definition import ResourceDefinition
from dagster._core.definitions.selector import (
CodeLocationSelector,
JobSelector,
RepositorySelector,
)
RunStatusSensorEvaluationFunction: TypeAlias = Union[
Callable[..., RawSensorEvaluationFunctionReturn],
Callable[..., RawSensorEvaluationFunctionReturn],
]
RunFailureSensorEvaluationFn: TypeAlias = Union[
Callable[..., RawSensorEvaluationFunctionReturn],
Callable[..., RawSensorEvaluationFunctionReturn],
]
@whitelist_for_serdes(old_storage_names={"PipelineSensorCursor"})
class RunStatusSensorCursor(
NamedTuple(
"_RunStatusSensorCursor",
[
("record_id", int),
# deprecated arg, used as a record cursor for the run-sharded sqlite implementation to
# filter records based on the update timestamp of the run. When populated, the record
# id is ignored (since it maybe run-scoped).
("update_timestamp", Optional[str]),
# debug arg, used to quickly inspect the last processed timestamp from the run status
# sensor's serialized state
("record_timestamp", Optional[str]),
],
)
):
def __new__(cls, record_id, update_timestamp=None, record_timestamp=None):
return super(RunStatusSensorCursor, cls).__new__(
cls,
record_id=check.int_param(record_id, "record_id"),
update_timestamp=check.opt_str_param(update_timestamp, "update_timestamp"),
record_timestamp=check.opt_str_param(record_timestamp, "record_timestamp"),
)
@staticmethod
def is_valid(json_str: str) -> bool:
try:
obj = deserialize_value(json_str, RunStatusSensorCursor)
return isinstance(obj, RunStatusSensorCursor)
except (JSONDecodeError, DeserializationError):
return False
def to_json(self) -> str:
return serialize_value(cast(NamedTuple, self))
@staticmethod
def from_json(json_str: str) -> "RunStatusSensorCursor":
return deserialize_value(json_str, RunStatusSensorCursor)
[docs]class RunStatusSensorContext:
"""The ``context`` object available to a decorated function of ``run_status_sensor``."""
def __init__(
self,
sensor_name,
dagster_run,
dagster_event,
instance,
context: Optional[
SensorEvaluationContext
] = None, # deprecated arg, but we need to keep it for backcompat
resource_defs: Optional[Mapping[str, "ResourceDefinition"]] = None,
logger: Optional[logging.Logger] = None,
partition_key: Optional[str] = None,
_resources: Optional[Resources] = None,
_cm_scope_entered: bool = False,
) -> None:
self._exit_stack = ExitStack()
self._sensor_name = check.str_param(sensor_name, "sensor_name")
self._dagster_run = check.inst_param(dagster_run, "dagster_run", DagsterRun)
self._dagster_event = check.inst_param(dagster_event, "dagster_event", DagsterEvent)
self._instance = check.inst_param(instance, "instance", DagsterInstance)
self._logger: Optional[logging.Logger] = logger or (context.log if context else None)
self._partition_key = check.opt_str_param(partition_key, "partition_key")
# Wait to set resources unless they're accessed
self._resource_defs = resource_defs
self._resources = _resources
self._cm_scope_entered = _cm_scope_entered
def for_run_failure(self) -> "RunFailureSensorContext":
"""Converts RunStatusSensorContext to RunFailureSensorContext."""
return RunFailureSensorContext(
sensor_name=self._sensor_name,
dagster_run=self._dagster_run,
dagster_event=self._dagster_event,
instance=self._instance,
logger=self._logger,
partition_key=self._partition_key,
resource_defs=self._resource_defs,
_resources=self._resources,
_cm_scope_entered=self._cm_scope_entered,
)
@property
def resource_defs(self) -> Optional[Mapping[str, "ResourceDefinition"]]:
return self._resource_defs
@property
def resources(self) -> Resources:
from dagster._core.definitions.scoped_resources_builder import (
IContainsGenerator,
)
from dagster._core.execution.build_resources import build_resources
if not self._resources:
"""
This is similar to what we do in e.g. the op context - we set up a resource
building context manager, and immediately enter it. This is so that in cases
where a user is not using any context-manager based resources, they don't
need to enter this SensorEvaluationContext themselves.
For example:
my_sensor(build_sensor_context(resources={"my_resource": my_non_cm_resource})
will work ok, but for a CM resource we must do
with build_sensor_context(resources={"my_resource": my_cm_resource}) as context:
my_sensor(context)
"""
instance = self.instance if self._instance else None
resources_cm = build_resources(resources=self._resource_defs or {}, instance=instance)
self._resources = self._exit_stack.enter_context(resources_cm)
if isinstance(self._resources, IContainsGenerator) and not self._cm_scope_entered:
self._exit_stack.close()
raise DagsterInvariantViolationError(
"At least one provided resource is a generator, but attempting to access"
" resources outside of context manager scope. You can use the following syntax"
" to open a context manager: `with build_schedule_context(...) as context:`"
)
return self._resources
@public
@property
def sensor_name(self) -> str:
"""The name of the sensor."""
return self._sensor_name
@public
@property
def dagster_run(self) -> DagsterRun:
"""The run of the job."""
return self._dagster_run
@public
@property
def dagster_event(self) -> DagsterEvent:
"""The event associated with the job run status."""
return self._dagster_event
@public
@property
def instance(self) -> DagsterInstance:
"""The current instance."""
return self._instance
@public
@property
def log(self) -> logging.Logger:
"""The logger for the current sensor evaluation."""
if not self._logger:
self._logger = InstigationLogger()
return self._logger
@public
@property
def partition_key(self) -> Optional[str]:
"""Optional[str]: The partition key of the relevant run."""
return self._partition_key
def __enter__(self) -> "RunStatusSensorContext":
self._cm_scope_entered = True
return self
def __exit__(self, *exc) -> None:
self._exit_stack.close()
self._logger = None
def merge_resources(self, resources_dict: Mapping[str, Any]) -> "RunStatusSensorContext":
"""Merge the specified resources into this context.
This method is intended to be used by the Dagster framework, and should not be called by user code.
Args:
resources_dict (Mapping[str, Any]): The resources to replace in the context.
"""
check.invariant(
self._resources is None,
"Cannot merge resources in context that has been initialized.",
)
from dagster._core.execution.build_resources import wrap_resources_for_execution
return RunStatusSensorContext(
sensor_name=self._sensor_name,
dagster_run=self._dagster_run,
dagster_event=self._dagster_event,
instance=self._instance,
logger=self._logger,
partition_key=self._partition_key,
resource_defs={
**(self._resource_defs or {}),
**wrap_resources_for_execution(resources_dict),
},
)
[docs]class RunFailureSensorContext(RunStatusSensorContext):
"""The ``context`` object available to a decorated function of ``run_failure_sensor``.
Attributes:
sensor_name (str): the name of the sensor.
dagster_run (DagsterRun): the failed run.
"""
@public
@property
def failure_event(self) -> DagsterEvent:
"""The run failure event.
If the run failed because of an error inside a step, get_step_failure_events will have more
details on the step failure.
"""
return self.dagster_event
[docs] @public
def get_step_failure_events(self) -> Sequence[DagsterEvent]:
"""The step failure event for each step in the run that failed.
Examples:
.. code-block:: python
error_strings_by_step_key = {
# includes the stack trace
event.step_key: event.event_specific_data.error.to_string()
for event in context.get_step_failure_events()
}
"""
records = self.instance.get_records_for_run(
run_id=self.dagster_run.run_id, of_type=DagsterEventType.STEP_FAILURE
).records
return [cast(DagsterEvent, record.event_log_entry.dagster_event) for record in records]
[docs]def build_run_status_sensor_context(
sensor_name: str,
dagster_event: DagsterEvent,
dagster_instance: DagsterInstance,
dagster_run: DagsterRun,
context: Optional[SensorEvaluationContext] = None,
resources: Optional[Mapping[str, object]] = None,
partition_key: Optional[str] = None,
) -> RunStatusSensorContext:
"""Builds run status sensor context from provided parameters.
This function can be used to provide the context argument when directly invoking a function
decorated with `@run_status_sensor` or `@run_failure_sensor`, such as when writing unit tests.
Args:
sensor_name (str): The name of the sensor the context is being constructed for.
dagster_event (DagsterEvent): A DagsterEvent with the same event type as the one that
triggers the run_status_sensor
dagster_instance (DagsterInstance): The dagster instance configured for the context.
dagster_run (DagsterRun): DagsterRun object from running a job
resources (Optional[Mapping[str, object]]): A dictionary of resources to be made available
to the sensor.
Examples:
.. code-block:: python
instance = DagsterInstance.ephemeral()
result = my_job.execute_in_process(instance=instance)
dagster_run = result.dagster_run
dagster_event = result.get_job_success_event() # or get_job_failure_event()
context = build_run_status_sensor_context(
sensor_name="run_status_sensor_to_invoke",
dagster_instance=instance,
dagster_run=dagster_run,
dagster_event=dagster_event,
)
run_status_sensor_to_invoke(context)
"""
from dagster._core.execution.build_resources import wrap_resources_for_execution
return RunStatusSensorContext(
sensor_name=sensor_name,
instance=dagster_instance,
dagster_run=dagster_run,
dagster_event=dagster_event,
resource_defs=wrap_resources_for_execution(resources),
logger=context.log if context else None,
partition_key=partition_key,
)
@overload
def run_failure_sensor(
name: RunFailureSensorEvaluationFn,
) -> SensorDefinition: ...
@overload
def run_failure_sensor(
name: Optional[str] = None,
minimum_interval_seconds: Optional[int] = None,
description: Optional[str] = None,
monitored_jobs: Optional[
Sequence[
Union[
JobDefinition,
GraphDefinition,
UnresolvedAssetJobDefinition,
"RepositorySelector",
"JobSelector",
"CodeLocationSelector",
]
]
] = None,
job_selection: Optional[
Sequence[
Union[
JobDefinition,
GraphDefinition,
UnresolvedAssetJobDefinition,
"RepositorySelector",
"JobSelector",
"CodeLocationSelector",
]
]
] = None,
monitor_all_code_locations: bool = False,
default_status: DefaultSensorStatus = DefaultSensorStatus.STOPPED,
request_job: Optional[ExecutableDefinition] = None,
request_jobs: Optional[Sequence[ExecutableDefinition]] = None,
monitor_all_repositories: bool = False,
) -> Callable[
[RunFailureSensorEvaluationFn],
SensorDefinition,
]: ...
[docs]@deprecated_param(
param="job_selection",
breaking_version="2.0",
additional_warn_text="Use `monitored_jobs` instead.",
)
@deprecated_param(
param="monitor_all_repositories",
breaking_version="2.0",
additional_warn_text="Use `monitor_all_code_locations` instead.",
)
def run_failure_sensor(
name: Optional[Union[RunFailureSensorEvaluationFn, str]] = None,
minimum_interval_seconds: Optional[int] = None,
description: Optional[str] = None,
monitored_jobs: Optional[
Sequence[
Union[
JobDefinition,
GraphDefinition,
UnresolvedAssetJobDefinition,
"RepositorySelector",
"JobSelector",
"CodeLocationSelector",
]
]
] = None,
job_selection: Optional[
Sequence[
Union[
JobDefinition,
GraphDefinition,
UnresolvedAssetJobDefinition,
"RepositorySelector",
"JobSelector",
"CodeLocationSelector",
]
]
] = None,
monitor_all_code_locations: Optional[bool] = None,
default_status: DefaultSensorStatus = DefaultSensorStatus.STOPPED,
request_job: Optional[ExecutableDefinition] = None,
request_jobs: Optional[Sequence[ExecutableDefinition]] = None,
monitor_all_repositories: Optional[bool] = None,
) -> Union[
SensorDefinition,
Callable[
[RunFailureSensorEvaluationFn],
SensorDefinition,
],
]:
"""Creates a sensor that reacts to job failure events, where the decorated function will be
run when a run fails.
Takes a :py:class:`~dagster.RunFailureSensorContext`.
Args:
name (Optional[str]): The name of the job failure sensor. Defaults to the name of the
decorated function.
minimum_interval_seconds (Optional[int]): The minimum number of seconds that will elapse
between sensor evaluations.
description (Optional[str]): A human-readable description of the sensor.
monitored_jobs (Optional[List[Union[JobDefinition, GraphDefinition, UnresolvedAssetJobDefinition, RepositorySelector, JobSelector, CodeLocationSelector]]]):
The jobs in the current repository that will be monitored by this failure sensor.
Defaults to None, which means the alert will be sent when any job in the current
repository fails.
monitor_all_code_locations (bool): If set to True, the sensor will monitor all runs in the
Dagster instance. If set to True, an error will be raised if you also specify
monitored_jobs or job_selection. Defaults to False.
job_selection (Optional[List[Union[JobDefinition, GraphDefinition, RepositorySelector, JobSelector, CodeLocationSelector]]]):
(deprecated in favor of monitored_jobs) The jobs in the current repository that will be
monitored by this failure sensor. Defaults to None, which means the alert will be sent
when any job in the repository fails.
default_status (DefaultSensorStatus): Whether the sensor starts as running or not. The default
status can be overridden from the Dagster UI or via the GraphQL API.
request_job (Optional[Union[GraphDefinition, JobDefinition, UnresolvedAssetJob]]): The job a RunRequest should
execute if yielded from the sensor.
request_jobs (Optional[Sequence[Union[GraphDefinition, JobDefinition, UnresolvedAssetJob]]]): (experimental)
A list of jobs to be executed if RunRequests are yielded from the sensor.
monitor_all_repositories (bool): (deprecated in favor of monitor_all_code_locations) If set to True,
the sensor will monitor all runs in the Dagster instance. If set to True, an error will be raised if you also specify
monitored_jobs or job_selection. Defaults to False.
"""
def inner(
fn: RunFailureSensorEvaluationFn,
) -> SensorDefinition:
check.callable_param(fn, "fn")
if name is None or callable(name):
sensor_name = fn.__name__
else:
sensor_name = name
jobs = monitored_jobs if monitored_jobs else job_selection
monitor_all = normalize_renamed_param(
monitor_all_code_locations,
"monitor_all_code_locations",
monitor_all_repositories,
"monitor_all_repositories",
)
@run_status_sensor(
run_status=DagsterRunStatus.FAILURE,
name=sensor_name,
minimum_interval_seconds=minimum_interval_seconds,
description=description,
monitored_jobs=jobs,
monitor_all_code_locations=monitor_all,
default_status=default_status,
request_job=request_job,
request_jobs=request_jobs,
)
@functools.wraps(fn)
def _run_failure_sensor(*args, **kwargs) -> Any:
args_modified = [
arg.for_run_failure() if isinstance(arg, RunStatusSensorContext) else arg
for arg in args
]
kwargs_modified = {
k: v.for_run_failure() if isinstance(v, RunStatusSensorContext) else v
for k, v in kwargs.items()
}
return fn(*args_modified, **kwargs_modified)
return _run_failure_sensor
# This case is for when decorator is used bare, without arguments
if callable(name):
return inner(name)
return inner
[docs]class RunStatusSensorDefinition(SensorDefinition):
"""Define a sensor that reacts to a given status of job execution, where the decorated
function will be evaluated when a run is at the given status.
Args:
name (str): The name of the sensor. Defaults to the name of the decorated function.
run_status (DagsterRunStatus): The status of a run which will be
monitored by the sensor.
run_status_sensor_fn (Callable[[RunStatusSensorContext], Union[SkipReason, DagsterRunReaction]]): The core
evaluation function for the sensor. Takes a :py:class:`~dagster.RunStatusSensorContext`.
minimum_interval_seconds (Optional[int]): The minimum number of seconds that will elapse
between sensor evaluations.
description (Optional[str]): A human-readable description of the sensor.
monitored_jobs (Optional[List[Union[JobDefinition, GraphDefinition, UnresolvedAssetJobDefinition, JobSelector, RepositorySelector, CodeLocationSelector]]]):
The jobs in the current repository that will be monitored by this sensor. Defaults to
None, which means the alert will be sent when any job in the repository fails.
monitor_all_code_locations (bool): If set to True, the sensor will monitor all runs in the
Dagster instance. If set to True, an error will be raised if you also specify
monitored_jobs or job_selection. Defaults to False.
default_status (DefaultSensorStatus): Whether the sensor starts as running or not. The default
status can be overridden from the Dagster UI or via the GraphQL API.
request_job (Optional[Union[GraphDefinition, JobDefinition]]): The job a RunRequest should
execute if yielded from the sensor.
request_jobs (Optional[Sequence[Union[GraphDefinition, JobDefinition]]]): (experimental)
A list of jobs to be executed if RunRequests are yielded from the sensor.
"""
def __init__(
self,
name: str,
run_status: DagsterRunStatus,
run_status_sensor_fn: RunStatusSensorEvaluationFunction,
minimum_interval_seconds: Optional[int] = None,
description: Optional[str] = None,
monitored_jobs: Optional[
Sequence[
Union[
JobDefinition,
GraphDefinition,
UnresolvedAssetJobDefinition,
"RepositorySelector",
"JobSelector",
"CodeLocationSelector",
]
]
] = None,
monitor_all_code_locations: Optional[bool] = None,
default_status: DefaultSensorStatus = DefaultSensorStatus.STOPPED,
request_job: Optional[ExecutableDefinition] = None,
request_jobs: Optional[Sequence[ExecutableDefinition]] = None,
required_resource_keys: Optional[Set[str]] = None,
):
from dagster._core.definitions.selector import (
CodeLocationSelector,
JobSelector,
RepositorySelector,
)
check.str_param(name, "name")
check.inst_param(run_status, "run_status", DagsterRunStatus)
check.callable_param(run_status_sensor_fn, "run_status_sensor_fn")
check.opt_int_param(minimum_interval_seconds, "minimum_interval_seconds")
check.opt_str_param(description, "description")
check.opt_list_param(
monitored_jobs,
"monitored_jobs",
(
JobDefinition,
GraphDefinition,
UnresolvedAssetJobDefinition,
RepositorySelector,
JobSelector,
CodeLocationSelector,
),
)
check.inst_param(default_status, "default_status", DefaultSensorStatus)
monitor_all_code_locations = check.opt_bool_param(
monitor_all_code_locations, "monitor_all_code_locations", default=False
)
resource_arg_names: Set[str] = {arg.name for arg in get_resource_args(run_status_sensor_fn)}
combined_required_resource_keys = (
check.opt_set_param(required_resource_keys, "required_resource_keys", of_type=str)
| resource_arg_names
)
# coerce CodeLocationSelectors to RepositorySelectors with repo name "__repository__"
monitored_jobs = [
job.to_repository_selector() if isinstance(job, CodeLocationSelector) else job
for job in (monitored_jobs or [])
]
self._run_status_sensor_fn = check.callable_param(
run_status_sensor_fn, "run_status_sensor_fn"
)
event_type = PIPELINE_RUN_STATUS_TO_EVENT_TYPE[run_status]
# split monitored_jobs into external repos, external jobs, and jobs in the current repo
other_repos = (
[x for x in monitored_jobs if isinstance(x, RepositorySelector)]
if monitored_jobs
else []
)
other_repo_jobs = (
[x for x in monitored_jobs if isinstance(x, JobSelector)] if monitored_jobs else []
)
current_repo_jobs = (
[x for x in monitored_jobs if not isinstance(x, (JobSelector, RepositorySelector))]
if monitored_jobs
else []
)
def _wrapped_fn(
context: SensorEvaluationContext,
) -> Iterator[Union[RunRequest, SkipReason, DagsterRunReaction, SensorResult]]:
# initiate the cursor to (most recent event id, current timestamp) when:
# * it's the first time starting the sensor
# * or, the cursor isn't in valid format (backcompt)
if context.cursor is None or not RunStatusSensorCursor.is_valid(context.cursor):
most_recent_event_records = context.instance.fetch_run_status_changes(
records_filter=event_type, limit=1
).records
most_recent_event_id = (
most_recent_event_records[0].storage_id
if len(most_recent_event_records) == 1
else -1
)
record_timestamp = (
utc_datetime_from_timestamp(most_recent_event_records[0].timestamp).isoformat()
if len(most_recent_event_records) == 1
else None
)
new_cursor = RunStatusSensorCursor(
record_id=most_recent_event_id, record_timestamp=record_timestamp
)
context.update_cursor(new_cursor.to_json())
yield SkipReason(f"Initiating {name}. Set cursor to {new_cursor}")
return
sensor_cursor = RunStatusSensorCursor.from_json(context.cursor)
# Fetch events after the cursor id
# * we move the cursor forward to the latest visited event's id to avoid revisits
# * when the daemon is down, bc we persist the cursor info, we can go back to where we
# left and backfill alerts for the qualified events (up to 5 at a time) during the downtime
if sensor_cursor.update_timestamp and context.instance.event_log_storage.is_run_sharded:
# The run status sensor cursor has the timestamp set... and the event log storage
# is run sharded. We need to query the index shard by timestamp instead of by
# record id (which is reindexed relative to some run sharded query). When we update
# the cursor, we should omit the timestamp, since this API only queries the global
# index shard instead of the run shard.
event_records = context.instance.fetch_run_status_changes(
records_filter=RunStatusChangeRecordsFilter(
event_type=cast(RunStatusChangeEventType, event_type),
after_timestamp=cast(
datetime, pendulum.parse(sensor_cursor.update_timestamp)
).timestamp(),
),
ascending=True,
limit=5,
).records
else:
# the cursor storage id is globally unique, either because the event log storage is
# not run sharded or because the cursor was set from an event returned from the
# index shard. When we update the cursor, we should omit the timestamp, since this
# API only queries the global index shard instead of the run shard.
event_records = context.instance.fetch_run_status_changes(
records_filter=RunStatusChangeRecordsFilter(
event_type=cast(RunStatusChangeEventType, event_type),
after_storage_id=sensor_cursor.record_id,
),
ascending=True,
limit=5,
).records
for event_record in event_records:
event_log_entry = event_record.event_log_entry
storage_id = event_record.storage_id
record_timestamp = utc_datetime_from_timestamp(event_record.timestamp).isoformat()
# get run info
run_records = context.instance.get_run_records(
filters=RunsFilter(run_ids=[event_log_entry.run_id])
)
# skip if we couldn't find the right run
if len(run_records) != 1:
context.update_cursor(
RunStatusSensorCursor(
record_id=storage_id, record_timestamp=record_timestamp
).to_json()
)
continue
dagster_run = run_records[0].dagster_run
job_match = False
# if monitor_all_repositories is provided, then we want to run the sensor for all jobs in all repositories
if monitor_all_code_locations:
job_match = True
code_location_name = (
context.code_location_origin.location_name
if context.code_location_origin
else None
)
# check if the run is in the current repository and (if provided) one of jobs specified in monitored_jobs
if (
not job_match
and
# the job has a repository (not manually executed)
dagster_run.external_job_origin
and
# the job belongs to the current code location
dagster_run.external_job_origin.repository_origin.code_location_origin.location_name
== code_location_name
and
# the job belongs to the current repository
dagster_run.external_job_origin.repository_origin.repository_name
== context.repository_name
):
if monitored_jobs:
if dagster_run.job_name in map(lambda x: x.name, current_repo_jobs):
job_match = True
else:
job_match = True
if not job_match:
# check if the run is one of the jobs specified by JobSelector or RepositorySelector (ie in another repo)
# make a JobSelector for the run in question
external_repository_origin = check.not_none(
dagster_run.external_job_origin
).repository_origin
run_job_selector = JobSelector(
location_name=external_repository_origin.code_location_origin.location_name,
repository_name=external_repository_origin.repository_name,
job_name=dagster_run.job_name,
)
if run_job_selector in other_repo_jobs:
job_match = True
# make a RepositorySelector for the run in question
run_repo_selector = RepositorySelector(
location_name=external_repository_origin.code_location_origin.location_name,
repository_name=external_repository_origin.repository_name,
)
if run_repo_selector in other_repos:
job_match = True
if not job_match:
# the run in question doesn't match any of the criteria for we advance the cursor and move on
context.update_cursor(
RunStatusSensorCursor(
record_id=storage_id, record_timestamp=record_timestamp
).to_json()
)
continue
serializable_error = None
resource_args_populated = validate_and_get_resource_dict(
context.resources, name, resource_arg_names
)
try:
with RunStatusSensorContext(
sensor_name=name,
dagster_run=dagster_run,
dagster_event=event_log_entry.dagster_event,
instance=context.instance,
resource_defs=context.resource_defs,
logger=context.log,
partition_key=dagster_run.tags.get("dagster/partition"),
) as sensor_context, user_code_error_boundary(
RunStatusSensorExecutionError,
lambda: f'Error occurred during the execution sensor "{name}".',
):
context_param_name = get_context_param_name(run_status_sensor_fn)
context_param = (
{context_param_name: sensor_context} if context_param_name else {}
)
sensor_return = run_status_sensor_fn(
**context_param,
**resource_args_populated,
)
if sensor_return is not None:
context.update_cursor(
RunStatusSensorCursor(
record_id=storage_id,
record_timestamp=record_timestamp,
).to_json()
)
if isinstance(sensor_return, SensorResult):
if sensor_return.cursor:
raise DagsterInvariantViolationError(
f"Error in run status sensor {name}: Sensor returned a"
" SensorResult with a cursor value. The cursor is managed"
" by the sensor and should not be modified by a user."
)
yield sensor_return
elif isinstance(
sensor_return,
(RunRequest, SkipReason, DagsterRunReaction),
):
yield sensor_return
else:
yield from sensor_return
return
except RunStatusSensorExecutionError as run_status_sensor_execution_error:
# When the user code errors, we report error to the sensor tick not the original run.
serializable_error = serializable_error_info_from_exc_info(
run_status_sensor_execution_error.original_exc_info
)
context.update_cursor(
RunStatusSensorCursor(
record_id=storage_id, record_timestamp=record_timestamp
).to_json()
)
# Yield DagsterRunReaction to indicate the execution success/failure.
# The sensor machinery would
# * report back to the original run if success
# * update cursor and job state
yield DagsterRunReaction(
dagster_run=dagster_run,
run_status=run_status,
error=serializable_error,
)
super(RunStatusSensorDefinition, self).__init__(
name=name,
evaluation_fn=_wrapped_fn,
minimum_interval_seconds=minimum_interval_seconds,
description=description,
default_status=default_status,
job=request_job,
jobs=request_jobs,
required_resource_keys=combined_required_resource_keys,
)
def __call__(self, *args, **kwargs) -> RawSensorEvaluationFunctionReturn:
context_param_name = get_context_param_name(self._run_status_sensor_fn)
context = get_or_create_sensor_context(
self._run_status_sensor_fn,
*args,
context_type=RunStatusSensorContext,
**kwargs,
)
context_param = {context_param_name: context} if context_param_name and context else {}
resources = validate_and_get_resource_dict(
context.resources if context else ScopedResourcesBuilder.build_empty(),
self._name,
self._required_resource_keys,
)
return self._run_status_sensor_fn(**context_param, **resources)
@property
def sensor_type(self) -> SensorType:
return SensorType.RUN_STATUS
[docs]@deprecated_param(
param="job_selection",
breaking_version="2.0",
additional_warn_text="Use `monitored_jobs` instead.",
)
@deprecated_param(
param="monitor_all_repositories",
breaking_version="2.0",
additional_warn_text="Use `monitor_all_code_locations` instead.",
)
def run_status_sensor(
run_status: DagsterRunStatus,
name: Optional[str] = None,
minimum_interval_seconds: Optional[int] = None,
description: Optional[str] = None,
monitored_jobs: Optional[
Sequence[
Union[
JobDefinition,
GraphDefinition,
UnresolvedAssetJobDefinition,
"RepositorySelector",
"JobSelector",
"CodeLocationSelector",
]
]
] = None,
job_selection: Optional[
Sequence[
Union[
JobDefinition,
GraphDefinition,
UnresolvedAssetJobDefinition,
"RepositorySelector",
"JobSelector",
"CodeLocationSelector",
]
]
] = None,
monitor_all_code_locations: Optional[bool] = None,
default_status: DefaultSensorStatus = DefaultSensorStatus.STOPPED,
request_job: Optional[ExecutableDefinition] = None,
request_jobs: Optional[Sequence[ExecutableDefinition]] = None,
monitor_all_repositories: Optional[bool] = None,
) -> Callable[
[RunStatusSensorEvaluationFunction],
RunStatusSensorDefinition,
]:
"""Creates a sensor that reacts to a given status of job execution, where the decorated
function will be run when a job is at the given status.
Takes a :py:class:`~dagster.RunStatusSensorContext`.
Args:
run_status (DagsterRunStatus): The status of run execution which will be
monitored by the sensor.
name (Optional[str]): The name of the sensor. Defaults to the name of the decorated function.
minimum_interval_seconds (Optional[int]): The minimum number of seconds that will elapse
between sensor evaluations.
description (Optional[str]): A human-readable description of the sensor.
monitored_jobs (Optional[List[Union[JobDefinition, GraphDefinition, UnresolvedAssetJobDefinition, RepositorySelector, JobSelector, CodeLocationSelector]]]):
Jobs in the current code locations that will be monitored by this sensor. Defaults to None, which means the alert will
be sent when any job in the code location matches the requested run_status. Jobs in external repositories can be monitored by using
RepositorySelector or JobSelector.
monitor_all_code_locations (Optional[bool]): If set to True, the sensor will monitor all runs in the Dagster instance.
If set to True, an error will be raised if you also specify monitored_jobs or job_selection.
Defaults to False.
job_selection (Optional[List[Union[JobDefinition, GraphDefinition, RepositorySelector, JobSelector, CodeLocationSelector]]]):
(deprecated in favor of monitored_jobs) Jobs in the current code location that will be
monitored by this sensor. Defaults to None, which means the alert will be sent when
any job in the code location matches the requested run_status.
default_status (DefaultSensorStatus): Whether the sensor starts as running or not. The default
status can be overridden from the Dagster UI or via the GraphQL API.
request_job (Optional[Union[GraphDefinition, JobDefinition, UnresolvedAssetJobDefinition]]): The job that should be
executed if a RunRequest is yielded from the sensor.
request_jobs (Optional[Sequence[Union[GraphDefinition, JobDefinition, UnresolvedAssetJobDefinition]]]): (experimental)
A list of jobs to be executed if RunRequests are yielded from the sensor.
monitor_all_repositories (Optional[bool]): (deprecated in favor of monitor_all_code_locations) If set to True, the sensor will monitor all runs in the Dagster instance.
If set to True, an error will be raised if you also specify monitored_jobs or job_selection.
Defaults to False.
"""
def inner(
fn: RunStatusSensorEvaluationFunction,
) -> RunStatusSensorDefinition:
check.callable_param(fn, "fn")
sensor_name = name or fn.__name__
jobs = monitored_jobs if monitored_jobs else job_selection
monitor_all = normalize_renamed_param(
monitor_all_code_locations,
"monitor_all_code_locations",
monitor_all_repositories,
"monitor_all_repositories",
)
if jobs and monitor_all:
DagsterInvalidDefinitionError(
f"Cannot specify both {'monitor_all_code_locations' if monitor_all_code_locations else 'monitor_all_repositories'} and"
f" {'monitored_jobs' if monitored_jobs else 'job_selection'}."
)
return RunStatusSensorDefinition(
name=sensor_name,
run_status=run_status,
run_status_sensor_fn=fn,
minimum_interval_seconds=minimum_interval_seconds,
description=description,
monitored_jobs=jobs,
monitor_all_code_locations=monitor_all,
default_status=default_status,
request_job=request_job,
request_jobs=request_jobs,
)
return inner