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Title
# ask-ai
t

Thomas Rolfsnes

03/06/2024, 9:34 AM
Can you give me a code example for multi_asset_sensor?
s

Scout

03/06/2024, 9:34 AM
Certainly! Here's an example of a
multi_asset_sensor
from the documentation:
Copy code
python from dagster import asset, multi_asset_sensor, RunRequest, AssetKey, define_asset_job  @asset def foo():     return 1  @asset def bar():     return 2  @asset def baz():     return 3  asset_job = define_asset_job("asset_job", [baz])  @multi_asset_sensor(monitored_assets=[foo.key, bar.key], job=asset_job) def my_sensor(context):     return RunRequest()
In this example,
foo
,
bar
, and
baz
are defined as assets. An asset job named
asset_job
is defined to materialize the
baz
asset. The
multi_asset_sensor
named
my_sensor
is set up to monitor the assets
foo
and
bar
. When the sensor is evaluated, if there are new materializations for either
foo
or
bar
, it will trigger a
RunRequest
to execute the
asset_job
.
t

Thomas Rolfsnes

03/06/2024, 9:36 AM
@Scout I get the following error; TypeError: sensor_connect_intraday() missing 1 required positional argument: ‘asset_event’
s

Scout

03/06/2024, 9:36 AM
The error message you're seeing indicates that the sensor function you've defined is missing a required positional argument named
asset_event
. When using
multi_asset_sensor
, the decorated function is expected to take an additional parameter that represents the event corresponding to the asset materialization. Here's an updated example that includes the
asset_event
parameter:
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python from dagster import asset, multi_asset_sensor, RunRequest, AssetKey, define_asset_job, EventRecordsFilter, DagsterEventType  @asset def foo():     return 1  @asset def bar():     return 2  @asset def baz():     return 3  asset_job = define_asset_job("asset_job", [baz])  @multi_asset_sensor(monitored_assets=[foo.key, bar.key], job=asset_job) def my_sensor(context, asset_event):     # You can use asset_event to access details about the materialization event     # For example, you can filter for specific event types like materialization     if asset_event.dagster_event.event_type == DagsterEventType.ASSET_MATERIALIZATION:         # Logic to determine if a RunRequest should be created based on the asset_event         return RunRequest(run_key="some_run_key", run_config={})     # Optionally, you can return SkipReason or nothing if no action is needed
In this updated example, the
my_sensor
function now takes an
asset_event
parameter, which is provided by the Dagster framework when the sensor is evaluated. This
asset_event
contains information about the asset materialization event that triggered the sensor. You can use this information to decide whether to create a
RunRequest
or take some other action. Make sure that your actual sensor function includes the
asset_event
parameter and uses it appropriately within the function body. If you continue to encounter issues, please ensure that your Dagster version supports
multi_asset_sensor
as expected and that you are following the latest documentation for your version.
t

Thomas Rolfsnes

03/06/2024, 9:46 AM
@Scout I am on the latest version, 1.6.8, and asset_event has been added as a parameter, but the error persists
s

Scout

03/06/2024, 9:46 AM
In Dagster version 1.6.8, if you're still encountering the
TypeError
after adding the
asset_event
parameter to your
multi_asset_sensor
function, it's possible that there may be a mismatch between the function signature and how Dagster is invoking the sensor. The
multi_asset_sensor
should be defined with two parameters:
context
and
asset_events
. Note that
asset_events
is plural, which means it expects a list of asset events, not a single event. This is because a multi-asset sensor can monitor multiple assets, and there may be multiple asset events to consider when the sensor is evaluated. Here's an example of how you might define a
multi_asset_sensor
with the correct signature:
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python from dagster import asset, multi_asset_sensor, RunRequest, AssetKey, define_asset_job  @asset def foo():     return 1  @asset def bar():     return 2  @asset def baz():     return 3  asset_job = define_asset_job("asset_job", [baz])  @multi_asset_sensor(monitored_assets=[foo.key, bar.key], job=asset_job) def my_sensor(context, asset_events):     # asset_events is a list of events, one for each monitored asset     for asset_event in asset_events:         # Perform some logic with each asset_event         if asset_event:             # If the logic determines a run should be requested, return a RunRequest             return RunRequest(run_key="some_run_key", run_config={})     # If no run is needed, you can return None or a SkipReason
In this example,
asset_events
is an iterable of events, one for each asset that the sensor is monitoring. The sensor function iterates over these events and decides whether to issue a
RunRequest
. If you've updated your sensor to use the correct signature and are still encountering issues, it may be helpful to check the following: 1. Ensure that the
multi_asset_sensor
decorator is correctly configured with the
monitored_assets
and
job
parameters. 2. Verify that the assets you are monitoring (
foo
and
bar
in the example) are correctly defined and materialized. 3. Check for any typos or errors in the sensor function definition. 4. Review the Dagster release notes or documentation for any changes or updates to the
multi_asset_sensor
API that may affect your code. If the problem persists after these checks, it may be beneficial to reach out to the Dagster community or support channels with specific details about your implementation for further assistance.
t

Thomas Rolfsnes

03/06/2024, 10:39 AM
@Scout how can I check that all assets have new materializations in multi_asset_sensor?
s

Scout

03/06/2024, 10:39 AM
To check that all assets have new materializations in a
multi_asset_sensor
, you can use the
asset_events
parameter provided to the sensor function. This parameter is a dictionary where each key is an
AssetKey
and each value is the latest materialization event for that asset, or
None
if there has been no materialization. Here's an example of how you can check that all monitored assets have new materializations:
Copy code
python from dagster import asset, multi_asset_sensor, RunRequest, AssetKey, define_asset_job  @asset def foo():     return 1  @asset def bar():     return 2  @asset def baz():     return 3  asset_job = define_asset_job("asset_job", [baz])  @multi_asset_sensor(monitored_assets=[foo.key, bar.key], job=asset_job) def my_sensor(context, asset_events):     # Check if all assets have new materializations     if all(event is not None for event in asset_events.values()):         # All assets have new materializations, so we can trigger a run         return RunRequest(run_key="some_run_key", run_config={})     # If not all assets have new materializations, you can return None or a SkipReason
In this example, the
my_sensor
function checks if all values in the
asset_events
dictionary are not
None
, which would indicate that each monitored asset has a new materialization. If this is the case, the sensor triggers a
RunRequest
to run the
asset_job
. If any of the assets do not have a new materialization (i.e., the corresponding value in
asset_events
is
None
), the sensor does not trigger a run. You can also return a
SkipReason
if you want to provide a message explaining why the sensor did not trigger a run. Remember to ensure that your assets are being materialized as expected and that the
multi_asset_sensor
is correctly configured to monitor the relevant assets.
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