Can you give me a code example for multi_asset_sensor?

Certainly! Here's an example of a

multi_asset_sensor

from the documentation:

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

.

@Scout I get the following error; TypeError: sensor_connect_intraday() missing 1 required positional argument: ‘asset_event’

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:

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.

@Scout I am on the latest version, 1.6.8, and asset_event has been added as a parameter, but the error persists

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:

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.

@Scout how can I check that all assets have new materializations in multi_asset_sensor?

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:

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.