@Scout what is the best way to add

asset_check

for a

multi_asset

To add

asset_check

for a

multi_asset

, you can define checks within the

@multi_asset

decorator using the

check_specs

argument. Each

AssetCheckSpec

declares a check that the decorated function should yield an

AssetCheckResult

for. Here's an example from the documentation:

python
from dagster import multi_asset, AssetOut, AssetCheckSpec, AssetCheckResult

@multi_asset(
    outs={
        "my_string_asset": AssetOut(),
        "my_int_asset": AssetOut(),
    },
    check_specs=[
        AssetCheckSpec("my_check", asset="my_string_asset"),
    ]
)
def my_function():
    # Your logic to compute the assets goes here
    my_string = "abc"
    my_int = 123

    # Perform your checks here
    check_passed = my_string == "abc"  # Replace with your actual check logic

    # Yield the AssetCheckResult for the check
    yield AssetCheckResult(
        check_name="my_check",
        asset_key="my_string_asset",
        success=check_passed,
    )

    # Return the asset values
    return my_string, my_int

In this example,

my_function

is responsible for computing the contents of the assets and performing the checks. The

check_specs

argument is used to define the checks associated with the assets. The function yields an

AssetCheckResult

for each check, indicating whether the check passed or failed, and then returns the asset values. Remember that the

asset

parameter in

AssetCheckSpec

should match the key of the asset you want to associate the check with. If you have multiple checks, you can extend the

check_specs

list with additional

AssetCheckSpec

instances for each check you want to define. Keep in mind that the example provided is a basic illustration, and you should adapt the check logic to suit your specific use case. Asset Checks on DBT Assets button Thank you for your feedback!

@Scout and how do I add asset checks for assets that are already existing, but I cannot modify the code of the asset, for example, i have a Asset factory function that generates

@multi_asset

If you have an existing

@multi_asset

that was created by a factory function and you cannot modify the original code, you can still add asset checks by using the

@asset_check

decorator to define separate check functions that target the assets you want to check. Here's how you can do it: 1. Define an

@asset_check

for each asset you want to check. The

@asset_check

decorator allows you to specify the asset key that the check should be associated with. 2. Implement the check logic within the decorated function, and return an

AssetCheckResult

indicating the outcome of the check. Here's an example of how you might define separate asset checks for existing assets:

python
from dagster import asset_check, AssetCheckResult

# Assuming you have an existing asset with the key "existing_asset_key"
existing_asset_key = "existing_asset_key"

@asset_check(asset_key=existing_asset_key)
def my_asset_check(context, data):
    # Implement your check logic here
    check_passed = some_check_function(data)
    
    # Return the result of the check
    return AssetCheckResult(
        check_name="my_asset_check",
        asset_key=existing_asset_key,
        success=check_passed,
        metadata={"details": "Additional information about the check"}
    )

In this example,

some_check_function

represents the logic of your check, which you would replace with your actual validation code. The

data

parameter is the data of the asset being checked, and

context

provides access to Dagster's execution context. By using the

@asset_check

decorator, you can define checks for existing assets without modifying the original asset code. These checks will be run whenever the asset is materialized, and the results will be available in the asset catalog. Remember to replace

"existing_asset_key"

with the actual key of the asset you want to check, and implement the appropriate check logic for your use case. Forgetting asset checks on Definitions button Thank you for your feedback!

@Scout can I have multiple asset checks for the same asset? and if yes, Does it have to be individual function for each check ?

Yes, you can have multiple asset checks for the same asset. Each check can be defined as an individual function using the

@asset_check

decorator, and you can associate each of these functions with the same asset by specifying the asset's key. Here's an example of how you might define multiple checks for the same asset:

python
from dagster import asset_check, AssetCheckResult

# Assuming you have an existing asset with the key "existing_asset_key"
existing_asset_key = "existing_asset_key"

@asset_check(asset_key=existing_asset_key)
def check_one(context, data):
    # Implement the first check logic here
    check_passed = check_one_logic(data)
    return AssetCheckResult(
        check_name="check_one",
        asset_key=existing_asset_key,
        success=check_passed,
        metadata={"details": "Additional information about check one"}
    )

@asset_check(asset_key=existing_asset_key)
def check_two(context, data):
    # Implement the second check logic here
    check_passed = check_two_logic(data)
    return AssetCheckResult(
        check_name="check_two",
        asset_key=existing_asset_key,
        success=check_passed,
        metadata={"details": "Additional information about check two"}
    )

# ... and so on for additional checks

In this example,

check_one_logic

and

check_two_logic

represent the logic for two separate checks. Each function is decorated with

@asset_check

and specifies the same

asset_key

, indicating that they apply to the same asset. Each check function must return an

AssetCheckResult

object, which contains the outcome of the check and any relevant metadata. By defining multiple functions, you can create a suite of checks that will all be run against the specified asset, and the results of these checks will be tracked independently in the asset catalog. This allows you to modularize your check logic and maintain clear separation between different validation rules for the same asset. Enable checks to depend on secondary ass... button Thank you for your feedback!

@Scout Can I have only one function to make multiple checks for a single asset and return multiple check outcomes ?

As of my knowledge cutoff date in early 2023, you cannot directly return multiple

AssetCheckResult

objects from a single

@asset_check

function. The

@asset_check

decorator is designed to create a one-to-one mapping between a check function and an asset, meaning that each check function is intended to return a single

AssetCheckResult

for the asset it is associated with. However, there is a feature request in the Dagster GitHub issues that discusses the need for multiple asset checks that execute in a single operation, which suggests that this capability might be considered for future implementation. The tracking issue is [#18068](https://github.com/dagster-io/dagster/issues/18068). If you need to perform multiple checks within a single function, you would typically define these checks within an

@op

or

@multi_asset

and yield multiple

AssetCheckResult

objects, one for each check. Here's an example using `@multi_asset`:

python
from dagster import multi_asset, AssetOut, AssetCheckSpec, AssetCheckResult

@multi_asset(
    outs={"my_asset": AssetOut()},
    check_specs=[
        AssetCheckSpec("check_one", asset="my_asset"),
        AssetCheckSpec("check_two", asset="my_asset"),
    ]
)
def my_asset_computation():
    # Your logic to compute the asset goes here
    asset_data = compute_asset_data()

    # Perform your checks here
    check_one_passed = check_one_logic(asset_data)
    check_two_passed = check_two_logic(asset_data)

    # Yield the AssetCheckResult for each check
    yield AssetCheckResult(
        check_name="check_one",
        asset_key="my_asset",
        success=check_one_passed,
    )
    yield AssetCheckResult(
        check_name="check_two",
        asset_key="my_asset",
        success=check_two_passed,
    )

    # Return the asset value
    return asset_data

In this example,

check_one_logic

and

check_two_logic

are functions that contain the logic for two different checks. The

my_asset_computation

function yields an

AssetCheckResult

for each check. Please note that the ability to yield multiple

AssetCheckResult

objects from a single function is subject to the capabilities of the Dagster version you are using and any updates that may have occurred after my knowledge cutoff date. Always refer to the latest Dagster documentation or check the GitHub repository for the most current information and features. RFC: Asset checks button Multi-Assets | Dagster button Thank you for your feedback!

@Scout So within a

multi_asset

is it possible to return an

Output

as well as

AssetCheckResult

?

As of my knowledge cutoff date, within a

multi_asset

, you can yield both

Output

objects and

AssetCheckResult

objects. The

Output

objects correspond to the assets being materialized, while the

AssetCheckResult

objects correspond to checks performed on those assets. Here's an example of how you might use

multi_asset

to yield both

Output

and `AssetCheckResult`:

python
from dagster import multi_asset, AssetOut, Output, AssetCheckResult

@multi_asset(
    outs={
        "my_asset": AssetOut(),
        # Define other assets if needed
    },
    check_specs=[
        AssetCheckSpec("my_check", asset="my_asset"),
        # Define other checks if needed
    ]
)
def my_asset_computation():
    # Your logic to compute the asset goes here
    asset_data = compute_asset_data()

    # Yield the asset data as an Output
    yield Output(asset_data, "my_asset")

    # Perform your check here
    check_passed = perform_check(asset_data)

    # Yield the AssetCheckResult for the check
    yield AssetCheckResult(
        check_name="my_check",
        asset_key="my_asset",
        success=check_passed,
    )

    # If you have other assets and checks, you would continue to yield their corresponding Outputs and AssetCheckResults

In this example,

compute_asset_data

is a placeholder for the logic that computes the data for the asset, and

perform_check

is a placeholder for the logic that performs the check on the asset data. The function yields an

Output

for the asset and an

AssetCheckResult

for the check. Please note that the ability to yield multiple results, including

Output

and

AssetCheckResult

objects, from a

multi_asset

function is subject to the capabilities of the Dagster version you are using. Always refer to the latest Dagster documentation or check the GitHub repository for the most current information and features. add key_prefix to multi_asset button Graph-Backed Assets | Dagster button Thank you for your feedback!