# Rule checks


Setup: the imports every example on this page uses

``` python
import tempfile

import dagster as dg
import dataframely as dy
import duckdb
import polars as pl
from dagster_duckdb_polars import DuckDBPolarsIOManager

import dagster_dataframely as dd
from dagster_dataframely.data import ParquetIOManager
from dagster_dataframely.errors import ColumnSchemaError
```


`dd.build_rule_checks` reports a schema's rules as asset checks on an asset that `dd.asset` did not build. The asset can be a plain `@dg.asset`, an asset another integration builds, or a `dg.AssetSpec` for a table written outside Dagster. The checks read the table and write nothing. A row that fails a rule stays in the table, and its check fails.


# Declaring the checks

Pass the schema and the asset key to `dd.build_rule_checks`:


``` python
class EventsSchema(dy.Schema):
    event_id = dy.Int64(primary_key=True)
    amount = dy.Int64(nullable=False, min=0)
    score = dy.Int64(
        nullable=True,
        max=10,
        metadata={"dagster_dataframely": {"severity": {"max": "warn"}}},
    )


events = dg.AssetSpec(
    "events", metadata=dd.wiring.get_column_schema_metadata(EventsSchema)
).with_io_manager_key("warehouse")
event_checks = dd.build_rule_checks(EventsSchema, asset="events")

{
    "step": event_checks.node_def.name,
    "checks": [(spec.name, spec.blocking) for spec in event_checks.check_specs],
}
```


    {'step': 'events__checks',
     'checks': [('dy_schema__columns', True),
      ('dy_rule__primary_key', True),
      ('dy_rule__event_id__nullability', True),
      ('dy_rule__amount__nullability', True),
      ('dy_rule__amount__min', True),
      ('dy_rule__score__max', False)]}


`dd.build_rule_checks` returns one `dg.AssetChecksDefinition`, which goes in `dg.Definitions(asset_checks=[...])`. Dagster runs every check in it in one step, named `<key>__checks` unless you pass `name=`.

The checks are the ones an asset built with `dd.asset` has: the column-schema check, then the checks for the schema's rules. `check_granularity` and `max_failure_examples` mean what they mean on `dd.asset`, and [Settings](settings.md) lists their sources. `dd.build_rule_checks` resolves each setting once, when you call it.

The Columns tab reads the asset's own definition metadata, so `dd.build_rule_checks` cannot fill it. Pass `dd.wiring.get_column_schema_metadata(EventsSchema)` as the asset's `metadata`, as `events` does above.


# How the checks read the table

The checks read the table as a Dagster input, through the asset's own IO manager, as a `pl.DataFrame`.

So the asset needs an IO manager that loads its table. `events` sets one with `dg.AssetSpec.with_io_manager_key`. The checks load an asset with no IO manager key through `io_manager`. If that IO manager does not store the table, the step fails while loading the input. For an asset another integration builds, such as a dbt model or a dlt resource, set the IO manager key where that integration takes one. The tests of `dd.build_rule_checks` set the key only with `dg.AssetSpec.with_io_manager_key`. [Open an issue](https://github.com/ozanozbeker/dagster-dataframely/issues) for an integration whose assets the checks cannot load.

The run below checks a DuckDB table that SQL wrote, as a dbt model would. It selects only the checks, as the "Execute all" button on the Checks tab does:


``` python
def warehouse_with(columns: str) -> str:
    """Create the `analytics.events` table in a new database, and return the database path."""
    database = f"{tempfile.mkdtemp()}/warehouse.duckdb"
    with duckdb.connect(database) as connection:
        connection.sql("create schema analytics")
        connection.sql(f"create table analytics.events ({columns})")
        connection.sql("insert into analytics.events values (1, 5, 1), (2, -1, 20)")
    return database


def check_run(database: str) -> dg.ExecuteInProcessResult:
    return dg.materialize(
        [events, event_checks],
        resources={
            "warehouse": DuckDBPolarsIOManager(database=database, schema="analytics")
        },
        selection=dg.AssetSelection.checks(event_checks),
        raise_on_error=False,
    )


result = check_run(warehouse_with("event_id BIGINT, amount BIGINT, score BIGINT"))

{
    evaluation.check_name: evaluation.severity.value
    for evaluation in result.get_asset_check_evaluations()
    if not evaluation.passed
}
```


    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - RUN_START - Started execution of run for "__ephemeral_asset_job__".
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - ENGINE_EVENT - Executing steps in process (pid: 4212)
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - RESOURCE_INIT_STARTED - Starting initialization of resources [io_manager, warehouse].
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - RESOURCE_INIT_SUCCESS - Finished initialization of resources [io_manager, warehouse].
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - LOGS_CAPTURED - Capturing logs for process (pid: 4212).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - STEP_START - Started execution of step "events__checks".
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - LOADED_INPUT - Loaded input "table" using input manager "warehouse"
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - STEP_INPUT - Got input "table" of type "DataFrame". (Type check passed).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - STEP_OUTPUT - Yielded output "events_dy_schema__columns" of type "Any". (Type check passed).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - ASSET_CHECK_EVALUATION - Asset check 'dy_schema__columns' on 'events' passed. Description: 'Every column matches.'
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - STEP_OUTPUT - Yielded output "events_dy_rule__primary_key" of type "Any". (Type check passed).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - ASSET_CHECK_EVALUATION - Asset check 'dy_rule__primary_key' on 'events' passed. Description: 'No row failed.'
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - STEP_OUTPUT - Yielded output "events_dy_rule__event_id__nullability" of type "Any". (Type check passed).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - ASSET_CHECK_EVALUATION - Asset check 'dy_rule__event_id__nullability' on 'events' passed. Description: 'No row failed.'
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - STEP_OUTPUT - Yielded output "events_dy_rule__amount__nullability" of type "Any". (Type check passed).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - ASSET_CHECK_EVALUATION - Asset check 'dy_rule__amount__nullability' on 'events' passed. Description: 'No row failed.'
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - STEP_OUTPUT - Yielded output "events_dy_rule__amount__min" of type "Any". (Type check passed).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - ASSET_CHECK_EVALUATION - Asset check 'dy_rule__amount__min' on 'events' did not pass. Description: '1 row failed.'
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - STEP_OUTPUT - Yielded output "events_dy_rule__score__max" of type "Any". (Type check passed).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - ASSET_CHECK_EVALUATION - Asset check 'dy_rule__score__max' on 'events' did not pass. Description: '1 row failed.'
    2026-10-22 02:12:01 +0000 - dagster - ERROR - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - events__checks - STEP_FAILURE - Execution of step "events__checks" failed.

    dagster._core.errors.DagsterAssetCheckFailedError: 1 blocking asset check failed with ERROR severity:
    events: dy_rule__amount__min

    Stack Trace:
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_plan.py", line 243, in dagster_event_sequence_for_step
        yield from check.generator(step_events)
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_step.py", line 543, in core_dagster_event_sequence_for_step
        raise DagsterAssetCheckFailedError(

    /home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/context_creation_job.py:273: RuntimeWarning: coroutine 'BaseEventLoop.shutdown_asyncgens' was never awaited
      pass
    RuntimeWarning: Enable tracemalloc to get the object allocation traceback
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - ENGINE_EVENT - Finished steps in process (pid: 4212) in 96ms
    2026-10-22 02:12:01 +0000 - dagster - ERROR - __ephemeral_asset_job__ - 254373cc-f4ca-4073-bfb4-8dd8aa5e7487 - 4212 - RUN_FAILURE - Execution of run for "__ephemeral_asset_job__" failed. Steps failed: ['events__checks'].


    {'dy_rule__amount__min': 'ERROR', 'dy_rule__score__max': 'WARN'}


# What a run reports

Row 2 fails `amount|min`, an `"error"` rule, and `score|max`, a `"warn"` rule.

**A failing `"error"` rule's check stops the assets downstream.** Each `"error"` rule's check is blocking, as it is for `dd.asset` with `filter=False`. So Dagster fails the check step and does not run the assets downstream of `events`:


``` python
result.success
```


    False


`dd.build_rule_checks` takes no `filter` argument, and it writes no error rows.

**A failing `"warn"` rule's check only reports.** Declare a rule `"warn"` to report its failures without stopping anything. [Rule severity](rule-severity.md) lists the ways to declare it.

The check results have the same descriptions and metadata as the results of an asset built with `dd.asset`. [What a run produces](what-a-run-produces.md#the-checks) lists them.

**A run writes the failure examples to the Dagster event log unredacted.**


# A dtype that differs from the schema's

A table that SQL wrote can store a different dtype from the one the schema declares. DuckDB's `INTEGER` reads back as `Int32`, so it does not match `dy.Int64`:


``` python
try:
    dg.materialize(
        [events, event_checks],
        resources={
            "warehouse": DuckDBPolarsIOManager(
                database=warehouse_with(
                    "event_id BIGINT, amount INTEGER, score BIGINT"
                ),
                schema="analytics",
            )
        },
        selection=dg.AssetSelection.checks(event_checks),
    )
except ColumnSchemaError as error:
    print(error)
```


    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - RUN_START - Started execution of run for "__ephemeral_asset_job__".
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - ENGINE_EVENT - Executing steps in process (pid: 4212)
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - events__checks - RESOURCE_INIT_STARTED - Starting initialization of resources [io_manager, warehouse].
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - events__checks - RESOURCE_INIT_SUCCESS - Finished initialization of resources [io_manager, warehouse].
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - LOGS_CAPTURED - Capturing logs for process (pid: 4212).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - events__checks - STEP_START - Started execution of step "events__checks".
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - events__checks - LOADED_INPUT - Loaded input "table" using input manager "warehouse"
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - events__checks - STEP_INPUT - Got input "table" of type "DataFrame". (Type check passed).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - events__checks - STEP_OUTPUT - Yielded output "events_dy_schema__columns" of type "Any". (Type check passed).
    2026-10-22 02:12:01 +0000 - dagster - DEBUG - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - events__checks - ASSET_CHECK_EVALUATION - Asset check 'dy_schema__columns' on 'events' did not pass. Description: '1 column does not match: amount.'
    2026-10-22 02:12:01 +0000 - dagster - ERROR - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - events__checks - STEP_FAILURE - Execution of step "events__checks" failed.

    dagster_dataframely.errors.ColumnSchemaError: Column 'amount' (expected Int64, got Int32) does not match EventsSchema. Declare the dtype the table stores in EventsSchema, or change what writes the table. This package never casts for you.

    Stack Trace:
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_plan.py", line 243, in dagster_event_sequence_for_step
        yield from check.generator(step_events)
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_step.py", line 505, in core_dagster_event_sequence_for_step
        for user_event in _step_output_error_checked_user_event_sequence(
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_step.py", line 184, in _step_output_error_checked_user_event_sequence
        for user_event in user_event_sequence:
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_step.py", line 88, in _process_asset_results_to_events
        for user_event in user_event_sequence:
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/compute.py", line 188, in execute_core_compute
        for step_output in _yield_compute_results(step_context, inputs, compute_fn, compute_context):
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/compute.py", line 157, in _yield_compute_results
        for event in iterate_with_context(
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_utils/__init__.py", line 394, in iterate_with_context
        next_output = next(iterator)
                      ^^^^^^^^^^^^^^
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/src/dagster_dataframely/_rule_checks.py", line 106, in _results
        raise ColumnSchemaError(

    /home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/context_creation_job.py:273: RuntimeWarning: coroutine 'BaseEventLoop.shutdown_asyncgens' was never awaited
      pass
    RuntimeWarning: Enable tracemalloc to get the object allocation traceback
    2026-10-22 02:12:01 +0000 - dagster - ERROR - __ephemeral_asset_job__ - 8a47920e-1c00-4bad-a9f8-abe27ad7f3dc - 4212 - RUN_FAILURE - Execution of run for "__ephemeral_asset_job__" failed. An exception was thrown during execution.

    dagster_dataframely.errors.ColumnSchemaError: Column 'amount' (expected Int64, got Int32) does not match EventsSchema. Declare the dtype the table stores in EventsSchema, or change what writes the table. This package never casts for you.

    Stack Trace:
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/api.py", line 742, in job_execution_iterator
        for event in job_context.executor.execute(job_context, execution_plan):
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/executor/in_process.py", line 71, in execute
        yield from iter(
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/api.py", line 873, in __iter__
        yield from self.iterator(
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/executor/in_process.py", line 28, in inprocess_execution_iterator
        yield from inner_plan_execution_iterator(
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_plan.py", line 85, in inner_plan_execution_iterator
        for step_event in check.generator(dagster_event_sequence_for_step(step_context)):
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_plan.py", line 303, in dagster_event_sequence_for_step
        raise failure
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_plan.py", line 243, in dagster_event_sequence_for_step
        yield from check.generator(step_events)
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_step.py", line 505, in core_dagster_event_sequence_for_step
        for user_event in _step_output_error_checked_user_event_sequence(
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_step.py", line 184, in _step_output_error_checked_user_event_sequence
        for user_event in user_event_sequence:
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_step.py", line 88, in _process_asset_results_to_events
        for user_event in user_event_sequence:
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/compute.py", line 188, in execute_core_compute
        for step_output in _yield_compute_results(step_context, inputs, compute_fn, compute_context):
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_core/execution/plan/compute.py", line 157, in _yield_compute_results
        for event in iterate_with_context(
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/.venv/lib/python3.12/site-packages/dagster/_utils/__init__.py", line 394, in iterate_with_context
        next_output = next(iterator)
                      ^^^^^^^^^^^^^^
      File "/home/runner/work/dagster-dataframely/dagster-dataframely/src/dagster_dataframely/_rule_checks.py", line 106, in _results
        raise ColumnSchemaError(


    Column 'amount' (expected Int64, got Int32) does not match EventsSchema. Declare the dtype the table stores in EventsSchema, or change what writes the table. This package never casts for you.


The column-schema check fails, and the step fails with [ColumnSchemaError](../reference/errors.ColumnSchemaError.md#dagster_dataframely.errors.ColumnSchemaError). The checks evaluate no rule. `dd.build_rule_checks` has no decorated function to cast in.


# Checking an asset you write yourself

`dd.build_rule_checks` also checks a plain `@dg.asset`. Use it when the write must not depend on the check results:


``` python
@dg.asset(metadata=dd.wiring.get_column_schema_metadata(EventsSchema))
def staged_events() -> pl.DataFrame:
    return pl.DataFrame({"event_id": [1, 2], "amount": [5, -1], "score": [1, 2]})


staged_checks = dd.build_rule_checks(EventsSchema, asset="staged_events")
```


<figure class="figure">
<p><img src="../assets/images/split-checks.png" class="img-fluid figure-img" /></p>
<figcaption>The Checks tab of the demo's <code>warehouse_orders</code> shows checks that run in their own step, after the IO manager writes the table. The selected check is blocking because its rule is <code>"error"</code>, and the rows that failed it are in the table, not in the error rows.</figcaption>
</figure>


The IO manager writes whatever the asset returns, and the checks run afterwards against the written table. Unlike with `dd.asset`, the table can contain rows that failed an `"error"` rule. Only a failing check reports them.


# Partitions

Pass the asset's `partitions_def`, and each run checks one partition:


``` python
days = dg.StaticPartitionsDefinition(["2026-10-01", "2026-10-02"])


@dg.asset(
    partitions_def=days, metadata=dd.wiring.get_column_schema_metadata(EventsSchema)
)
def daily_events(context: dg.AssetExecutionContext) -> pl.DataFrame:
    amount = 5 if context.partition_key == "2026-10-01" else -1
    return pl.DataFrame({"event_id": [1], "amount": [amount], "score": [1]})


daily_checks = dd.build_rule_checks(
    EventsSchema, asset="daily_events", partitions_def=days
)
```


    /home/runner/work/dagster-dataframely/dagster-dataframely/src/dagster_dataframely/_checks.py:137: PreviewWarning: Specifying a partitions_def on an AssetCheckSpec is currently in preview, and may have breaking changes in patch version releases. This feature is not considered ready for production use.
      column_schema = dg.AssetCheckSpec(
    /home/runner/work/dagster-dataframely/dagster-dataframely/src/dagster_dataframely/_checks.py:147: PreviewWarning: Specifying a partitions_def on an AssetCheckSpec is currently in preview, and may have breaking changes in patch version releases. This feature is not considered ready for production use.
      dg.AssetCheckSpec(


The checks read only that partition's rows, and Dagster records each evaluation under the partition. So the checks validate each partition separately, as an asset built with `dd.asset` does. Nothing checks that `partitions_def` matches the asset's. Without `partitions_def`, the checks read every partition at once. With `dg.FilesystemIOManager`, the input is a `dict`, and Dagster fails the step with `DagsterTypeCheckDidNotPass`.


# Selecting checks

A run can select any of the checks, and it reports only those. Each run still validates the whole table, or the whole partition, so selecting one check takes as long as selecting all of them.