feat(dbt): suppress experimental warning when invoking @dbt_assets (d…

…agster-io#22528)

## Summary & Motivation
When using `@dbt_assets`, I get a bunch of errors like:

```
2024-06-13 11:06:20 -0400 - dagster - WARNING - /Users/rexledesma/dagster-labs/dagster/python_modules/dagster/dagster/_core/decorator_utils.py:203: ExperimentalWarning: Parameter `tags` of initializer `AssetOut.__init__` is experimental. It may break in future versions, even between dot releases. To mute warnings for experimental functionality, invoke warnings.filterwarnings("ignore", category=dagster.ExperimentalWarning) or use one of the other methods described at https://docs.python.org/3/library/warnings.html#describing-warning-filters.
  return fn(*args, **kwargs)

2024-06-13 11:06:20 -0400 - dagster - WARNING - /Users/rexledesma/dagster-labs/dagster/python_modules/dagster/dagster/_core/decorator_utils.py:203: ExperimentalWarning: Parameter `tags` of initializer `AssetOut.__init__` is experimental. It may break in future versions, even between dot releases. To mute warnings for experimental functionality, invoke warnings.filterwarnings("ignore", category=dagster.ExperimentalWarning) or use one of the other methods described at https://docs.python.org/3/library/warnings.html#describing-warning-filters.
  return fn(*args, **kwargs)

2024-06-13 11:06:20 -0400 - dagster - WARNING - /Users/rexledesma/dagster-labs/dagster/python_modules/dagster/dagster/_core/decorator_utils.py:203: ExperimentalWarning: Parameter `tags` of initializer `AssetOut.__init__` is experimental. It may break in future versions, even between dot releases. To mute warnings for experimental functionality, invoke warnings.filterwarnings("ignore", category=dagster.ExperimentalWarning) or use one of the other methods described at https://docs.python.org/3/library/warnings.html#describing-warning-filters.
  return fn(*args, **kwargs)
```

This does not inspire confidence when I am using these APIs. My thought
process on this is:

1. If we use experimental APIs on behalf of the user in the default
case, they should not be shown.
2. Experimental warnings should only be shown once per call site, not
once per invocation.
3. If an entrypoint for an integration is experimental (e.g.
`DbtProject`), an experimental warning should be shown once, at
instantiation of the experimental entrypoint. If the entrypoint itself
is implemented using experimental APIs, those subsequent warnings should
be suppressed (i.e. we should follow (1)).

In this PR, we follow (1) for `@dbt_assets`.

## How I Tested These Changes
pytest

python_modules/libraries/dagster-dbt/dagster_dbt/asset_decorator.py

@@ -23,7 +23,7 @@
     LocalFileCodeReference,
 )
 from dagster._core.definitions.tags import StorageKindTagSet
-from dagster._utils.warnings import experimental_warning
+from dagster._utils.warnings import suppress_dagster_warnings
 
 from dagster_dbt.dbt_project import DbtProject
 
@@ -54,6 +54,7 @@
 )
 
 
+@suppress_dagster_warnings
 def dbt_assets(
     *,
     manifest: DbtManifestParam,
@@ -550,9 +551,6 @@ def get_dbt_multi_asset_args(
             parent_unique_ids_for_asset_key.add(parent_unique_id)
             parent_resource_types_for_asset_key.add(dbt_parent_resource_props["resource_type"])
 
-            if parent_partition_mapping:
-                experimental_warning("DagsterDbtTranslator.get_partition_mapping")
-
             # Add this parent as an internal dependency
             output_internal_deps.add(parent_asset_key)
 
@@ -570,8 +568,6 @@ def get_dbt_multi_asset_args(
             dbt_parent_resource_props=dbt_resource_props,
         )
         if self_partition_mapping and has_self_dependency(dbt_resource_props):
-            experimental_warning("+meta.dagster.has_self_dependency")
-
             deps.add(
                 AssetDep(
                     asset=asset_key,

python_modules/libraries/dagster-dbt/dagster_dbt/core/resources_v2.py

@@ -364,7 +364,7 @@ def to_default_asset_events(
                         "This test was included in Dagster's asset check"
                         " selection, and was likely executed due to dbt indirect selection."
                     )
-                    logger.warn(message)
+                    logger.warning(message)
 
                 yield from self._yield_observation_events_for_test(
                     dagster_dbt_translator=dagster_dbt_translator,

python_modules/libraries/dagster-dbt/dagster_dbt/dagster_dbt_translator.py

@@ -8,7 +8,7 @@
     PartitionMapping,
     _check as check,
 )
-from dagster._annotations import public
+from dagster._annotations import experimental, public
 from dagster._core.definitions.asset_key import (
     CoercibleToAssetKeyPrefix,
     check_opt_coercible_to_asset_key_prefix_param,
@@ -125,6 +125,7 @@ def get_asset_key(self, dbt_resource_props: Mapping[str, Any]) -> AssetKey:
         return default_asset_key_fn(dbt_resource_props)
 
     @public
+    @experimental(emit_runtime_warning=False)
     def get_partition_mapping(
         self,
         dbt_resource_props: Mapping[str, Any],
@@ -323,6 +324,7 @@ def get_owners(self, dbt_resource_props: Mapping[str, Any]) -> Optional[Sequence
         return default_owners_from_dbt_resource_props(dbt_resource_props)
 
     @public
+    @experimental(emit_runtime_warning=False)
     def get_freshness_policy(
         self, dbt_resource_props: Mapping[str, Any]
     ) -> Optional[FreshnessPolicy]:
@@ -376,6 +378,7 @@ def get_freshness_policy(self, dbt_resource_props: Mapping[str, Any]) -> Optiona
         return default_freshness_policy_fn(dbt_resource_props)
 
     @public
+    @experimental(emit_runtime_warning=False)
     def get_auto_materialize_policy(
         self, dbt_resource_props: Mapping[str, Any]
     ) -> Optional[AutoMaterializePolicy]: