feat(dbt): Support defining default values for columns and metrics (#325

)

* feat(dbt): Support defining default values for columns and metrics
* Removing unnecessary test
* Fixing logic

src/preset_cli/cli/superset/sync/dbt/datasets.py

@@ -3,7 +3,9 @@
 """
 
 # pylint: disable=consider-using-f-string
+from __future__ import annotations
 
+import copy
 import json
 import logging
 from typing import Any, Dict, List, Optional, Tuple
@@ -17,7 +19,7 @@
 from preset_cli.api.operators import OneToMany
 from preset_cli.cli.superset.sync.dbt.lib import create_engine_with_check
 from preset_cli.exceptions import CLIError, SupersetError
-from preset_cli.lib import raise_cli_errors
+from preset_cli.lib import dict_merge, raise_cli_errors
 
 DEFAULT_CERTIFICATION = {"details": "This table is produced by dbt"}
 
@@ -171,6 +173,7 @@ def compute_metrics(
     dbt_metrics: List[Any],
     reload_columns: bool,
     merge_metadata: bool,
+    metric_defaults: Dict[str, Any] | None = None,
 ) -> List[Any]:
     """
     Compute the final list of metrics that should be used to update the dataset
@@ -187,16 +190,23 @@ def compute_metrics(
 
     for name, metric_definition in model_metrics.items():
         if reload_columns or merge_metadata or name not in current_dataset_metrics:
+            final_metric = {}
             if name in current_dataset_metrics:
                 metric_definition["id"] = current_dataset_metrics[name]["id"]
-            final_dataset_metrics.append(metric_definition)
+            if metric_defaults:
+                final_metric = copy.deepcopy(metric_defaults)
+                dict_merge(final_metric, metric_definition)
+            final_dataset_metrics.append(final_metric or metric_definition)
 
     # Preserving Superset metadata
     if not reload_columns:
         for name, metric in current_dataset_metrics.items():
             if not merge_metadata or name not in model_metrics:
                 # remove data that is not part of the update payload
                 metric = clean_metadata(metric)
+                if merge_metadata and metric_defaults:
+                    final_metric = copy.deepcopy(metric_defaults)
+                    dict_merge(metric, final_metric)
                 final_dataset_metrics.append(metric)
 
     return final_dataset_metrics
@@ -233,6 +243,7 @@ def compute_columns_metadata(
     dataset_columns: List[Any],
     reload_columns: bool,
     merge_metadata: bool,
+    column_defaults: Dict[str, Any] | None = None,
 ) -> List[Any]:
     """
     Adds dbt metadata to dataset columns.
@@ -251,13 +262,20 @@ def compute_columns_metadata(
         dbt_metadata[column]["verbose_name"] = column
         for key, value in definition.pop("meta", {}).get("superset", {}).items():
             dbt_metadata[column][key] = value
+        if column_defaults:
+            final_column = copy.deepcopy(column_defaults)
+            dict_merge(final_column, dbt_metadata[column])
+            dbt_metadata[column] = final_column
 
     for column in dataset_columns:
         name = column["column_name"]
         if name in dbt_metadata:
             for key, value in dbt_metadata[name].items():
                 if reload_columns or merge_metadata or not column.get(key):
                     column[key] = value
+        elif column_defaults and (reload_columns or merge_metadata):
+            for key, value in column_defaults.items():
+                column[key] = value
 
         # remove data that is not part of the update payload
         column = clean_metadata(column)
@@ -338,12 +356,17 @@ def sync_datasets(  # pylint: disable=too-many-locals, too-many-arguments
             failed_datasets.append(model["unique_id"])
             continue
 
+        default_configs = (
+            model.get("meta", {}).get("superset", {}).pop("default_configs", {})
+        )
+
         # compute metrics
         final_dataset_metrics = compute_metrics(
             dataset["metrics"],
             metrics.get(model["unique_id"], []),
             reload_columns,
             merge_metadata,
+            metric_defaults=default_configs.get("metrics", {}),
         )
 
         # compute columns
@@ -387,6 +410,7 @@ def sync_datasets(  # pylint: disable=too-many-locals, too-many-arguments
                 current_dataset_columns,
                 reload_columns,
                 merge_metadata,
+                column_defaults=default_configs.get("columns", {}),
             )
             try:
                 client.update_dataset(