fix: Dynamically choose pydantic config field name to resolve deprecation warning (#1194)

Resolves #1047

### Description

The diff speaks for itself, choose the appropriate pydantic model config
field based on the version of pydantic in the environment.

This avoids the deprecation warning:

```
<my_repo>\env\Lib\site-packages\pydantic\_internal\_config.py:373: UserWarning: Valid config keys have changed in V2:
* 'allow_population_by_field_name' has been renamed to 'validate_by_name'
  warnings.warn(message, UserWarning)
```

### Checklist

- [X] I have run this code in development and it appears to resolve the
stated issue
- [x] I have updated the `CHANGELOG.md` and added information about my
change to the "dbt-databricks next" section.

---------

Signed-off-by: Korijn van Golen <[email protected]>
Co-authored-by: Ben Cassell <[email protected]>

Author: Korijn

CHANGELOG.md

@@ -3,6 +3,7 @@
 ### Fixes
 
 - Fix issue causing MV/STs to always trigger as having their config changed ([1181](http://github.com/databricks/dbt-databricks/pull/1181))
+- Fix pydantic v2 deprecation warning "Valid config keys have changed in V2" (thanks @Korijn!) ([1194](https://github.com/databricks/dbt-databricks/pull/1194))
 
 ## dbt-databricks 1.10.12 (September 8, 2025)
 

dbt/adapters/databricks/python_models/python_config.py

@@ -3,6 +3,8 @@
 
 from pydantic import BaseModel, Field, validator
 
+from .util import PYDANTIC_IS_V1
+
 DEFAULT_TIMEOUT = 60 * 60 * 24
 
 JOB_PERMISSIONS = {"CAN_VIEW", "CAN_MANAGE_RUN", "CAN_MANAGE"}
@@ -84,4 +86,7 @@ def run_name(self) -> str:
         return f"{self.catalog}-{self.schema_}-{self.identifier}-{uuid.uuid4()}"
 
     class Config:
-        allow_population_by_field_name = True
+        if PYDANTIC_IS_V1:
+            allow_population_by_field_name = True
+        else:
+            populate_by_name = True

dbt/adapters/databricks/python_models/util.py

@@ -0,0 +1,16 @@
+from importlib.metadata import version
+
+
+def is_pydantic_v1() -> bool:
+    """Check if the installed version of pydantic is v1."""
+    try:
+        pydantic_version = version("pydantic")
+        major = int(pydantic_version.split(".")[0])
+        return major < 2
+    except Exception:
+        # If we can't determine the version, assume v1 for compatibility
+        # See: https://github.com/databricks/dbt-databricks/pull/976#issuecomment-2748680090
+        return True
+
+
+PYDANTIC_IS_V1 = is_pydantic_v1()