chore: Migrate Metrics models to pydantic v2

BALSAMIC/models/metrics.py

@@ -1,8 +1,8 @@
 """QC validation metrics model."""
 import logging
-from typing import Optional, Any, List
+from typing import Optional, Any, List, Annotated
 
-from pydantic.v1 import BaseModel, validator
+from pydantic import BaseModel, AfterValidator
 
 from BALSAMIC.constants.metrics import VALID_OPS
 
@@ -34,13 +34,26 @@ class Metric(BaseModel):
         condition (MetricCondition, required) : Metric validation condition.
     """
 
-    header: Optional[str]
+    header: Optional[str] = None
     id: str
     input: str
     name: str
     step: str
-    value: Any = ...
-    condition: Optional[MetricCondition] = ...
+    value: Any
+    condition: Optional[MetricCondition]
+
+
+def validate_metric(metric: Metric):
+    """Checks if a metric meets its filtering condition."""
+    if metric.condition and not VALID_OPS[metric.condition.norm](
+        metric.value, metric.condition.threshold
+    ):
+        raise ValueError(
+            f"QC metric {metric.name}: {metric.value} validation has failed. "
+            f"(Condition: {metric.condition.norm} {metric.condition.threshold}, ID: {metric.id})."
+        )
+    LOG.info(f"QC metric {metric.name}: {metric.value} meets its condition.")
+    return metric
 
 
 class MetricValidation(BaseModel):
@@ -50,17 +63,4 @@ class MetricValidation(BaseModel):
         metrics (List[Metric], required) : Metric model to validate.
     """
 
-    metrics: List[Metric]
-
-    @validator("metrics", each_item=True)
-    def validate_metrics(cls, metric):
-        """Checks if a metric meets its filtering condition."""
-        if metric.condition and not VALID_OPS[metric.condition.norm](
-            metric.value, metric.condition.threshold
-        ):
-            raise ValueError(
-                f"QC metric {metric.name}: {metric.value} validation has failed. "
-                f"(Condition: {metric.condition.norm} {metric.condition.threshold}, ID: {metric.id})."
-            )
-        LOG.info(f"QC metric {metric.name}: {metric.value} meets its condition.")
-        return metric
+    metrics: List[Annotated[Metric, AfterValidator(validate_metric)]]

CHANGELOG.rst

@@ -49,6 +49,7 @@ Changed:
 * Update `reference.json` file to use relative paths https://github.com/Clinical-Genomics/BALSAMIC/pull/1251
 * Update pydantic to v2 while maintaining support for v1 models https://github.com/Clinical-Genomics/BALSAMIC/pull/1253
 * `PCT_PF_READS_IMPROPER_PAIRS` QC threshold lowered to 5% https://github.com/Clinical-Genomics/BALSAMIC/issues/1265
+* Migrate Metrics models to pydantic v2 https://github.com/Clinical-Genomics/BALSAMIC/pull/1270
 
 Fixed:
 ^^^^^^

tests/models/test_metric_models.py

@@ -4,11 +4,7 @@
 
 import pytest
 
-from BALSAMIC.models.metrics import (
-    MetricValidation,
-    Metric,
-    MetricCondition,
-)
+from BALSAMIC.models.metrics import MetricValidation, Metric, MetricCondition
 
 
 def test_metric_condition():
@@ -21,7 +17,7 @@ def test_metric_condition():
     metric_model: MetricCondition = MetricCondition(**metric_condition)
 
     # THEN assert retrieved values from the created model
-    assert metric_model.dict().items() == metric_condition.items()
+    assert metric_model.model_dump() == metric_condition
 
 
 def test_metric_pass_validation():
@@ -42,7 +38,7 @@ def test_metric_pass_validation():
     metric_model: Metric = Metric(**metrics)
 
     # THEN assert retrieved values from the created model
-    assert metric_model.dict().items() == metrics.items()
+    assert metric_model.model_dump() == metrics
 
 
 def test_metric_fail_validation():
@@ -54,7 +50,7 @@ def test_metric_fail_validation():
     # THEN the model raises an error due to an incomplete input
     with pytest.raises(ValueError) as input_exc:
         Metric(**invalid_input)
-    assert "field required" in str(input_exc.value)
+    assert "Field required" in str(input_exc.value)
 
 
 def test_metric_validation_pass(qc_extracted_metrics: dict):
@@ -64,7 +60,7 @@ def test_metric_validation_pass(qc_extracted_metrics: dict):
     model: MetricValidation = MetricValidation(metrics=qc_extracted_metrics)
 
     # THEN assert retrieved values from the created model
-    assert model.dict()["metrics"] == qc_extracted_metrics
+    assert model.model_dump()["metrics"] == qc_extracted_metrics
 
 
 def test_metric_validation_fail(qc_extracted_metrics: dict):