feat: adjustments to comply with pre-commits

Author: d0choa

poetry.lock

@@ -101,7 +101,11 @@ def amend_version(
 
 
 class DatasourceVersionSeeker(ABC):
-    """Interface for datasource version seeker."""
+    """Interface for datasource version seeker.
+
+    Raises:
+        NotImplementedError: if method is not implemented in the subclass
+    """
 
     @staticmethod
     @abstractmethod
@@ -115,7 +119,7 @@ def seek_version(text: str) -> str:
             str: seeked version
 
         Raises:
-            ValueError: if version can not be seeked
+            NotImplementedError: if method is not implemented in the subclass
 
         """
         raise NotImplementedError

src/gentropy/common/version_engine.py

@@ -55,8 +55,7 @@ def extract_maximum_coloc_probability_per_region_and_gene(
             DataFrame: table with the maximum colocalisation scores for the provided study loci
 
         Raises:
-            ValueError: if filter_by_qtl is not in the list of valid QTL types
-            ValueError: if filter_by_colocalisation_method is not in the list of valid colocalisation methods
+            ValueError: if filter_by_qtl is not in the list of valid QTL types or is not in the list of valid colocalisation methods
         """
         from gentropy.colocalisation import ColocalisationStep
 

src/gentropy/dataset/colocalisation.py

@@ -211,8 +211,7 @@ def valid_rows(self: Self, invalid_flags: list[str], invalid: bool = False) -> S
             Self: filtered dataset.
 
         Raises:
-            ValueError: If the Dataset does not contain a QC column.
-            ValueError: If the invalid_flags elements do not exist in QC mappings flags.
+            ValueError: If the Dataset does not contain a QC column or if the invalid_flags elements do not exist in QC mappings flags.
         """
         # If the invalid flags are not valid quality checks (enum) for this Dataset we raise an error:
         invalid_reasons = []

src/gentropy/dataset/dataset.py

@@ -71,8 +71,7 @@ def extract_variant_index_from_vep(
             VariantIndex: Variant index dataset.
 
         Raises:
-            ValueError: Failed reading file.
-            ValueError: The dataset is empty.
+            ValueError: Failed reading file or if the dataset is empty.
         """
         # To speed things up and simplify the json structure, read data following an expected schema:
         vep_schema = cls.get_schema()

src/gentropy/datasource/ensembl/vep_parser.py

@@ -201,8 +201,7 @@ def _generate_feature_matrix(self, write_feature_matrix: bool) -> L2GFeatureMatr
             L2GFeatureMatrix: Feature matrix with gold standards annotated with features.
 
         Raises:
-            ValueError: If write_feature_matrix is set to True but a path is not provided.
-            ValueError: If dependencies to build features are not set.
+            ValueError: If write_feature_matrix is set to True but a path is not provided or if dependencies to build features are not set.
         """
         if self.gs_curation and self.interactions and self.v2g:
             study_locus_overlap = StudyLocus(

src/gentropy/l2g.py

@@ -135,8 +135,7 @@ def save(self: LocusToGeneModel, path: str) -> None:
             path (str): Path to save the persisted model. Should end with .skops
 
         Raises:
-            ValueError: If the model has not been fitted yet
-            ValueError: If the path does not end with .skops
+            ValueError: If the model has not been fitted yet or if the path does not end with .skops
         """
         if self.model is None:
             raise ValueError("Model has not been fitted yet.")
@@ -215,7 +214,7 @@ def export_to_hugging_face_hub(
             local_repo (str): Path to the folder where the contents of the model repo + the documentation are located. This is used to push the model to the Hugging Face Hub.
 
         Raises:
-            Exception: If the push to the Hugging Face Hub fails
+            RuntimeError: If the push to the Hugging Face Hub fails
         """
         from sklearn import __version__ as sklearn_version
 
@@ -241,4 +240,4 @@ def export_to_hugging_face_hub(
                 for p in Path(local_repo).glob("*"):
                     p.unlink()
                 Path(local_repo).rmdir()
-            raise e
+            raise RuntimeError from e

src/gentropy/method/l2g/model.py

@@ -23,6 +23,9 @@ class SUSIE_inf:
 
     Note: code copied from fine-mapping-inf package as a placeholder
     https://github.com/FinucaneLab/fine-mapping-inf
+
+    Raises:
+        RuntimeError: if missing LD or if unsupported variance estimation
     """
 
     @staticmethod
@@ -89,8 +92,7 @@ def susie_inf(  # noqa: C901
                 lbf -- length-p array of log-Bayes-factors for each CS
 
         Raises:
-            RuntimeError: if missing LD
-            RuntimeError: if unsupported variance estimation method
+            RuntimeError: if missing LD or if unsupported variance estimation method
         """
         p = len(z)
         # Precompute V,D^2 in the SVD X=UDV', and V'X'y and y'y
@@ -428,6 +430,7 @@ def cred_inf(
 
         Raises:
             RuntimeError: if missing inputs for purity filtering
+            ValueError: if either LD or V, Dsq are None
         """
         if (V is None or Dsq is None or n is None) and LD is None:
             raise RuntimeError("Missing inputs for purity filtering")