STYLE: Format with black (#237)

python/varspark/featuresource.py

@@ -2,6 +2,7 @@
 import pandas as pd
 from typedecorator import params, Nullable
 
+
 class FeatureSource(object):
     def __init__(self, _jvm, _vs_api, _jsql, sql, _jfs):
         self._jfs = _jfs
@@ -12,7 +13,7 @@ def __init__(self, _jvm, _vs_api, _jsql, sql, _jfs):
 
     @params(sample_list_str=str)
     def extract_samples(sample_list_str):
-        """ Convert the sample list string to a list of sample names.
+        """Convert the sample list string to a list of sample names.
 
         :param (str) sample_list_str: The string representation of the sample list.
 
@@ -23,29 +24,32 @@ def extract_samples(sample_list_str):
 
     @params(feature=object)
     def unpack_feature_data(feature):
-        """ Unpack feature data from byte array into a tuple of integers.
+        """Unpack feature data from byte array into a tuple of integers.
 
         :param feature: The feature object containing the data.
 
         return tuple: A tuple containing unpacked integers.
         """
         byte_string = feature.data().valueAsByteArray()
-        format_string = f'{len(byte_string)}B'
+        format_string = f"{len(byte_string)}B"
         return struct.unpack(format_string, byte_string)
 
     @params(features_ref=object)
     def collect_feature_data(features_ref):
-        """ Collect and organize feature data into a dictionary.
+        """Collect and organize feature data into a dictionary.
 
         :param features_ref: The list of feature objects.
 
         :return dict: A dictionary with feature labels as keys and unpacked data as values.
         """
-        return {feature.label(): FeatureSource.unpack_feature_data(feature) for feature in features_ref}
+        return {
+            feature.label(): FeatureSource.unpack_feature_data(feature)
+            for feature in features_ref
+        }
 
     @params(self=object, scala=Nullable(bool))
     def to_df(self, scala=False):
-        """ Converts a Feature Source RDD to a pandas dataframe.
+        """Converts a Feature Source RDD to a pandas dataframe.
 
         :param (bool) scala: Indicates whether to use the scala version of DataFrame conversion
 
@@ -56,7 +60,7 @@ def to_df(self, scala=False):
             jdf.count()
             jdf.createOrReplaceTempView("df")
             features = self.sql.table("df").toPandas()
-            features.set_index('variant_id', inplace=True)
+            features.set_index("variant_id", inplace=True)
             return features
         else:
             features_ref = self._jfs.features().collect()