(change)config object implementation

src/stimulus/data/data_handlers.py

@@ -36,24 +36,27 @@
 class DatasetManager:
     """Class for managing the dataset.
 
-    This class handles loading and organizing dataset configuration from YAML files.
+    This class handles organizing dataset configuration from YAML data.
     It manages column categorization into input, label and meta types based on the config.
 
     Attributes:
-        config (dict): The loaded configuration dictionary from YAML
+        config (dict): The configuration dictionary
         column_categories (dict): Dictionary mapping column types to lists of column names
 
     Methods:
-        _load_config(config_path: str) -> dict: Loads the config from a YAML file.
         categorize_columns_by_type() -> dict: Organizes the columns into input, label, meta based on the config.
     """
 
     def __init__(
         self,
-        config_path: str,
+        config: yaml_data.YamlConfigDict,
     ) -> None:
-        """Initialize the DatasetManager."""
-        self.config = self._load_config(config_path)
+        """Initialize the DatasetManager.
+        
+        Args:
+            config: The configuration dictionary
+        """
+        self.config = config
         self.column_categories = self.categorize_columns_by_type()
 
     def categorize_columns_by_type(self) -> dict:
@@ -71,7 +74,7 @@ def categorize_columns_by_type(self) -> dict:
                 }
 
         Example:
-            >>> manager = DatasetManager("config.yaml")
+            >>> manager = DatasetManager(config)
             >>> categories = manager.categorize_columns_by_type()
             >>> print(categories)
             {
@@ -93,24 +96,6 @@ def categorize_columns_by_type(self) -> dict:
 
         return {"input": input_columns, "label": label_columns, "meta": meta_columns}
 
-    def _load_config(self, config_path: str) -> yaml_data.YamlConfigDict:
-        """Loads and parses a YAML configuration file.
-
-        Args:
-            config_path (str): Path to the YAML config file
-
-        Returns:
-            dict: Parsed configuration dictionary
-
-        Example:
-            >>> manager = DatasetManager()
-            >>> config = manager._load_config("config.yaml")
-            >>> print(config["columns"][0]["column_name"])
-            'hello'
-        """
-        with open(config_path) as file:
-            return yaml_data.YamlSubConfigDict(**yaml.safe_load(file))
-
     def get_split_columns(self) -> list[str]:
         """Get the columns that are used for splitting."""
         return self.config.split.split_input_columns
@@ -270,16 +255,16 @@ class DatasetHandler:
 
     def __init__(
         self,
-        config_path: str,
+        config: yaml_data.YamlConfigDict,
         csv_path: str,
     ) -> None:
         """Initialize the DatasetHandler with required config.
 
         Args:
-            config_path (str): Path to the dataset configuration file.
-            csv_path (str): Path to the CSV data file.
+            config: The dataset configuration dictionary
+            csv_path: Path to the CSV data file
         """
-        self.dataset_manager = DatasetManager(config_path)
+        self.dataset_manager = DatasetManager(config)
         self.columns = self.read_csv_header(csv_path)
         self.data = self.load_csv(csv_path)
 
@@ -331,9 +316,14 @@ def save(self, path: str) -> None:
 class DatasetProcessor(DatasetHandler):
     """Class for loading dataset, applying transformations and splitting."""
 
-    def __init__(self, config_path: str, csv_path: str) -> None:
-        """Initialize the DatasetProcessor."""
-        super().__init__(config_path, csv_path)
+    def __init__(self, config: yaml_data.YamlConfigDict, csv_path: str) -> None:
+        """Initialize the DatasetProcessor.
+        
+        Args:
+            config: The dataset configuration dictionary
+            csv_path: Path to the CSV data file
+        """
+        super().__init__(config, csv_path)
 
     def add_split(self, split_manager: SplitManager, *, force: bool = False) -> None:
         """Add a column specifying the train, validation, test splits of the data.
@@ -394,13 +384,20 @@ class DatasetLoader(DatasetHandler):
 
     def __init__(
         self,
-        config_path: str,
+        config: yaml_data.YamlConfigDict,
         csv_path: str,
         encoder_loader: loaders.EncoderLoader,
         split: Union[int, None] = None,
     ) -> None:
-        """Initialize the DatasetLoader."""
-        super().__init__(config_path, csv_path)
+        """Initialize the DatasetLoader.
+        
+        Args:
+            config: The dataset configuration dictionary
+            csv_path: Path to the CSV data file
+            encoder_loader: Loader for handling data encoding
+            split: Optional split index (0=train, 1=val, 2=test)
+        """
+        super().__init__(config, csv_path)
         self.encoder_manager = EncodeManager(encoder_loader)
         self.data = self.load_csv_per_split(csv_path, split) if split is not None else self.load_csv(csv_path)