fix: pylint errors

pyproject.toml

@@ -146,7 +146,7 @@ isort.required-imports = ["from __future__ import annotations"]
 
 
 [tool.pylint]
-py-version = "3.10"
+py-version = "3.11"
 ignore-paths = [".*/_version.py"]
 reports.output-format = "colorized"
 similarities.ignore-imports = "yes"

src/fasthep_flow/config.py

@@ -32,8 +32,7 @@ def validate_type(cls, value: str) -> str:
         """Validate the type field
         Any specified type needs to be a Python class that can be imported"""
         # Split the string to separate the module from the class name
-        if value in ALIASES:
-            value = ALIASES[value]
+        value = ALIASES.get(value, value)
         module_path, class_name = value.rsplit(".", 1)
         try:
             # Import the module

src/fasthep_flow/orchestration.py

@@ -21,6 +21,7 @@
 
 
 def create_dask_cluster() -> Any:
+    """Create a Dask cluster - to be used with Hamilton Dask adapter."""
     cluster = LocalCluster()
     client = Client(cluster)
     logger.info(client.cluster)
@@ -34,6 +35,7 @@ def create_dask_cluster() -> Any:
 
 
 def create_dask_adapter(client_type: str) -> Any:
+    """Create a Hamilton adapter for Dask execution"""
     from hamilton.plugins import h_dask
 
     client = DASK_CLIENTS[client_type]()
@@ -48,6 +50,7 @@ def create_dask_adapter(client_type: str) -> Any:
 
 
 def create_local_adapter() -> Any:
+    """Create a Hamilton adapter for local execution."""
     return base.SimplePythonGraphAdapter(base.DictResult())
 
 
@@ -62,7 +65,7 @@ def workflow_to_hamilton_dag(
     output_path: str,
     # method: str = "local"
 ) -> Any:
-    """Convert a workflow into a Hamilton flow."""
+    """Convert a workflow into a Hamilton DAG."""
     task_functions = load_tasks_module(workflow)
     # adapter = PRECONFIGURED_ADAPTERS[method]()
     cache_dir = Path(output_path) / ".hamilton_cache"

src/fasthep_flow/workflow.py

@@ -54,6 +54,7 @@ def {task_name}() -> dict[str, Any]:
 
 
 def get_task_source(obj: Any, task_name: str) -> str:
+    """Retrieve the source code of a task object and return a function definition."""
     # Capture the object definition
     obj_attrs = {}
 
@@ -72,11 +73,21 @@ def get_task_source(obj: Any, task_name: str) -> str:
 
 
 def get_config_hash(config_file: Path) -> str:
+    """Reads the config file and returns a shortened hash."""
     with config_file.open("rb") as f:
         return hashlib.file_digest(f, "sha256").hexdigest()[:8]
 
 
 def create_save_path(base_path: Path, workflow_name: str, config_hash: str) -> Path:
+    """
+    Creates a save path for the workflow and returns the generated path.
+
+    @param base_path: Base path for the save location.
+    @param workflow_name: Name of the workflow.
+    @param config_hash: Hash of the configuration file.
+
+    returns: Path to the save location.
+    """
     date = datetime.now().strftime("%Y.%m.%d")
     # TODO: instead of date, create a "touched" file that is updated every time the workflow is saved
     path = Path(f"{base_path}/{workflow_name}/{date}/{config_hash}/").resolve()
@@ -163,6 +174,10 @@ def save(self, base_path: Path = Path("~/.fasthep/flow")) -> str:
 
     @staticmethod
     def load(path: Path | str) -> Workflow:
+        """
+        Load a workflow from a file.
+        @param path: Path to the directory containing the workflow file.
+        """
         path = Path(path)
         workflow_file = path / "workflow.pkl"
         with workflow_file.open("rb") as f:
@@ -172,6 +187,7 @@ def load(path: Path | str) -> Workflow:
 
 
 def load_tasks_module(workflow: Workflow) -> ModuleType:
+    """Load tasks from a tasks.py file in the workflow save path."""
     task_location = workflow.save_path
     task_spec = importlib.machinery.PathFinder().find_spec("tasks", [task_location])
     if task_spec is None: