ref: use dataclass for Task as well

replace custom __init__ by from_config classmethod

src/sirocco/core.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import logging
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from typing import TYPE_CHECKING, Generic, Literal, TypeVar
 
 from termcolor import colored
@@ -43,16 +43,17 @@ def __str__(self) -> str:
         return f"{self.name} [{self.date}]"
 
 
+@dataclass
 class Task(NodeStr):
-    """Internal representation of a task node"""
 
-    color: str = "light_red"
 
     name: str
-    outputs: list[Data]
-    inputs: list[Data]
-    wait_on: list[Task]
+    workflow: Workflow
+    outputs: list[Data] = field(default_factory=list)
+    inputs: list[Data] = field(default_factory=list)
+    wait_on: list[Task] = field(default_factory=list)
     date: datetime | None = None
+    color: str = "light_red"
     # TODO: This list is too long. We should start with the set of supported
     #       keywords and extend it as we support more
     command: str | None = None
@@ -68,35 +69,31 @@ class Task(NodeStr):
     src: str | None = None
     conda_env: str | None = None
 
-    def __init__(self, config: ConfigTask, task_ref: ConfigCycleTask, workflow: Workflow, date: datetime | None = None):
-        self.name = config.name
-        self.date = date
-        self.inputs = []
-        self.outputs = []
-        self.wait_on = []
-        self.workflow = workflow
-        # Long list of not always supported keywords
-        self.command = config.command
-        self.command_option = config.command_option
-        self.input_arg_options = config.input_arg_options
-        self.host = config.host
-        self.account = config.account
-        self.plugin = config.plugin
-        self.config = config.config
-        self.uenv = config.uenv
-        self.nodes = config.nodes
-        self.walltime = config.walltime
-        self.src = config.src
-        self.conda_env = config.conda_env
-
+    # use classmethod instead of custom init
+    @classmethod
+    def from_config(cls, config: ConfigTask, task_ref: ConfigCycleTask, workflow: Workflow, date: datetime | None = None) -> Self:
+        inputs: list[Data] = []
         for input_spec in task_ref.inputs:
-            for data in workflow.data.get(input_spec, self.date):
+            for data in workflow.data.get(input_spec, date):
                 if data is not None:
-                    self.inputs.append(data)
+                    inputs.append(data)
+
+        outputs: list[Data] = []
         for output_spec in task_ref.outputs:
-            self.outputs.append(self.workflow.data[output_spec.name, self.date])
+            outputs.append(workflow.data[output_spec.name, date])
+
+        new = cls(
+            date=date,
+            inputs=inputs,
+            outputs=outputs,
+            workflow=workflow,
+            **dict(config)  # use the fact that pydantic models can be turned into dicts easily
+        )  # this works because dataclass has generated this init for us
+
         # Store for actual linking in link_wait_on_tasks() once all tasks are created
-        self._wait_on_specs = task_ref.depends
+        new._wait_on_specs = task_ref.depends
+
+        return new
 
     def link_wait_on_tasks(self):
         for wait_on_spec in self._wait_on_specs:
@@ -274,7 +271,7 @@ def __init__(self, workflow_config: ConfigWorkflow) -> None:
                 for task_ref in cycle_config.tasks:
                     task_name = task_ref.name
                     task_config = workflow_config.task_dict[task_name]
-                    self.tasks[task_name, date] = (task := Task(task_config, task_ref, workflow=self, date=date))
+                    self.tasks[task_name, date] = (task := Task.from_config(task_config, task_ref, workflow=self, date=date))
                     cycle_tasks.append(task)
                 self.cycles[cycle_name, date] = Cycle(name=cycle_name, tasks=cycle_tasks, date=date)