Refactor the exporter into a package-backed module layout.

Split the previous monolithic implementation into focused modules for CLI handling, workflow loading, runtime bootstrap, load ordering, planning, rendering, and file I/O. Keep the public compatibility surface intact by preserving the legacy top-level wrapper while adding as the documented entrypoint. This reduces cross-cutting coupling inside the exporter and makes the runtime/bootstrap behavior easier to evolve without carrying unrelated concerns in one file.
2026-03-29 14:09:24 -05:00
parent 1630a1ab79
commit 9e7e474b05
16 changed files with 818 additions and 893 deletions
@@ -0,0 +1,75 @@
+import copy
+
+from typing import TextIO
+
+from .generator.planner import WorkflowPlanner
+from .generator.render import WorkflowRenderer
+from .io import write_python_output
+from .load_order import LoadOrderDeterminer
+from .workflow_loader import load_frontend_workflow_data, load_workflow_data
+
+
+class ExportApplication:
+    """High-level exporter orchestration."""
+
+    def __init__(
+        self,
+        workflow: str = "",
+        frontend_workflow: str | dict | None = None,
+        input_file: str = "",
+        output_file: str | TextIO = "",
+        queue_size: int = 1,
+        node_class_mappings: dict | None = None,
+        needs_init_custom_nodes: bool = False,
+        node_mapping_loader=None,
+        custom_node_importer=None,
+    ):
+        if input_file and workflow:
+            raise ValueError("Can't provide both input_file and workflow")
+        if not input_file and not workflow:
+            raise ValueError("Needs input_file or workflow")
+        if not output_file:
+            raise ValueError("Needs output_file")
+
+        self.workflow = workflow
+        self.frontend_workflow = frontend_workflow
+        self.input_file = input_file
+        self.output_file = output_file
+        self.queue_size = queue_size
+        self.node_mapping_loader = node_mapping_loader
+        self.custom_node_importer = custom_node_importer
+        self.node_class_mappings = (
+            node_class_mappings
+            if node_class_mappings is not None
+            else self.node_mapping_loader()
+        )
+        self.needs_init_custom_nodes = needs_init_custom_nodes
+        self.base_node_class_mappings = copy.deepcopy(self.node_class_mappings)
+
+    def execute(self) -> None:
+        data = load_workflow_data(self.workflow, self.input_file)
+        metadata_workflow_data = load_frontend_workflow_data(self.frontend_workflow)
+
+        missing_node_types = {
+            node_data["class_type"]
+            for node_data in data.values()
+            if node_data["class_type"] not in self.node_class_mappings
+        }
+        if self.needs_init_custom_nodes or missing_node_types:
+            self.custom_node_importer()
+            self.base_node_class_mappings = copy.deepcopy(self.node_class_mappings)
+
+        load_order = LoadOrderDeterminer(
+            data, self.node_class_mappings
+        ).determine_load_order()
+        plan = WorkflowPlanner(
+            self.node_class_mappings, self.base_node_class_mappings
+        ).build_plan(
+            load_order,
+            data,
+            metadata_workflow_data,
+            queue_size=self.queue_size,
+        )
+        generated_code = WorkflowRenderer().render(plan)
+        write_python_output(self.output_file, generated_code)
+        print(f"Code successfully generated and written to {self.output_file}")