Merge pull request #23 from qua-platform/fix/run-modes

avoid running node through library

qualibrate_runner/api/dependencies.py

@@ -19,22 +19,29 @@ def get_state() -> State:
 
 
 @cache
-def get_library(
+def get_cached_library(
     settings: Annotated[QualibrateRunnerSettings, Depends(get_settings)],
 ) -> QualibrationLibrary:
     return settings.calibration_library_resolver(
         settings.calibration_library_folder
     )
 
 
-@cache
+def get_library(
+    library: Annotated[QualibrationLibrary, Depends(get_cached_library)],
+    rescan: bool = False,
+) -> QualibrationLibrary:
+    if rescan:
+        library.rescan()
+    return library
+
+
 def get_nodes(
     library: Annotated[QualibrationLibrary, Depends(get_library)],
 ) -> Mapping[str, QualibrationNode]:
     return cast(Mapping[str, QualibrationNode], library.get_nodes())
 
 
-@cache
 def get_graphs(
     library: Annotated[QualibrationLibrary, Depends(get_library)],
 ) -> Mapping[str, QualibrationGraph]:
@@ -61,11 +68,3 @@ def get_graph(
             status_code=422, detail=f"Unknown graph name {name}"
         )
     return graph
-
-
-CACHED_DEPENDENCIES = (get_library, get_nodes, get_graphs)
-
-
-def cache_clear() -> None:
-    for func in CACHED_DEPENDENCIES:
-        func.cache_clear()

qualibrate_runner/api/routes/get_runnables.py

@@ -4,10 +4,6 @@
 from qualibrate.qualibration_graph import QualibrationGraph
 from qualibrate.qualibration_node import QualibrationNode
 
-from qualibrate_runner.api.dependencies import (
-    cache_clear,
-    get_library,
-)
 from qualibrate_runner.api.dependencies import (
     get_graph as get_qgraph,
 )
@@ -20,38 +16,22 @@
 from qualibrate_runner.api.dependencies import (
     get_nodes as get_qnodes,
 )
-from qualibrate_runner.config import (
-    QualibrateRunnerSettings,
-    get_settings,
-)
 
 get_runnables_router = APIRouter()
 
 
 @get_runnables_router.get("/get_nodes")
 def get_nodes(
     nodes: Annotated[Mapping[str, QualibrationNode], Depends(get_qnodes)],
-    settings: Annotated[QualibrateRunnerSettings, Depends(get_settings)],
-    rescan: bool = False,
 ) -> Mapping[str, Any]:
-    if rescan:
-        cache_clear()
-        library = get_library(settings)
-        nodes = get_qnodes(library)
     return {node_name: node.serialize() for node_name, node in nodes.items()}
 
 
 @get_runnables_router.get("/get_graphs")
 def get_graphs(
     graphs: Annotated[Mapping[str, QualibrationNode], Depends(get_qgraphs)],
-    settings: Annotated[QualibrateRunnerSettings, Depends(get_settings)],
-    rescan: bool = False,
     cytoscape: bool = False,
 ) -> Mapping[str, Any]:
-    if rescan:
-        cache_clear()
-        library = get_library(settings)
-        graphs = get_qgraphs(library)
     return {
         graph_name: graph.serialize(cytoscape=cytoscape)
         for graph_name, graph in graphs.items()

qualibrate_runner/core/run_job.py

@@ -1,12 +1,13 @@
 import traceback
 from datetime import datetime
-from typing import Any, Mapping, Type
+from typing import Any, Mapping, Type, cast
 
 from fastapi import HTTPException, status
 from pydantic import BaseModel, ValidationError
 from qualibrate.qualibration_graph import QualibrationGraph
 from qualibrate.qualibration_library import QualibrationLibrary
 from qualibrate.qualibration_node import QualibrationNode
+from qualibrate.run_summary.node import NodeRunSummary
 
 from qualibrate_runner.config import State
 from qualibrate_runner.core.models.last_run import (
@@ -50,11 +51,9 @@ def run_node(
         runnable_type=RunnableType.NODE,
     )
     try:
-        library = get_active_library_or_error()
-        node = library.nodes[node.name]
-        result = library.run_node(
-            node.name, node.parameters_class(**passed_input_parameters)
-        )
+        result = node.run(passed_parameters=passed_input_parameters)
+        result = cast(NodeRunSummary, result)
+        node = QualibrationNode.last_executed_node
     except Exception as ex:
         state.last_run = LastRun(
             name=state.last_run.name,
@@ -104,9 +103,12 @@ def run_workflow(
     try:
         library = get_active_library_or_error()
         workflow = library.graphs[workflow.name]
-        result = library.run_graph(
-            workflow.name,
-            workflow.full_parameters_class(**passed_input_parameters),
+        input_parameters = workflow.full_parameters_class(
+            **passed_input_parameters
+        )
+        result = workflow.run(
+            nodes=input_parameters.nodes.model_dump(),
+            **input_parameters.parameters.model_dump(),
         )
         print("Graph completed. Result:", result)
     except Exception as ex: