Hi gang,
Is there any reasonable way to make asyncio and kedro work together? I have some external IO client that provides only async interface and I can't make it work from sync context, since there is already a running and managed asyncio loop somewhere in kedro. Do coroutines as kedro nodes make any sense?

hi, does kedro support out of the box google cloud logging lib in logging formats? I am not clear on the documentation how advanced adding custom handlers is possible or do I have to do it manually? When would it be better to initialize? After or before kedro loading?

Hi, I'm testing after upgrading to 0.19.9 and I found what seems like a bug - after running the pipeline for the second time with a runner (like during test cases) the output is no longer saved (in catalog or returned as a value from pipeline). That wasn't the case in 0.19.8

Hi, I have a weird bug to report, but I'm not sure how to investigate it/debug. After adding some benign changes to pipeline registry, kedro-viz (9.2.0) started to randomly crash with javascript type error at some pipelines (resulting in whole screen going white-blank and needs to refresh). Those are the changes between commits (before commit all works fine, after commit it consistently crashes on some (seemingly somewhat random - the lower the pipe in the list the higher chance to crash) subset of pipelines with uncaught exception). That's the whole diff of the commit:

@@ -79,7 +79,16 @@ def register_pipelines() -> dict[str, Pipeline]:
             group_class, input_schema, pipelines[f"training_{group_class}"], pipelines[f"inference_{group_class}"]
         )
 
-    pipelines = {k: pipelines[k] for k in sorted(pipelines.keys())}  # sorting for kedro-viz selection box
-    pipelines["__default__"] = sum(pipelines[f"training_and_inference_{gc}"] for gc in GROUP_CLASSES)  # type: ignore

+    # pipelines = {k: pipelines[k] for k in sorted(pipelines.keys())}  # sorting for kedro-viz selection box
+    order = ["input", "data", "feature", "fgu", "layer", "pricing", "inference", "training"]
+    pipelines = {
+        k: pipelines[k]
+        for k in sorted(
+            pipelines.keys(),
+            key=lambda x: str(order.index(x.split("_")[0]) if x.split("_")[0] in order else len(order)) + x,
+        )
+    } # reordering pipelines in kedro-viz based on order list
+    pipelines["__default__"] = pipelines["input_na"]