Flyte enables production-grade orchestration for machine learning workflows and data processing created to accelerate local workflows to production.

Flyte

Does anyone know how to search through runs and outputs in python? I for some reason cannot figure out how to do that. I am trying to see how much metadata I can parse through in python.

Thanks for your help!

hey <@U03KECGDUBU> are you using FlyteRemote? <https://docs.flyte.org/projects/flytekit/en/latest/design/control_plane.html#design-control-plane>

<@U01DYLVUNJE> that looks exactly like what I am looking for! Thank you

On the off chance is there a local version of this? Perhaps to look at a projects local runs?

yep, the cluster you get access to in `FlyteRemote` depends on the `config` argument.

`Config.auto()` will do <https://docs.flyte.org/projects/flytekit/en/latest/generated/flytekit.configuration.Config.html#flytekit.configuration.Config.auto|this> to try and automatically find the config file, but you can use `Config.for_sandbox()` for a `flytectl sandbox` cluster and `Config.for_endpoint()`  for a specific endpoint identified via dns

now that I think of it, not sure if `for_sandbox` will work for a `flytectl demo` -started cluster

<@UNR3C6Y4T> <@U0265RTUJ5B> do you know ^^ ?

Awesome and thank you all for the information! I will give it a shot.

For context some people are talking about <https://www.tensorflow.org/tfx/guide/mlmd|ML Metadata (MLMD)> and like tracking metadata. Flyte inherently does this, the question is what surfacing the information looks like and will be pretty straight forward to investigate.

&gt; Flyte inherently does this, the question is what surfacing the information looks like and will be pretty straight forward to investigate
yes! we’ve been trying to figure out what kinds of utility functions to provide… for example, if we had:

```remote = FlyteRemote(...)
remote.fetch_executions_with_output_type(sklearn.base.BaseEstimator)```
would get all executions with sklearn models as outputs.

If you could articulate your different use cases, we’d love to figure out what those utility functions would be!

Flyte is already a versioned data artifact store and model registry, we just don’t have a seamless interface for that… so please do let us know here (or even on a <https://github.com/flyteorg/flyte/issues/new?assignees=&amp;labels=enhancement%2Cuntriaged&amp;template=feature_request.yaml&amp;title=%5BCore+feature%5D+|feature request> what that interface might look like

That blew my mind. I will talk to <@U03AJ6YUNCS> <@U03JA1VR0SJ> and see if there are requirements anywhere.

<@U01DYLVUNJE> Thanks to your help I can look at executions using python. I was wondering if there was a way to look at the values of inputs and outputs within a workflow?

They show up with `remote.fetch_execution` with a task, but I can’t figure out how to look at individual tasks within a workflow.

So assuming the execution is a workflow:

```execution = remote.fetch_execution(...)

# make sure all the nodes are synced
synced_execution = remote.sync(execution, sync_nodes=True)

# get the node execution inputs/outputs
synced_execution.node_executions["n1"].inputs
synced_execution.node_executions["n1"].outputs["model_file"]```
<https://docs.flyte.org/projects/flytekit/en/latest/design/control_plane.html#retrieving-inspecting-executions>

The you can get all the node keys with
```synced_execution.node_executions.keys()```
I forget now how the node execution keys are named… but that should allow you to get input/output data from tasks / subworkflow executions

Exactly what I needed :slightly_smiling_face: