"""
Inspecting Workflow and Task Executions
---------------------------------------

Flytectl
========

Flytectl supports inspecting execution by retrieving its details. For a deeper dive, refer to the
`API reference <https://docs.flyte.org/projects/flytectl/en/stable/gen/flytectl_get_execution.html>`__ guide.

Monitor the execution by providing the execution id from create command which can be task or workflow execution. ::

    flytectl get execution -p flytesnacks -d development <execid>

For more details use ``--details`` flag which shows node executions along with task executions on them. ::

    flytectl get execution -p flytesnacks -d development <execid> --details

If you prefer to see yaml/json view for the details then change the output format using the -o flag. ::

    flytectl get execution -p flytesnacks -d development <execid> --details -o yaml

To see the results of the execution you can inspect the node closure outputUri in detailed yaml output. ::

    "outputUri": "s3://my-s3-bucket/metadata/propeller/flytesnacks-development-<execid>/n0/data/0/outputs.pb"


FlyteRemote
===========

With FlyteRemote, you can fetch the inputs and outputs of executions and inspect them.

.. code-block:: python

    from flytekit.remote import FlyteRemote

    # FlyteRemote object is the main entrypoint to API
    remote = FlyteRemote(
        config=Config.for_endpoint(endpoint="flyte.example.net"),
        default_project="flytesnacks",
        default_domain="development",
    )
    
    execution = remote.fetch_execution(
        name="fb22e306a0d91e1c6000", project="flytesnacks", domain="development"
    )

    input_keys = execution.inputs.keys()
    output_keys = execution.outputs.keys()

    # The inputs and outputs correspond to the top-level execution or the workflow itself.
    # To fetch a specific output, say, a model file:
    model_file = execution.outputs["model_file"]
    with open(model_file) as f:
        ...

    # You can use FlyteRemote.sync() to sync the entity object's state with the remote state during the execution run.
    synced_execution = remote.sync(execution, sync_nodes=True)
    node_keys = synced_execution.node_executions.keys()

    # node_executions will fetch all the underlying node executions recursively.
    # To fetch output of a specific node execution:
    node_execution_output = synced_execution.node_executions["n1"].outputs["model_file"]

"""