import pandas as pd
from sklearn.datasets import load_wine

from flytekit import task, workflow
from flytekit.configuration import ImageConfig, Config
from flytekit.types.pickle import FlytePickle
from flytekit.remote import FlyteRemote

# 🧱 @task decorators define the building blocks of your pipeline
@task
def get_data() -> pd.DataFrame:
    """Get the wine dataset."""
    return load_wine(as_frame=True).frame


# 🔀 @workflows decorators define the flow of data through the tasks
@workflow
def training_workflow(x:int) -> pd.DataFrame:
    """Put all of the steps together into a single workflow."""
    data = get_data()
    return data


# FlyteRemote object is the main entrypoint to API
remote = FlyteRemote(
    config=Config.auto(),
    default_project="flytesnacks",
    default_domain="development",
)

remote.execute(
    training_workflow,
    inputs={'x':0},
    image_config=ImageConfig.auto_default_image(),
    version="v2"
    )

remote.fast_package

register_script

register_workflow

register_script

register_workflow

pip install -U flytekit