(my_project) ➜  my_project git:(main) ✗ tree
.
├── Dockerfile
├── LICENSE
├── README.md
├── requirements.txt
└── workflows
    ├── __init__.py
    ├── __pycache__
    │   ├── __init__.cpython-311.pyc
    │   └── example.cpython-311.pyc
    ├── example.py
    └── mike
        ├── __pycache__
        │   └── demo.cpython-311.pyc
        └── demo.py

(my_project) ➜  my_project git:(main) ✗ cat workflows/mike/demo.py
def add(a, b):
    return a + b

def minus(a, b):
    return a - b

"""A simple Flyte example."""

import typing
from flytekit import task, workflow

from mike.demo import add, minus

@task
def say_hello(name: str) -> str:
    """A simple Flyte task to say "hello".

    The @task decorator allows Flyte to use this function as a Flyte task, which
    is executed as an isolated, containerized unit of compute.
    """
    print(f"1 + 2 = {add(1, 2)}")
    return f"hello {name}!"


@task
def greeting_length(greeting: str) -> int:
    """A task the counts the length of a greeting."""
    print(f"3 - 1 = {minus(3, 1)}")
    return len(greeting)

@workflow
def wf(name: str = "union") -> typing.Tuple[str, int]:
    """Declare workflow called `wf`.

    The @workflow decorator defines an execution graph that is composed of tasks
    and potentially sub-workflows. In this simple example, the workflow is
    composed of just one task.

    There are a few important things to note about workflows:
    - Workflows are a domain-specific language (DSL) for creating execution
      graphs and therefore only support a subset of Python's behavior.
    - Tasks must be invoked with keyword arguments
    - The output variables of tasks are Promises, which are placeholders for
      values that are yet to be materialized, not the actual values.
    """
    greeting = say_hello(name=name)
    greeting_len = greeting_length(greeting=greeting)
    return greeting, greeting_len


if __name__ == "__main__":
    # Execute the workflow, simply by invoking it like a function and passing in
    # the necessary parameters
    print(f"Running wf() { wf(name='passengers') }")

Dockerfile

(my_project) ➜  my_project git:(main) ✗ python workflows/example.py
1 + 2 = 3
3 - 1 = 2
Running wf() DefaultNamedTupleOutput(o0='hello passengers!', o1=17)
(my_project) ➜  my_project git:(main) ✗ pyflyte run workflows/example.py wf
Failed with Unknown Exception <class 'ModuleNotFoundError'> Reason: No module named 'mike'
No module named 'mike'

simple-example

pyflyte init …

docker_build.sh

BTW, do you have any idea how good Flyte is if we run it locally? I mean can it still orchestrate a fairly complex workflow without using K8s and docker container?