Quickstart

Let’s get you up and running with your first workflow.

What you’ll need

Python 3.10+ in a virtual environment
Access to a Union/Flyte instance (you’ll need the URL and a project where you can run workflows)

Install the SDK

Install the flyte package (currently in beta, so prerelease flag required):

pip install --pre flyte

Verify it worked:

flyte --version

Configure your connection

Create a config file pointing to your Union instance. Replace the placeholder values with your actual endpoint and project name:

            
        
flyte create config \
    --endpoint my-org.my-company.com \
    --domain development \
    --project my-project \
    --builder remote

This creates ./.flyte/config.yaml in your current directory. See Setting up a configuration file for more options.

Run flyte get config to check which configuration is currently active.

Write your first workflow

Create hello.py:

hello.py

# hello.py

import flyte

# The `hello_env` TaskEnvironment is assigned to the variable `env`.
# It is then used in the `@env.task` decorator to define tasks.
# The environment groups configuration for all tasks defined within it.
env = flyte.TaskEnvironment(name="hello_env")

# We use the `@env.task` decorator to define a task called `fn`.
@env.task
def fn(x: int) -> int: # Type annotations are required
    slope, intercept = 2, 5
    return slope * x + intercept

# We also use the `@env.task` decorator to define another task called `main`.
# This is the is the entrypoint task of the workflow.
# It calls the `fn` task defined above multiple times using `flyte.map`.
@env.task
def main(x_list: list[int] = list(range(10))) -> float:
    y_list = list(flyte.map(fn, x_list)) # flyte.map is like Python map, but runs in parallel.
    y_mean = sum(y_list) / len(y_list)
    return y_mean

Here’s what’s happening:

TaskEnvironment specifies configuration for your tasks (container image, resources, etc.)
@env.task turns Python functions into tasks that run remotely
Both tasks share the same env, so they’ll have identical configurations

Run it

With your config file in place:

            
        
.
├── hello.py
└── .flyte
    └── config.yaml

Run the workflow:

flyte run hello.py main

This packages your code and sends it to your Union/Flyte instance for execution.

See the results

You’ll see output like:

            
        
cg9s54pksbjsdxlz2gmc
https://my-instance.example.com/v2/runs/project/my-project/domain/development/cg9s54pksbjsdxlz2gmc
Run 'a0' completed successfully.

Click the link to view your run in the UI:

V2 UI

Next steps

Now that you’ve run your first workflow:

Why Flyte?: Understand what makes Flyte different
Flyte basics: Learn core concepts through working examples