Basics#

In this section, you’ll learn how to use the basic building blocks of Flyte using flytekit. flytekit is a python SDK for developing flyte workflows and task and can be used generally, whenever stateful computation is desirable. flytekit-developed workflows and tasks are completely runnable locally, unless they need some advanced backend functionality like starting a distributed spark cluster.

In this section we’ll take a look at how to write flyte tasks, compose them together to form a workflow, and then read, manipulate and cache data.

Hello World

Hello World

Tasks

Tasks

Workflows

Workflows

Imperative Workflows

Imperative Workflows

Add Docstrings to Workflows

Add Docstrings to Workflows

Launch Plans

Launch Plans

Flyte Decks

Flyte Decks

Caching

Caching

Run Bash Scripts Using ShellTask

Run Bash Scripts Using ShellTask

Reference Task

Reference Task

Reference Launch Plan

Reference Launch Plan

Working With Files

Working With Files

Working With Folders

Working With Folders

Named Outputs

Named Outputs

Decorating Tasks

Decorating Tasks

Decorating Workflows

Decorating Workflows

Cache Serializing

Cache Serializing

Gallery generated by Sphinx-Gallery