YAML specification#

This page outlines the Executor YAML file specification. These configurations can be used in a Deployment with Deployment(uses='exec.yml), in a Flow with Flow().add(uses='exec.yml) or loaded directly via Executor.load_config('exec.yml').

Note that Executor YAML configuration always refers back to an Executor defined in a Python file.

Example#

The following is an example Executor configuration:

jtype: MyExecutor
with:
  match_args: {}
py_modules:
  - executor.py
metas:
  name: Indexer
  description: Indexes all Documents
  url: https://github.com/janedoe/indexer
  keywords: ['indexer', 'executor']

Keywords#

jtype#

String specifying the Executor’s Python type. Used to locate the correct class in the Python files given by py_modules.

with#

Collection containing keyword arguments passed to the Executor’s __init__() method. Valid values depend on the Executor.

py_modules#

List of strings defining the Executor’s Python dependencies. Most notably this must include the Python file containing the Executor definition itself, as well as any other files it imports.

metas#

Collection containing meta-information about the Executor.

Your Executor is annotated with this information when publishing to Executor Hub. To get better appeal on Executor Hub, set the metas fields to the correct values:

  • name: Human-readable name of the Executor.

  • description: Human-readable description of the Executor.

  • url: URL of where to find more information about the Executor, normally a GitHub repo URL.

  • keywords: A list of strings to help users filter and locate your package.