Executor is a self-contained component and performs a group of tasks on a
You can create an Executor by extending the
Executor class and adding logic to endpoint methods.
Why should you use Executors?¶
Once you have learned
DocumentArray, you can use all its power and expressiveness to build a neural search application.
But what if you want to go bigger? Organize your code into modules, serve and scale them independently as microservices? That’s exactly what Executors enable you to do.
Executors let you organize your DocumentArray-based functions into logical entities that can share configuration state, following OOP.
Executors convert your local functions into functions that can be distributed inside a Flow.
Executors inside a Flow can process multiple DocumentArrays concurrently, and be deployed easily to the cloud as part of your neural search application.
Executors can be easily containerized and shared with your colleagues using
jina hub push/pull
Minimum working example¶
from jina import Executor, requests class MyExecutor(Executor): @requests def foo(self, docs, **kwargs): print(docs) # process docs here
Executor and Flow are the two fundamental concepts in Jina.