Executor File Structure

Besides organizing your Executor code inline-ly (i.e. with Flow.add() in the same file), you can also write it as “extern” module and then use it via YAML. This is useful when your Executor’s logic is too complicated to fit into a single file.

from jina import Executor, Flow, Document, requests


class MyExecutor(Executor):

    @requests
    def foo(self, **kwargs):
        print(kwargs)


f = Flow().add(uses=MyExecutor)

with f:
    f.post(on='/random_work', inputs=Document(), on_done=print)
foo.py
from jina import Executor, Flow, Document, requests


class MyExecutor(Executor):

    @requests
    def foo(self, **kwargs):
        print(kwargs)


f = Flow().add(uses=MyExecutor)

with f:
    f.post(on='/random_work', inputs=Document(), on_done=print)
my.yml
jtype: MyExecutor
metas:
  py_modules:
    - foo.py
  name: awesomeness
  description: my first awesome executor
requests:
  /random_work: foo
flow.py
from jina import Flow, Document

f = Flow().add(uses='my.yml')

with f:
    f.post(on='/random_work', inputs=Document(), on_done=print)

Single Python file

When you are only working with a single python file (let’s call it my_executor.py), you can simply put it at the root of the repository, and import it directly in config.yml

jtype: MyExecutor
metas:
  py_modules:
    - my_executor.py

Multiple Python files

Caution

This way of repository structure is currently not compatible with JinaD, when adding the executor to a Flow using uses='config.yml', as JinaD only supports a flat file structure. In this case, it is recommended that you containerize your executor, and use it with JinaD in your Flow either via uses='jinahub+docker://...' or uses='docker://...'.

When you are working with multiple python files, you should organize them as a Python package and put them in a special folder inside your repository (as you would normally do with Python packages). Specifically, you should do the following:

  • put all your Python files inside a special folder (call it executor, as a convention), and put an __init__.py file inside it

    • because of how Jina registers executors, make sure to import your executor in this file (see the contents of executor/__init__.py in the example below).

  • use relative imports (from .bar import foo, and not from bar import foo) inside the python modules in this folder

  • Only list executor/__init__.py under py_modules in config.yml - this way Python knows that you are importing a package, and makes sure that all the relative imports within your package work properly

To make things more specific, take this repository structure as an example:

.
├── config.yml
└── executor
    ├── helper.py
    ├── __init__.py
    └── my_executor.py

The contents of executor/__init__.py is

from .my_executor import MyExecutor

the contents of executor/helper.py is

def print_something():
    print('something')

and the contents of executor/my_executor.py is

from jina import Executor, requests

from .helper import print_something

class MyExecutor(Executor):
    @requests
    def foo(self, **kwargs):
        print_something()

Finally, the contents of config.yml - notice that only the executor/__init__.py file needs to be listed under py_modules

jtype: MyExecutor
metas:
  py_modules:
    - executor/__init__.py

This was a relatively simple example, but this way of structuring python modules works for any python package structure, however complex. Consider this slightly more complicated example

.
├── config.yml           # Remains exactly the same as before
└── executor
    ├── helper.py
    ├── __init__.py
    ├── my_executor.py
    └── utils/
        ├── __init__.py  # Required inside all executor sub-folders
        ├── data.py
        └── io.py

Here you can then import from utils/data.py in my_executor.py like this: from .utils.data import foo, and do any other kinds of relative imports that python enables.

The best thing is that no matter how complicated your package structure, “importing” it in your config.yml file is super easy - you always put only executor/__init__.py under py_modules.