Coding in Python/YAML#

In the docs, you often see two coding styles when describing a Jina project:

Pythonic#: Flows, Deployments and Executors are all written in Python files, and the entrypoint is via Python.
YAMLish#: Executors are written in Python files, and the Deployment or Flow are defined in a YAML file. The entrypoint can still be used via Python or the Jina CLI jina deployment --uses deployment.yml or jina flow --uses flow.yml.

For example, the server-side code follows the Pythonic style. It can be written in YAMLish style as follows:

executor.py

from jina import Executor, requests
from docarray import DocList
from docarray.documents import TextDoc


class FooExec(Executor):
    @requests
    async def add_text(self, docs: DocList[TextDoc], **kwargs) -> DocList[TextDoc]:
        for d in docs:
            d.text += 'hello, world!'


class BarExec(Executor):
    @requests
    async def add_text(self, docs: DocList[TextDoc], **kwargs) -> DocList[TextDoc]:
        for d in docs:
            d.text += 'goodbye!'

flow.yml

jtype: Flow
with:
  port: 12345
executors:
- uses: FooExec
  replicas: 3
  py_modules: executor.py
- uses: BarExec
  replicas: 2
  py_modules: executor.py

Entrypoint

jina flow --uses flow.yml

In general, the YAML style can be used to represent and configure a Flow or Deployment which are the objects orchestrating the serving of Executors and applications. The YAMLish style separates the Flow or Deployment representation from the Executor logic code. It is more flexible to configure and should be used for more complex projects in production. In many integrations such as JCloud and Kubernetes, YAMLish is preferred.

Note that the two coding styles can be converted to each other easily. To load a Flow YAML into Python and run it:

from jina import Flow

f = Flow.load_config('flow.yml')

with f:
    f.block()

To dump a Flow into YAML:

from jina import Flow

Flow().add(uses=FooExec, replicas=3).add(uses=BarExec, replicas=2).save_config(
    'flow.yml'
)

Hint: YAML and Python duality (with, add, uses_with)

If you are used to the Pythonic way of building Deployments and Flows, and then you need to start working with YAML, a good way to think about this translation is to think of YAML as a direct translation of what you would type in Python.

So, every with clause is like an instantiation of an object, be it a Flow, Deployment or Executor (a call to its constructor). And when a Flow has a list of Executors, each entry on the list is a call to the Flow’s add() method. This is why Deployments and Flows sometimes need the argument uses_with to override the Executor’s defaults.