We provide three ways of using Hub Executors in your project. Each has its own use case and benefits.

Use as-is#

You can use a Hub Executor as-is via Executor.from_hub():

from jina import Executor, Document, DocumentArray

exec = Executor.from_hub('jinahub://DummyHubExecutor')
da = DocumentArray([Document()])
assert da.texts == ['hello']

The Hub Executor will be pulled to your local machine and run as a native Python object. You can use a line-debugger to step in/out exec object, set breakpoints, and observe how it behaves. You can directly feed in a DocumentArray. After you build some confidence in that Executor, you can move to the next step: Using it as a part of your Flow.


Not all Executors on the Hub can be directly run in this way - some require extra dependencies. In that case, you can add .from_hub(..., install_requirements=True) to install the requirements automatically. Be careful - these dependencies may not be compatible with your local packages and may override your local development environment.


Hub Executors are cached locally on the first pull. Afterwards, they will not be updated.

To keep up-to-date with upstream, use .from_hub(..., force_update=True).

Use in Flow as container#

Use prebuilt images from Hub in your Python code:

from jina import Flow

# SECRET must be provided for private Executor
f = Flow().add(uses='jinahub+docker://<UUID>[:<SECRET>][/<TAG>]')

If you do not provide a /<TAG>, it defaults to /latest, which means using the latest tag.


To use a private Executor, you must provide the SECRET which is generated after jina hub push.



If you are a Mac user, please use host.docker.internal as your URL when you want to connect a local port from an Executor Docker container.

For example: PostgreSQLStorage will connect PostgreSQL server which was started locally. Then you must use it with:

from jina import Flow, Document

f = Flow().add(
    uses_with={'hostname': 'host.docker.internal'},
with f:
    resp ='/index', inputs=Document())

When jinahub+docker:// executors are not loading properly or are having issues during initialization, please ensure sufficient Docker resources are allocated.

Mount local volumes#

You can mount volumes into your dockerized Executor by passing a list of volumes to the volumes argument:

f = Flow().add(
    volumes=['host/path:/path/in/container', 'other/volume:/app'],


If you want your containerized Executor to operate inside one of these volumes, remember to set its workspace accordingly!

If you do not specify volumes, Jina will automatically mount a volume into the container. In this case, the volume source will be your default Executor workspace, and the volume destination will be /app. Additionally, automatic volume setting will try to move the Executor’s workspace into the volume destination. Depending on the default executor workspace on your system this may not always succeed, so explicitly mounting a volume and setting a workspace is recommended.

You can disable automatic volume setting by passing f.add(..., disable_auto_volume=True).

Use in Flow via source code#

Use the source code from Hubble in your Python code:

from jina import Flow

f = Flow().add(uses='jinahub://<UUID>[:<SECRET>][/<TAG>]')

Set/override default parameters#

The default parameters of the published Executor may not be ideal for your use case. You can override any of these by passing uses_with and uses_metas as parameters.

from jina import Flow

f = Flow().add(
    uses_with={'param1': 'new_value'},
    uses_metas={'name': 'new_name'},

Pull only#

You can also use jina hub CLI to pull an Executor without actually using it in the Flow.

Pull the Docker image#

jina hub pull jinahub+docker://<UUID>[:<SECRET>][/<TAG>]

You can find the Executor by running docker images. You can also indicate which version of the Executor you want to use by naming the /<TAG>.

jina hub pull jinahub+docker://DummyExecutor/v1.0.0

Pull the source code#

jina hub pull jinahub://<UUID>[:<SECRET>][/<TAG>]

The source code of the Executor will be stored at ~/.jina/hub-packages.