Class DeployClient

azureml.deploy.DeployClient(host, auth=None, use=None)

Defines the factory for creating Deployment Clients.

Basic Usage Module implementation plugin with use property:

Find and Load module from an import reference:

from azureml.deploy import DeployClient
from azureml.deploy.server import MLServer

host = 'http://localhost:12800'
ctx = ('username', 'password')
mls_client = DeployClient(host, use=MLServer, auth=ctx)

Find and Load module as defined by use from namespace str:

host = 'http://localhost:12800'
ctx = ('username', 'password')

mls_client = DeployClient(host, use=MLServer, auth=ctx)
mls_client = DeployClient(host, use='azureml.deploy.server.MLServer',
auth=ctx)

Find and Load module from a file/path tuple:

host = 'http://localhost:12800'
ctx = ('username', 'password')

use = ('azureml.deploy.server.MLServer', '/path/to/mlserver.py')
mls_client = DeployClient(host, use=use, auth=ctx)

Create a new Deployment Client.

Arguments

host

Server HTTP/HTTPS endpoint, including the port number.

auth

(optional) Authentication context. Not all deployment clients require authentication. The auth is required for MLServer

use

(required) Deployment implementation to use (ex) use='MLServer' to use The ML Server.