Getting started with the Dapr client Python SDK

How to get up and running with the Dapr Python SDK

The Dapr client package allows you to interact with other Dapr applications from a Python application.

Prerequisites

Install the Dapr Python package before getting started.

Import the client package

The dapr package contains the DaprClient, which is used to create and use a client.

from dapr.clients import DaprClient

Initialising the client

You can initialise a Dapr client in multiple ways:

Default values:

When you initialise the client without any parameters it will use the default values for a Dapr sidecar instance (127.0.0.1:50001).

from dapr.clients import DaprClient

with DaprClient() as d:
    # use the client

Specifying an endpoint on initialisation:

When passed as an argument in the constructor, the gRPC endpoint takes precedence over any configuration or environment variable.

from dapr.clients import DaprClient

with DaprClient("mydomain:50051?tls=true") as d:
    # use the client

Environment variables:

Dapr Sidecar Endpoints

You can use the standardised DAPR_GRPC_ENDPOINT environment variable to specify the gRPC endpoint. When this variable is set, the client can be initialised without any arguments:

export DAPR_GRPC_ENDPOINT="mydomain:50051?tls=true"
from dapr.clients import DaprClient

with DaprClient() as d:
    # the client will use the endpoint specified in the environment variables

The legacy environment variables DAPR_RUNTIME_HOST, DAPR_HTTP_PORT and DAPR_GRPC_PORT are also supported, but DAPR_GRPC_ENDPOINT takes precedence.

Dapr API Token

If your Dapr instance is configured to require the DAPR_API_TOKEN environment variable, you can set it in the environment and the client will use it automatically.
You can read more about Dapr API token authentication here.

Building blocks

The Python SDK allows you to interface with all of the Dapr building blocks.

Invoke a service

from dapr.clients import DaprClient

with DaprClient() as d:
    # invoke a method (gRPC or HTTP GET)    
    resp = d.invoke_method('service-to-invoke', 'method-to-invoke', data='{"message":"Hello World"}')

    # for other HTTP verbs the verb must be specified
    # invoke a 'POST' method (HTTP only)    
    resp = d.invoke_method('service-to-invoke', 'method-to-invoke', data='{"id":"100", "FirstName":"Value", "LastName":"Value"}', http_verb='post')

Save & get application state

from dapr.clients import DaprClient

with DaprClient() as d:
    # Save state
    d.save_state(store_name="statestore", key="key1", value="value1")

    # Get state
    data = d.get_state(store_name="statestore", key="key1").data

    # Delete state
    d.delete_state(store_name="statestore", key="key1")

Query application state (Alpha)

    from dapr import DaprClient

    query = '''
    {
        "filter": {
            "EQ": { "state": "CA" }
        },
        "sort": [
            {
                "key": "person.id",
                "order": "DESC"
            }
        ]
    }
    '''

    with DaprClient() as d:
        resp = d.query_state(
            store_name='state_store',
            query=query,
            states_metadata={"metakey": "metavalue"},  # optional
        )

Publish & subscribe to messages

Publish messages

from dapr.clients import DaprClient

with DaprClient() as d:
    resp = d.publish_event(pubsub_name='pubsub', topic_name='TOPIC_A', data='{"message":"Hello World"}')

Subscribe to messages

from cloudevents.sdk.event import v1
from dapr.ext.grpc import App
import json

app = App()

# Default subscription for a topic
@app.subscribe(pubsub_name='pubsub', topic='TOPIC_A')
def mytopic(event: v1.Event) -> None:
    data = json.loads(event.Data())
    print(f'Received: id={data["id"]}, message="{data ["message"]}"' 
          ' content_type="{event.content_type}"',flush=True)

# Specific handler using Pub/Sub routing
@app.subscribe(pubsub_name='pubsub', topic='TOPIC_A',
               rule=Rule("event.type == \"important\"", 1))
def mytopic_important(event: v1.Event) -> None:
    data = json.loads(event.Data())
    print(f'Received: id={data["id"]}, message="{data ["message"]}"' 
          ' content_type="{event.content_type}"',flush=True)

Interact with output bindings

from dapr.clients import DaprClient

with DaprClient() as d:
    resp = d.invoke_binding(binding_name='kafkaBinding', operation='create', data='{"message":"Hello World"}')

Retrieve secrets

from dapr.clients import DaprClient

with DaprClient() as d:
    resp = d.get_secret(store_name='localsecretstore', key='secretKey')

Configuration

Get configuration

from dapr.clients import DaprClient

with DaprClient() as d:
    # Get Configuration
    configuration = d.get_configuration(store_name='configurationstore', keys=['orderId'], config_metadata={})

Subscribe to configuration

import asyncio
from time import sleep
from dapr.clients import DaprClient

async def executeConfiguration():
    with DaprClient() as d:
        storeName = 'configurationstore'

        key = 'orderId'

        # Wait for sidecar to be up within 20 seconds.
        d.wait(20)

        # Subscribe to configuration by key.
        configuration = await d.subscribe_configuration(store_name=storeName, keys=[key], config_metadata={})
        while True:
            if configuration != None:
                items = configuration.get_items()
                for key, item in items:
                    print(f"Subscribe key={key} value={item.value} version={item.version}", flush=True)
            else:
                print("Nothing yet")
        sleep(5)

asyncio.run(executeConfiguration())

Distributed Lock

from dapr.clients import DaprClient

def main():
    # Lock parameters
    store_name = 'lockstore'  # as defined in components/lockstore.yaml
    resource_id = 'example-lock-resource'
    client_id = 'example-client-id'
    expiry_in_seconds = 60

    with DaprClient() as dapr:
        print('Will try to acquire a lock from lock store named [%s]' % store_name)
        print('The lock is for a resource named [%s]' % resource_id)
        print('The client identifier is [%s]' % client_id)
        print('The lock will will expire in %s seconds.' % expiry_in_seconds)

        with dapr.try_lock(store_name, resource_id, client_id, expiry_in_seconds) as lock_result:
            assert lock_result.success, 'Failed to acquire the lock. Aborting.'
            print('Lock acquired successfully!!!')

        # At this point the lock was released - by magic of the `with` clause ;)
        unlock_result = dapr.unlock(store_name, resource_id, client_id)
        print('We already released the lock so unlocking will not work.')
        print('We tried to unlock it anyway and got back [%s]' % unlock_result.status)

Workflow

from dapr.ext.workflow import WorkflowRuntime, DaprWorkflowContext, WorkflowActivityContext
from dapr.clients import DaprClient

instanceId = "exampleInstanceID"
workflowComponent = "dapr"
workflowName = "hello_world_wf"
eventName = "event1"
eventData = "eventData"

def main():
    with DaprClient() as d:
        host = settings.DAPR_RUNTIME_HOST
        port = settings.DAPR_GRPC_PORT
        workflowRuntime = WorkflowRuntime(host, port)
        workflowRuntime = WorkflowRuntime()
        workflowRuntime.register_workflow(hello_world_wf)
        workflowRuntime.register_activity(hello_act)
        workflowRuntime.start()

        # Start the workflow
        start_resp = d.start_workflow(instance_id=instanceId, workflow_component=workflowComponent,
                        workflow_name=workflowName, input=inputData, workflow_options=workflowOptions)
        print(f"start_resp {start_resp.instance_id}")

        # ...

        # Pause Test
        d.pause_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        print(f"Get response from {workflowName} after pause call: {getResponse.runtime_status}")

        # Resume Test
        d.resume_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        print(f"Get response from {workflowName} after resume call: {getResponse.runtime_status}")
        
        sleep(1)
        # Raise event
        d.raise_workflow_event(instance_id=instanceId, workflow_component=workflowComponent,
                    event_name=eventName, event_data=eventData)

        sleep(5)
        # Purge Test
        d.purge_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        try:
            getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        except DaprInternalError as err:
            if nonExistentIDError in err._message:
                print("Instance Successfully Purged")

        
        # Kick off another workflow for termination purposes 
        # This will also test using the same instance ID on a new workflow after
        # the old instance was purged
        start_resp = d.start_workflow(instance_id=instanceId, workflow_component=workflowComponent,
                        workflow_name=workflowName, input=inputData, workflow_options=workflowOptions)
        print(f"start_resp {start_resp.instance_id}")

        # Terminate Test
        d.terminate_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        sleep(1)
        getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        print(f"Get response from {workflowName} after terminate call: {getResponse.runtime_status}")

        # Purge Test
        d.purge_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        try:
            getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
        except DaprInternalError as err:
            if nonExistentIDError in err._message:
                print("Instance Successfully Purged")

        workflowRuntime.shutdown()

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