temporal-lib-py 1.3.1

A wrapper library for candid-based temporal authentication

temporal-lib-py

This library provides a partial wrapper for the Client.connect method from temporalio/sdk-python by adding candid-based authentication, Google IAM-based authentication and encryption. It also provides a partial wrapper for the Temporal Worker by adding a Sentry interceptor which can be enabled through config.

Building

This library uses poetry for packaging and managing dependencies. To build the wheel file simply run:

poetry build -f wheel

Usage

Client

The following code shows how a client connection is created by using the original (vanilla) temporalio sdk:

from temporalio.client import Client
async def main():
    client = await Client.connect("localhost:7233")
    ...

In order to add authorization and encryption capabilities to this client we replace the connect call as follows:

Candid-based authorization

from temporallib.client import Client, Options
from temporallib.auth import AuthOptions, MacaroonAuthOptions, KeyPair
from temporallib.encryption import EncryptionOptions
async def main():
    # alternatively options could be loaded from a yaml file as the one showed below
    cfg = Options(
        host="localhost:7233",
        auth=AuthOptions(provider="candid", config=MacaroonAuthOptions(keys=KeyPair(...))),
        encryption=EncryptionOptions(key="key")
        ...
    )
    client = await Client.connect(cfg)
	...

The structure of the YAML file which can be used to construct the Options is as follows:

host: "localhost:7233"
queue: "test-queue"
namespace: "test"
encryption:
  key: "HLCeMJLLiyLrUOukdThNgRfyraIXZk918rtp5VX/uwI="
auth:
  provider: "candid"
  config:
    macaroon_url: "http://localhost:7888/macaroon"
    username: "test"
    keys:
      private: "MTIzNDU2NzgxMjM0NTY3ODEyMzQ1Njc4MTIzNDU2Nzg="
      public: "ODc2NTQzMjE4NzY1NDMyMTg3NjU0MzIxODc2NTQzMjE="
tls_root_cas: |
  'base64 certificate'

Google IAM-based authorization

from temporallib.client import Client, Options
from temporallib.auth import AuthOptions, GoogleAuthOptions
from temporallib.encryption import EncryptionOptions
async def main():
    # alternatively options could be loaded from a yaml file as the one showed below
    cfg = Options(
        host="localhost:7233",
        auth=AuthOptions(provider="google", config=GoogleAuthOptions(private_key=...)),
        encryption=EncryptionOptions(key="key")
        ...
    )
    client = await Client.connect(cfg)
	...

The structure of the YAML file which can be used to construct the Options is as follows:

host: "localhost:7233"
queue: "test-queue"
namespace: "test"
encryption:
  key: "HLCeMJLLiyLrUOukdThNgRfyraIXZk918rtp5VX/uwI="
auth:
  provider: "google"
  config:
    type: "service_account"
    project_id: "REPLACE_WITH_PROJECT_ID"
    private_key_id: "REPLACE_WITH_PRIVATE_KEY_ID"
    private_key: "REPLACE_WITH_PRIVATE_KEY"
    client_email: "REPLACE_WITH_CLIENT_EMAIL"
    client_id: "REPLACE_WITH_CLIENT_ID"
    auth_uri: "https://accounts.google.com/o/oauth2/auth"
    token_uri: "https://oauth2.googleapis.com/token"
    auth_provider_x509_cert_url: "https://www.googleapis.com/oauth2/v1/certs"
    client_x509_cert_url: "REPLACE_WITH_CLIENT_CERT_URL"
tls_root_cas: |
  'base64 certificate'

Worker

The following code shows how a Worker is created by using the original (vanilla) temporalio sdk:

from temporalio.worker import Worker
from temporalio.client import Client
async def main():
    client = await Client.connect("localhost:7233")
    worker = Worker(
        client,
        task_queue=task_queue,
        workflows=workflows,
        activities=activities,
    )
    await worker.run()
    ...

In order to add Sentry logging capabilities to this worker we replace the worker initialization as follows:

from temporallib.worker import Worker, WorkerOptions, SentryOptions
from temporallib.client import Client

client = await Client.connect(cfg)
worker = Worker(
    client,
    task_queue=task_queue,
    workflows=workflows,
    activities=activities,
    worker_opt=WorkerOptions(sentry=SentryOptions(dsn="dsn", release="release", environment="environment", redact_params=True)),
)
await worker.run()

Note that you can optionally enable parameter redaction to hide event parameters that are sent to Sentry.

Samples

More examples of workflows using this library can be found here:

• temporal-lib-samples