yellowdog-sdk documentation

Release v15.2.1.

The YellowDog SDK allows you to integrate the YellowDog Platform into your Python applications.

Requirements

Our SDK is tested against all supported versions of Python: https://devguide.python.org/versions/#supported-versions

Versions as early as Python 3.7 should work, but we recommend using a version of Python that is not end-of-life.

Download & Install

Add yellowdog-sdk to your requirements.txt:

yellowdog-sdk==15.2.1

Then install with:

$ pip install -r requirements.txt

Imports are from the yellowdog_client package, e.g.:

from yellowdog_client import PlatformClient

Usage

Authenticating

To start using this SDK, you first need to create an Application in the YellowDog Platform Portal. This provides you with an api key and secret to authenticate with the platform.

The PlatformClient provides access to all functionality and may be constructed as follows:

from yellowdog_client import PlatformClient
from yellowdog_client.model import ServicesSchema, ApiKey

client = PlatformClient.create(
    ServicesSchema(defaultUrl="https://portal.yellowdog.co/api"),
    ApiKey("my_app_key",  "my_app_secret")
)

The PlatformClient is split into several clients, each covering a specific area of functionality. All clients are available as attributes of the PlatformClient.

Compute Client

The ComputeClient allows control of compute requirements, their instances and templates.

Finding data

To retrieve all currently active compute requirements:

requirements = client.compute_client.get_compute_requirements(ComputeRequirementSearch()).list_all()

To retrieve the details of a specific compute requirement:

req_id = "ydid:compreq:000000:6c9343f5-ddd7-4903-bcbf-12c7a6bf1e1a"
requirement = client.compute_client.get_compute_requirement_by_id(req_id)

To get latest status of a compute requirement:

requirement = client.compute_client.get_compute_requirement(requirement)

To retrieve all available compute requirement templates:

templates = client.compute_client.find_all_compute_requirement_templates()

Provisioning

One way to provision compute is to use a template that either you or somebody else has already created in the YellowDog Platform Portal:

from yellowdog_client.model import ComputeRequirementTemplateUsage

request = ComputeRequirementTemplateUsage(
    templateId="ydid:crt:000000:f00646c4-38e6-4c9a-9a40-fdbcc30be0b1",
    requirementName="my requirement for 3 nodes",
    requirementNamespace="MY_PROJECT",
    requirementTag="tests",
    targetInstanceCount=3
)

compute_requirement = client.compute_client.provision_compute_requirement_template(request)

Note

To grant access to a specific cloud provider, you need to have a keyring created in the YellowDog Platform Portal along with credentials for that provider.

In this example, a keyring named MY_KEYRING is used, containing a credential named OCI_CREDENTIAL.

To create a keyring, go to YellowDog Platform Portal, navigate to ACCOUNT -> Keyrings -> Create Keyring

Controlling

With requirements up and running, you can stop, reprovision, or terminate compute requirements, or control individual instances.

Stopping a compute requirement will stop all active instances in the compute requirement:

client.compute_client.stop_compute_requirement(requirement)

Warning

Not all cloud providers support stopping cloud instances.

Starting a compute requirement will start all stopped instances:

client.compute_client.start_compute_requirement(requirement)

Terminating a compute requirement will terminate all active instances:

client.compute_client.terminate_compute_requirement(requirement)

Retrieving instance information for a compute requirement:

instances = client.compute_client.get_instances(InstanceSearch(computeRequirementId=requirement.id)).list_all()

You can also terminate individual instances of a compute requirement.

Stopping individual instances of a compute requirement:

instance1 = instances[0]
instance2 = instances[1]
client.compute_client.stop_instances(requirement, [instance1, instance2])

Starting individual instances of a compute requirement:

client.compute_client.start_instances(requirement, [instance1, instance2])

Restarting individual instances of a compute requirement:

client.compute_client.restart_instances(requirement, [instance1, instance2])

Terminating individual instances of a compute requirement:

client.compute_client.terminate_instances(requirement, [instance1, instance2])

See also

yellowdog_client.compute.ComputeClient

Work Client & Worker Pool Client

The WorkClient allows you to specify the work that you want the YellowDog Scheduler to perform.

The WorkerPoolClient allows to you create worker pools to execute this work.

Finding data

To retrieve all created work requirements:

work_requirements = client.work_client.find_all_work_requirements()

To retrieve information about a work requirement by its id:

req_id = "ydid:workreq:000000:UNIQUE_ID"
work_requirement = client.work_client.get_work_requirement_by_id(req_id)

Provisioning

Provisioned worker pools are linked to compute requirements and created in a similar manner:

from datetime import timedelta
from yellowdog_client.model import ComputeRequirementTemplateUsage
from yellowdog_client.model import ProvisionedWorkerPoolProperties
from yellowdog_client.model import AutoShutdown

worker_pool = client.worker_pool_client.provision_worker_pool(
    ComputeRequirementTemplateUsage(
        templateId="ydid:crt:000000:UNIQUE_ID",
        requirementNamespace="my_tests",
        requirementName="HelloWorldCompute",
        targetInstanceCount=1
    ),
    ProvisionedWorkerPoolProperties(
        idlePoolShutdown=AutoShutdown(timeout=timedelta(seconds=30)),
        workerTag="HelloWorldTag"
    )
)

To create a work requirement, utilizing the above worker pool (linked by tag “HelloWorldTag”):

from yellowdog_client.model import RunSpecification
from yellowdog_client.model import Task
from yellowdog_client.model import TaskGroup
from yellowdog_client.model import WorkRequirement

task = Task(
    name="EchoHelloWorld",
    taskType="docker",
    arguments=["hello-world"]
)

work_requirement = WorkRequirement(
    namespace="my_tests",
    name="HelloWorldWork",
    taskGroups=[
        TaskGroup(
            name="HelloWorldGroup",
            runSpecification=RunSpecification(
                taskTypes=["docker"],
                maxWorkers=1,
                maximumTaskRetries=3,
                workerTags=["HelloWorldTag"]
            )
        )
    ]
)

work_requirement = client.work_client.add_work_requirement(work_requirement)
tasks = client.work_client.add_tasks_to_task_group(work_requirement.taskGroups[0], [task])

By default, a worker pool is decoupled from a specific piece of work. This means that workers in the pool can be claimed by any tasks, as long as those workers are capable of doing those tasks. To accommodate this behaviour, a worker pool is automatically shutdown when it has become idle for 10 minutes. This provides a buffer period for new work to be added before the worker pool is automatically shutdown.

An alternative pattern is to tightly couple a worker pool to specific pieces of work using worker tags (“HelloWorldTag” in this example). Workers with this tag will only be claimed by tasks that also have that tag. When using this pattern, the default autoshutdown period is inefficient and you may either reduce it (as in this example), or add all of your work first and switch off the autoshutdown period entirely.

Controlling

To shut down a worker pool:

client.worker_pool_client.shutdown_worker_pool(compute_requirement.id)

To cancel a work requirement:

client.work_client.cancel_work_requirement(work_requirement)
# WorkRequirement

See also

yellowdog_client.scheduler.WorkClient yellowdog_client.scheduler.WorkerPoolClient

Keyring Client

The KeyringClient allows retrieval of YellowDog keyrings and the addition/removal of credentials from those keyrings.

Finding data

To retrieve all available keyrings:

keyrings = client.keyring_client.find_all_keyrings()

Creating and editing

To create a new keyring:

keyring = client.keyring_client.create_keyring("my_keyring", "My keyring holding all the credentials")

To add new credentials to the keyring:

from yellowdog_client.model import AwsCredential
from yellowdog_client.model import AzureInstanceCredential

aws_credential = AwsCredential(
    name="My aws credential",
    accessKeyId="AWS_ACCESS",
    secretAccessKey="AWS_SECRET"
)

azure_credential = AzureInstanceCredential(
    name="My azure credential",
    adminUserName="my_azure_username",
    adminPassword="my_azure_password"
)

keyring = client.keyring_client.put_credential(keyring, aws_credential)
keyring = client.keyring_client.put_credential(keyring, azure_credential)

See also

yellowdog_client.account.KeyringClient

Images Client

See also

yellowdog_client.images.ImagesClient

Usage Client

See also

yellowdog_client.usage.AllowancesClient

Cloud Info Client

See also

yellowdog_client.cloud_info.CloudInfoClient

API Reference

Contact

YellowDog Limited

https://yellowdog.co/

support@yellowdog.co

License

Please contact support@yellowdog.co for license details.