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Manage workflows

Retrieve workflow

By ID

2.3.1

Retrieve an existing workflow by its ID:

Coming soon

Retrieve workflow by its ID
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from pyatlan.client.atlan import AtlanClient

client = AtlanClient()

result = client.workflow.find_by_id(  # (1)
    id="atlan-snowflake-miner-1714638976"
)
  1. You can find a workflow by its identifier using the find_by_id() method of the workflow client, providing the id for the specific workflow. In this example, we're retrieving the SnowflakeMiner workflow.

Coming soon

By type

1.9.5 1.10.6

Retrieve existing workflows by its type:

Retrieve workflows by its type
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List<WorkflowSearchResult> results = WorkflowSearchRequest // (1)
            .findByType(SnowflakeMiner.PREFIX, 5); // (2)
  1. You can search for existing workflows through the WorkflowSearchRequest class.
  2. You can find workflows by their type using the findByType() helper method and providing the prefix for one of the packages. In this example, we do so for the SnowflakeMiner. (You can also specify the maximum number of resulting workflows you want to retrieve as results.)
Retrieve workflows by its type
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from pyatlan.client.atlan import AtlanClient
from pyatlan.model.enums import WorkflowPackage

client = AtlanClient()

results = client.workflow.find_by_type(  # (1)
    prefix=WorkflowPackage.SNOWFLAKE_MINER, max_results=5
)
  1. You can find workflows by their type using the workflow client find_by_type()method and providing the prefix for one of the packages. In this example, we do so for the SnowflakeMiner. (You can also specify the maximum number of resulting workflows you want to retrieve as results.)
Retrieve workflows by its type
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var results = WorkflowSearchRequest // (1)
            .findByType(SnowflakeMiner.PREFIX, 5); // (2)
  1. You can search for existing workflows through the WorkflowSearchRequest class.
  2. You can find workflows by their type using the findByType() helper method and providing the prefix for one of the packages. In this example, we do so for the SnowflakeMiner. (You can also specify the maximum number of resulting workflows you want to retrieve as results.)

Update workflow source credentials

1.8.4 1.9.0

To update workflow source credentials for example, for Snowflake:

Update workflow source credentials
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AtlanClient client = Atlan.getDefaultClient()

Credential snowflakeCredential = client.credentials.get( // (1)
    "972a87c1-28d7-8bf2-896d-ea5bd3e9c691"
    ).toCredential()
    .authType("basic") // (2)
    .username("username") // (3)
    .password("password")
    .extra("role", "role-here")
    .extra("warehouse", "warehouse-here")
    .build() // (4)

CredentialResponse response = snowflakeCredential.update() // (5)
  1. You can retrieve the workflow credential object by providing its GUID.
  2. You must specify the authentication type of the credential.
  3. You must provide the sensitive details such as the username, password, and extra when updating credentials. This behavior aligns with the Atlan workflow config update UI.
  4. Build the minimal Credential object.
  5. Now, use the update() method of the Credential object to update this new credentials in Atlan after initially testing it for successful validation.
Update workflow source credentials
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from pyatlan.client.atlan import AtlanClient

client = AtlanClient()

snowflake_credential = client.credentials.get(
    guid="972a87c1-28d7-8bf2-896d-ea5bd3e9c691"
).to_credential() # (1)

# Basic Authentication
snowflake_credential.auth_type = "basic" # (2)
snowflake_credential.username = "username" # (3)
snowflake_credential.password = "password"
snowflake_credential.extras = {
    "role": "role-here",
    "warehouse": "warehouse-here",
}

response = client.credentials.test_and_update( # (4)
    credential=snowflake_credential
)
  1. You can retrieve the workflow credential object by providing its GUID.
  2. You must specify the authentication type of the credential.
  3. You must provide the sensitive details such as the username, password, and extras when updating credentials. This behavior aligns with the Atlan workflow config update UI.
  4. Now, pass the credential object to the test_and_update() method to update this new credentials in Atlan after initially testing it to confirm its successful validation.
Update workflow source credentials
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val client = Atlan.getDefaultClient()

val snowflakeCredential = client.credentials.get( // (1)
    "972a87c1-28d7-8bf2-896d-ea5bd3e9c691"
    ).toCredential()
    .authType("basic") // (2)
    .username("username") // (3)
    .password("password")
    .extra("role", "role-here")
    .extra("warehouse", "warehouse-here")
    .build() // (4)

val response = snowflakeCredential.update() // (5)
  1. You can retrieve the workflow credential object by providing its GUID.
  2. You must specify the authentication type of the credential.
  3. You must provide the sensitive details such as the username, password, and extra when updating credentials. This behavior aligns with the Atlan workflow config update UI.
  4. Build the minimal Credential object.
  5. Now, use the update() method of the Credential object to update this new credentials in Atlan after initially testing it for successful validation.

Update workflow configuration

2.3.1

To update workflow configuration for example, for Snowflake:

Coming soon

Update workflow configuration
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from pyatlan.client.atlan import AtlanClient

client = AtlanClient()

result = client.workflow.find_by_id(  # (1)
    id="atlan-snowflake-1714638976"
)

workflow_task = result.source.spec.templates[0].dag.tasks[0]
workflow_params = workflow_task.arguments.parameters # (2)

for option in workflow_params:
    if option.name == "enable-lineage": # (3)
        option.value = True

response = client.workflow.update(workflow=result.to_workflow()) # (4)
  1. You can find a workflow by its identifier using the find_by_id() method of the workflow client, providing the id for the specific workflow. In this example, we're retrieving the Snowflake workflow for an update.
  2. Retrieve the workflow template and specific task that you need to update.
  3. Update the specific workflow parameter. In this example, we're enabling lineage for the Snowflake workflow.
  4. Convert the workflow search result object to a workflow object and pass that to the update() method to actually perform the workflow update in Atlan.

Coming soon

Retrieve workflow run

By ID

2.4.2

Retrieve an existing workflow run by its ID:

Coming soon

Retrieve workflow run by its ID
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from pyatlan.client.atlan import AtlanClient

client = AtlanClient()

result = client.workflow.find_run_by_id(  # (1)
    id="atlan-snowflake-miner-1714638976-mzdza"
)
  1. You can find a workflow run by its identifier using the find_run_by_id() method of the workflow client, providing the id for the specific workflow run. In this example, we're retrieving the existing SnowflakeMiner workflow run.

Coming soon

Retrieve all workflow runs

2.1.8

By their phase:

To retrieve all existing workflow runs based on their phase, such as Succeeded, Running, Failed, etc

Coming soon

Retrieve all workflow runs by their phase
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from pyatlan.client.atlan import AtlanClient
from pyatlan.model.enums import AtlanWorkflowPhase

client = AtlanClient()

response = client.workflow.get_runs(
    workflow_name="atlan-snowflake-miner-1714638976",
    workflow_phase=AtlanWorkflowPhase.RUNNING,
    from_=0,
    size=100,
) # (1)

  1. To retrieve all existing workflow runs based on their phase, you need to specify:

    • name of the workflow as displayed in the UI, eg: atlan-snowflake-miner-1714638976.
    • phase of the given workflow (e.g: Succeeded, Running, Failed, etc)
    • starting index of the search results (default: 0).
    • maximum number of search results to return (default: 100).

Coming soon

Stop a running workflow

2.1.8

To stop a running workflow:

Coming soon

Retrieve all workflow runs by their phase
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from pyatlan.client.atlan import AtlanClient

client = AtlanClient()

runs = client.workflow.get_runs(
    workflow_name="atlan-snowflake-miner-1714638976",
    workflow_phase=AtlanWorkflowPhase.RUNNING,
) # (1)

response = client.workflow.stop(
    workflow_run_id=runs[0].id
) # (2)
  1. First, retrieve all existing running workflows.
  2. From the list of existing running workflows, provide the identifier of the specific workflow run to the client.workflow.stop() method, e.g: atlan-snowflake-miner-1714638976-9wfxz.

Delete a workflow

2.1.8

To delete a workflow:

Coming soon

Delete a workflow
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from pyatlan.client.atlan import AtlanClient

client = AtlanClient()

client.workflow.delete(
    workflow_name="atlan-snowflake-miner-1714638976"
) # (1)

  1. To delete an existing workflow, specify:

    • name of the workflow as displayed in the UI (e.g: atlan-snowflake-miner-1714638976).

Coming soon