Connection delete package
The connection delete package deletes a connection and all its related assets.
Soft-delete (archive) assets
To soft-delete (archive) all assets in a connection:
- Java
- Python
- Kotlin
- Raw REST API
Workflow workflow = ConnectionDelete.creator( // (1)
"default/snowflake/1234567890", false // (2)
).build() // (3)
.toWorkflow(); // (4)
WorkflowResponse response = workflow.run(client); // (5)
-
The
ConnectionDeletepackage will create a workflow to delete a connection and its assets using thecreator()method. -
You need to provide the following:
- qualified name of the connection whose assets should be deleted.
- whether to permanently delete the connection and its assets (hard-delete) (
true), or only archive (soft-delete) them (false).
-
Build the minimal package object.
-
Convert the package into a
Workflowobject. -
Run the workflow using the
run()method on the object you've created. Because this operation will execute work in Atlan, you must provide it anAtlanClientthrough which to connect to the tenant.Workflows run asynchronously
Remember that workflows run asynchronously. See the packages and workflows introduction for details on how to check the status and wait until the workflow has been completed. :::
from pyatlan.client.atlan import AtlanClient
from pyatlan.model.packages import ConnectionDelete
client = AtlanClient()
workflow = ConnectionDelete( # (1)
qualified_name="default/snowflake/1234567890", purge=False # (2)
).to_workflow() # (3)
response = client.workflow.run(workflow) # (4)
-
The
ConnectionDeletepackage will create a workflow to delete a connection and its assets. -
You need to provide the following:
- qualified name of the connection whose assets should be deleted.
- whether to permanently delete the connection and its assets
(hard-delete) (
True), or only archive (soft-delete) them (False).
-
Convert the package into a
Workflowobject. -
Run the workflow by invoking the
run()method on the workflow client, passing the created object.Workflows run asynchronously
Remember that workflows run asynchronously. See the packages and workflows introduction for details on how to check the status and wait until the workflow has been completed. :::
val workflow = ConnectionDelete.creator( // (1)
"default/snowflake/1234567890", false // (2)
).build() // (3)
.toWorkflow() // (4)
val response = workflow.run(client) // (5)
-
The
ConnectionDeletepackage will create a workflow to delete a connection and its assets using thecreator()method. -
You need to provide the following:
- qualified name of the connection whose assets should be deleted.
- whether to permanently delete the connection and its assets (hard-delete) (
true), or only archive (soft-delete) them (false).
-
Build the minimal package object.
-
Convert the package into a
Workflowobject. -
Run the workflow using the
run()method on the object you've created. Because this operation will execute work in Atlan, you must provide it anAtlanClientthrough which to connect to the tenant.Workflows run asynchronously
Remember that workflows run asynchronously. See the packages and workflows introduction for details on how to check the status and wait until the workflow has been completed. :::
We recommend creating the workflow only via the UI. To rerun an existing workflow, see the steps below.
Hard-delete (purge) assets
A hard-delete (purge) is permanent and irreversible. Be certain that you want to entirely remove all of the assets in a connection before running in this way!
To hard-delete (purge) all assets in a connection:
- Java
- Python
- Kotlin
- Raw REST API
Workflow workflow = ConnectionDelete.creator( // (1)
"default/snowflake/1234567890", true // (2)
).build() // (3)
.toWorkflow(); // (4)
WorkflowResponse response = workflow.run(client); // (5)
-
The
ConnectionDeletepackage will create a workflow to delete a connection and its assets using thecreator()method. -
You need to provide the following:
- qualified name of the connection whose assets should be deleted.
- whether to permanently delete the connection and its assets (hard-delete) (
true), or only archive (soft-delete) them (false).
-
Build the minimal package object.
-
Convert the package into a
Workflowobject. -
Run the workflow using the
run()method on the object you've created. Because this operation will execute work in Atlan, you must provide it anAtlanClientthrough which to connect to the tenant.Workflows run asynchronously
Remember that workflows run asynchronously. See the packages and workflows introduction for details on how to check the status and wait until the workflow has been completed. :::
from pyatlan.client.atlan import AtlanClient
from pyatlan.model.packages import ConnectionDelete
client = AtlanClient()
workflow = ConnectionDelete( # (1)
qualified_name="default/snowflake/1234567890", purge=True # (2)
).to_workflow() # (3)
response = client.workflow.run(workflow) # (4)
-
The
ConnectionDeletepackage will create a workflow to delete a connection and its assets. -
You need to provide the following:
- qualified name of the connection whose assets should be deleted.
- whether to permanently delete the connection and its assets
(hard-delete) (
True), or only archive (soft-delete) them (False).
-
Convert the package into a
Workflowobject. -
Run the workflow by invoking the
run()method on the workflow client, passing the created object.Workflows run asynchronously
Remember that workflows run asynchronously. See the packages and workflows introduction for details on how to check the status and wait until the workflow has been completed. :::
val workflow = ConnectionDelete.creator( // (1)
"default/snowflake/1234567890", true // (2)
).build() // (3)
.toWorkflow() // (4)
val response = workflow.run(client) // (5)
-
The
ConnectionDeletepackage will create a workflow to delete a connection and its assets using thecreator()method. -
You need to provide the following:
- qualified name of the connection whose assets should be deleted.
- whether to permanently delete the connection and its assets (hard-delete) (
true), or only archive (soft-delete) them (false).
-
Build the minimal package object.
-
Convert the package into a
Workflowobject. -
Run the workflow using the
run()method on the object you've created. Because this operation will execute work in Atlan, you must provide it anAtlanClientthrough which to connect to the tenant.Workflows run asynchronously
Remember that workflows run asynchronously. See the packages and workflows introduction for details on how to check the status and wait until the workflow has been completed. :::
We recommend creating the workflow only via the UI. To rerun an existing workflow, see the steps below.
Re-run existing workflow
To re-run an existing connection delete workflow:
- Java
- Python
- Kotlin
- Raw REST API
List<WorkflowSearchResult> existing = WorkflowSearchRequest // (1)
.findByType(client, ConnectionDelete.PREFIX, 5); // (2)
// Determine which of the results is the Connection delete workflow you want to re-run...
WorkflowRunResponse response = existing.get(n).rerun(client); // (3)
-
You can search for existing workflows through the
WorkflowSearchRequestclass. -
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 theConnectionDelete. (You can also specify the maximum number of resulting workflows you want to retrieve as results.) -
Once you've found the workflow you want to re-run, you can simply call the
rerun()helper method on the workflow search result. TheWorkflowRunResponseis just a subtype ofWorkflowResponseso has the same helper method to monitor progress of the workflow run. Because this operation will execute work in Atlan, you must provide it anAtlanClientthrough which to connect to the tenant.- Optionally, you can use the
rerun(client, true)method with idempotency to avoid re-running a workflow that's already in running or in a pending state. This will return details of the already running workflow if found, and by default, it's set tofalse
Workflows run asynchronously - Optionally, you can use the
Remember that workflows run asynchronously. See the packages and workflows introduction for details on how you can check the status and wait until the workflow has been completed. :::
from pyatlan.client.atlan import AtlanClient
from pyatlan.model.enums import WorkflowPackage
client = AtlanClient()
existing = client.workflow.find_by_type( # (1)
prefix=WorkflowPackage.CONNECTION_DELETE, max_results=5
)
# Determine which Connection delete workflow (n)
# from the list of results you want to re-run.
response = client.workflow.rerun(existing[n]) # (2)
-
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 theConnectionDelete. (You can also specify the maximum number of resulting workflows you want to retrieve as results.) -
Once you've found the workflow you want to re-run, you can simply call the workflow client
rerun()method.- Optionally, you can use
rerun(idempotent=True)to avoid re-running a workflow that's already in running or in a pending state. This will return details of the already running workflow if found, and by default, it's set toFalse.
Workflows run asynchronously - Optionally, you can use
Remember that workflows run asynchronously. See the packages and workflows introduction for details on how you can check the status and wait until the workflow has been completed. :::
val existing = WorkflowSearchRequest // (1)
.findByType(client, ConnectionDelete.PREFIX, 5) // (2)
// Determine which of the results is the
// connection delete workflow you want to re-run...
val response = existing.get(n).rerun(client) // (3)
-
You can search for existing workflows through the
WorkflowSearchRequestclass. -
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 theConnectionDelete. (You can also specify the maximum number of resulting workflows you want to retrieve as results.) -
Once you've found the workflow you want to re-run, you can simply call the
rerun()helper method on the workflow search result. TheWorkflowRunResponseis just a subtype ofWorkflowResponseso has the same helper method to monitor progress of the workflow run. Because this operation will execute work in Atlan, you must provide it anAtlanClientthrough which to connect to the tenant.- Optionally, you can use the
rerun(client, true)method with idempotency to avoid re-running a workflow that's already in running or in a pending state. This will return details of the already running workflow if found, and by default, it's set tofalse
Workflows run asynchronously - Optionally, you can use the
Remember that workflows run asynchronously. See the packages and workflows introduction for details on how you can check the status and wait until the workflow has been completed. :::
- Find the existing workflow.
- Send through the resulting re-run request.
{
"from": 0,
"size": 5,
"query": {
"bool": {
"filter": [
{
"nested": {
"path": "metadata",
"query": {
"prefix": {
"metadata.name.keyword": {
"value": "atlan-connection-delete" // (1)
}
}
}
}
}
]
}
},
"sort": [
{
"metadata.creationTimestamp": {
"nested": {
"path": "metadata"
},
"order": "desc"
}
}
],
"track_total_hits": true
}
-
Searching by the
atlan-connection-deleteprefix will make sure you only find existing connection delete workflows.Name of the workflow
The name of the workflow will be nested within the _source.metadata.name property of the response object.
(Remember since this is a search, there could be multiple results, so you may want to use the other details
in each result to determine which workflow you really want.)
:::
{
"namespace": "default",
"resourceKind": "WorkflowTemplate",
"resourceName": "atlan-connection-delete-1684500411" // (1)
}
- Send the name of the workflow as the
resourceNameto rerun it.