Tableau assets package
The Tableau assets package crawls Tableau assets and publishes them to Atlan for discovery.
Direct extraction
This should only be used to create the workflow the first time. Each time you run this method it will create a new connection and new assets within that connection — which could lead to duplicate assets if you run the workflow this way multiple times with the same settings.
Instead, when you want to re-crawl assets, re-run the existing workflow (see Re-run existing workflow below).
To crawl Tableau assets directly from Tableau:
- Java
- Python
- Kotlin
- Raw REST API
Workflow crawler = TableauCrawler.creator( // (1)
client, // (2)
"production", // (3)
List.of(client.getRoleCache().getIdForName("$admin")), // (4)
null,
null
)
.direct( // (5)
"example.online.tableau.com",
"atlan-site",
true
)
.basicAuth( // (6) (7)
"atlan-user",
"atlan-pass"
)
.include( // (8)
List.of("fc2923bd-cf94-2b29-9cdd-9cc2f7a4f029")
)
.exclude(List.of()) // (9)
.crawlUnpublished(true) // (10)
.crawlHiddenFields(false) // (11)
.alternateHost("https://alternate.tableau.com") // (12)
.build() // (13)
.toWorkflow(); // (14)
WorkflowResponse response = crawler.run(client); // (15)
-
The
TableauCrawlerpackage will create a workflow to crawl assets from Tableau. -
You must provide Atlan client.
-
You must provide a name for the connection that the Tableau assets will exist within.
-
You must specify at least one connection admin, either:
- everyone in a role (in this example, all
$adminusers). - a list of groups (names) that will be connection admins.
- a list of users (names) that will be connection admins.
- everyone in a role (in this example, all
-
To configure the crawler for extracting data directly from Tableau then you must provide the following information:
- hostname of your Tableau instance.
- site to crawl within Tableau.
- whether to use SSL for the connection.
-
When using
basicAuth(), you must provide the following information:- your username for accessing Tableau.
- your password for accessing Tableau.
-
or you also can use
personalAccessToken()auth, then you must provide the following information:- your username for accessing Tableau.
- your access token for accessing Tableau.
-
You can also optionally specify the list of projects to include in crawling. For Tableau assets, this should be specified as a list of project GUIDs. (If set to null, all projects will be crawled.)
-
You can also optionally specify the list of projects to exclude from crawling. For Tableau assets, this should be specified as a list of project GUIDs. (If set to null, no projects will be excluded.)
-
You can also optionally set whether to crawl unpublished worksheets and dashboards (
true) or not (false). -
You can also optionally set whether to crawl hidden datasource fields (
true) or not (false). -
You can also optionally set an alternate host to use for the "View in Tableau" button for assets in the UI.
-
Build the minimal package object.
-
Now, you can convert the package into a
Workflowobject. -
You can then 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 you can check the status and wait until the workflow has been completed. :::
from pyatlan.client.atlan import AtlanClient
from pyatlan.model.packages import TableauCrawler
client = AtlanClient()
crawler = (
TableauCrawler( # (1)
client=client, # (2)
connection_name="production", # (3)
admin_roles=[client.role_cache.get_id_for_name("$admin")], # (4)
admin_groups=None,
admin_users=None,
)
.direct( # (5)
hostname="example.online.tableau.com",
site="atlan-site",
port=443,
ssl_enabled=True,
)
.basic_auth( # (6) # (7)
username="atlan-user",
password="atlan-pass",
)
.include(projects=["fc2923bd-cf94-2b29-9cdd-9cc2f7a4f029"]) # (8)
.exclude(projects=[]) # (9)
.crawl_unpublished(True) # (10)
.crawl_hidden_fields(False) # (11)
.alternate_host(hostname="https://alternate.tableau.com") # (12)
.to_workflow() # (13)
)
response = client.workflow.run(crawler) # (14)
-
Base configuration for a new Tableau crawler.
-
You must provide a client instance.
-
You must provide a name for the connection that the Tableau assets will exist within.
-
You must specify at least one connection admin, either:
- everyone in a role (in this example, all
$adminusers). - a list of groups (names) that will be connection admins.
- a list of users (names) that will be connection admins.
- everyone in a role (in this example, all
-
To configure the crawler for extracting data directly from Tableau then you must provide the following information:
- hostname of your Tableau instance.
- port number of the Tableau instance (use
443for the default). - site to crawl within Tableau.
- whether to use SSL for the connection.
-
When using
basic_auth(), you must provide the following information:- your username for accessing Tableau.
- your password for accessing Tableau.
-
or you also can use
personal_access_token()auth, then you must provide the following information:- your username for accessing Tableau.
- your access token for accessing Tableau.
-
You can also optionally specify the list of projects to include in crawling. For Tableau assets, this should be specified as a list of project GUIDs. (If set to None, all projects will be crawled.)
-
You can also optionally specify the list of projects to exclude from crawling. For Tableau assets, this should be specified as a list of project GUIDs. (If set to None, no projects will be excluded.)
-
You can also optionally set whether to crawl hidden datasource fields (
True) or not (False). -
You can also optionally set whether to crawl unpublished worksheets and dashboards (
True) or not (False). -
You can also optionally set an alternate host to use for the "View in Tableau" button for assets in the UI.
-
Now, you can 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 you can check the status and wait until the workflow has been completed. :::
val crawler = TableauCrawler.creator( // (1)
client, // (2)
"production", // (3)
listOf(client.getRoleCache().getIdForName("\$admin")), // (4)
null,
null
)
.direct( // (5)
"example.online.tableau.com",
"atlan-site",
true
)
.basicAuth( // (6) (7)
"atlan-user",
"atlan-pass"
)
.include( // (8)
listOf("fc2923bd-cf94-2b29-9cdd-9cc2f7a4f029")
)
.exclude(emptyList()) // (9)
.crawlUnpublished(true) // (10)
.crawlHiddenFields(false) // (11)
.alternateHost("https://alternate.tableau.com") // (12)
.build() // (13)
.toWorkflow() // (14)
val response = crawler.run(client) // (15)
-
The
TableauCrawlerpackage will create a workflow to crawl assets from Tableau. -
You must provide Atlan client.
-
You must provide a name for the connection that the Tableau assets will exist within.
-
You must specify at least one connection admin, either:
- everyone in a role (in this example, all
$adminusers). - a list of groups (names) that will be connection admins.
- a list of users (names) that will be connection admins.
- everyone in a role (in this example, all
-
To configure the crawler for extracting data directly from Tableau then you must provide the following information:
- hostname of your Tableau instance.
- site to crawl within Tableau.
- whether to use SSL for the connection.
-
When using
basicAuth(), you must provide the following information:- your username for accessing Tableau.
- your password for accessing Tableau.
-
or you also can use
personalAccessToken()auth, then you must provide the following information:- your username for accessing Tableau.
- your access token for accessing Tableau.
-
You can also optionally specify the list of projects to include in crawling. For Tableau assets, this should be specified as a list of project GUIDs. (If set to null, all projects will be crawled.)
-
You can also optionally specify the list of projects to exclude from crawling. For Tableau assets, this should be specified as a list of project GUIDs. (If set to null, no projects will be excluded.)
-
You can also optionally set whether to crawl unpublished worksheets and dashboards (
true) or not (false). -
You can also optionally set whether to crawl hidden datasource fields (
true) or not (false). -
You can also optionally set an alternate host to use for the "View in Tableau" button for assets in the UI.
-
Build the minimal package object.
-
Now, you can convert the package into a
Workflowobject. -
You can then 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 you can 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.
Offline extraction
This should only be used to create the workflow the first time. Each time you run this method it will create a new connection and new assets within that connection — which could lead to duplicate assets if you run the workflow this way multiple times with the same settings.
Instead, when you want to re-crawl assets, re-run the existing workflow (see Re-run existing workflow below).
To crawl Tableau assets from the S3 bucket:
- Java
- Python
- Kotlin
- Raw REST API
from pyatlan.client.atlan import AtlanClient
from pyatlan.model.packages import TableauCrawler
client = AtlanClient()
crawler = (
TableauCrawler( # (1)
client=client, # (2)
connection_name="production", # (3)
admin_roles=[client.role_cache.get_id_for_name("$admin")], # (4)
admin_groups=None,
admin_users=None,
)
.s3( # (5)
bucket_name="test-bucket",
bucket_prefix="test-prefix",
bucket_region="test-region",
)
.to_workflow() # (6)
)
response = client.workflow.run(crawler) # (7)
-
Base configuration for a new Tableau crawler.
-
You must provide a client instance.
-
You must provide a name for the connection that the Tableau assets will exist within.
-
You must specify at least one connection admin, either:
- everyone in a role (in this example, all
$adminusers). - a list of groups (names) that will be connection admins.
- a list of users (names) that will be connection admins.
- everyone in a role (in this example, all
-
When using
s3(), you need to provide the following information:- name of the bucket/storage that contains the extracted metadata files.
- prefix is everything after the bucket/storage name, including the
path. - (Optional) name of the region if applicable.
-
Now, you can 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 you can 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 workflow for Tableau assets:
- Java
- Python
- Kotlin
- Raw REST API
List<WorkflowSearchResult> existing = WorkflowSearchRequest // (1)
.findByType(client, TableauCrawler.PREFIX, 5); // (2)
// Determine which of the results is the Tableau 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 theTableauCrawler. (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 is already in running or in a pending state. This will return details of the already running workflow if found, and by default, it is 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.TABLEAU, max_results=5
)
# Determine which Tableau 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 theTableauCrawler. (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 is already in running or in a pending state. This will return details of the already running workflow if found, and by default, it is 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, TableauCrawler.PREFIX, 5) // (2)
// Determine which of the results is the
// Tableau 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 theTableauCrawler. (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 is already in running or in a pending state. This will return details of the already running workflow if found, and by default, it is 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-tableau" // (1)
}
}
}
}
}
]
}
},
"sort": [
{
"metadata.creationTimestamp": {
"nested": {
"path": "metadata"
},
"order": "desc"
}
}
],
"track_total_hits": true
}
-
Searching by the
atlan-tableauprefix will ensure you only find existing Tableau assets 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-tableau-1684500411" // (1)
}
- Send the name of the workflow as the
resourceNameto rerun it.