## Glue assets package

URL: https://docs.atlan.com/apps/connectors/etl-tools/aws-glue/sdk/references/package-reference

> Programmatically crawl and manage AWS Glue assets in Atlan using the Python SDK (pyatlan). Reference for the Glue assets package.

:::warning[Deprecated—use the app reference]
This package is deprecated. Use the [app reference](app-reference) for the new `client.app` builder, or see [Manage apps](https://docs.atlan.com/llms/platform/python/manage-apps/llms.txt).
:::

# Glue assets package

The [Glue assets package](https://ask.atlan.com/hc/en-us/articles/6335637665681)
crawls AWS glue assets and publishes them to Atlan for discovery.

:::warning[Will create a new connection]
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](#re-run-existing-workflow) below).
:::
To crawl assets from AWS glue using the IAM user authentication:

### Java

```java showLineNumbers title="Glue assets crawling using IAM user auth"
Workflow crawler = GlueCrawler.creator( // (1)
 client, // (2)
 "production", // (3)
 List.of(client.getRoleCache().getIdForName("$admin")), // (4)
 null,
 null,
 false, // (5)
 false, // (6)
 0L // (7)
 )
 .iamUserAuth( // (8)
 "your-access-key",
 "your-secret-key"
 )
 .direct("ap-south-1") // (9)
 .include( // (10)
 List.of("dev-project")
 )
 .exclude(List.of()) // (11)
 .build() // (12)
 .toWorkflow(); // (13)
WorkflowResponse response = crawler.run(client); // (14)
```

1. The `GlueCrawler` package will create a workflow to crawl assets from AWS Glue.
2. You must provide Atlan client.
3. You must provide a name for the connection that the AWS Glue assets will exist within.
4. You must specify at **least one connection admin**, either:

 - everyone in a role (in this example, all `$admin` users).
 - a list of groups (names) that will be connection admins.
 - a list of users (names) that will be connection admins.

5. You can specify whether you want to allow queries to this connection (`true`) or deny all query access to the connection (`false`).
6. You can specify whether you want to allow data previews on this connection (`true`) or deny all sample data previews to the connection (`false`).
7. You can specify a maximum number of rows that can be accessed for any asset in the connection.
8. When using `iamUserAuth()`, you need to provide the following information:

 - access key for accessing AWS Glue.
 - secret key for accessing AWS Glue.

9. You must provide AWS region where Glue is set up.
10. You can also optionally specify the list of schema names to include in crawling. (If set to null, all schemas will be crawled.)
11. You can also optionally specify the list of schema names to exclude from crawling. (If set to null, no schemas will be excluded.)
12. Build the minimal package object.
13. Now, you can convert the package into a `Workflow` object.
14. 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 an `AtlanClient`](https://docs.atlan.com/llms/platform/python/set-up-sdk/llms.txt) through which to connect to the tenant.

 :::warning[Workflows run asynchronously]
Remember that workflows run asynchronously. See the [packages and workflows introduction](https://docs.atlan.com/llms/platform/python/packages/llms.txt) for details on how you can check the status and wait until the workflow has been completed.
 :::

### Python

```python showLineNumbers title="Glue assets crawling using IAM user auth"
from pyatlan.client.atlan import AtlanClient
from pyatlan.model.packages import GlueCrawler

client = AtlanClient()

crawler = (
 GlueCrawler( # (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,
 row_limit=0, # (5)
 allow_query=False, # (6)
 allow_query_preview=False, # (7)
 )
 .iam_user_auth( # (8)
 access_key="your-access-key",
 secret_key="your-secret-key",
 )
 .direct(region="ap-south-1") # (9)
 .include(assets=['dev-project']) # (10)
 .exclude(assets=[]) # (11)
 .to_workflow() # (12)
)
response = client.workflow.run(crawler) # (13)
```

1. Base configuration for a new AWS Glue crawler.
2. You must provide a client instance.
3. You must provide a name for the connection that the AWS Glue assets will exist within.
4. You must specify at **least one connection admin**, either:

 - everyone in a role (in this example, all `$admin` users).
 - a list of groups (names) that will be connection admins.
 - a list of users (names) that will be connection admins.
5. You can specify a maximum number of rows that can be accessed for any asset in the connection.
6. You can specify whether you want to allow queries to this connection
(`True`) or deny all query access to the connection (`False`).
7. You can specify whether you want to allow data previews on this connection
(`True`) or deny all sample data previews to the connection (`False`).
8. When using `iam_user_auth()`, you need to provide the following information:

 - access key for accessing AWS Glue.
 - secret key for accessing AWS Glue.
9. You must provide AWS region where Glue is set up.
10. You can also optionally specify the list of schema names to include in crawling.
(If set to None, all schemas will be crawled.)
11. You can also optionally specify the list of schema names to exclude from crawling.
(If set to None, no schemas will be excluded.)
12. Now, you can convert the package into a `Workflow` object.
13. Run the workflow by invoking the `run()` method on the workflow client, passing the created object.

 :::warning[Workflows run asynchronously]
Remember that workflows run asynchronously. See the [packages and workflows introduction](https://docs.atlan.com/llms/platform/python/packages/llms.txt)
for details on how you can check the status and wait until the workflow has been completed.
 :::

### Kotlin

```kotlin showLineNumbers title="Glue assets crawling using IAM user auth"
val crawler = GlueCrawler.creator( // (1)
 client, // (2)
 "production", // (3)
 listOf(client.getRoleCache().getIdForName("\$admin")), // (4)
 null,
 null,
 false, // (5)
 false, // (6)
 0L // (7)
 )
 .iamUserAuth( // (8)
 "your-access-key",
 "your-secret-key"
 )
 .direct("ap-south-1") // (9)
 .include( // (10)
 listOf("dev-project")
 )
 .exclude(emptyList()) // (11)
 .build() // (12)
 .toWorkflow() // (13)
val response = crawler.run(client) // (14)
```

1. The `GlueCrawler` package will create a workflow to crawl assets from AWS Glue.
2. You must provide Atlan client.
3. You must provide a name for the connection that the AWS Glue assets will exist within.
4. You must specify at **least one connection admin**, either:

 - everyone in a role (in this example, all `$admin` users).
 - a list of groups (names) that will be connection admins.
 - a list of users (names) that will be connection admins.

5. You can specify whether you want to allow queries to this connection (`true`) or deny all query access to the connection (`false`).
6. You can specify whether you want to allow data previews on this connection (`true`) or deny all sample data previews to the connection (`false`).
7. You can specify a maximum number of rows that can be accessed for any asset in the connection.
8. When using `iamUserAuth()`, you need to provide the following information:

 - access key for accessing AWS Glue.
 - secret key for accessing AWS Glue.

9. You must provide AWS region where Glue is set up.
10. You can also optionally specify the list of schema names to include in crawling. (If set to null, all schemas will be crawled.)
11. You can also optionally specify the list of schema names to exclude from crawling. (If set to null, no schemas will be excluded.)
12. Build the minimal package object.
13. Now, you can convert the package into a `Workflow` object.
14. 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 an `AtlanClient`](https://docs.atlan.com/llms/platform/python/set-up-sdk/llms.txt) through which to connect to the tenant.

 :::warning[Workflows run asynchronously]
Remember that workflows run asynchronously. See the [packages and workflows introduction](https://docs.atlan.com/llms/platform/python/packages/llms.txt) for details on how you can check the status and wait until the workflow has been completed.
 :::

### Raw REST API

:::tip[Create the workflow via UI only]
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 Glue assets:

### Java

```java showLineNumbers title="Re-run existing Glue workflow"
List existing = WorkflowSearchRequest // (1)
 .findByType(client, GlueCrawler.PREFIX, 5); // (2)
// Determine which of the results is the Glue workflow you want to re-run...
WorkflowRunResponse response = existing.get(n).rerun(client); // (3)
```

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 `GlueCrawler`. (You can also specify the maximum number of resulting workflows you want to retrieve as results.)
3. Once you've found the workflow you want to re-run, you can simply call the `rerun()` helper method on the workflow search result. The `WorkflowRunResponse` is just a subtype of `WorkflowResponse` so has the same helper method to monitor progress of the workflow run. Because this operation will execute work in Atlan, you must [provide it an `AtlanClient`](https://docs.atlan.com/llms/platform/python/set-up-sdk/llms.txt) through 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 to `false`

 :::warning[Workflows run asynchronously]
Remember that workflows run asynchronously. See the [packages and workflows introduction](https://docs.atlan.com/llms/platform/python/packages/llms.txt)
for details on how you can check the status and wait until the workflow has been completed.
 :::

### Python

```python showLineNumbers title="Re-run existing Glue workflow"
from pyatlan.client.atlan import AtlanClient
from pyatlan.model.enums import WorkflowPackage

client = AtlanClient()

existing = client.workflow.find_by_type( # (1)
 prefix=WorkflowPackage.GLUE, max_results=5
)

# Determine which Glue workflow (n)

# from the list of results you want to re-run.

response = client.workflow.rerun(existing[n]) # (2)
```

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 `GlueCrawler`. (You can also specify
the **maximum number of resulting workflows** you want to retrieve as results.)
2. 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 to `False`.

 :::warning[Workflows run asynchronously]
Remember that workflows run asynchronously. See the [packages and workflows introduction](https://docs.atlan.com/llms/platform/python/packages/llms.txt)
for details on how you can check the status and wait until the workflow has been completed.
 :::

### Kotlin

```kotlin showLineNumbers title="Re-run existing Glue workflow"
val existing = WorkflowSearchRequest // (1)
 .findByType(client, GlueCrawler.PREFIX, 5) // (2)
// Determine which of the results is the
// Glue workflow you want to re-run...
val response = existing.get(n).rerun(client) // (3)
```

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 `GlueCrawler`. (You can also specify the maximum number of resulting workflows you want to retrieve as results.)
3. Once you've found the workflow you want to re-run, you can simply call the `rerun()` helper method on the workflow search result. The `WorkflowRunResponse` is just a subtype of `WorkflowResponse` so has the same helper method to monitor progress of the workflow run. Because this operation will execute work in Atlan, you must [provide it an `AtlanClient`](https://docs.atlan.com/llms/platform/python/set-up-sdk/llms.txt) through 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 to `false`

 :::warning[Workflows run asynchronously]
Remember that workflows run asynchronously. See the [packages and workflows introduction](https://docs.atlan.com/llms/platform/python/packages/llms.txt)
for details on how you can check the status and wait until the workflow has been completed.
 :::

### Raw REST API

:::warning[Requires multiple steps through the raw REST API]
1. Find the existing workflow.
2. Send through the resulting re-run request.
:::
```json showLineNumbers title="POST /api/service/workflows/indexsearch"
{
 "from": 0,
 "size": 5,
 "query": {
 "bool": {
 "filter": [
 {
 "nested": {
 "path": "metadata",
 "query": {
 "prefix": {
 "metadata.name.keyword": {
 "value": "atlan-glue" // (1)
 }
 }
 }
 }
 }
 ]
 }
 },
 "sort": [
 {
 "metadata.creationTimestamp": {
 "nested": {
 "path": "metadata"
 },
 "order": "desc"
 }
 }
 ],
 "track_total_hits": true
}
```

1. Searching by the `atlan-glue` prefix will ensure you only find existing Glue assets workflows.

 :::tip[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.)
 :::
```json title="POST /api/service/workflows/submit"
{
 "namespace": "default",
 "resourceKind": "WorkflowTemplate",
 "resourceName": "atlan-glue-1684500411" // (1)
}
```

2. Send the name of the workflow as the `resourceName` to rerun it.

---