## Fivetran enrichment package

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

> Programmatically enrich Fivetran assets in Atlan with column-level lineage using the Python SDK (pyatlan). Reference for the Fivetran enrichment package.

# Fivetran enrichment package

The [Fivetran enrichment package](https://ask.atlan.com/hc/en-us/articles/8427123490065) enriches existing assets in Atlan associated with Fivetran connectors with column-level lineage.

:::warning[Requires access to Fivetran's metadata API]
:::

## Direct API

:::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 enrich assets from Fivetran via API:

### Java

```java showLineNumbers title="Fivetran enrichment via API"
Workflow fivetran = FivetranCrawler.directApiAuth( // (1)
 "production", // (2)
 "E77yqOsBPrRXpVp0", // (3)
 "XLQR73AKwGYmjzk5vlBMAUG4wo13VyY"); // (4)
WorkflowResponse response = fivetran.run(client); // (5)
```

1. The `FivetranCrawler` package will create a workflow to enrich assets from Fivetran. The `directApiAuth()` method creates a workflow for crawling assets from Fivetran's API.
2. You must provide a name for the connection for Fivetran enrichment. (Though this is currently unused since the workflow only enriches existing assets, and does not create any new assets.)
3. You must provide your API key for access to Fivetran's metadata API.
4. You must specify your API secret for access to Fivetran's metadata API.
5. 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

:::warning[Coming soon]
:::

### Kotlin

```kotlin showLineNumbers title="Fivetran enrichment via API"
val fivetran = FivetranCrawler.directApiAuth( // (1)
 "production", // (2)
 "E77yqOsBPrRXpVp0", // (3)
 "XLQR73AKwGYmjzk5vlBMAUG4wo13VyY") // (4)
val response = fivetran.run(client) // (5)
```

1. The `FivetranCrawler` package will create a workflow to enrich assets from Fivetran. The `directApiAuth()` method creates a workflow for crawling assets from Fivetran's API.
2. You must provide a name for the connection for Fivetran enrichment. (Though this is currently unused since the workflow only enriches existing assets, and does not create any new assets.)
3. You must provide your API key for access to Fivetran's metadata API.
4. You must specify your API secret for access to Fivetran's metadata API.
5. 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 Fivetran assets:

### Java

```java showLineNumbers title="Re-run existing Fivetran workflow"
List existing = WorkflowSearchRequest // (1)
 .findByType(client, FivetranCrawler.PREFIX, 5); // (2)
// Determine which of the results is the Fivetran 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 `FivetranCrawler`. (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

:::warning[Coming soon]
:::

### Kotlin

```kotlin showLineNumbers title="Re-run existing Fivetran workflow"
val existing = WorkflowSearchRequest // (1)
 .findByType(client, FivetranCrawler.PREFIX, 5) // (2)
// Determine which of the results is the Fivetran 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 `FivetranCrawler`. (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-fivetran" // (1)
 }
 }
 }
 }
 }
 ]
 }
 },
 "sort": [
 {
 "metadata.creationTimestamp": {
 "nested": {
 "path": "metadata"
 },
 "order": "desc"
 }
 }
 ],
 "track_total_hits": true
}
```

1. Searching by the `atlan-fivetran` prefix will ensure you only find existing Fivetran 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-fivetran-1684500411" // (1)
}
```

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

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