OpenMetadata/openmetadata-docs/content/v1.1.0/connectors/dashboard/metabase/cli.md

---
title: Run Metabase Connector using the CLI
slug: /connectors/dashboard/metabase/cli
---

# Run Metabase using the metadata CLI

| Stage      | PROD                         |
|------------|------------------------------|
| Dashboards | {% icon iconName="check" /%} |
| Charts     | {% icon iconName="check" /%} |
| Owners     | {% icon iconName="cross" /%} |
| Tags       | {% icon iconName="cross" /%} |
| Datamodels | {% icon iconName="cross" /%} |
| Lineage    | {% icon iconName="check" /%} |

In this section, we provide guides and references to use the Metabase connector.

Configure and schedule Metabase metadata and profiler workflows from the OpenMetadata UI:

- [Requirements](#requirements)
- [Metadata Ingestion](#metadata-ingestion)

## Requirements

{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%}
To deploy OpenMetadata, check the Deployment guides.
{%/inlineCallout%}

To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
custom Airflow plugins to handle the workflow deployment.

**Note:** We have tested Metabase with Versions `0.42.4` and `0.43.4`.

### Python Requirements

To run the Metabase ingestion, you will need to install:

```bash
pip3 install "openmetadata-ingestion[metabase]"
```

## Metadata Ingestion

All connectors are defined as JSON Schemas.
[Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/dashboard/metabaseConnection.json)
you can find the structure to create a connection to Metabase.

In order to create and run a Metadata Ingestion workflow, we will follow
the steps to create a YAML configuration able to connect to the source,
process the Entities if needed, and reach the OpenMetadata server.

The workflow is modeled around the following
[JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json)

### 1. Define the YAML Config

This is a sample config for Metabase:

### 1. Define the YAML Config

{% codePreview %}

{% codeInfoContainer %}

#### Source Configuration - Service Connection

{% codeInfo srNumber=1 %}

**username**: Username to connect to Metabase, for ex. `user@organization.com`. This user should have access to relevant dashboards and charts in Metabase to fetch the metadata.

{% /codeInfo %}

{% codeInfo srNumber=2 %}

**password**: Password of the user account to connect with Metabase.

{% /codeInfo %}

{% codeInfo srNumber=3 %}

**hostPort**: The hostPort parameter specifies the host and port of the Metabase instance. This should be specified as a string in the format `http://hostname:port` or `https://hostname:port`. For example, you might set the hostPort parameter to `https://org.metabase.com:3000`.

{% /codeInfo %}

#### Source Configuration - Source Config

{% codeInfo srNumber=4 %}

The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/dashboardServiceMetadataPipeline.json):

- **dbServiceNames**: Database Service Names for ingesting lineage if the source supports it.
- **dashboardFilterPattern**, **chartFilterPattern**, **dataModelFilterPattern**: Note that all of them support regex as include or exclude. E.g., "My dashboard, My dash.*, .*Dashboard".
- **includeOwners**: Set the 'Include Owners' toggle to control whether to include owners to the ingested entity if the owner email matches with a user stored in the OM server as part of metadata ingestion. If the ingested entity already exists and has an owner, the owner will not be overwritten.
- **includeTags**: Set the 'Include Tags' toggle to control whether to include tags in metadata ingestion.
- **includeDataModels**: Set the 'Include Data Models' toggle to control whether to include tags as part of metadata ingestion.
- **markDeletedDashboards**: Set the 'Mark Deleted Dashboards' toggle to flag dashboards as soft-deleted if they are not present anymore in the source system.

{% /codeInfo %}

#### Sink Configuration

{% codeInfo srNumber=5 %}

To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.

{% /codeInfo %}

{% partial file="workflow-config.md" /%}

{% /codeInfoContainer %}

{% codeBlock fileName="filename.yaml" %}

```yaml
source:
  type: metabase
  serviceName: <service name>
  serviceConnection:
    config:
      type: Metabase
```
```yaml {% srNumber=1 %}
      username: <username>
```
```yaml {% srNumber=2 %}
      password: <password>
```
```yaml {% srNumber=3 %}
      hostPort: <hostPort>
```
```yaml {% srNumber=4 %}
  sourceConfig:
    config:
      type: DashboardMetadata
      markDeletedDashboards: True
      # dbServiceNames:
      #   - service1
      #   - service2
      # dashboardFilterPattern:
      #   includes:
      #     - dashboard1
      #     - dashboard2
      #   excludes:
      #     - dashboard3
      #     - dashboard4
      # chartFilterPattern:
      #   includes:
      #     - chart1
      #     - chart2
      #   excludes:
      #     - chart3
      #     - chart4

```
```yaml {% srNumber=5 %}
sink:
  type: metadata-rest
  config: {}
```

{% partial file="workflow-config-yaml.md" /%}

{% /codeBlock %}

{% /codePreview %}

### 2. Run with the CLI

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:

```bash
metadata ingest -c <path-to-yaml>
```

Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration,
you will be able to extract metadata from different sources.