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---
title: Run Metabase Connector using the CLI
slug: /connectors/dashboard/metabase/cli
---
# Run Metabase using the metadata CLI
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| 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 %}
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**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 %}
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**password**: Password of the user account to connect with Metabase.
{% /codeInfo %}
{% codeInfo srNumber=3 %}
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**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.