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| --- | ||
| title: Looker | ||
| description: Grai integration for Looker to extract Dashboards and LookML output into your data observability stack. | ||
| --- | ||
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| import { Callout } from "nextra-theme-docs"; | ||
| import { LookerIcon } from "../../components/Integrations"; | ||
| import Image from "next/image"; | ||
| import InlineLogo from "../../components/InlineLogo"; | ||
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| <InlineLogo logo={<LookerIcon width="200"/>} title="(alpha)" /> | ||
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| The Looker integration synchronizes your Dashboards and LookML from Looker into Grai | ||
| In this way you can quickly identify which data is being used by your BI tools, which data is not, and more. | ||
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| ## Web App | ||
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| <Image | ||
| src="/images/docs/core/integrations/looker.png" | ||
| height={600} | ||
| width={1200} | ||
| alt="Metabase Integration Homescreen" | ||
| /> | ||
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| ### Fields | ||
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| | Field | Value | Example | | ||
| | --------------- | ------------------------------------------------------------------ | -------- | | ||
| | Source | Name of the source for this connection | Looker | | ||
| | Name | Name for connection | Looker | | ||
| | Namespace | Namespace for the connection, see [namespace](/concepts/namespace) | default | | ||
| | base_url | Base url of your looker instance | | | ||
| | client_id | Client ID for the Looker API | | | ||
| | client_secret | Client Secret for the Looker API | | | ||
| | namespaces | An Optional JSON string (see below) | | | ||
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| You can find more information about generating a client id and secret [here](https://cloud.google.com/looker/docs/admin-panel-users-users#api_keys). | ||
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| #### Namespaces | ||
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| <Callout type="info" emoji="ℹ️"> | ||
| If the namespaces field is not provided, Grai will create a default namespace for each Explore on your behalf. | ||
| You can always update the namespaces field later to customize your namespace organization. | ||
| </Callout> | ||
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| In order to automatically tie your data lineage together, Grai needs to know which Grai namespace corresponds to each lookML model. | ||
| The namespaces field should be a JSON string with the Grai namespace for each dashboard id e.g. | ||
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| ```json | ||
| { | ||
| "<model>": "<namespace>" | ||
| } | ||
| ``` | ||
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| ## Python Library | ||
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| ### Installation | ||
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| Install the Metabase Grai integration with pip | ||
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| ```shell copy | ||
| pip install grai-source-looker | ||
| ``` | ||
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| This installs the Grai Looker integration, which is now ready to run in python | ||
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| ### Connecting & Syncing | ||
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| The integration comes equipped with the client library already but we will need a python terminal or Jupyter Notebook to execute a few commands to establish a connection and begin querying the server. | ||
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| Spin up your favorite python terminal then: | ||
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| ```python copy | ||
| import os | ||
| from grai_source_looker.base import LookerIntegration | ||
| ``` | ||
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| For now we will use the default user credentials though you are free to create a new user / api keys from the server admin interface at http://localhost:8000/admin. | ||
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| ```python copy | ||
| client = ClientV1("localhost", "8000", username="null@grai.io", password="super_secret") | ||
| ``` | ||
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| Using example variables, in order to update the server with your metadata, simply run: | ||
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| ```python copy | ||
| from grai_source_looker.base import LookerIntegration | ||
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| integration = LookerIntegration(base_url=<your_url>, | ||
| client_id=<your_client_id>, | ||
| client_secret=<your_client_secret>, | ||
| namespace=<your_namespace>, | ||
| ) | ||
| nodes, edges = integration.get_nodes_and_edges() | ||
| client.post([nodes, edges]) | ||
| ``` |
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