# Import a Notebook

> Import a Notebook activity in the Databricks connector.

## Project compatibility

Windows | Cross-platform

## Overview

| Description | API Method | API Path |
| --- | --- | --- |
| Import base64-encoded content into the Databricks workspace as a notebook at the given path. Set overwrite to replace an existing object. | POST | `/notebook_import` |

## Input

| Parameter | Description | Data Type |
| --- | --- | --- |
| Databricks Notebook Path \* | Destination workspace path, for example /Users/me/my_notebook. | string |
| Content \* | Base64-encoded notebook content. For example, `IyBEYXRhYnJpY2tzIG5vdGVib29rIHNvdXJjZQpwcmludCgiaGVsbG8iKQo=`. | string |
| Language | PYTHON, SCALA, SQL or R. For example, `PYTHON`. | string |
| Overwrite | Replace the object if it already exists. | boolean |

\* Required parameter.

## Output

| Parameter | Description | Data Type |
| --- | --- | --- |
| Object ID | ID of the notebook created in the workspace. | integer |

:::note
You might see variations in the output depending on where you run the activity. In API workflows and Maestro Flow, a single response object containing all the fields is returned. In RPA workflows, not all fields are exposed, but you can still retrieve them from the exposed response object.
:::