> For the complete documentation index, see [llms.txt](https://george-jen.gitbook.io/data-science-and-apache-spark/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://george-jen.gitbook.io/data-science-and-apache-spark/start-spylon-kernel-on-jupyter-notebook.md).

# Start Spylon-kernel on Jupyter-notebook

Spylon kernel in Jupyter notebook is a great way to quickly run a few Scala commands in the following seciton of Scala Warm Ups.

If you are on Windows, start Anaconda Navigator (if you are on Mac or Linux, scrow to the end of the page)

![](/files/-M6wGuZxEm2Ld2T_FpbP)

Switch to virtual environment spark

![](/files/-M6wHFcYgWdrlQaaQLsb)

If jupyter notebook is not installed, install it in Navigator under spark virtual environment; otherwise, launch jupyter-notebook inside spark virtual environment

![](/files/-M6wHnx6KrBQ8Qhscxel)

select spylon-kernel in the drop down list, you should have completed install spylon kernel in earlier section:

<https://george-jen.gitbook.io/data-science-and-apache-spark/install-findspark-add-spylon-kernel-for-scala>

![](/files/-M6wIH0lhTqbRoSAxLnS)

Change name of noteook from untitled, and start practicing Scala codes in the blue code section in the Scala warm up sections:

<https://george-jen.gitbook.io/data-science-and-apache-spark/type-of-variable-mutable-or-immutable>

![](/files/-M6wItrQBgGT_lY6nDCd)

If you are on MacOS or Linux, simply start a terminal and run below:

conda activate spark

nohup jupyter-notebook &

Then select spylon-kernel from the drop down list in Jupyter-notebook and start the notebook


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://george-jen.gitbook.io/data-science-and-apache-spark/start-spylon-kernel-on-jupyter-notebook.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
