# Code notebooks[¶](https://doc.dataiku.com/dss/latest/notebooks/index.html#code-notebooks "Permalink to this headline")

In addition to the Flow where you perform the “production” work of your project with both visual recipes and code recipes, and visual analysis where you can visually perform data preparation and machine learning, DSS features code notebooks for exploratory / experimental work using code.

* SQL notebook

+ Creating a SQL notebook

+ Cells and history

* Python notebooks

+ Creating a Python notebook

- From a dataset

- From the notebooks list

+ Using the Python notebook

- Available APIs

- Spark

- Unloading

* Predefined notebooks

+ Creating a notebook from a prebuilt template

+ Creating your own prebuilt templates

* Containerized notebooks

+ Configuring containers for notebooks

- Builtin environment

- Code envs

+ Running a notebook in a container

- Dependencies

- Writing files from notebook code

* Installing Jupyter Extensions

+ List available extensions

+ List enabled extensions

+ Enable an extension

+ Disable an extension

+ Customize an extension
