In this section, we'll recommend optional software regarding code editing. While not mandatory, it might help considerably to use them, especially for newcomers, for whom plain code editing software can be daunting.

Notebooks are a great way of sharing code that contains text, explanations, figures, and other rich content. It is used extensively in the data science community because it can store and display the result of long-running operations, while also providing a dynamic runtime to edit and execute the content in.

The code for this book is available on GitHub as plain Python code, but also in the form of Jupyter Notebooks. Each chapter will have its own notebook that serves as an example.

To install Jupyter and launch your first notebook, follow these steps:

1. While in the Magenta environment, execute the following command:

> pip install jupyter

2. Now, we can start the Jupyter server by executing the following command (also while in the Magenta environment):

> jupyter notebook

The Jupyter interface will be shown in a web browser. The previous command should have launched your default browser. If not, use the URL in the output of the command to open it.

3. Once in the notebook UI, you should see your disk content. Navigate to the code for this book and load the notebook from Chapter01/notebook.ipynb.
4. Make sure the selected kernel is Python 3. This kernel corresponds to the Python interpreter that's been installed in your Magenta environment.
5. Run the code blocks using the Run button for each cell. This will make sure that Jupyter executes in a proper environment by printing the TensorFlow and Magenta versions.

This is what the notebook should look like:

The usage of an Integrated Development Environment (IDE) is not necessary for this book since all the examples run from the command line. However, an IDE is a good tool to use since it provides autocompletion, integrated development tools, refactoring options, and more. It is also really useful for debugging since you can step into the code directly.

A good IDE for this book is JetBrains's PyCharm (www.jetbrains.com/pycharm), a Python IDE with a community (open source) edition that provides everything you need.

Whether you use PyCharm or another IDE, you'll need to change Python interpreter to the one we installed previously. This is the equivalent of activating our Magenta environment using Conda. In the project settings in the IDE, find the Python interpreter settings and change it to the installation path of our environment.

If you don't remember its location, use the following commands:

> conda activate magenta
> conda info
...
    active env location : C:\Users\Packt\Miniconda3\envs\magenta
...

On Windows, the Python interpreter is in the root folder, while on Linux or macOS, it is in the bin directory under it.