Allow about 10-30 minutes for the installation depending on your connection speed.Īfter installing be sure to check for updates before proceeding further. Downloading and installing the software is well documented and easy to follow. For this course the recommended package is Anaconda available from Continuum Analytics. This will also allow you to install additional code libraries to meet particular needs.Ĭhoosing this option will require an initial software installation and routine updates. This will provide you with reliable off-line access to a computational environment. So for this course be sure to use latest verstion, currently 3.6, of the Python language.ġ.1.2.2 Installing Jupyter/Python on your Laptop ¶įor regular off-line use you should consider installing a Jupyter Notebook/Python environment directly on your laptop.
It has taken years for the major scientific libraries to complete the transition from 2.x to 3.x, but it is now safe to recommend Python 3.x for widespread use. Version 3.5 is the most recent release of the 3.x series which represents the future direction of language. Version 2.7 released in 2010, which was the last release of the 2.x series. Important Note Regarding Versions There are two versions of Python in widespread use. The kernal can be located on the same laptop as your web browser or located in an on-line cloud service. A kernal is simply a program that runs in the background, maintains workspace memory for variables and functions, and executes Python code. To execute Python code in a notebook you will need access to a Python kernal.
The next step is to learn how to execute computations that may be embedded in a Jupyter notebook. Since you're reading this notebook, you already know how to view a Jupyter notebook.
Jupyter notebooks are documents that can be viewed and executed inside any modern web browser. 1.1.2 Step 0: Gain Executable Access to Jupyter Notebooks ¶