Install instructions#

We generally recommend creating a conda environment to isolate any code from other dependencies. The ISLP package does not have unusual dependencies, but this is still good practice.

Mac OS X / Linux#

To create a conda environment in a Mac OS X or Linux environment run:

conda create --name islp

To run python code in this environment, you must activate it:

conda activate islp


On windows, create a Python environment called islp in the Anaconda app. This can be done by selecting Environments on the left hand side of the app’s screen. After creating the environment, open a terminal within that environment by clicking on the “Play” button.

Installing ISLP#

Having completed the steps above, we use pip to install the ISLP package:

pip install ISLP

Frozen environment#


Python packages change frequently. The labs here are built with specific versions of the various packages.

To ensure you have the same package versions as those built here, run:

pip install -r

For more specific install instructions go to ISLP_labs.

Torch requirements#

The ISLP labs use torch and various related packages for the lab on deep learning. Most of the requirements are included in the requirements for ISLP though the labs also use torchinfo and torchvision. These will be installed by the requirements.txt above.


Because torch and related libraries change frequently, you will note that we have pinned the versions at specific versions that were used to make current verisons of the labs.


Mac OS X#

If JupyterLab is not already installed, run the following after having activated your islp environment:

pip install jupyterlab


Either use the same pip command above or install JupyterLab from the Home tab. Ensure that the environment is your islp environment. This information appears near the top left in the Anaconda Home page.

Google Colab#

The notebooks for the labs can be run in Google Colab with a few caveats:

  • Labs that use files in the filesystem will require one to mount your Google Drive. See help

  • The packages will have to be reinstalled each time a new runtime is started. For most labs, inserting pip install ISLP at the top of the notebook will suffice, though Colab will ask you to restart after installation.