Software installation

Conda is an open-source package and environment management system that runs on Windows, macOS, and Linux. The conda repository contains a large number of open-source certified packages enabling scientific work. It is recommended that you install the minimal installer for conda named miniconda that includes only conda, Python, the packages they depend on, and a small number of other useful packages, including pip, zlib.

Download and install miniconda¶

Retrieve miniconda from the following website

https://docs.conda.io/en/latest/miniconda.html

Install the version for 64 bit computers.

OBS for MacOS, there are different downloads for intel and M1 processors. Follow these steps to find out what is on your laptop:

1. Click the Apple icon in the top-left corner of your Mac.

2. This will bring up a drop-down menu. Pick the top option: About This Mac.

3. The resulting window should show you the information you need: look for intel or M1

Create conda environments and install packages¶

All in one step¶

Get all packages needed for course in one step with use of a YML file

(base) % conda env create -f cb1020.yml

where the file cb1020.yml contains

name: cb1020
channels:
  - conda-forge
dependencies:
  - python
  - jupyterlab
  - jupyterlab-spellchecker
  - jupyterlab_code_formatter
  - black
  - isort
  - ipywidgets
  - numpy
  - scipy
  - matplotlib
  - pandas
  - mesa
  - scikit-learn
  - llama-cpp-python

Some additional features are then made available in your notebooks such as a spell checker and a Python code formatter.

Step-by-step (if you did not follow the all-in-one-step procedure)¶

Start a conda terminal, or Anaconda Powershell as it is referred to on a Windows system. Conda supports multiple environments and you start in the one named base as is typically indicated by the prompt. To create a new and additional environment named cb1020, enter the following command line statement

(base) % conda create -n cb1020

You can list your conda environments

(base) % conda env list

The activated environment will be marked with an asterisk (the base environment to begin with) and you can activate your new environment with the command

(base) % conda activate cb1020

as should be indicated by getting a modified prompt.

Install packages into this environment

(cb1020) % conda install numpy scipy matplotlib jupyterlab mesa -c conda-forge

Try it out¶

You should now be ready to start JupyterLab with the commands

(base) % conda activate cb1020
(cb1020) % jupyter lab

which should open in the web browser interface.