Conda environment

A Conda environment is an isolated software environment that is used to manage dependencies for a project and you decide where it is located.

You will need a environment.yml file that documents the dependencies:

name: coderefinery
channels:
  - conda-forge
  - bioconda
dependencies:
  - python >= 3.10
  - black
  - click
  - flit
  - ipywidgets
  - isort
  - jupyterlab
  - jupyterlab_code_formatter
  - jupyterlab-git
  - matplotlib
  - myst-parser
  - nbdime
  - numpy
  - pandas
  - pytest
  - pytest-cov
  - scalene
  - seaborn
  - snakemake-minimal
  - sphinx
  - sphinx-autoapi
  - sphinx-autobuild
  - sphinx_rtd_theme >= 2.0
  - vulture
  - scikit-image

Before you create a virtual environment

Create a new directory for this course.
In this directory, create an environment.yml file and copy-paste the dependencies above into it.

Choose the tool to manage the environment

If you are already using one of these tools, please continue using the tool that you like and know. If you are new to this, we recommend using Miniconda or Miniforge.

Anaconda
- Advantages: easy to install, easy to use, good for beginners
- Disadvantages: large download, installs more than we will need, license restrictions
Miniconda
- Advantages: small size, installs only what you need
- Disadvantages: no graphical interface, license restrictions
Miniforge
- Advantages: small size, no license restrictions
- Disadvantages: no graphical interface
Micromamba
- Advantages: fast, small size
- Disadvantages: no graphical interface
Pixi
- Advantages: fast and new
- Disadvantages: new and less tested and not documented here

Creating the virtual environment

Open your terminal shell (e.g. Bash or Zsh).
Activate conda using conda activate or source ~/miniconda3/bin/activate.

Run the following command:

$ conda env create --file environment.yml

Make sure that you see “coderefinery” in the output when you ask for a list of all available environments:
```
$ conda env list
```