There are many ways to use python, I’ve gone with mamba as the environment manager for now.

Using Anaconda/Mambaforge

Instead of using the full Anaconda install, I’ve switched to Mambaforge. The key differences are:

• mamaba is a faster better version of conda
• it installs a minimal install without the tons of packages present in the default anaconda install, and defaults to the conda-forge channel.

See the Mamba docs for more info.

Install Mamba

Install the latest version of mambaforge on linux/mac :

curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-$(uname)-$(uname -m).sh"
bash Mambaforge-$(uname)-$(uname -m).sh

Using environments

So here we create a new environment which will use Python 3.11.

conda create -n py311 python=3.11

This installs pip by default, which is a great as some packages I use are only available on pip.

The basic commands:

• Activate the env: mamba activate py311

• Show installed packages: mamba list
  • search for a specific package: mamba list | grep pandas
• Show all conda envs: mamba env list
• Remove an environment: remove env remove -n py310 --all

Install packages from a file:

mamba install --file requirements.txt

Write the packages in use to disk:

This will include both the conda and pip installed packeges in an environment, long as pip was installed inside the environment.

mamba list --explicit > py.txt

Now if I git clone this repo somewhere else, I can recreate the environment by:

mamba env create --file py.txt

Jupyter lab

These days I’m using the VS code jupyter notebook hotness, but just in case:

mamba install jupyterlab