Variants of Anaconda
If you're a conda
user, you may have heard of the Anaconda distribution of Python.
In this set of notes, however, I've also referenced the Miniforge distribution of Python.
What's the difference here?
How do you pick which one to use?
To answer those questions, we must first understand what is a distribution of Python.
Python can get distributed to users in many ways. You can download it directly from the official Python Software Foundation's (PSF) website. Or you can install it onto your system using the official Anaconda installer, through Homebrew, or through your official Linux package manager. Each way of installing Python can be thought of as a distribution of Python. Each distribution of Python differs ever so slightly. Official Python from the PSF comes with just the standard library. Anaconda, however, ships with the standard library and many other packages that are relevant for data science.
What is common across all Python distributions, however,
is that it will ship with a Python executable that, at the end of installation,
should be discoverable on your PATH
environment variable.
Most commonly, there will be a Python package installer
that ships with the distribution as well.
This can be pip
, the official tool for installing Python packages,
or it could be conda
, which was developed by the company Anaconda.
As such, the anatomy of a distribution is essentially nothing more than:
PATH
,With that aside, let's look at three distributions of Python that are relevant to this set of notes.
The Anaconda distribution of Python is the official distribution from Anaconda.
It ships with a modern version of Python,
both pip
and conda
package managers,
and a whole slew of default data science packages
(pandas
, numpy
, scikit-learn
, scipy
, matplotlib
, for example).
With the Anaconda distribution,
conda
is configured such that
packages are installed from the anaconda
repository of packages,
hosted by Anaconda itself.
Its default installation location is ~/anaconda
or ~/anaconda3
.
The Miniconda Python distribution also comes from Anaconda.
It looks like Anaconda except it ships with fewer packages in the base environment.
You wouldn't, for example, find pandas
installed for you.
This was mostly intended to keep the base environment small for use within Docker containers.
Its default installation location is ~/miniconda
or ~/miniconda3
.
This distribution of Python comes from the open-source developer team behind conda-forge
.
Miniforge looks like Miniconda, but instead of configuring conda
to pull packages from the anaconda
repository,
conda
packages are instead pulled from the conda-forge
repository of packages by default.
This has the advantage of being able to pull more bleeding-edge versions of packages that you may use.
Additionally, Miniforge Python ships with mamba
as well. (See: Use Mamba as a faster drop-in replacement for conda)
Depends on your persona! If you're an indie hacker type, I would strongly recommend the Miniforge Python as it is lightweight and fast to get set up with and fully open source. On the other hand, if you're more inclined to want enterprise support, vetting of packages, and wish to support a company that backs so much of the Python open source world, then I would recommend reaching out to Anaconda and talking with their sales reps.
Install Anaconda on your machine
Anaconda is a way to get a Python installed on your system.
One of the neat but oftentimes confusing things about Python is that you can have multiple Python executables living around on your system. Anaconda makes it easy for you to:
Why is this a good thing? Primarily because you might have individual projects that need different version of Python and different versions of packages that are built for Python. Also, default Python installations, such as the ones shipped with older versions of macOS, tend to be versions behind the latest, which is to the detriment of your projects. Some built-in apps in an operating system may depend on that old version of Python (such as iPhoto), which means if you mess up the installation, you might break those built-in apps. Hence, you will want a tool that lets you easily create isolated Python environments.
The Anaconda Python distribution fulfills the following key needs:
Installing Anaconda on your local machine thus helps you get easy access to Python, Jupyter (see: Use Jupyter as an experimentation playground), and other tools for modelling and analysis.
To install the Miniforge variant of Anaconda, which will be lighter-weight than the full Anaconda distribution, using the following command:
cd ~
wget "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh" -O anaconda.sh
This will send you to your home directory, and then download the Miniforge bash script installer from Anaconda's download page as anaconda.sh
.
Now, install Anaconda:
bash anaconda.sh -b -p $HOME/anaconda/
This will install the Anaconda distribution of Python onto your system inside your home directory. You can now install packages at will, without needing sudo privileges!
Use Mamba as a faster drop-in replacement for conda
Mamba is a project originally developed by the Quantstack team. They went in and solved some of the annoyances with the conda package manager - specifically the problem of how long it takes to solve an environment specification.
Mamba is available on conda-forge and PyPI. Follow the instructions on the mamba repo to install it.
If you have muscle memory and want to make the switch from conda
to mamba
as easy as possible, you can use a shell alias inside your sourced .aliases
file:
alias conda="mamba"
See the page Create shell command aliases for your commonly used commands for more information on shell aliases.