In my case, I chose the “64-Bit Graphical Installer” to have that nice GUI Anaconda offers. A list will show up, choose the option “ Download Anaconda installers.” Here you will see the Anaconda installers for all operating systems.ĭownload any 64-bit installer for macOS (both work fine with M1 models thanks to Rosetta2 ). Go to Anaconda and click on the “Get started” button. With this option, we will be able to manage Anaconda using the graphical installer. The steps below will help you download the Anaconda installer with all the packages used for data science.

Setting up Python with Miniforge - Step 1: Install Homebrew - Step 2: Install miniforge - Step 3: Setup and activate a virtual environment - Step 4: Install any Python library Option 1: Setting up Python and Data Science Packages with Anaconda Setting up Python and Data Science Packages with Anaconda - Step 1: Download and Install Anaconda - Step 2: Launch Jupyter Notebook/Lab - Step 3: Install any additional library 2. Python will work fine, just keep in mind that people see a 20–30% performance penalty when running x86–64 programs with Rosetta2 compared to native ARM64 Table of Contents 1. Note: The approaches mentioned in this guide won’t help you run Python natively on the M1 Macs but through Rosetta2. Anaconda brings all the tools (including Python and Jupyter Notebook) and packages used in data science with one install, while miniforge gives you the freedom to set up the conda environment as you want, so you need to install any package on your own. In this guide, I will show you how to easily set up Python on any M1 Mac using anaconda and miniforge. After buying an M1 Mac, I realized how confusing is to properly set up Python with all data science packages (and non-data science packages) on the new Mac models.Īccording to this long Anaconda guide to the Apple Silicon, there are 3 options for running Python on the M1 - pyenv, anaconda, and miniforge.

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