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How to Install and Set Up Miniconda on macOS

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If you’re starting with Python and want a lightweight way to manage packages and environments, Miniconda is a great choice. It provides Conda, a powerful tool for creating isolated environments and managing Python packages, without all the extras included in Anaconda.

This guide walks you step-by-step through installing and setting up Miniconda on macOS, using both the graphical installer (GUI) and the terminal installer. We’ll also cover how to install Jupyter Notebook for interactive coding.


Tip: Intel vs Apple Silicon

Not sure which installer to download?

  1. On your Mac, click the  Apple menu → About This Mac.
  2. In the Overview tab, check Processor/Chip:
    • If it says Intel → download the macOS (Intel) installer.
    • If it says Apple M1/M2/M3/M4 → download the macOS (Apple Silicon arm64) installer.

1. Download Miniconda

Option A – GUI Installer (Beginner-friendly)

  1. Go to the Anaconda Download page.
    👉 Yes, Miniconda is downloaded from the same Anaconda page — just scroll to the Miniconda section.
  2. Under Miniconda Installers → macOS, download the installer that matches your Mac:
    • macOS (Intel) – for Intel-based Macs.
    • macOS (Apple Silicon M1/M2/M3/M4) – for Apple Silicon Macs.
  3. Double-click the downloaded .pkg file and follow the on-screen instructions.

Option B – Terminal Installer (For advanced users or server setups)

  1. Open the Terminal.app.
  2. Use curl to download the latest installer for Apple Silicon Macs: curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh (For Intel Macs, replace arm64 with x86_64 in the filename.)
  3. Make the installer executable: chmod +x Miniconda3-latest-MacOSX-arm64.sh
  4. Run the installer: bash Miniconda3-latest-MacOSX-arm64.sh
  5. Press Enter to continue, read and accept the license (yes), and choose an install location (default is ~/miniconda3).

2. Initialize Conda

At the end of installation, you’ll be asked if you want to initialize Conda:

  • ✔ Recommended: say yes (or run conda init later). This updates your shell startup file (e.g., .zshrc) so Conda works in every new terminal session.
  • ❌ Skip if you prefer manual control and want to initialize Conda only when needed.

If you skipped earlier, run manually:

conda init zsh

Restart your terminal. You should see (base) in your prompt, showing that the base Conda environment is active.

Check Conda’s version to confirm installation:

conda --version

3. Create and Manage Environments

Create a new environment:

conda create -n myenv python=3.11
conda activate myenv

Install packages inside it:

conda install numpy pandas

Deactivate when done:

conda deactivate

4. Install Jupyter Notebook

With Miniconda ready, you can easily install Jupyter Notebook:

conda install jupyter notebook

Launch it:

jupyter notebook

A browser window will open. Click New → Python 3 to start a notebook.

Try:

print("Hello, world!")

5. Troubleshooting

  • conda: command not found → Run conda init zsh and restart Terminal.
  • Multiple Python installs → Keep Conda separate; avoid mixing with system Python.
  • Reinstall from scratch → Delete ~/miniconda3 and reinstall.

🎯 Final Notes

  • Beginners: Use the GUI installer for the easiest setup.
  • Advanced users: Use the terminal installer for speed, automation, or remote servers.
  • Always create separate Conda environments for each project.
  • Jupyter Notebook works seamlessly with Conda environments — just activate the one you need before launching.
Previous articleHow to Install and Set Up Miniconda and Install Jupytor Notebook Windows
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Heartin Kanikathottu
As a seasoned Cloud and Security Architect, I’ve led transformative initiatives in key roles, including Vice President at Morgan Stanley, Principal Architect at Societe Generale, and Tech Lead & Cloud Security Architect at VMware, among others. I’m also an internationally published author with multiple books available on platforms like Amazon and O'Reilly. Notably, one of my books was recognized as the 8th best cloud computing book of all time in 2020, reflecting the impact of my contributions to the field. With over 15 professional certifications from providers such as Microsoft (Azure), Amazon (AWS), Oracle (Java), Pivotal (Spring), and IBM, I bring a wealth of expertise to my work. Academically, I hold dual Master’s degrees in Cloud Computing and Data Analytics. I’m passionate about sharing knowledge and mentoring others, which is why I actively speak at global technical forums such as Tech Opportunities Fest at Platform Calgary, Google's Kubernetes Meetup, Java User Group, Elasticsearch Meetup, and the Agile India Conference.

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