Jupyter Mac Install

You've probably heard a lot about the MacBook that contains the new Apple M1 chip. Quick summary: It's fast. Like, really fast. You, a data scientist or related tech professional, may have bought one.

  1. Installation with pip. If you use pip, you can install it with: pip install jupyterlab. If installing using pip install -user, you must add the user-level bin directory to your PATH environment variable in order to launch jupyter lab. If you are using a Unix derivative (FreeBSD, GNU / Linux, OS X), you can achieve this by using export PATH.
  2. Sep 12, 2021 Mac Install Jupyter Notebook; Jupyter Mac Install; To install pip, go through How to install PIP on Windows? And follow the instructions provided. Installing Jupyter Notebook using Anaconda: Anaconda is an open-source software that contains Jupyter, spyder, etc that are used for large data processing, data analytics, heavy scientific computing.

Step 5: If you've installed Python but had trouble installing Jupyter, then go to your Terminal and type pip3 install jupyter. If that doesn't work, then head here and follow the instructions. Now to fix the Jupyter kernel issue! At this point, Python and Jupyter should be installed. You want to stop your kernel from repeatedly dying.

Disclaimer: We'll attempt to keep this updated as best we can. These instructions are up to date as of November 30, 2020.

Your goal: Run a Jupyter notebook.

Either you're opening a notebook right now and your kernel instantly dies, or you haven't been able to get a Jupyter notebook operational yet. That's why we're here! In this blog, we'll walk through how to get Jupyter functional on your M1 computer -- starting with the download step and ending with a fully operational Jupyter notebook. (We'll assume you don't know if you have Jupyter on your computer yet! If you know with certainty that you have Jupyter downloaded, you can skip down here.)

Check if Python & Jupyter are already installed.

Step 1: Open up your Terminal by holding Command and hitting Space, which should bring up your Spotlight Search.Then, type Terminaland hit Return.

Jupyter Mac Install

Step 2:In your Terminal, typejupyter notebook and hit Return.

  • If your Terminal looks like the image directly below and a Jupyter interface opens in your browser like the the second image below, then Jupyter is installed. You're almost done. (It's OK if you get a kernel error, we'll figure that out later!) Skip to step 6.
  • If, instead, your Terminal says command not found: jupyter then you need to see if Python is even installed before you can install Jupyter. Move to step 3.

Step 3: Let's check if Python has been installed. In the terminal, type python3 and hit Return.

  • If you see something similar Python 3.X.Y, with the >>> at the bottom, then great! That means Python 3 is installed. Go ahead and type quit(). Jump ahead to step 5.
  • If you get a command not found: python3 error, this means that you need to install Python. New Mac operating systems should have it already installed, so if you're finding an error, make sure that there isn't a typo somewhere. Move to step 4.

Step 4: You can install Python by going to XCode Command Line Tools. You'll need to login with your Apple ID and follow the instructions. Note that the normal Anaconda download won't work here, as the M1 computer isn't 64-bit. Once you're done, head back up to Step 3.

Step 5: If you've installed Python but had trouble installing Jupyter, then go to your Terminal and type pip3 install jupyter. If that doesn't work, then head here and follow the instructions.

Now to fix the Jupyter kernel issue!

At this point, Python and Jupyter should be installed. You want to stop your kernel from repeatedly dying.

Step 6: In your Terminal, typejupyter notebook and hit Return. Once you do, then click 'New' (on the right-hand side) and open up a Python 3 notebook.

  • If you're able to run commands in your notebook – great! The tutorial is over. Skip to the bottom for a note about TensorFlow (if TensorFlow is what you care about) or feel free to check out some of our other posts, mostly about computer vision, here.

Step 7: Thanks to this link and user burakozdamarpublicizing George Hotz' YouTube video, we learned a workaround that will stop your Jupyter notebook kernel from... well, stopping.

You will need to use the Terminal and/or Finder to find a filepath in your system that ends with ipykernel/eventloops.py. (On my system, it is lib/python3.8/site-packages/ipykernel/eventloops.py, but yours may vary slightly. The important thing is that you find the eventloops.py file.) You will make one change to this file.

  • Open Terminal.
  • Type nano filepath/ipykernel/eventloops.py where filepath should be the specific filepath that takes you to that specific eventloops.py in the ipykernel folder. Hit Enter. You should see the following:
  • Use your arrow keys to navigate to def _use_appnope(), which is the first function toward the bottom of the screenshot above. The return line is what we are going to edit.
  • In that return line, use your arrow keys to navigate all the way to the right-hand side of that line. After V('10.9'), you are going to add:

and platform.mac_ver()[2] != 'arm64'

The full line should look like this when you are done:

  • Once you have made that edit and are sure you haven't created a typo, then hold Control and hit x to exit.
  • It will ask you to save. Press y.Then pressReturn.

I recognize: this process is a very 'do as I say and don't ask any questions' process. If you want to know more, George Hotz excellently describes the debugging process in his video; you can jump to around where he makes the change (47 minutes, 30 seconds) here. Note that George also edits the docstring (the text between the '' triple quotation marks '') to better reflect what the function is doing – checking for Apple Silicon.

Step 8: If you've followed the above steps, you should be good to go! I usually quit the Terminal (hold Command and press Q) because I think that, sometimes, updates won't immediately take effect without restarting the Terminal. Make sure that it works by returning to step 6 and writing commands in your Jupyter notebook.

You should now be set up to go!


Thanks for following along! I hope this is helpful. Let us know if you spot any mistakes or needed updates (use the email button on the left side of the screen) – I want to keep this as helpful as possible for people, and new technology tends to change very quickly.

Bonus: Want to use TensorFlow?

If your goal is to install TensorFlow, it isn't officially supported yet on the M1. However, you can create a virtual environment following the instructions here. Notice that while there are workarounds for certain TensorFlow features, other features like object_detection are not yet supported. If you learn of workarounds, let us know by emailing us!

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Education, Getting Started, Tutorials

Here's how to install Jupyter with python and R integration on OSX using Homebrew.

Read this tutorial on how to install Homebrew on OS X.

Mac Os X come with Pythong 2.7 pre-installed but many Machine Learning packages are progressing to Python 3.x. Therefore, it's recommended you start using Python 3 and the best way to do that is to first install pyenv version manager. This will allow you to install any version of Python you'd like.

First update Homebrew package manager.

Install pyenv version manager.

Install Python 3.x using pyenv. You can see a list of version from the Python website.

Double check your work.

Jupyter Mac Install

You'll also need to configure your ~/.bash_profile.

If you need more help with pyenv, I suggest you reading my other article titled Installing multiple versions of python on OS X using Homebrew

If you only want to use Python 3.x for a specific project, then cd to your specific directory and type:

If you'd prefer to just have Python 3.x installed globally throughout your operating system, then type:

Jupyter is an acronym for Julia, Python and R but these days, other languages are also included such as Ruby.

Now it's time to start the jupyter notebook.

You're Done Installing Jupyter. Please proceed if you now want to use R language with Jupyter.


Jupiter Mac Installer

If you're struggling to get configure bash profile, this has also worked for a few different developers.

Although it takes a little bit of extra work to get R working with Jupyter, it's totally worth it. Otherwise, if you want to import data, clean it, structure it and process it, you'll have to have to learn all of these other Python libraries to do what R does natively.

Anaconda Jupyter Install Mac

  • NumPy supports scientific computing and linear algebra support.
  • Pandas provide data frames which make it easy to access and analyze data. This is a data manipulation tool.
  • Mat plotlib is a 2D publication library that produces high quality graphics.
  • Scikit-learn's purpose is to support machine learning and therefore it's used for many of the tasks performed routinely in machine learning. A few key features are:
    • It works well with the libraries stated above.
    • It helps integrate the algorithms we will use for predictive models.
    • Methods that will help us pre-process data.
    • Methods for helping us measure the performance of our models.
    • Methods for splitting data into test sets
    • Methods for pre-processing data before training.
    • Methods for creating trained models, tuning models and identifying which features within the models are important.