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How to Run Jupyter Notebooks on MacOS Catalina — in Four Steps
Latest   Machine Learning

How to Run Jupyter Notebooks on MacOS Catalina — in Four Steps

ifttt-user
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July 20, 2023
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Last Updated on July 20, 2023 by Editorial Team

Author(s): Pushkar Pushp

Originally published on Towards AI.

How to Run Jupyter Notebooks on MacOS Catalina — in Four Steps

In my previous blog, I walked you through all steps to run a jupyter notebook. If you’re a data scientist or developer and upgraded to macOS Catalina 10.15, then you might have faced some issues with the jupyter notebook. The latest version of Mac Catalina functionality is different than the previous s version. Follow the below steps to configure and run a jupyter notebook on the latest Catalina version.

There are four easy steps to configure a jupyter notebook.

Step I: Install the anaconda distribution.

The preferable way to go forward is to use a command-line installer instead of a graphic.

Use this link to download CLI https://repo.anaconda.com/archive/Anaconda3-2020.02-MacOSX-x86_64.sh

Once downloaded, go to the terminal and run.

shasum -a 256 /Downloads/Anaconda3-2020.02-MacOSX-x86_64.sh

The next step is to install anaconda with python3, not python2, as it is obsolete in use nowadays.

To start the installation, run below command in your terminal.

bash ~/Downloads/Anaconda3-2020.02-MacOSX-x86_64.sh

Instead of Downloads, use your installation path of anaconda distribution and similarly replace Anaconda3–2020.02-MacOSX-x86_64.sh with your filename.

The screen appears like this,

You need to press Enter here,

Read the license agreement and scroll to the bottom.

Enter yes. Next, it asks for a location to install.

Again Press Enter.

Once you press enter, message props, “Do you wish the installer to initialize Anaconda3 by running conda init?”

Enter Yes

The default shell for Catalina is zsh, so our next step is to install Zsh

Step II: Set-up macOS Terminal with Zsh

For Catalina

First set-up Xcode command-line tools, also known as Xcode-select

xcode-select --install

If there is some issue, try running the below script.

xcode-select — reset

Then you need to install a software package management system for macOS, i.e., Homebrew.

Run the below command.

/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"

The next step is to install a default shell for Catalina, i.e., zsh.
brew install zsh

brew install zsh

Now we need to integrate zsh in iterm2. If you are not having iterm2, install it using brew.

brew cask install iterm2

For zsh — iterm2 integration ,

sh -c "$(curl -fsSL https://raw.githubusercontent.com/robbyrussell/oh-my-zsh/master/tools/install.sh)"

Step III: Conda, Pip, and Jupyter installation

Use brew to install conda, run below command.

brew cask install miniconda

Update conda to the latest version.

conda update conda

For pip, you can either use conda or easy install.

Conda way

conda install pip

Easy install way

sudo easy_install pip

For nbextensions run following command

conda install -c conda-forge jupyter_contrib_nbextensions

Lastly, for jupyter installation use, brew.

brew install jupyter

Step IV: Creating a Virtual environment and link it to ipykernel

I always prefer to create a virtual environment for my projects to avoid conflict of package dependencies.

To create a virtual environment, pass the name of the environment with the python version to be used. Suppose we want to create an environment named Cat and want to use the Python 3.8.2 version.

Run below command to create the ‘Cat’ environment.

conda create -n Cat python=3.8.2 anaconda

To activate the environment, pass Cat to conda activate.

conda activate Cat

Open a new Zsh window and install ipykernel.

pip install — user ipykernel

The next step is to link the kernel to the virtual environment.

python -m ipykernel install --user --name=Cat

If you want to display the name of the environment, say “Cat_Virtual.”, use below command.

python -m ipykernel install — user — name Cat — display-name “Cat_Virtual”

Go to iterm2 and run.

jupyter notebook

Open any notebook; it appears like this,

Enjoy! U+1F60A

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} strongTag.remove(); }); }); } removeStrongFromHeadings(); "use strict"; window.onload = () => { /* //This is an object for each category of subjects and in that there are kewords and link to the keywods let keywordsAndLinks = { //you can add more categories and define their keywords and add a link ds: { keywords: [ //you can add more keywords here they are detected and replaced with achor tag automatically 'data science', 'Data science', 'Data Science', 'data Science', 'DATA SCIENCE', ], //we will replace the linktext with the keyword later on in the code //you can easily change links for each category here //(include class="ml-link" and linktext) link: 'linktext', }, ml: { keywords: [ //Add more keywords 'machine learning', 'Machine learning', 'Machine Learning', 'machine Learning', 'MACHINE LEARNING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ai: { keywords: [ 'artificial intelligence', 'Artificial intelligence', 'Artificial Intelligence', 'artificial Intelligence', 'ARTIFICIAL INTELLIGENCE', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, nl: { keywords: [ 'NLP', 'nlp', 'natural language processing', 'Natural Language Processing', 'NATURAL LANGUAGE PROCESSING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, des: { keywords: [ 'data engineering services', 'Data Engineering Services', 'DATA ENGINEERING SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, td: { keywords: [ 'training data', 'Training Data', 'training Data', 'TRAINING DATA', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ias: { keywords: [ 'image annotation services', 'Image annotation services', 'image Annotation services', 'image annotation Services', 'Image Annotation Services', 'IMAGE ANNOTATION SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, l: { keywords: [ 'labeling', 'labelling', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, pbp: { keywords: [ 'previous blog posts', 'previous blog post', 'latest', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, mlc: { keywords: [ 'machine learning course', 'machine learning class', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, }; //Articles to skip let articleIdsToSkip = ['post-2651', 'post-3414', 'post-3540']; //keyword with its related achortag is recieved here along with article id function searchAndReplace(keyword, anchorTag, articleId) { //selects the h3 h4 and p tags that are inside of the article let content = document.querySelector(`#${articleId} .entry-content`); //replaces the "linktext" in achor tag with the keyword that will be searched and replaced let newLink = anchorTag.replace('linktext', keyword); //regular expression to search keyword var re = new RegExp('(' + keyword + ')', 'g'); //this replaces the keywords in h3 h4 and p tags content with achor tag content.innerHTML = content.innerHTML.replace(re, newLink); } function articleFilter(keyword, anchorTag) { //gets all the articles var articles = document.querySelectorAll('article'); //if its zero or less then there are no articles if (articles.length > 0) { for (let x = 0; x < articles.length; x++) { //articles to skip is an array in which there are ids of articles which should not get effected //if the current article's id is also in that array then do not call search and replace with its data if (!articleIdsToSkip.includes(articles[x].id)) { //search and replace is called on articles which should get effected searchAndReplace(keyword, anchorTag, articles[x].id, key); } else { console.log( `Cannot replace the keywords in article with id ${articles[x].id}` ); } } } else { console.log('No articles found.'); } } let key; //not part of script, added for (key in keywordsAndLinks) { //key is the object in keywords and links object i.e ds, ml, ai for (let i = 0; i < keywordsAndLinks[key].keywords.length; i++) { //keywordsAndLinks[key].keywords is the array of keywords for key (ds, ml, ai) //keywordsAndLinks[key].keywords[i] is the keyword and keywordsAndLinks[key].link is the link //keyword and link is sent to searchreplace where it is then replaced using regular expression and replace function articleFilter( keywordsAndLinks[key].keywords[i], keywordsAndLinks[key].link ); } } function cleanLinks() { // (making smal functions is for DRY) this function gets the links and only keeps the first 2 and from the rest removes the anchor tag and replaces it with its text function removeLinks(links) { if (links.length > 1) { for (let i = 2; i < links.length; i++) { links[i].outerHTML = links[i].textContent; } } } //arrays which will contain all the achor tags found with the class (ds-link, ml-link, ailink) in each article inserted using search and replace let dslinks; let mllinks; let ailinks; let nllinks; let deslinks; let tdlinks; let iaslinks; let llinks; let pbplinks; let mlclinks; const content = document.querySelectorAll('article'); //all articles content.forEach((c) => { //to skip the articles with specific ids if (!articleIdsToSkip.includes(c.id)) { //getting all the anchor tags in each article one by one dslinks = document.querySelectorAll(`#${c.id} .entry-content a.ds-link`); mllinks = document.querySelectorAll(`#${c.id} .entry-content a.ml-link`); ailinks = document.querySelectorAll(`#${c.id} .entry-content a.ai-link`); nllinks = document.querySelectorAll(`#${c.id} .entry-content a.ntrl-link`); deslinks = document.querySelectorAll(`#${c.id} .entry-content a.des-link`); tdlinks = document.querySelectorAll(`#${c.id} .entry-content a.td-link`); iaslinks = document.querySelectorAll(`#${c.id} .entry-content a.ias-link`); mlclinks = document.querySelectorAll(`#${c.id} .entry-content a.mlc-link`); llinks = document.querySelectorAll(`#${c.id} .entry-content a.l-link`); pbplinks = document.querySelectorAll(`#${c.id} .entry-content a.pbp-link`); //sending the anchor tags list of each article one by one to remove extra anchor tags removeLinks(dslinks); removeLinks(mllinks); removeLinks(ailinks); removeLinks(nllinks); removeLinks(deslinks); removeLinks(tdlinks); removeLinks(iaslinks); removeLinks(mlclinks); removeLinks(llinks); removeLinks(pbplinks); } }); } //To remove extra achor tags of each category (ds, ml, ai) and only have 2 of each category per article cleanLinks(); */ //Recommended Articles var ctaLinks = [ /* ' ' + '

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