Python Installation for Data Science - Overview

So far in this program, you have worked in Google Colab, which provides a cloud-based coding environment.

We will transition to using a Python environment stored on your local machine.
- Jupyter Notebook will replace Google Colab.
- GitHub Desktop will sync your work.

Installation Timeline/Deadline

In the Data Enrichment course, you will need to submit a CORE ASSIGNMENT containing the error-free test notebook that is included within these instructions. This will ensure that you have the tools you will need to be successful.
We recommend you begin the step-by-step installation AS SOON AS POSSIBLE to ensure you have time to troubleshoot any difficulties you may encounter.
These steps should take ~30-90 minutes, depending on the speed of your machine and internet connection.
If you run into issues during installation, see the "How to Ask for Help" secton at the bottom of this page.
The dojo-env-setup repository, which you will clone in Step 2.1, contains a backup copy of the entire set of instructions on the README, for convenience.

Note: if you previously installed the dojo-env and are upgrading to the current version, please see the "Updating to New dojo-env" instructions

Installation Overview:

By the end of this installation, you will:

1) Install or Set Up a Terminal application:

The terminal is the primary application you will use to execute programming commands.
- Mac and Linux users should already have a Terminal application installed.
- Windows users will install additional software (Windows Terminal + Git for Windows)

2) Install a Python distribution:

The foundation/infrastructure for installing our custom Python environment.

Windows and Intel-Macs will install Anaconda.
Apple Chip Macs will installing a lightweight alternative called miniforge.

3) Install GitHub Desktop

Desktop application for working with and managing git repositories.

4) Create our custom Python environment (dojo-env)

An environment is a bundle of specific versions of python packages that are mutually compatible.
We will install our custom `dojo-env`` Python environment, located in the dojo-env-setup repository.

5) Test & customize the environment using Jupyter Notebook

Jupyter Notebook will replace Google Colab on your local computer.

6) Install Visual Studio Code as a secondary code editor.

A special text editor designed for code. It has many extensions and languages available.
We will use it to edit special files later in the course, but it can also run notebooks too!

OS-Specific Instructions

Please make sure you select the correct instructions page, based on your computer's operating system!

Supported Operating Systems

We have prepared environment files (.yml files) for 4 different OS configurations:

Windows (10 & 11)
Mac (with Intel Processors)†
Mac (Apple Chips)†

†Mac users - if you don't know which type of Mac you have :

Check the "About this Mac" screen for your computer:

Click on the Apple symbol in the top-left corner of your screen > Click "About This Mac".
A window with your computer's specs will appear like the one in the screenshots below, depending on how which version of macOS you have installed.

If it has a "Processor" line that says "Intel" you should follow the Instructions: Mac (Intel Processor).
If it has a "Chip" line that says "Apple" then you should follow the Instructions: Mac (Apple Chip).

Installation Instructions Pages

Please review the How to Ask for Help Section At the Bottom of this page if you get stuck!

For New Installations:

For updating Pre-Existing Install:

Updating to a New dojo-env

Troubleshooting

Troubleshooting Documentation

You can find the troubleshooting lessons on this GitHub Pages site: https://chastityb.github.io/dojo-env-setup-instructions/troubleshooting/

How to Ask for Help

If you encounter an error during installation: You may continue to work through the first half of the data enrichment week 1 lessons & assignments while troubleshooting your local installation! The first lessons and assignments can be completed using Google Colab.

First, read a little further down in the instructions to make sure we do not already address the error message that you ran into.
Second, please check the "Troubleshooting" chapter on the learnig platform for a lesson that mentions your problem. about the problem you are running into. (The Troubleshooting section is the 3rd chapter in this course - see the screenshot below)
Image Not Showing Possible Reasons
- The image file may be corrupted
- The server hosting the image is unavailable
- The image path is incorrect
- The image format is not supported
Learn More →
Third, reach out on the #ds-python-installation Discord channel with the following info:
- A) Which step are you on? (e.g. Step 2.3.3 Confirm the env was created)
- B) Which OS you are using (e.g. Windows 10, Windows 11, Mac with an mchip, Mac with an Intel processor, etc.)
- C) Let us know if you've previously installed an older version of Python.
- D) Attach your copy of the environment tester notebook and the FINAL_REPORT.txt files.
- E) Include any additional screenshots of the error/issue you are running into, whenever possible.
- F) Add any additional details or info you think may be helpful for us to know.
  - For example:
    - "My computer is really old and I think that may be part of the problem."
    - "I share this computer with someone else who also uses python"
    - "This is my work computer and I am not an administrator." etc
Fourth, if you do not receive a response by the end of the day on Discord, please email your instructor with the same information.
- An instructor or TA will get back to you within 1 business day with the next steps for you to try.
- You will most likely need to set up a Zoom call and share your screen for us to help.

Now, navigate to the correct instructions page, based on your operating system, as explained above:

APPENDIX

Links of Interest

08/23/23 Note: Switch to the v2023 branch in the dojo-env-setup repo in GitHub Desktop for the correct env files.

Reference: Helpful Commands

Installation Commands

To activate dojo-env and add it to Jupyter (after installation)

conda activate dojo-env               
python -m ipykernel install --user --name dojo-env --display-name "Python (dojo-env)"

To re-add conda command:

# Generic command (doesn't always work)
conda init

# Windows
conda init  bash

# Mac 
conda init zsh

Uninstall commands

Uninstall dojo-env

To remove the current dojo-env:

conda activate base                             
conda remove --name dojo-env --all

Then answer y for yes

Setting Default Env

For Mac Users (using the default terminal - zsh)

touch ~/.zshrc
echo "conda activate dojo-env" >> ~/.zshrc
echo 'alias jnb="jupyter notebook"' >> ~/.zshrc
echo 'alias lab="jupyter lab"' >> ~/.zshrc

For Windows Users (or mac users who switched to bash)

To set dojo-env as the default Python env and add Jupyter shortcuts

Note: you may need to replace ~ with the full path to your user folder. (e.g. "/Users/codingdojo/.bash_profile" instead of "~/.bash_profile")

touch ~/.bash_profile
echo "conda activate dojo-env" >> ~/.bash_profile
echo 'alias jnb="jupyter notebook"' >> ~/.bash_profile
echo 'alias lab="jupyter lab"' >> ~/.bash_profile

Managing Jupyter Kernels

To see the list of kernels that jupyter will display as options:

jupyter kernelspec list

To remove a kernel that no longer exists (replace <kernel name> with name of kernel from the jupyter kernelspec list command ):

jupyter kernelspec remove <kernel name>

# Example:
jupyter kernelspec remove dojo-env-old