Miniconda and Anaconda for Python Guide

Overview

The Markdown Files in this repository will contain instructions on installing and setting up Miniconda and Anaconda Distribution to get started. These files will also contain cruicial information on how to use Miniconda and Anaconda Distribution in any project workflow that relies on Python and managing Python packages/libraries imported into the project.

About Conda, Miniconda, and Anaconda Distribution

Both Miniconda and Anaconda Distributions contains useful Python-based tools for machine learning and data science, and they both have Conda when installing them.

Conda is the package manager that allow developers to install, uninstall, and manage these Python-based tools for any Python-based project.

Miniconda is the lightweight version of Anaconda Distribution, where it comes with fewer Python-based tools when installed but also uses less memory space than Anaconda Distribution.

Structure of the Instructional Markdown Files for Miniconda and Anaconda Distribution

1) Installing Miniconda or Anaconda Distribution (only when you haven't installed them yet)

• Best practices for organizing the installed Miniconda or Anaconda Distribution files for better organization and easier navigation and/or operation 2) Setting up Miniconda or Anaconda Distribution
• Verify that Miniconda or Anaconda Distribution is successfully installed and usable in either Command Prompt, Microsoft Powershell, or Git Bash
• If not, configure so that Miniconda or Anaconda Distribution can be used by the chosen Terminal-based program: Command Prompt, Microsoft Powershell, or Git Bash 3) Creating a new Python virtual environment with Conda that came with Miniconda or Anaconda Distribution (only when for a project repository doesn't have an already existing Python virtual environment)
• Will include all commands to perform this action in Command Prompt, Microsoft Powershell, and Git Bash 4) Activating a Python virtual environment with Conda (only when for a project repository does have an already existing Python virtual environment AND when you want to start working on the project)
• Will include all commands to perform this action in Command Prompt, Microsoft Powershell, and Git Bash 5) Deactivating a Python virtual environemnt with Conda (only when only when for a project repository does have an already existing Python virtual environment AND when you want to stop working on the project and relax)
• Will include all commands to perform this action in Command Prompt, Microsoft Powershell, and Git Bash 6) Project Workflow of using Anaconda Distribution or Miniconda Distribution to implement when working on any Python project
• Will also include mentions of using Git and GitHub to store these Python-based projects and update them with new changes