(Part 1 of series Blueprint for a Modern Research Computing Environment)
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In this article, we’ll build the foundation of our Python development environment.
By the end, you’ll have:
AI tools (like Claude, Grok, Gemini, or ChatGPT) give the best troubleshooting advice when they have the exact text of the tutorial. To ensure the AI understands what you are trying to build, we will give it the actual file.
1. Download the tutorial file
2. Upload it to your AI
Part1.md into the chat).3. Ask for Help Copy and paste this exact prompt into the chat along with your file:
I have attached the markdown file for the tutorial I am following. Please read it so you understand the specific environment I am trying to build.
I need help with the following:
Step [X]: [paste exact step text from the blog]
Command I ran: [paste exact command]
What happened: [paste full output/error — if the terminal was truly blank, say so explicitly]
Please help me troubleshoot and fix this error. You can use your general knowledge to solve the problem, but your solution MUST align with the architecture and tools taught in the attached file. Do not suggest alternative setups that contradict the tutorial. Once fixed, tell me what to do next in the article.
To go deeper on a step before you run a command:
I have attached the
Part1.mdfile. Look at Step [X] and explain exactly what the command does and why we are doing it before I run it.
Think of this series as the roadmap and your AI assistant as your learning companion.
A Windows Terminal window should now open.
Run:
wsl --list --online
Choose the Ubuntu version you’d like to install.
For this series, we’ll use: Ubuntu-24.04
Run:
wsl --install -d Ubuntu-24.04
Windows will:
Restart your computer if prompted.
Open Ubuntu from the Start Menu.
If you don’t see it yet, open Windows Terminal and run:
wsl -d Ubuntu-24.04
The first launch may take a minute.
Ubuntu will ask you to create:
Choose any username you’d like.
While typing your password, nothing will appear on the screen. This is normal.
Press Enter after typing the password.
Run:
sudo apt update
Then:
sudo apt upgrade -y
Ubuntu may ask for the password you created.
Run:
sudo apt install -y wget curl git build-essential ca-certificates
These utilities are commonly required by development tools.
Move to your home directory:
cd ~
Download Miniconda:
wget [https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh](https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh)
Run:
bash Miniconda3-latest-Linux-x86_64.sh
During installation:
yes to accept it.yes.Close Ubuntu. Open it again.
You should now see (base) at the beginning of the terminal prompt.
Run:
conda --version
Then:
python --version
Then:
pip --version
Each command should display a version number.
Before moving on, let’s understand where your files are stored.
Your Linux home directory is:
/home/<your-username>
or simply ~.
To return here at any time:
cd ~
To see your current location:
pwd
Inside Ubuntu, your Windows drives appear under /mnt:
| Windows Drive | WSL Path |
|---|---|
| C:\ | /mnt/c |
| D:\ | /mnt/d |
| E:\ | /mnt/e |
By default, Miniconda is installed in:
~/miniconda3
Although you can work inside /mnt/c or /mnt/d, it’s generally recommended to keep Python projects inside your Linux home directory.
For example:
/home/<your-username>/
└── projects/
Don’t worry — the projects directory doesn’t exist yet. We’ll create it properly in a later article on Linux essentials for Python developers.
For now, simply remember that your home directory (~) is the recommended place for your future projects.
You now have WSL2, Ubuntu, and Miniconda installed and ready to use.
Next: Part 2 — Terminal Basics and File Navigation | Previous: Preface — Blueprint for a Modern Research Computing Environment