1.3.2 VS Code Configuration

What this section is about

In this section, we’ll configure VS Code into a development tool that works well for Python and AI learning. You’ll finish editor installation, extension setup, the built-in terminal, and common shortcut settings, so your later coding practice has a stable and convenient workspace.

Learning objectives

• Install VS Code and choose the interface language you prefer
• Install essential extensions for Python development
• Learn to use the built-in terminal in VS Code
• Master 10 of the most commonly used shortcuts
• Understand AI-assisted programming tools

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Why choose VS Code?

Editor	Pros	Cons
VS Code	Free, lightweight, rich extensions, great AI support	For large projects, it may be less intelligent than PyCharm
PyCharm	Strongest Python support, convenient refactoring	Community Edition is free but limited; Professional Edition costs money
Vim/NeoVim	Extremely fast, geeky	Steep learning curve

VS Code is currently the most widely used code editor in the world, and it has excellent support for Python and AI development. For beginners, it is the best choice.

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Install VS Code

macOS

# Install with Homebrew (recommended)
brew install --cask visual-studio-code

# Or download from the official website: https://code.visualstudio.com

After installation, configure command-line launch:

1. Open VS Code
2. Press Cmd + Shift + P and type “shell command”
3. Select Shell Command: Install ‘code’ command in PATH

After that, you can use the code command in the terminal to open files and folders:

code .                  # Open the current folder with VS Code
code ~/projects         # Open a specific folder
code hello.py           # Open a specific file

Windows

# Install with winget
winget install Microsoft.VisualStudioCode

# Or download from the official website: https://code.visualstudio.com

During installation, check “Add to PATH” so you can use the code command in the terminal.

Ubuntu

# Method 1: use snap (recommended)
sudo snap install code --classic

# Method 2: use apt
sudo apt install software-properties-common apt-transport-https wget
wget -q https://packages.microsoft.com/keys/microsoft.asc -O- | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://packages.microsoft.com/repos/vscode stable main"
sudo apt update
sudo apt install code

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Interface Language (Optional)

1. Open VS Code
2. Press Ctrl + Shift + X (Cmd + Shift + X on macOS) to open the Extensions panel
3. Search for the language pack you prefer, such as English Language Pack, Chinese (Simplified), or Japanese Language Pack
4. Click Install
5. Restart VS Code, and the interface will switch to that language

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Install essential extensions

Open the Extensions panel (the square icon on the left sidebar, or press Ctrl/Cmd + Shift + X), then search for and install the following extensions:

Must-have extensions

Extension	Purpose	Search keyword
Python	Python syntax support, debugging, running	ms-python.python
Pylance	Python intelligent suggestions, type checking	ms-python.vscode-pylance
Jupyter	Run notebooks in VS Code	ms-toolsai.jupyter
GitLens	Enhanced Git features, see who changed which line	eamodio.gitlens
Black Formatter	Format Python code consistently	ms-python.black-formatter

Recommended extensions

Extension	Purpose
autoDocstring	Automatically generate Python function docstrings
Ruff	Fast linting and import cleanup for Python
indent-rainbow	Use colors to distinguish indentation levels
Error Lens	Show error messages directly at the end of code lines
Material Icon Theme	More attractive file icons

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Configure the Python interpreter

After installing the Python extension, you need to tell VS Code which Python environment to use:

1. Press Ctrl/Cmd + Shift + P to open the Command Palette
2. Type Python: Select Interpreter
3. Select the conda environment you created earlier (for example, ai-course)

You should see a list of options like this:

Python 3.11.7 ('ai-course')    ~/miniconda3/envs/ai-course/bin/python
Python 3.12.1 ('base')         ~/miniconda3/bin/python

Choose the ai-course one.

Automatic detection

The Python extension in VS Code will automatically detect all Python environments on your system, including conda and venv environments. If you can’t see the environment you want, try activating that environment in the terminal first with conda activate, then open VS Code by typing code . in the terminal.

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Use the built-in terminal

VS Code comes with a built-in terminal, so you don’t need to open a separate terminal window.

Open the terminal

Shortcut: Ctrl + ` (the key in the upper-left corner of the keyboard, below ESC)

Or from the menu: Terminal → New Terminal

Example: complete the full development workflow in VS Code

# 1. Activate the environment in the terminal
conda activate ai-course

# 2. Create a project folder
mkdir my-first-project
cd my-first-project

# 3. Open this folder with VS Code (it will open in a new window)
code .

Then in VS Code:

1. In the file explorer on the left, click the New File icon and create hello.py
2. Write the code:

name = input("What is your name?")
print(f"Hello, {name}! Welcome to the AI world 🤖")

3. Click the ▶ Run button in the upper-right corner (or press Ctrl/Cmd + Shift + P → “Run Python File”)
4. Check the output in the terminal

Terminal tips

• Multiple terminals: click the + button in the top-right of the terminal panel to open more terminals
• Split view: you can split the editor and terminal side by side, so you can write code while watching the terminal
• Terminal type: you can choose different shells such as bash, zsh, and PowerShell

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Most commonly used shortcuts

You don’t need to memorize everything. First remember the top 5, and look up the rest when you need them.

Basic operations

Action	Windows/Linux	macOS
Command Palette (most important!)	Ctrl + Shift + P	Cmd + Shift + P
Quick Open File	Ctrl + P	Cmd + P
Open/Close Terminal	Ctrl + `	Ctrl + `
Save	Ctrl + S	Cmd + S
Undo	Ctrl + Z	Cmd + Z

Edit code

Action	Windows/Linux	macOS
Duplicate current line	Shift + Alt + ↓	Shift + Option + ↓
Move current line	Alt + ↑/↓	Option + ↑/↓
Delete current line	Ctrl + Shift + K	Cmd + Shift + K
Multi-cursor editing	Alt + Click	Option + Click
Comment code	Ctrl + /	Cmd + /
Format code	Shift + Alt + F	Shift + Option + F

Search and navigation

Action	Windows/Linux	macOS
Global search	Ctrl + Shift + F	Cmd + Shift + F
Search within file	Ctrl + F	Cmd + F
Find and replace	Ctrl + H	Cmd + Option + F
Go to line	Ctrl + G	Ctrl + G

Example: the power of multi-cursor editing

Suppose you need to rename 5 variable names from data1, data2… to dataset1, dataset2…:

data1 = load("file1.csv")
data2 = load("file2.csv")
data3 = load("file3.csv")
data4 = load("file4.csv")
data5 = load("file5.csv")

Steps:

1. Select the first data
2. Press Ctrl/Cmd + D five times to select all data occurrences one by one
3. Type dataset

All 5 places are changed at the same time, and it’s done in 2 seconds.

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AI-assisted programming tools

There are now many AI tools that can help you write code in VS Code. As a learner in an AI course, it’s worth knowing about them:

GitHub Copilot

• Automatically completes code as you type
• Press Tab to accept suggestions
• Eligible education accounts may receive free access through GitHub Education
• Extension search: GitHub.copilot

Codeium

• Free AI code completion tool
• Similar to Copilot, completely free for individual users
• Extension search: Codeium.codeium

Usage advice

Advice for learners

During the learning stage, do not rely too much on AI code completion. It is like a calculator—if you start using a calculator before you’ve learned mental arithmetic, you’ll never learn math well.

Recommendations:

• For the first two stages (Python basics): turn off AI completion and write code yourself
• After the 4th stop: you can turn on AI completion, but make sure to understand every line of code it generates
• When building projects: feel free to use it to improve efficiency

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Recommended VS Code settings

Press Ctrl/Cmd + , to open Settings, then search for and change the following options:

Setting	Recommended value	Reason
Auto Save	afterDelay	Auto-save so you never have to worry about forgetting Ctrl+S
Font Size	14 or 15	Slightly larger code font, easier on the eyes
Tab Size	4	Standard Python indentation
Word Wrap	on	Automatically wrap long lines
Minimap	off	Turn off the small map on the right to save screen space

Or edit settings.json directly (Ctrl/Cmd + Shift + P → “Open Settings JSON”):

{
    "files.autoSave": "afterDelay",
    "editor.fontSize": 14,
    "editor.tabSize": 4,
    "editor.wordWrap": "on",
    "editor.minimap.enabled": false,
    "python.terminal.activateEnvironment": true,
    "editor.formatOnSave": true,
    "[python]": {
        "editor.defaultFormatter": "ms-python.black-formatter"
    },
    "python.analysis.typeCheckingMode": "basic"
}

Why not use older Python formatting settings?

Older tutorials often show "python.formatting.provider": "black". Newer VS Code Python tooling uses formatter extensions instead. If format-on-save does not work, first check that Black Formatter is installed and that the selected interpreter is your project environment.

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Hands-on practice

1. Install VS Code and the essential extensions (Python, Pylance, Jupyter, GitLens)
2. Create a project and open it with VS Code:

mkdir vscode-practice && cd vscode-practice && code .

3. Create practice.py and write the following code:

# Practice VS Code shortcuts
tasks = [
    "load config",
    "validate dataset",
    "run smoke test",
    "write metrics",
    "commit changes",
]

for i, task in enumerate(tasks):
    print(f"{i + 1}. {task}")

# Calculate the average task label length
avg_len = sum(len(task) for task in tasks) / len(tasks)
print(f"\nAverage task label length: {avg_len:.1f} characters")

4. Run the code (click the ▶ button in the upper-right corner)
5. Try these shortcuts:
   • Use Ctrl/Cmd + / to comment out the last two lines
   • Use Alt + ↑/↓ to move one line of code
   • Use Ctrl/Cmd + D to multi-select one word
   • Use Ctrl/Cmd + Shift + F to search globally for “task”

Project reference and review notes

1. code . should open the current project folder, not a single detached file.
2. The selected Python interpreter should match your course environment. Check the VS Code status bar or the command palette.
3. Running practice.py should print five AI project task lines and an average task label length.
4. If the Run button uses the wrong Python, run the file from the integrated terminal and then fix the selected interpreter.
5. The shortcut practice passes when you can undo your edits and still run the script successfully.

Evidence to Keep

Keep this page’s proof of learning as a small evidence card:

Environment

Python/Node/editor/notebook version and selected interpreter/kernel

Verification

one command or notebook cell proving the setup works

Project Folder

where dependencies, scripts, and notebooks live

Failure Check

wrong interpreter, missing package, stale kernel, or editor path mismatch

Expected Output

setup screenshot or terminal output plus one fallback note