Python Development Environment Setup

This project contains everything you need to set up a Python development environment in Visual Studio Code on Ubuntu (WSL), with support for running Python scripts and Jupyter notebooks.

Important: If you're using VS Code on Windows with Ubuntu through WSL, please refer to the WSL Setup Guide for specific instructions.

Files in this Project

• docs/wsl_setup_guide.md - Specific instructions for using VS Code with WSL (Windows Subsystem for Linux)
• docs/python_environment_setup.md - Detailed instructions for setting up your Python environment
• setup_environment.py - Helper script to set up a Python virtual environment
• setup_jupyter.py - Helper script to set up Jupyter notebook support
• number_game.py - A simple number guessing game to test Python script execution
• python_basics.ipynb - A sample Jupyter notebook to test notebook functionality
• requirements.txt - List of Python packages required for this project:
  • ipykernel and jupyter - Required for Jupyter notebook functionality
  • numpy, pandas, matplotlib - Used in the sample notebook for data manipulation and visualization
  • pylint and autopep8 - Code linting and formatting tools for better code quality
• .vscode/settings.json - VS Code settings for Python development
• .vscode/launch.json - VS Code launch configurations for running Python scripts

Quick Start Guide

1. Install VS Code Extensions

   • Open VS Code on Windows
   • Go to Extensions (Ctrl+Shift+X)
   • Search for and install:
     • Remote - WSL (by Microsoft)
     • Python (by Microsoft)
     • Jupyter (by Microsoft)
     • Pylance (by Microsoft)
     • IntelliCode (by Microsoft)

2. Set Up Python Environment (One-time Setup)

   • Open a terminal in VS Code connected to WSL (Terminal > New Terminal)
   • The terminal should show that you're in your Ubuntu WSL environment
   • Run the setup script:

     # Run in VS Code's WSL terminal (one-time setup)
     python3 setup_environment.py

   • This script will:
     1. Create a Python virtual environment
     2. Ask you to activate the virtual environment
     3. Install required packages
     4. Register a Jupyter kernel
   • When prompted, activate your virtual environment:

     # Run this when the script prompts you
     source .venv/bin/activate

   • After activation, the script will continue automatically
   • Note: You only need to run setup_environment.py once for initial setup, but you'll need to activate the virtual environment (source .venv/bin/activate) each time you open a new terminal

3. Optional: Additional Jupyter Setup

   • The setup_environment.py script already sets up Jupyter support
   • If you need to set up Jupyter separately, you can run:

     # Only needed if you want to set up Jupyter separately
     # Run in VS Code's WSL terminal with virtual environment activated
     python setup_jupyter.py

   • This script will install Jupyter packages and register your kernel for use with VS Code

4. Test Python Script Execution

   • Open number_game.py in VS Code connected to WSL
   • Run it by clicking the play button in the top-right corner or pressing F5
   • Follow the prompts in the VS Code terminal to play the number guessing game

5. Test Jupyter Notebook

   • Open python_basics.ipynb in VS Code connected to WSL
   • When prompted, select the Python kernel you registered
   • Run the cells by clicking the play button or pressing Shift+Enter

Troubleshooting

If you encounter any issues:

1. Python Interpreter Not Found

   • Press Ctrl+Shift+P
   • Type "Python: Select Interpreter"
   • Choose the Python interpreter in your virtual environment

2. Jupyter Notebook Not Working

   • Make sure you've installed the Jupyter extension
   • Ensure your virtual environment is activated
   • Try running setup_jupyter.py again

3. Virtual Environment Issues

   • If the virtual environment isn't working, try creating it manually in your Ubuntu WSL terminal:

     # Run these commands in your Ubuntu WSL terminal
     python3 -m venv .venv
     source .venv/bin/activate

Daily Workflow After Setup

Once you've completed the initial setup, here's your typical workflow for Python development:

1. Start VS Code and Connect to WSL

   • Open VS Code on Windows
   • Click the green button in the bottom-left corner
   • Select "Connect to WSL" (or open VS Code directly from your Ubuntu terminal with code .)

2. Activate Your Virtual Environment

   • Open a terminal in VS Code (Terminal > New Terminal)
   • Activate the virtual environment:

     # Run this each time you open a new VS Code WSL terminal
     source .venv/bin/activate

   • You'll see (.venv) at the beginning of your terminal prompt when it's activated

3. Work on Python Files

   • Open Python files in VS Code
   • Run scripts with the play button or F5
   • Debug with breakpoints as needed

4. Work with Jupyter Notebooks

   • Open .ipynb files in VS Code
   • Select your registered kernel if prompted
   • Run cells with the play button or Shift+Enter

Additional Resources

For more detailed information, refer to the python_environment_setup_plan.md and wsl_setup_guide.md files, which contain comprehensive instructions for setting up your Python development environment.