#Lesson 02: Development Environment Setup

# Update package lists
sudo apt update && sudo apt upgrade -y

# Install build essentials
sudo apt install -y build-essential curl wget git

# Install Homebrew (package manager for macOS)
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# Verify installation
brew --version

# In PowerShell (Administrator)
wsl --install

# Restart computer

# After restart, set Ubuntu as default
wsl --set-default-version 2
wsl --install -d Ubuntu-22.04

python3 --version

sudo apt install -y software-properties-common
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt update
sudo apt install -y python3.11 python3.11-venv python3.11-dev

brew install python@3.11

# Install pip if needed
python3.11 -m ensurepip --upgrade

# Create virtual environment for this course
python3.11 -m venv ~/ai-infra-venv

# Activate virtual environment
source ~/ai-infra-venv/bin/activate

# On Windows WSL:
source ~/ai-infra-venv/bin/activate

# Verify Python in venv
which python
python --version  # Should show 3.11.x

# For bash
echo 'alias activate-ai="source ~/ai-infra-venv/bin/activate"' >> ~/.bashrc
source ~/.bashrc

# For zsh (macOS default)
echo 'alias activate-ai="source ~/ai-infra-venv/bin/activate"' >> ~/.zshrc
source ~/.zshrc

# Make sure venv is activated
source ~/ai-infra-venv/bin/activate

# Upgrade pip
pip install --upgrade pip

# Install core ML and infrastructure packages
pip install \
    torch torchvision \
    tensorflow \
    transformers \
    numpy pandas scikit-learn \
    fastapi uvicorn \
    requests httpx \
    pyyaml python-dotenv \
    pytest pytest-asyncio \
    black flake8 mypy

sudo apt install -y git

brew install git

# Set your name and email
git config --global user.name "Your Name"
git config --global user.email "your.email@example.com"

# Verify configuration
git config --list

# Generate SSH key
ssh-keygen -t ed25519 -C "your.email@example.com"

# Press Enter to accept default location
# Enter a passphrase (optional but recommended)

# Start SSH agent
eval "$(ssh-agent -s)"

# Add SSH key
ssh-add ~/.ssh/id_ed25519

# Copy public key
cat ~/.ssh/id_ed25519.pub
# Copy the output

ssh -T git@github.com
# Should see: "Hi username! You've successfully authenticated"

# Remove old versions
sudo apt remove docker docker-engine docker.io containerd runc

# Install dependencies
sudo apt update
sudo apt install -y apt-transport-https ca-certificates curl gnupg lsb-release

# Add Docker's official GPG key
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg

# Set up stable repository
echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

# Install Docker Engine
sudo apt update
sudo apt install -y docker-ce docker-ce-cli containerd.io docker-compose-plugin

# Add your user to docker group (avoid sudo)
sudo usermod -aG docker $USER

# Log out and log back in for group change to take effect

# Install Docker Desktop
brew install --cask docker

# Start Docker Desktop from Applications
# Wait for it to finish starting (whale icon in menu bar)

# Check version
docker --version

# Run test container
docker run hello-world

# Should see "Hello from Docker!" message

curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
sudo install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl

brew install kubectl

kubectl version --client

curl -LO https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64
sudo install minikube-linux-amd64 /usr/local/bin/minikube

brew install minikube

minikube version

# Start minikube (we'll use this in Module 04)
# Don't run this yet if low on resources
# minikube start --driver=docker

curl https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3 | bash

helm version

# Linux/macOS
curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
unzip awscliv2.zip
sudo ./aws/install

# macOS alternative
brew install awscli

# Verify
aws --version

# Configure (if you have AWS account)
aws configure
# Enter Access Key ID, Secret Access Key, region (us-east-1), output format (json)

# Linux
curl https://sdk.cloud.google.com | bash
exec -l $SHELL

# macOS
brew install --cask google-cloud-sdk

# Initialize
gcloud init

# Linux
curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash

# macOS
brew update && brew install azure-cli

# Login
az login

# Download .deb package
wget -qO- https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor > packages.microsoft.gpg
sudo install -o root -g root -m 644 packages.microsoft.gpg /etc/apt/trusted.gpg.d/
sudo sh -c 'echo "deb [arch=amd64] https://packages.microsoft.com/repos/vscode stable main" > /etc/apt/sources.list.d/vscode.list'
sudo apt update
sudo apt install code

brew install --cask visual-studio-code

code --install-extension ms-python.python
code --install-extension ms-python.vscode-pylance
code --install-extension ms-azuretools.vscode-docker
code --install-extension ms-kubernetes-tools.vscode-kubernetes-tools
code --install-extension eamodio.gitlens
code --install-extension redhat.vscode-yaml
code --install-extension github.copilot  # Optional, requires subscription

#!/bin/bash
# save as verify-setup.sh

echo "=== Verifying ML Infrastructure Development Environment ==="
echo ""

# Python
echo "Python Version:"
python --version || echo "❌ Python not found"
echo ""

# Pip packages
echo "Key Python Packages:"
python -c "import torch; print(f'PyTorch: {torch.__version__}')" || echo "❌ PyTorch not installed"
python -c "import tensorflow as tf; print(f'TensorFlow: {tf.__version__}')" || echo "❌ TensorFlow not installed"
python -c "import fastapi; print(f'FastAPI: {fastapi.__version__}')" || echo "❌ FastAPI not installed"
echo ""

# Git
echo "Git Version:"
git --version || echo "❌ Git not found"
echo ""

# Docker
echo "Docker Version:"
docker --version || echo "❌ Docker not found"
docker ps > /dev/null 2>&1 && echo "✅ Docker running" || echo "⚠️  Docker not running (start Docker Desktop)"
echo ""

# Kubernetes
echo "Kubernetes Tools:"
kubectl version --client --short || echo "❌ kubectl not found"
minikube version --short || echo "❌ minikube not found"
helm version --short || echo "❌ helm not found"
echo ""

# Cloud CLI (at least one)
echo "Cloud CLIs:"
aws --version 2>/dev/null && echo "✅ AWS CLI installed" || echo "⚠️  AWS CLI not installed"
gcloud --version 2>/dev/null && echo "✅ GCloud CLI installed" || echo "⚠️  GCloud CLI not installed"
az --version 2>/dev/null && echo "✅ Azure CLI installed" || echo "⚠️  Azure CLI not installed"
echo ""

echo "=== Verification Complete ==="
echo "If you see ❌ errors, review the installation steps for those tools."

chmod +x verify-setup.sh
./verify-setup.sh

# Create workspace directory
mkdir -p ~/ai-infra-learning
cd ~/ai-infra-learning

# Initialize git repository
git init

# Create standard structure
mkdir -p {modules/01-foundations,projects/{project-01,project-02,project-03},exercises,notes}

# Create .gitignore
cat > .gitignore << 'EOF'
# Python
__pycache__/
*.py[cod]
*$py.class
*.so
.Python
env/
venv/
*.egg-info/
.pytest_cache/

# IDEs
.vscode/
.idea/
*.swp
*.swo

# OS
.DS_Store
Thumbs.db

# Logs
*.log

# Environment variables
.env
.env.local

# Data files (don't commit large files)
*.csv
*.h5
*.pkl
*.pth
*.ckpt

# Model files
models/
*.model
*.weights

# Docker
*.tar
EOF

# Create README
cat > README.md << 'EOF'
# AI Infrastructure Learning Journey

This repository contains my work for the AI Infrastructure Engineer curriculum.

## Structure

- `modules/` - Notes and exercises for each module
- `projects/` - Hands-on projects
- `exercises/` - Practice exercises
- `notes/` - Personal learning notes

## Progress

- [ ] Module 01: Foundations
- [ ] Project 01: Basic Model Serving
- ...
EOF

# Initial commit
git add .
git commit -m "Initial setup: Project structure"

# Connect to GitHub (create repo at github.com first)
# git remote add origin git@github.com:yourusername/ai-infra-learning.git
# git push -u origin main

sudo usermod -aG docker $USER
# Log out and log back in

# Update pip and setuptools
pip install --upgrade pip setuptools wheel

# Try again
pip install <package-name>

# Delete and recreate
minikube delete
minikube start --driver=docker --memory=4096

# AWS
aws configure

# GCloud
gcloud auth login
gcloud config set project <your-project-id>

# Azure
az login