# Install all dependencies and set up database
make setup

# Or install components separately
make install          # Install frontend + backend dependencies
make init-db         # Initialize SQLite database
make populate-db     # Add mock data for development

# Start both frontend and backend servers
make dev

# Or start them individually
make dev-frontend    # Frontend on http://localhost:9002
make dev-backend     # Backend API on http://localhost:8000

npm run lint                # Frontend linting (in frontend directory)
npm run typecheck           # TypeScript type checking

make reset-db               # Drop and recreate database with fresh data
make populate-db           # Add mock benchmark data

make build                  # Build frontend for production
make clean                  # Clean up generated files and caches

# Set authentication token
export MEMORY_TRACKER_TOKEN=your_token_here

# List available binaries and environments
memory-tracker list-binaries
memory-tracker list-environments

# Run benchmarks on CPython commits
memory-tracker benchmark /path/to/cpython HEAD~5..HEAD \
  --binary-id default \
  --environment-id linux-x86_64

# Parallel processing with 4 workers
memory-tracker benchmark /path/to/cpython HEAD~10..HEAD \
  --binary-id default \
  --environment-id linux-x86_64 \
  --max-workers 4

# Local checkout mode (sequential only)
memory-tracker benchmark /path/to/cpython HEAD~5..HEAD \
  --binary-id default \
  --environment-id linux-x86_64 \
  --local-checkout

# Development with hot reload
docker-compose -f docker-compose.dev.yml up

# Production deployment
docker-compose up

# Benchmark recent commits with parallel processing
memory-tracker benchmark ~/cpython HEAD~20..HEAD \
  --binary-id optimized \
  --environment-id linux-x86_64 \
  --max-workers 8 \
  --batch-size 4

# Force overwrite existing results
memory-tracker benchmark ~/cpython HEAD~10..HEAD \
  --binary-id default \
  --environment-id linux-x86_64 \
  --force