Optimize chess game performance: eliminate redundant allocations and I/O

[Copilot]

Identified and resolved performance bottlenecks causing inefficient memory usage and redundant computations during gameplay.

Caching optimizations

• Piece rendering: Cache sprite sheet loads and pre-scaled surfaces by (type, color, size) to eliminate per-frame image I/O and scaling operations
• Movement indicators: Cache high-res circle surfaces by square size
• UI components: Cache popup overlays (with resize detection) and button state images

Algorithm improvements

• Move validation: Replace O(n²) board copying with in-place modifications + restore pattern

  # Before: Deep copy board for every move
  new_board = [row[:] for row in board]
  
  # After: Modify in-place, restore after check
  original = board[y][x]
  board[y][x] = piece_code
  is_valid = not is_check(board, opponent)
  board[y][x] = original

• Check detection: Direct board iteration with early return (eliminates flatten + list comprehensions)
• Castling validation: Cache king square attack check for both directions
• Display pipeline: Remove redundant pygame.display.flip() call

Impact

Eliminates thousands of allocations and I/O operations per second during active gameplay.

Original prompt

Identify and suggest improvements to slow or inefficient code

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