Implement BFS and DFS on GridsStep 5 of 5

Largest region

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Step 5: Largest region

Image region detection: find the biggest blob. The grid holds 1s and 0s; return the size (cell count) of the largest connected region of 1s.

Write max_region_size(grid) that returns the number of cells in the largest 4-directionally connected group of 1s, or 0 if there are no 1s.

This is Step 3's scan with a twist: instead of just counting regions, measure each one. Flood every unvisited region, count its cells, and track the maximum size seen.

Hints
Starter code
def neighbors(grid, r, c):
    """Return in-bounds 4-directional neighbor coords: up, down, left, right."""
    rows = len(grid)
    cols = len(grid[0]) if rows else 0
    result = []
    for nr, nc in ((r - 1, c), (r + 1, c), (r, c - 1), (r, c + 1)):
        if 0 <= nr < rows and 0 <= nc < cols:
            result.append((nr, nc))
    return result


def max_region_size(grid):
    """Return the size of the largest connected region of 1s."""
    # TODO: flood each unvisited region, count its cells, track the max
    pass
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