First part was not much harder to crack but it still took plenty of time. But second part was tricky.

### Part 1

```
import numpy as np
data,data1 = get_data(day=9)
dl = len(data1[0])
dt = np.array([int(d) for dt in data1 for d in dt])
dt = dt.reshape(-1, dl)
nums = []
pos = []
dc = len(dt[0])
dr = len(dt)
for r in range(len(dt)):
for c in range(len(dt[0])):
if r==0:
if c==0:
if dt[r,c]<dt[r+1, c] and dt[r,c]<dt[r, c+1]:
nums.append(dt[r,c])
pos.append((r,c))
elif c==dc-1:
if dt[r,c]<dt[r+1, c] and dt[r,c]<dt[r, c-1]:
nums.append(dt[r,c])
pos.append((r,c))
else:
if dt[r,c]<dt[r+1, c] and dt[r,c]<dt[r, c+1] and dt[r,c]<dt[r, c-1]:
nums.append(dt[r,c])
pos.append((r,c))
elif r==dr-1:
if c==0:
if dt[r,c]<dt[r-1, c] and dt[r,c]<dt[r, c+1]:
nums.append(dt[r,c])
pos.append((r,c))
elif c==dc-1:
if dt[r,c]<dt[r-1, c] and dt[r,c]<dt[r, c-1]:
nums.append(dt[r,c])
pos.append((r,c))
else:
if dt[r,c]<dt[r-1, c] and dt[r,c]<dt[r, c+1] and dt[r,c]<dt[r, c-1]:
nums.append(dt[r,c])
pos.append((r,c))
else:
if c==0:
if dt[r,c]<dt[r-1, c] and dt[r,c]<dt[r, c+1] and dt[r,c]<dt[r+1, c]:
nums.append(dt[r,c])
pos.append((r,c))
elif c==dc-1:
if dt[r,c]<dt[r-1, c] and dt[r,c]<dt[r, c-1] and dt[r,c]<dt[r+1, c]:
nums.append(dt[r,c])
pos.append((r,c))
else:
if dt[r,c]<dt[r-1, c] and dt[r,c]<dt[r, c+1] and dt[r,c]<dt[r, c-1] and dt[r,c]<dt[r+1, c]:
nums.append(dt[r,c])
pos.append((r,c))
nums
```

### Part 2

I thought I had to use some sort of Searching algorithm like DFS or BFS but I found a solution on StackOverflow using NumPy.

```
from scipy import ndimage
label, num_label = ndimage.label(dt < 9)
size = np.bincount(label.ravel())
top3 = sorted(size[1:], reverse=True)[:3]
print(np.prod(top3))
```

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