Compare two arrays with different size - python numpy

With NumPy arrays, you might want to work in a vectorized manner for performance and also to make use of array-slicing. With that in mind, here's one approach for input arrays a and b -

n = min(len(a), len(b))
out_idx = np.flatnonzero(a[:n] == b[:n])
out_val = a[out_idx] # or b[out_idx] both work

This takes care of multiple matches.

Sample run -

In [224]: a = np.array([3, 8, 9, 2, 1, 7])

In [225]: b = np.array([1, 2, 9, 7, 5, 7, 0, 4])

In [226]: n = min(len(a), len(b))
     ...: out_idx = np.flatnonzero(a[:n] == b[:n])
     ...: out_val = a[out_idx]
     ...: 

In [227]: out_idx
Out[227]: array([2, 5])

In [228]: out_val
Out[228]: array([9, 7])

For a list of tuples as output for indices and their values -

In [229]: zip(out_idx, out_val)
Out[229]: [(2, 9), (5, 7)]

For a pretty dictionary output of indices and corresponding values -

In [230]: {i:j for i,j in zip(out_idx, out_val)}
Out[230]: {2: 9, 5: 7}