Sums of variable size chunks of a list where sizes are given by other list
You can make use of np.bincount
with weights
:
groups = np.repeat(np.arange(len(b)), b)
np.bincount(groups, weights=a)
Output:
array([ 1., 9., 35.])
NumPy has a tool to do slice based sumreduction with np.add.reduceat

In [46]: np.add.reduceat(a,np.cumsum(np.r_[0,b[:1]]))
Out[46]: array([ 1, 9, 35])
You mean something like this?
a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
b = [2, 3, 5]
def some_function(a, b): # couldnt come up with a name :D
last_index = 0
for i in b:
print(sum(a[last_index:last_index + i]))
last_index += i
some_function(a, b)