If you’re doing much numerical work with arrays like this, I’d suggest `numpy`

, which comes with a cumulative sum function `cumsum`

:

```
import numpy as np
a = [4,6,12]
np.cumsum(a)
#array([4, 10, 22])
```

Numpy is often faster than pure python for this kind of thing, see in comparison to @Ashwini’s `accumu`

:

```
In [136]: timeit list(accumu(range(1000)))
10000 loops, best of 3: 161 us per loop
In [137]: timeit list(accumu(xrange(1000)))
10000 loops, best of 3: 147 us per loop
In [138]: timeit np.cumsum(np.arange(1000))
100000 loops, best of 3: 10.1 us per loop
```

But of course if it’s the only place you’ll use numpy, it might not be worth having a dependence on it.