Python functional programming

Functions can be returned as objects

def build_taxer(rate):
    def taxer(amount):
        return amount * (float(rate) / 100)
    return taxer

list comprehensions can replace map and filter, but compute the whole list is slow
```
[i	*2 for i in range(10) if i%2==0]
```

list is slow actually we only need to compute part of the list

def is_prime(n):
    return not any(n%k==0 for k in xrange(2,n))

in contrast to any(seq), all(seq) returns true if all elements of the sequence are true