Assuming that I have a list with huge number of items.
l = [ 1, 4, 6, 30, 2, ... ]
I want to get the number of items from that list, where
from itertools import imap
sum(imap(my_condition, l))
You can use a generator expression:
>>> l = [1, 3, 7, 2, 6, 8, 10]
>>> sum(1 for i in l if i % 4 == 3)
2
or even
>>> sum(i % 4 == 3 for i in l)
2
which uses the fact that int(True) == 1
.
Alternatively, you could use itertools.imap
(python 2) or simply map
(python 3):
>>> def my_condition(x):
... return x % 4 == 3
...
>>> sum(map(my_condition, l))
2
you could do something like:
l = [1,2,3,4,5,..]
count = sum(1 for i in l if my_condition(i))
which just adds 1 for each element that satisfies the condition.
You want a generator comprehension rather than a list here.
For example,
l = [1, 4, 6, 7, 30, 2]
def my_condition(x):
return x > 5 and x < 20
print sum(1 for x in l if my_condition(x))
# -> 2
print sum(1 for x in range(1000000) if my_condition(x))
# -> 14
Or use itertools.imap
(though I think the explicit list and generator expressions look somewhat more Pythonic).
Note that, though it's not obvious from the sum
example, you can compose generator comprehensions nicely. For example,
inputs = xrange(1000000) # In Python 3 and above, use range instead of xrange
odds = (x for x in inputs if x % 2) # Pick odd numbers
sq_inc = (x**2 + 1 for x in odds) # Square and add one
print sum(x/2 for x in sq_inc) # Actually evaluate each one
# -> 83333333333500000
The cool thing about this technique is that you can specify conceptually separate steps in code without forcing evaluation and storage in memory until the final result is evaluated.
This can also be done using reduce
if you prefer functional programming
reduce(lambda count, i: count + my_condition(i), l, 0)
This way you only do 1 pass and no intermediate list is generated.