A few comments.
As Quincunx writes, you only need to check the integer range from 1..sqrt(n) which would translate into something like this for i in xrange(1, sqrt(n) + 1): ...
. This optimization alone vastly speeds up things.
You can use the triangle number formula (which I didn't know until just now, thank you Quincunx), or you can use another approach for finding the triangle numbers than recursion and dictionary lookups. You only need the next number in the sequence, so there is no point in saving it. Function calls involves significant overhead in Python, so recursion is usually not recommended for number crunching. Also, why the cast to float
, I didn't quite get that ?
I see that you are already using xrange
instead of range
to build the int
stream. I assume you know that xrange
is faster because it is implemented as a generator function. You can do that too. This makes things a lot smoother as well.
I've tried to do just that, use generators, and the code below finds the 500th triangle number in ~16sec on my machine (YMMV). But I've also used a neat trick to find the divisors, which is the quadratic sieve.
Here is my code:
def triangle_num_generator():
""" return the next triangle number on each call
Nth triangle number is defined as SUM([1...N]) """
n = 1
s = 0
while 1:
s += n
n += 1
yield s
def triangle_num_naive(n):
""" return the nth triangle number using the triangle generator """
tgen = triangle_num_generator()
ret = 0
for i in range(n):
ret = tgen.next()
return ret
def divisor_gen(n):
""" finds divisors by using a quadrativ sieve """
divisors = []
# search from 1..sqrt(n)
for i in xrange(1, int(n**0.5) + 1):
if n % i is 0:
yield i
if i is not n / i:
divisors.insert(0, n / i)
for div in divisors:
yield div
def divisors(n):
return [d for d in divisor_gen(n)]
num_divs = 0
i = 1
while num_divs < 500:
i += 1
tnum = triangle_num_naive(i)
divs = divisors(tnum)
num_divs = len(divs)
print tnum # 76576500
Running it produces the following output on my humble machine:
morten@laptop:~/documents/project_euler$ time python pr012.py
76576500
real 0m16.584s
user 0m16.521s
sys 0m0.016s
Using the triangle formula instead of the naive approach:
real 0m3.437s
user 0m3.424s
sys 0m0.000s