[Tutor] How inefficient is this code?

[C Smith]

I see. Thanks that is exactly what I was looking for. Would your
example be an instance of an object-oriented approach,
compartmentalizing things into functions?

On Wed, May 7, 2014 at 7:55 PM, Joe Cortes <escozzia at gmail.com> wrote:
> Welcome to the wonderful world of generators!
>
> Looking at your code, you'll notice two things. First, you're
> iterating over all the numbers twice: once to calculate them, and then
> another time to actually do the sum. What's worse, at any given point
> in time, you're only really using fibs[-1] and fibs[-2], and yet
> you're still building this huge list with all the numbers. This is bad
> in terms of memory efficiency. Luckily, it's such a common problem
> that Python offers a really nice, really Pythonic solution. You can
> define the following function:
>
> def fib(top):
>     first = 1 # As an aside, consider starting the sequence from 0, 1.
>     next = 2
>     yield first
>     while next < top:
>          yield next
>          # For kicks, try rewriting the following three lines as a
> tuple assignment.
>          new_next = next + first
>          first = next
>          next = new_next
>
> Now, how do you use this? This being Python, there is a super simple
> way to do this:
>
> sum = 0
> for num in fib(4000000):
>      if num % 2 == 0:
>             sum += num
> print sum
>
>
> So, what's going on here? fib is mostly straightforward, but that
> yield keyword might look new.
> Here's the deal: when you have a function that uses the yield keyword,
> that function becomes usable in the context of a for loop. Every time
> it hits a yield it will, well, yield that value out to the for loop.
> At the end of an iteration, control will be handed back to the
> function, which will do its magic, and yield another value. Again, the
> value will be sent out to the for loop, in this case as the "num"
> variable, for use in that iteration.
> When the function hits a return (or reaches the end of its body), the
> for loop ends.
>
> This is called a generator function, and is a really nice way to
> simplify and optimize your loops.
>
> You can read more about generators here: https://wiki.python.org/moin/Generators
>
>
> On Wed, May 7, 2014 at 7:27 PM, C Smith <illusiontechniques at gmail.com> wrote:
>> A topic came up on slashdot concerning "intermediate" programming,
>> where the poster expressed the feeling that the easy stuff is too easy
>> and the hard stuff is too hard.
>>
>> Someone did point out that 'intermediate' programming would still
>> involve actually selling code or at least some professional
>> experience, so this would probably fall into the category of 'novice'.
>>
>> I feel similarly right now and the cs 101 classes from udacity or
>> coursera or the opencourseware stuff are very easy and boring. I tried
>> the class "design of computer programs" on udacity and made it about
>> halfway before being overwhelmed. The class involved making an api for
>> a regex-like function to parse text (if I am communicating that
>> correctly, it was sort of rewriting regex functionality in Python
>> terms), and it seemed to go over a very definite cliff in terms of
>> difficulty. Could someone provide a concise example of decorator use?
>>
>> Someone suggested projecteuler.net and I started blazing through
>> things I had done before, when I realized this would be a good time to
>> start more efficient practices instead of code that just happens to
>> work and may be very inefficient.
>>
>> #sum all even fib seq integers under 4 million
>> fibs = [1,2]
>> sum = 0
>> while fibs[-1] < 4000000:
>>     nexty = fibs[-1] + fibs[-2]
>>     fibs.append(nexty)
>>
>> for xer in fibs:
>>     if xer%2 == 0:
>>         sum += xer
>> print sum
>>
>> This gets the correct solution, but what would be ways to improve
>> speed or use more complicated parts of Python to do the same thing.
>> Thanks in advance
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