help with making my code more efficient
Larry.Martell at gmail.com
Larry.Martell at gmail.com
Fri Dec 21 15:36:16 EST 2012
On Friday, December 21, 2012 10:57:19 AM UTC-7, Larry.... at gmail.com wrote:
> On Thursday, December 20, 2012 8:31:18 PM UTC-7, Dave Angel wrote:
> > On 12/20/2012 08:46 PM, Larry.Martell at gmail.com wrote:
> > > On Thursday, December 20, 2012 6:17:04 PM UTC-7, Dave Angel wrote:
> > >> <snip>
> > > Of course it's a fragment - it's part of a large program and I was just showing the relevant parts.
> > But it seems these are methods in a class, or something, so we're
> > missing context. And you use self without it being an argument to the
> > function. Like it's a global.
> I didn't show the entire method, only what I thought was relevant to my issue. The method is declared as:
>
> def generate_data(self):
> > > <snip>
> > > Yes, the code works. I end up with just the rows I want.
> > >> Are you only concerned about speed, not fixing features?
> > > Don't know what you mean by 'fixing features'. The code does what I want, it just takes too long.
> > >> As far as I can tell, the logic that includes the time comparison is bogus.
> > > Not at all.
> > >> You don't do anything there to worry about the value of tup[2], just whether some
> > >> item has a nearby time. Of course, I could misunderstand the spec.
> > > The data comes from a database. tup[2] is a datetime column. tdiff comes from a datetime.timedelta()
> > I thought that tup[1] was the datetime. In any case, the loop makes no
> > sense to me, so I can't really optimize it, just make suggestions.
> Yes, tup[1] is the datetime. I mistyped last night.
> > >> Are you making a global called 'self' ? That name is by convention only
> > >> used in methods to designate the instance object. What's the attribute
> > >> self?
> > > Yes, self is my instance object. self.message contains the string of interest that I need to look for.
> > >> Can cdata have duplicates, and are they significant?
> > > No, it will not have duplicates.
> > >> Is the list sorted in any way?
> > > Yes, the list is sorted by tool and datetime.
> > >> Chances are your performance bottleneck is the doubly-nested loop. You
> > >> have a list comprehension at top-level code, and inside it calls a
> > >> function that also loops over the 600,000 items. So the inner loop gets
> > >> executed 360 billion times. You can cut this down drastically by some
> > >> judicious sorting, as well as by having a map of lists, where the map is
> > >> keyed by the tool.
> > > Thanks. I will try that.
> > So in your first loop, you could simply split the list into separate
> > lists, one per tup[0] value, and the lists as dictionary items, keyed by
> > that tool string.
> > Then inside the determine() function, make a local ref to the particular
> > list for the tool.
> > recs = messageTimes[tup[0]]
> I made that change ant went from taking over 2 hours to 54 minutes. A dramatic improvement, but still not adequate for my app.
> > Instead of a for loop over recs, use a binary search to identify the
> > first item that's >= date_time-tdiff. Then if it's less than
> > date_time+tdiff, return True, otherwise False. Check out the bisect
> > module. Function bisect_left() should do what you want in a sorted list.
> Didn't know about bisect. Thanks. I thought it would be my savior for sure. But unfortunaly when I added that, it blows up with out of memory.
The out of memory error had nothing to do with using bisect. I had introduced a typo that I really though would have caused a variable referenced before assignment error. But it did not do that, and instead somehow caused all the memory in my machine to get used up. When I fixed that, it worked really well with bisect. The code that was taking 2 hours was down to 20 minutes, and even better, a query that was taking 40 minutes was down to 8 seconds.
Thanks very much for all your help.
> This was the code I had:
>
> times = messageTimes[tup[0]]
>
> le = bisect.bisect_right(times, tup[1])
>
> ge = bisect.bisect_left(times, tup[1])
>
> return (le and tup[1]-times[le-1] <= tdiff) or (ge != len(times) and times[ge]-tup[1] <= tdiff)
>
>
>
> > >>> cdata[:] = [tup for tup in cdata if determine(tup)]
>
> >
>
> > >> As the code exists, there's no need to copy the list. Just do a simple
>
> > >> bind.
>
> >
>
> > > This statement is to remove the items from cdata that I don't want. I don't know what you mean by bind. I'm not familiar with that python function.
>
> >
>
> > Every "assignment" to a simple name is really a rebinding of that name.
>
> > cdata = [tup for tup in cdata if determine(tup)]
>
> >
>
> > will rebind the name to the new object, much quicker than copying. If
>
> > this is indeed a top-level line, it should be equivalent. But if in
>
> > fact this is inside some other function, it may violate some other
>
> > assumptions. In particular, if there are other names for the same
>
> > object, then you're probably stuck with modifying it in place, using
>
> > slice notation.
>
>
>
> The slice notation was left over when when cdata was a tuple. Now that it's a list I don't need that any more.
>
>
>
> > BTW, a set is generally much more memory efficient than a dict, when you
>
> > don't use the "value". But since I think you'll be better off with a
>
> > dict of lists, it's a moot point.
>
>
>
> I'm going back to square 1 and try and do all from SQL.
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