On Fri, Oct 31, 2008 at 8:34 AM, Dinesh B Vadhia
<[EMAIL PROTECTED]> wrote:
> Hi Kent
>
> The code is very simple:
>
> dict_long_lists = defaultdict(list)
> for long_list in dict_long_lists.itervalues()
> for element in long_list:
> array_a[element] = m + n + p# m,n,
instead of a list.
Hth
Dinesh
Message: 1
Date: Thu, 30 Oct 2008 22:19:52 -0400
From: "Kent Johnson" <[EMAIL PROTECTED]>
Subject: Re: [Tutor] fast list traversal
To: "Shawn Milochik" <[EMAIL PROTECTED]>
Cc: tutor@python.org
Message-ID:
<[EMAIL PROTECTE
On Thu, Oct 30, 2008 at 4:55 PM, Shawn Milochik <[EMAIL PROTECTED]> wrote:
> I just ran a very crude test.
>
> Results: Lists load more quickly but iterate more slowly. Dictionaries
> take longer to load but iteration takes about half the time.
Here are my results using timeit and Python 2.6:
I
Hello Dinesh!
On Thursday 30 October 2008, Dinesh B Vadhia wrote:
> Bob: Nothing special is being done on the elements of the list -
> additions/subtractions/ - and storing the results in an array.
> That's it.
You could convert the list into a numpy array first, and you could try
to express th
> They seem pretty similar. Here are two tests (code follows). Perhaps I
> could have loaded them differently and it would have made more of a
> difference. In this case I just made a list and populated the sets
> from it.
>
> Results for 999 iterations:
>Set:
>Load: 1.2
a for-loop.
Btw, cannot move to Python 2.6 or 3.0 until Numpy/Scipy catches up.
Dinesh
From: wesley chun
Sent: Thursday, October 30, 2008 3:06 PM
To: Dinesh B Vadhia
Cc: tutor@python.org
Subject: Re: [Tutor] fast list traversal
based on the all the performance questions, i would say agree
On Thu, Oct 30, 2008 at 6:06 PM, wesley chun <[EMAIL PROTECTED]> wrote:
> based on the all the performance questions, i would say agree that
> dictionary access is faster than lists (hashes exist cuz they're fast)
> but they use up more memory, as shown in shawn's numbers. also, one of
> the reason
based on the all the performance questions, i would say agree that
dictionary access is faster than lists (hashes exist cuz they're fast)
but they use up more memory, as shown in shawn's numbers. also, one of
the reasons why slots was added to classes was because the attribute
dictionary began to i
On Thu, Oct 30, 2008 at 4:05 PM, Kent Johnson <[EMAIL PROTECTED]> wrote:
> On Thu, Oct 30, 2008 at 2:46 PM, Shawn Milochik <[EMAIL PROTECTED]> wrote:
>
>> You might try using dictionaries instead. I've had phenomenal speed
>> gains by switching lists to dictionaries before, although that may
>> hav
On Thu, Oct 30, 2008 at 2:46 PM, Shawn Milochik <[EMAIL PROTECTED]> wrote:
> You might try using dictionaries instead. I've had phenomenal speed
> gains by switching lists to dictionaries before, although that may
> have had more to do with the fact that I needed to access certain
> values, rather
On Thu, Oct 30, 2008 at 2:36 PM, Dinesh B Vadhia
<[EMAIL PROTECTED]> wrote:
> I need to process a large number (> 20,000) of long and variable length
> lists (> 5,000 elements) ie.
>
> for element in long_list:
> # the result of this operation is not
> a list
>
> The performance is reas
Bob: Nothing special is being done on the elements of the list -
additions/subtractions/ - and storing the results in an array. That's it.
Dinesh
From: bob gailer
Sent: Thursday, October 30, 2008 11:40 AM
To: Dinesh B Vadhia
Cc: tutor@python.org
Subject: Re: [Tutor] fast list trav
On Thu, Oct 30, 2008 at 2:40 PM, bob gailer <[EMAIL PROTECTED]> wrote:
> Dinesh B Vadhia wrote:
>>
>> I need to process a large number (> 20,000) of long and variable length
>> lists (> 5,000 elements) ie.
>> for element in long_list:
>># the result of this operation is
>> not a list
>
Dinesh B Vadhia wrote:
I need to process a large number (> 20,000) of long and variable
length lists (> 5,000 elements) ie.
for element in long_list:
# the result of this operation
is not a list
The performance is reasonable but I wonder if there are faster Python
methods?
I d
I need to process a large number (> 20,000) of long and variable length lists
(> 5,000 elements) ie.
for element in long_list:
# the result of this operation is not a
list
The performance is reasonable but I wonder if there are faster Python methods?
Dinesh
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