there other candidates?
thank you.
On Nov 23, 4:02 am, Paul Rudin wrote:
> per writes:
> > hi all,
>
> > i am looking for a python package to make it easier to create a
> > "pipeline" of scripts (all in python). what i do right now is have a
> > set of
hi all,
i am looking for a python package to make it easier to create a
"pipeline" of scripts (all in python). what i do right now is have a
set of scripts that produce certain files as output, and i simply have
a "master" script that checks at each stage whether the output of the
previous script
On Sep 5, 7:07 pm, "Rhodri James" wrote:
> On Sat, 05 Sep 2009 23:54:08 +0100, per wrote:
> > On Sep 5, 6:42 pm, "Rhodri James" wrote:
> >> On Sat, 05 Sep 2009 22:54:41 +0100, per wrote:
> >> > I'm trying to efficiently "split&
On Sep 5, 6:42 pm, "Rhodri James" wrote:
> On Sat, 05 Sep 2009 22:54:41 +0100, per wrote:
> > I'm trying to efficiently "split" strings based on what substrings
> > they are made up of.
> > i have a set of strings that are comprised of know
I'm trying to efficiently "split" strings based on what substrings
they are made up of.
i have a set of strings that are comprised of known substrings.
For example, a, b, and c are substrings that are not identical to each
other, e.g.:
a = "0" * 5
b = "1" * 5
c = "2" * 5
Then my_string might be:
hi all,
i am using the standard unittest module to unit test my code. my code
contains several print statements which i noticed are repressed when i
call my unit tests using:
if __name__ == '__main__':
suite = unittest.TestLoader().loadTestsFromTestCase(TestMyCode)
unittest.TextTestRunner
est option.
thanks for the suggestion, will look into gadfly in the meantime.
On Jun 17, 11:38 pm, Emile van Sebille wrote:
> On 6/17/2009 8:28 PM per said...
>
> > hi all,
>
> > i'm looking for a native python package to run a very simple data
> > base. i was orig
hi all,
i'm looking for a native python package to run a very simple data
base. i was originally using cpickle with dictionaries for my problem,
but i was making dictionaries out of very large text files (around
1000MB in size) and pickling was simply too slow.
i am not looking for fancy SQL oper
On Apr 20, 11:08 pm, Steven D'Aprano
wrote:
> On Mon, 20 Apr 2009 11:39:35 -0700, per wrote:
> > hi all,
>
> > i am generating a list of random tuples of numbers between 0 and 1 using
> > the rand() function, as follows:
>
> > for i in range(0, n):
&g
hi all,
i am generating a list of random tuples of numbers between 0 and 1
using the rand() function, as follows:
for i in range(0, n):
rand_tuple = (rand(), rand(), rand())
mylist.append(rand_tuple)
when i generate this list, some of the random tuples might be
very close to each other, nume
On Mar 22, 10:51 pm, Paul Rubin <http://phr...@nospam.invalid> wrote:
> per writes:
> > i would like to split the dictionary into smaller ones, containing
> > only hundreds of thousands of keys, and then try to pickle them.
>
> That already sounds like the wrong app
hi all,
i have a very large dictionary object that is built from a text file
that is about 800 MB -- it contains several million keys. ideally i
would like to pickle this object so that i wouldnt have to parse this
large file to compute the dictionary every time i run my program.
however currentl
hi all,
i have a file that declares some global variables, e.g.
myglobal1 = 'string'
myglobal2 = 5
and then some functions. i run it using ipython as follows:
[1] %run myfile.py
i notice then that myglobal1 and myglobal2 are not imported into
python's interactive namespace. i'd like them too -
hi all,
what's the most efficient / preferred python way of parsing tab
separated data into arrays? for example if i have a file containing
two columns one corresponding to names the other numbers:
col1\t col 2
joe\t 12.3
jane \t 155.0
i'd like to parse into an array() such that i
hi all,
i have a program that essentially loops through a textfile file thats
about 800 MB in size containing tab separated data... my program
parses this file and stores its fields in a dictionary of lists.
for line in file:
split_values = line.strip().split('\t')
# do stuff with split_value
On Feb 28, 11:53 pm, per wrote:
> On Feb 28, 11:24 pm, Carl Banks wrote:
>
>
>
> > On Feb 28, 7:30 pm, per wrote:
>
> > > hi all,
>
> > > i recently installed a new version of a package using python setup.py
> > > install --prefix=/my/homed
On Feb 28, 11:24 pm, Carl Banks wrote:
> On Feb 28, 7:30 pm, per wrote:
>
> > hi all,
>
> > i recently installed a new version of a package using python setup.py
> > install --prefix=/my/homedir on a system where i don't have root
> > access. the old packa
hi all,
i recently installed a new version of a package using python setup.py
install --prefix=/my/homedir on a system where i don't have root
access. the old package still resides in /usr/lib/python2.5/site-
packages/ and i cannot erase it.
i set my python path as follows in ~/.cshrc
setenv PYT
thanks to everyone for the excellent suggestions. a few follow up q's:
1] is Try-Except really slower? my dict actually has two layers, so
my_dict[aKey][bKeys]. the aKeys are very small (less than 100) where
as the bKeys are the ones that are in the millions. so in that case,
doing a Try-Except o
hello
i have an optimization questions about python. i am iterating through
a file and counting the number of repeated elements. the file has on
the order
of tens of millions elements...
i create a dictionary that maps elements of the file that i want to
count
to their number of occurs. so i iter
cy so much...
thanks.
On Jan 13, 12:24 am, brent wrote:
> On Jan 12, 8:55 pm, Per Freem wrote:
>
>
>
> > On Jan 12, 10:58 pm, Steven D'Aprano
>
> > wrote:
> > > On Mon, 12 Jan 2009 14:49:43 -0800, Per Freem wrote:
> > > > thanks for your repli
i forgot to add, my naive_find is:
def naive_find(intervals, start, stop):
results = []
for interval in intervals:
if interval.start >= start and interval.stop <= stop:
results.append(interval)
return results
On Jan 12, 11:55 pm, Per Freem wrote:
> On Jan 12, 10:58 p
On Jan 12, 10:58 pm, Steven D'Aprano
wrote:
> On Mon, 12 Jan 2009 14:49:43 -0800, Per Freem wrote:
> > thanks for your replies -- a few clarifications and questions. the
> > is_within operation is containment, i.e. (a,b) is within (c,d) iff a
> >>= c and b <= d
thanks for your replies -- a few clarifications and questions. the
is_within operation is containment, i.e. (a,b) is within (c,d) iff a
>= c and b <= d. Note that I am not looking for intervals that
overlap... this is why interval trees seem to me to not be relevant,
as the overlapping interval pro
hello,
suppose I have two lists of intervals, one significantly larger than
the other.
For example listA = [(10, 30), (5, 25), (100, 200), ...] might contain
thousands
of elements while listB (of the same form) might contain hundreds of
thousands
or millions of elements.
I want to count how many i
FYI: the '/*.*' is part of the error message returned.
-Original Message-
From: ch...@rebertia.com [mailto:ch...@rebertia.com] On Behalf Of Chris
Rebert
Sent: Wednesday, January 07, 2009 6:40 PM
To: Per Olav Kroka
Cc: python-list@python.org
Subject: Re: listdir reports [Error
Per B.Sederberg princeton.edu> writes:
> I'll see if I can make a really small example program that eats up memory on
> our cluster. That way we'll have something easy to work with.
Now this is weird. I figured out the bug and it turned out that every time you
call numpy
eally small example program that eats up memory on our
cluster. That way we'll have something easy to work with.
Thanks,
Per
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ifference I can see is that our cluster is stuck on a really old
version of gcc with the RedHat Enterprise that's on there, but I found
no suggestions of memory issues online.
So, does anyone have any suggestions for how I can debug this problem?
If my program ate up memory on all machines, then I would know where
to start and would blame some horrible programming on my end. This
just seems like a less straightforward problem.
Thanks for any help,
Per
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Yeah, Thanks Am,
I can be considered as an advanced google user, presumably.. But I am
not a advanced programmer yet.
If everyone can generate unlimited number of queries, soon the
user-query-data, which I believe is google's most advantage, will be in
chaos. Can they simply ignore some queries f
I am doing a Natural Language processing project for academic use,
I think google's rich retrieval information and query-segment might be
of help, I downloaded google api, but there is query limit(1000/day),
How can I write python code to simulate the browser-like-activity to
submit more than 10k
Thanks Ron,
surely set is the simplest way to understand the question, to see
whether there is a non-empty intersection. But I did the following
thing in a silly way, still not sure whether it is going to be linear
time.
def foo():
l = [...]
s = [...]
dic = {}
for i in l:
d
http://jaynes.colorado.edu/PythonIdioms.html
"""Use dictionaries for searching, not lists. To find items in common
between two lists, make the first into a dictionary and then look for
items in the second in it. Searching a list for an item is linear-time,
while searching a dict for an item is con
ort
port 20: this port goes to cnhd47/console port
port 21: this port goes to cnhd46/console port
To connect to a port, just enter the following command:
telnet msp-t01
... an extra should give you the prompt.
is always 20
is the port number...
example, connect to cnhd47/console port:
telne
sdfdsafasd
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