Samir wrote:
For my small list, I didn't notice a
discernible increase in speed, but I may have to try it with a larger
list size.
About speed, and memory consumption:
List comprehensions
(http://docs.python.org/tut/node7.html#SECTION007140000000000000000) are
just shortcuts for for-loops. I do not believe there is any speed
benefit. However, there are generators, they basically load one part of
an iterator (a list in this case) at a time, this can greatly reduce
memory usage.
Have a look at PEP 289:
http://www.python.org/dev/peps/pep-0289/
Here is the list comprehension as a generator (actually 2):
n = ((int(i) for i in k) for k in a)
Note, you can't just print a generator, it only computes something when
needed:
>>> print n
<generator object at 0xb7820e2c>
You can, however iterate over it:
In [2]: for k in n:
....: for i in k:
....: print i,
....:
....:
1 2 3 4 5 6 7 8 9 0
In [3]: n = ((int(i) for i in k) for k in a)
In [49]: list(n)
Out[49]:
[<generator object at 0xb77d03ec>,
<generator object at 0xb77d03cc>,
<generator object at 0xb77d046c>,
<generator object at 0xb77d04ac>]
Each sub-list is a generator too!
In [50]: n = ((int(i) for i in k) for k in a)
In [51]: for i in list(n): # list() converts the variable n to a list
....: list(i)
....:
....:
Out[51]: [1, 2]
Out[51]: [3]
Out[51]: [4, 5, 6]
Out[51]: [7, 8, 9, 0]
This is only going to make a difference if you were dealing with a
*very* large data set. I thought I would show you even if you never user
them, for learning purposes. Note: a generator is one way, redefine it
every time you use it.
--
Andrew
--
http://mail.python.org/mailman/listinfo/python-list
