On 2016-01-06 18:36, high5stor...@gmail.com wrote:
> I have a list of 163.840 integers. What is a fast & pythonic way to
> process this list in 1,280 chunks of 128 integers?
That's a modest list, far from huge.
You have lots of options, but the following seems the most pythonic to
me:
# I don't know how you populate your data so
# create some junk data
from random import randint
data = [randint(0,1000) for _ in range(163840)]
import itertools as i
GROUP_SIZE = 128
def do_something(grp, vals):
for _, val in vals:
# I don't know what you want to do with each
# pair. You can print them:
# print("%s: %s" % (grp, val))
# or write them to various chunked files:
with open("chunk%04i.txt" % grp, "w") as f:
f.write(str(val))
f.write("\n")
# but here's the core logic:
def key_fn(x):
# x is a tuple of (index, value)
return x[0] // GROUP_SIZE
# actually iterate over the grouped data
# and do something with it:
for grp, vals in i.groupby(enumerate(data), key_fn):
do_something(grp, vals)
-tkc
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