Scott McCarty wrote:
> Sorry to ask this question. I have search the list archives and googled,
> but I don't even know what words to find what I am looking for, I am just
> looking for a little kick in the right direction.
>
> I have a Python based log analysis program called petit (
> http://crunchtools.com/petit). I am trying to modify it to manage the main
> object types to and from disk.
>
> Essentially, I have one object which is a list of a bunch of "Entry"
> objects. The Entry objects have date, time, date, etc fields which I use
> for analysis techniques. At the very beginning I build up the list of
> objects then would like to start pickling it while building to save
> memory. I want to be able to process more entries than I have memory. With
> a strait list it looks like I could build from xreadlines(), but once you
> turn it into a more complex object, I don't quick know where to go.
>
> I understand how to pickle the entire data structure, but I need something
> that will manage the memory/disk allocation? Any thoughts?
You can write multiple pickled objects into a single file:
import cPickle as pickle
def dump(filename, items):
with open(filename, "wb") as out:
dump = pickle.Pickler(out).dump
for item in items:
dump(item)
def load(filename):
with open(filename, "rb") as instream:
load = pickle.Unpickler(instream).load
while True:
try:
item = load()
except EOFError:
break
yield item
if __name__ == "__main__":
filename = "tmp.pickle"
from collections import namedtuple
T = namedtuple("T", "alpha beta")
dump(filename, (T(a, b) for a, b in zip("abc", [1,2,3])))
for item in load(filename):
print item
To get random access you'd have to maintain a list containing the offsets of
the entries in the file.
However, a simple database like SQLite is probably sufficient for the kind
of entries you have in mind, and it allows operations like aggregation,
sorting and grouping out of the box.
Peter
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