Thank you all for your answers! I must say I'm really impressed by the
willing to help and the quick responses in this group (since it is my
first post)!
I solved the problem using SQL-queries. I added a id, the same for
each item in a chain (two or more similar posts) and just updated the
databas
Fisherking wrote:
Hi,
I hope you can help me with this optimizing problem!
I have a large list of dictionaries (about 250 000 of them). Two or
more of these dictionaries contains the same data (not more than five
or six of them per item) e.g. [{'a':1,'b':'2','c':3} , {'d':
4,'e':'5','f':6},{'a':
Fisherking wrote:
Hi,
I hope you can help me with this optimizing problem!
I have a large list of dictionaries (about 250 000 of them). Two or
more of these dictionaries contains the same data (not more than five
or six of them per item) e.g. [{'a':1,'b':'2','c':3} , {'d':
4,'e':'5','f':6},{'a':
Fisherking wrote:
> I hope you can help me with this optimizing problem!
> I have a large list of dictionaries (about 250 000 of them). Two or
> more of these dictionaries contains the same data (not more than five
> or six of them per item) e.g. [{'a':1,'b':'2','c':3} , {'d':
> 4,'e':'5','f':6},{
Hi,
2009/2/12 Paul Rubin :
> Fisherking writes:
>> Which are the best way of searching through the list and extract the
>> items that are the same.
hmmm how about using sqlites in memory database and let SQL take care
of finding that for you?
hth
Martin
--
http://soup.alt.delete.co.at
http:/
Fisherking writes:
> Which are the best way of searching through the list and extract the
> items that are the same.
Sort the list, then scan through looking for duplicates, which will be
adjacent to each other.
--
http://mail.python.org/mailman/listinfo/python-list
Hi,
I hope you can help me with this optimizing problem!
I have a large list of dictionaries (about 250 000 of them). Two or
more of these dictionaries contains the same data (not more than five
or six of them per item) e.g. [{'a':1,'b':'2','c':3} , {'d':
4,'e':'5','f':6},{'a':1,'b':'2','c':3} , {
