Processing file with lists.

Alice Bevan–McGregor alice at
Thu Nov 25 10:52:32 CET 2010

You describe a two-part problem.  The first, loading the data, is 
easily accomplished with the Python CSV module:

e.g.: reader = csv.reader(open('filename', 'rb'), delimiter=';', 

In the above example, you can iterate over 'reader' in a for loop to 
read out each row.  The values will be returned in a list.

You could also use a DictReader to make the data more naturally 
accessible using name=value pairs.

> I want  to know how  could  I process this file using ' lists '  ,
> that  could  answer   questions like . How many ? ,  Who did .. ?
> etc.

This isn't very clear, but if your dataset is small (< 1000 rows or so) 
you can fairly quickly read the data into RAM then run through the data 
with loops designed to pull out certain data, though it seems your data 
would need additional processing.  (The authorship information should 
be split into two separate columns, for example.)

An alternative would be to load the data into a relational database 
like MySQL or even SQLite (which offers in-memory databases), or an 
object database such as MongoDB which supports advanced querying using 

You'd have to examine the documentation on these different systems to 
see which would best fit your use case.  I prefer Mongo as it is very 
easy to get data into and out of, supports SQL-like queries, and 
map/reduce is extremely powerful.

	— Alice.

More information about the Python-list mailing list