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For this project i will need a CSV to be created which can be uploaded to ioffer.com
I have two xmls/excel files with over 2500 products. You will have to create a csv file then upload it to ioffer.com. Before proceeding with project you must do only the first two products so i can check the work.

I have a tab delimited flat file on a linux server….
the first line of the file is the column names ie (customer, address etc)
I need a script that will allow me to search (within a web browser)this file by 2 of its fields and write the results/matches to a comma delimited flat file that can be easily saved to the desktop …

On search field will be the company name and the other is going to be a date…. I would also like the date field to be searched with a span of time IE (from 11-20-2009 thru 11-29-2009)

The script should be self contained with a simple .html UI
with 2 fields to enter the sets of search terms…
I also want the option to change the 2 fields ‘searched’ from within the script as a variable.

I can provide a sample file if needed

I need an advanced filter to use with excel. Ideally it should work within excel (a macro), but if it is a standalone script/application I will also consider it.

The data I have, looks like this (the list will typically have a 1000 to 2000 rows) -

column 1(URLs) column 2 (emails)
a.com name1(at)x1.com
b.com name2(at)x2.com,name3(at)x2.com
c.com name3(at)x3.com
d.com name4(at)x4.com

column 3 (filters)
name3(at)x2.com
name3(at)x3.com
name5(at)5.com

The filter must work like this -
Column 3 contains emails which I do not want, so they must be filtered out of the first two columns. If any email in column 3 appears in column 2, then that entry under column 2 must be deleted together with the entry in column 1 that is on the same row. ALL the entries in column 3 must be compared to every single entry under column 2.

If there are more than one email address in column 2 (on the same row separated by a comma – there will be up to 3 email addresses separated by a comma), and just one of them matches an entry under column 3, then just that specific email address must be deleted together with its leading or following “comma”, leaving the other email addresses and the entry in column 1 untouched.

To show that you understand what the filter needs to do, you might want to post the result to the example data above in the private message board.