Python: handling a large set of data. Scipy or Rpy? And how?
As @gsk3 noted, bigmemory is a great package for this, along with the packages biganalytics and bigtabulate (there are more, but these are worth checking out).  There's also ff, though that isn't as easy to use.
Common to both R and Python is support for HDF5 (see the ncdf4 or NetCDF4 packages in R), which makes it very speedy and easy to access massive data sets on disk.  Personally, I primarily use bigmemory, though that's R specific.  As HDF5 is available in Python and is very, very fast, it's probably going to be your best bet in Python.
In my python environment, the Rpy and Scipy packages are already installed. 
The problem I want to tackle is such:
1) A huge set of financial data are stored in a text file. Loading into Excel is not possible
2) I need to sum a certain fields and get the totals.
3) I need to show the top 10 rows based on the totals.
Which package (Scipy or Rpy) is best suited for this task? 
If so, could you provide me some pointers (e.g. documentation or online example) that can help me to implement a solution?
Speed is a concern. Ideally scipy and Rpy can handle the large files when even when the files are so large that they cannot be fitted into memory