Strange question this, I know. 
I have a code base in fortran 77 that for the most part parses large non-binary files, does some manipulation to these files and then does a lot of file writing. The code base does not do any matrix manipulation or number crunching. This legacy code is in fortran because a lot of other code bases do require serious number crunching. This was originally just written in fortran because there was knowledge of fortran.
My proposal is to re-write this entirely in python (most likely 3.3). Maintenance of the fortran code is just as difficult as you would expect, and the tests are as poor as you can imagine. Obviously python would help a lot here.
Is there any performance hits (or even gains) in terms of the file handling speed in python? Currently the majority of run time of this system is in reading/writing the files.
Thanks in advance
In general, unless your particular compiler and available toolset does especially counter-productive things, one programming language is able to do IO as fast as another. In many programming languages, a naive approach may be sub-optimal - like all performance-related aspects of programming, this is something that is solved by appropriate design, and appropriate use of the available tools (such as parallel processing, use of buffered, threaded IO, for example). 
Python isn't especially bad at IO, offers buffered IO and threading capabilities, and is easy to extend with C (and therefore probably not that hard to interact with Fortran). Python is likely to be a completely reasonable technology to incrementally replace parts of your codebase - indeed, if you can first make IO fast in python, you can probably compile an extension which ultimately calls your Fortran code.
File handling speed of python 3.3 compared to fortran 77