Importing large integers from a mixed datatype file with numpy genfromtxt
Question: I have a file with the format:

    
    
    1    2.5264    24106644528  astring
    

I would like to import the data. I am using:

    
    
    >>> numpy.genfromtxt('myfile.dat',dtype=None)
    
    Traceback (most recent call last):
      File "<pyshell#4>", line 1, in <module>
        numpy.genfromtxt('myfile.dat',skip_header=27,dtype=None)
      File "C:\Python27\lib\site-packages\numpy\lib\npyio.py", line 1691, in genfromtxt
        output = np.array(data, dtype=ddtype)
    OverflowError: Python int too large to convert to C long
    

I checked the maximum integer on my (32-bit) system:

    
    
    >>> import sys
    >>> sys.maxint
    2147483647
    

Is there a way to increase the integer limit? Or can I get around my import
problem another way (without putting '.0' after all of the ints in file)?


Answer: Realised I can do this:

    
    
    >>> numpy.genfromtxt('myfile.dat',dtype=['i4','f8','f8','a14'])
    
    array((1, 2.5264, 24106644528.0, 'astring'), 
      dtype=[('f0', '<i4'), ('f1', '<f8'), ('f2', '<f8'), ('f3', 'S14')])
    

