Numpy's loadtxt(): OverflowError: Python int too large to convert to C long
You need to use a compound dtype, with a separate type per column.  Or you can use np.genfromtxt without specifying any dtype, and it will be determined automatically, per each column, which may give you what you need with less effort (but perhaps slightly less performance and less error checking too).
I'm trying to load a matrix from a file using numpy. When I use any dtype other than float I get this error:
OverflowError: Python int too large to convert to C long 
The code: 
X = np.loadtxt(feats_file_path, delimiter=' ', dtype=np.int64 )
The problem is that my matrix has only integers and I can't use a float because the first column in the matrix are integer "keys" that refer to node ids. When I use a float, numpy "rounds" the integer id into something like 32423e^10, and I don't want this behavior.
So my questions:

How to solve the OverflowError?
If it's not possible to solve, then how could I prevent numpy from doing that to the ids?