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A related problem is that float(n) isn't always correctly rounded for an integer 
n. A contrived example:
>>> n = 2**68 + 2**16 - 1
>>> float(n)
2.9514790517935283e+20
Here the difference between float(n) and the true value of n is around 0.99998 
ulps; a correctly rounded float() would have error at most 0.5 ulps.
I don't regard this as terribly serious: from looking at the code, I *think* 
it's always true that the error is strictly less than 1 ulp, which is just 
enough to guarantee that float(n) == n whenever n is exactly representable as a 
float.
In contrast, the division of two integers can produce results that are up to 3.5 
ulps out from the true value. This is, in my opinion, a worryingly large error 
for a simple calculation.