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The short answer: use math if you are doing simple computations with only with scalars (and no lists or arrays). Use numpy if you are doing scientific computations with matrices, arrays, or large datasets.
Numpy is a scientific computation library in python and has values for a number of numerical constants including pi. You can use numpy. pi or np.
As you can see, the pi value is given to fifteen decimal places in Python. The number of digits provided depends on the underlying C compiler. Python prints the first fifteen digits by default, and math. pi always returns a float value.
>>> import math
>>> import numpy as np
>>> import scipy
>>> math.pi == np.pi == scipy.pi
True
So it doesn't matter, they are all the same value.
The only reason all three modules provide a pi value is so if you are using just one of the three modules, you can conveniently have access to pi without having to import another module. They're not providing different values for pi.
One thing to note is that not all libraries will use the same meaning for pi, of course, so it never hurts to know what you're using. For example, the symbolic math library Sympy's representation of pi is not the same as math and numpy:
import math
import numpy
import scipy
import sympy
print(math.pi == numpy.pi)
> True
print(math.pi == scipy.pi)
> True
print(math.pi == sympy.pi)
> False
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