On Thu, 2022-09-08 at 21:15 -0400, Warren Weckesser wrote:
On 9/8/22, Andrew Nelson <andyfaff@gmail.com> wrote:
<snip>
For many types, this function makes an attempt to return a string that would yield an object with the same value when passed to eval();
Sebastian, is this an explicit goal of the change? (Personally, I've gotten used to not taking this too seriously, but my world view is biased by the long-term use of NumPy, which has never followed this guideline.)
To me, that should be mainly a guiding principle maybe not a strict goal. But I do wonder if there are any alternative thoughts on what the representation should be? Since I doubt Python will add infix operators that allow `123.4_f64` soon that is probably not worth a thought :). For booleans I think we previously had rather settled on `np.True_` and `np.False_`. Cheers, Sebastian
If that is a goal, than the floating point types with precision greater than double precision will need to display the argument of the type as a string. For example, the following is run on a platform where numpy.longdouble is extended precision (80 bits):
``` In [161]: longpi = np.longdouble('3.14159265358979323846')
In [162]: longpi Out[162]: 3.1415926535897932385
In [163]: np.longdouble(3.1415926535897932385) # Argument is parsed as 64 bit float Out[163]: 3.141592653589793116
In [164]: np.longdouble('3.1415926535897932385') # Correctly reproduces the longdouble Out[164]: 3.1415926535897932385 ```
Warren
I think it definitely we should definitely have:
repr(np.float32(34.3)) == 'float32(34.3)' And str(np.float32(34.3)) == '34.3'
It seems buglike not to have that.
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