If the user pass as a expected value a numpy array created like
numpy.array(5); it will creates an array with one element without shape,
when used with approx it will raise an error
'TypeError: iteration over a 0-d array'
- Avoid importing numpy unless necessary.
- Mention numpy arrays and dictionaries in the docs.
- Add numpy to the list of tox dependencies.
- Don't unnecessarily copy arrays or allocate empty space for them.
- Use code from compat.py rather than writing py2/3 versions of things
myself.
- Avoid reimplementing __repr__ for built-in types.
- Add an option to consider NaN == NaN, because sometimes people use NaN
to mean "missing data".
This fixes#1994. It turned out to require a lot of refactoring because
subclassing numpy.ndarray was necessary to coerce python into calling
the right `__eq__` operator.
This commit also:
- Dramatically increases the number of unit tests , mostly by borrowing
from the standard library's unit tests for math.isclose().
- Refactors approx() into two classes, one of which handles comparing
individual numbers (ApproxNonIterable) and another which uses the
first to compare individual numbers or sequences of numbers.
This was a challenge because it had to work in python2 and python3,
which have almost opposite unicode models, and I couldn't use the six
library. I'm also not sure the solution I found would work in python3
before python3.3, because I use the u'' string prefix which I think was
initially not part of python3.
Anthony Sottile
Bruno Oliveira
Kale Kundert
abrammer
Marcelo Duarte Trevisani
Ronny Pfannschmidt
Tadeu Manoel
mike
hugovk
Andras Tim
Michal Wajszczuk