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Nov 26, 2023
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Wonderful start, just a few points that I didn't mention when we went through it last week
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| @pytest.mark.parametrize("rate, periods, payments, future_value, exp_result", [ | ||
| (0.07, 20, 0, 12000, -3101.0280337664), | ||
| (0.025, 4, 0, 1000, -905.9506447998), | ||
| (-0.07, 56, 0, 1200000, -69845129.5182595000), | ||
| (0.05, 20, 0, -12000, 4522.6737944760), | ||
| (0.05, 356.5288568, 0, -25000.00, 0.0006971776), | ||
| (0.05, 50, 0, 0, 0.0000000000), | ||
| (0.05, 26, 500, 0, -7187.5926504975), | ||
| ]) |
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These values should be strings, not floats. A float stores an inexact representation of most numbers, the decimal representation of that number will not be the same as the floating point representation. For example see:
>>> from decimal import Decimal
>>> Decimal(0.1) == Decimal("0.1")
False
>>> Decimal(0.1)
Decimal('0.1000000000000000055511151231257827021181583404541015625')
>>> Decimal("0.1")
Decimal('0.1')
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| if number_type is Decimal: | ||
| assert result == pytest.approx(exp_result, rel=0.2) |
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Please prefer the routines in numpy.testing over those in pytest.
In this case, we should not be testing that two values are approximately equal, but that they are exactly equal as, when we are using Decimal, we should be keeping arbitrary precision.
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| assert_allclose(float(result), float( | ||
| exp_result), atol=1e-10) |
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