Some of Hypothesis's numpy/pandas strategies use a "fill" argument to
speed up generating large arrays, by generating a single fill value
and sharing that value among many array slots instead of filling every
single slot individually.
When no "fill" argument is provided, Hypothesis tries to detect
whether it is OK to automatically use the "elements" argument as a
fill strategy, so that it can still use the faster approach.
This patch fixes a bug that would cause that optimization to trigger
in some cases where it isn't 100% guaranteed to be OK.
If this makes some of your numpy/pandas tests run more slowly, try
adding an explicit "fill" argument to the relevant strategies to
ensure that Hypothesis always uses the faster approach.
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