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Hypothesis

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4.32.1

Not secure
-------------------

This release changes how the shrinker represents its progress internally. For large generated test cases
this should result in significantly less memory usage and possibly faster shrinking. Small generated
test cases may be slightly slower to shrink but this shouldn't be very noticeable.

4.32.0

Not secure
-------------------

This release makes :func:`~hypothesis.extra.numpy.arrays` more pedantic about
``elements`` strategies that cannot be exactly represented as array elements.

In practice, you will see new warnings if you were using a ``float16`` or
``float32`` dtype without passing :func:`~hypothesis.strategies.floats` the
``width=16`` or ``width=32`` arguments respectively.

The previous behaviour could lead to silent truncation, and thus some elements
being equal to an explicitly excluded bound (:issue:`1899`).

4.31.1

Not secure
-------------------

This patch changes an internal use of MD5 to SHA hashes, to better support
users subject to FIPS-140. There is no user-visible or API change.

Thanks to Alex Gaynor for this patch.

4.31.0

Not secure
-------------------

This release simplifies the logic of the :attr:`~hypothesis.settings.print_blob` setting by removing the option to set it to ``PrintSettings.INFER``.
As a result the ``print_blob`` setting now takes a single boolean value, and the use of ``PrintSettings`` is deprecated.

4.28.2

Not secure
-------------------

This patch improves the docstrings of several Hypothesis strategies, by
clarifying markup and adding cross-references. There is no runtime change.

Thanks to Elizabeth Williams and Serah Njambi Rono for their contributions
at the SciPy 2019 sprints!

4.28.1

Not secure
-------------------

This patch improves the behaviour of the :func:`~hypothesis.strategies.text`
strategy when passed an ``alphabet`` which is not a strategy. The value is
now interpreted as ``include_characters`` to :func:`~hypothesis.strategies.characters`
instead of a sequence for :func:`~hypothesis.strategies.sampled_from`, which
standardises the distribution of examples and the shrinking behaviour.

You can get the previous behaviour by using
``lists(sampled_from(alphabet)).map("".map)`` instead.

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