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TST: Add the first test using hypothesis #14440

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TST: Add the first test using hypothesis #14440

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28ecf82
TST: Add the first test using hypothesis
kitchoi Sep 6, 2019
28887ac
Make test input reproducible
kitchoi Sep 9, 2019
7ceadc7
Merge branch 'master' into tst-first-hypothesis-test
kitchoi Sep 9, 2019
baa728a
Merge branch 'master' into tst-first-hypothesis-test
kitchoi Dec 9, 2019
4aa0f72
Bump version of hypothesis
kitchoi Dec 9, 2019
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5 changes: 5 additions & 0 deletions INSTALL.rst.txt
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Expand Up @@ -33,8 +33,13 @@ Building NumPy requires the following installed software:

This is required for testing numpy, but not for using it.

4) hypothesis__ (optional)

This is required for testing numpy, but not for using it.

Python__ http://www.python.org
pytest__ http://pytest.readthedocs.io
hypothesis__ https://hypothesis.readthedocs.io


.. note::
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14 changes: 14 additions & 0 deletions numpy/core/tests/test_arrayprint.py
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Expand Up @@ -12,6 +12,10 @@
)
import textwrap

import hypothesis
import hypothesis.extra.numpy


class TestArrayRepr(object):
def test_nan_inf(self):
x = np.array([np.nan, np.inf])
Expand Down Expand Up @@ -399,6 +403,16 @@ def test_wide_element(self):
"[ 'xxxxx']"
)

@hypothesis.seed(43)
@hypothesis.given(hypothesis.extra.numpy.from_dtype(np.dtype("U")))
def test_any_text(self, text):
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My main question here is: are the text strings that are generated by hypothesis 100% reproducible over time/versions? And if not, what's the workflow to deal with a bug report for some random string by random user on some OS/install method/etc.?

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Thanks. Commit 28887ac should address this.

I tested the reproducibility with the following approach:
Before making the change in 28887ac

  1. Add a side-effect in the test to append the text to a file ~/text.txt
  2. Set PYTHONHASHSEED=random
  3. Run the test once, mv ~/text.txt ~/text0.txt
  4. Run the test again, diff ~/text.txt ~/text0.txt -> The files are different.
  5. Then make the change in 28887ac
  6. Perform step 3 and 4, the files are now identical.

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We can also use the @example directive to force a known failing case into the test once reported by a user or by the CI system

a = np.array([text, text, text])
assert_equal(a[0], text)
assert_equal(
np.array2string(a, max_line_width=len(repr(text)) * 2 + 3),
"[{0!r} {0!r}\n {0!r}]".format(text)
)

@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
def test_refcount(self):
# make sure we do not hold references to the array due to a recursive
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1 change: 1 addition & 0 deletions test_requirements.txt
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@@ -1,4 +1,5 @@
cython==0.29.14
hypothesis==4.53.1
pytest==5.3.1
pytz==2019.3
pytest-cov==2.8.1
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