Hypothesis

Hypothesis is a library that allows you to write tests that are parameterised from a source of examples. It then generates simple and understandable examples that can be used to make your tests fail and find bugs with little effort.

1. Install Hypothesis:

   Linux/macOS

   $ bin/python -m pip install hypothesis
   

   Windows

   C:> Scripts\python -m pip install hypothesis
   

   Alternatively, Hypothesis can also be installed with extensions, for example:

   Linux/macOS

   $ bin/python -m pip install hypothesis[numpy,pandas]
   

   Windows

   C:> Scripts\python -m pip install hypothesis[numpy,pandas]
   

2. Write a test:

   1. Imports:

      import pytest
      from hypothesis import given
      from hypothesis.strategies import floats, lists
      

   2. Test:

      @given(lists(floats(allow_nan=False, allow_infinity=False), min_size=1))
      def test_mean(ls):
          mean = sum(ls) / len(ls)
          assert min(ls) <= mean <= max(ls)
      

3. Perform test:

   Linux/macOS

   $ bin/python -m pytest test_hypothesis.py
   ============================= test session starts ==============================
   platform darwin -- Python 3.9.7, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
   rootdir: /Users/veit/cusy/trn/python-basics/docs/test
   plugins: hypothesis-6.23.2
   collected 1 item
   
   test_hypothesis.py F                                                     [100%]
   
   =================================== FAILURES ===================================
   __________________________________ test_mean ___________________________________
   
       @given(lists(floats(allow_nan=False, allow_infinity=False), min_size=1))
   >   def test_mean(ls):
   
   test_hypothesis.py:6:
   _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
   
   ls = [9.9792015476736e+291, 1.7976931348623157e+308]
   
       @given(lists(floats(allow_nan=False, allow_infinity=False), min_size=1))
       def test_mean(ls):
           mean = sum(ls) / len(ls)
   >       assert min(ls) <= mean <= max(ls)
   E       assert inf <= 1.7976931348623157e+308
   E        +  where 1.7976931348623157e+308 = max([9.9792015476736e+291, 1.7976931348623157e+308])
   
   test_hypothesis.py:8: AssertionError
   ---------------------------------- Hypothesis ----------------------------------
   Falsifying example: test_mean(
       ls=[9.9792015476736e+291, 1.7976931348623157e+308],
   )
   =========================== short test summary info ============================
   FAILED test_hypothesis.py::test_mean - assert inf <= 1.7976931348623157e+308
   ============================== 1 failed in 0.44s ===============================
   

   Windows

   C:> Scripts\python -m pytest test_hypothesis.py
   ============================= test session starts ==============================
   platform win32 -- Python 3.9.7, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
   rootdir: C:\Users\veit\python-basics\docs\test
   plugins: hypothesis-6.23.2
   collected 1 item
   
   test_hypothesis.py F                                                     [100%]
   
   =================================== FAILURES ===================================
   __________________________________ test_mean ___________________________________
   
       @given(lists(floats(allow_nan=False, allow_infinity=False), min_size=1))
   >   def test_mean(ls):
   
   test_hypothesis.py:6:
   _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
   
   ls = [9.9792015476736e+291, 1.7976931348623157e+308]
   
       @given(lists(floats(allow_nan=False, allow_infinity=False), min_size=1))
       def test_mean(ls):
           mean = sum(ls) / len(ls)
   >       assert min(ls) <= mean <= max(ls)
   E       assert inf <= 1.7976931348623157e+308
   E        +  where 1.7976931348623157e+308 = max([9.9792015476736e+291, 1.7976931348623157e+308])
   
   test_hypothesis.py:8: AssertionError
   ---------------------------------- Hypothesis ----------------------------------
   Falsifying example: test_mean(
       ls=[9.9792015476736e+291, 1.7976931348623157e+308],
   )
   =========================== short test summary info ============================
   FAILED test_hypothesis.py::test_mean - assert inf <= 1.7976931348623157e+308
   ============================== 1 failed in 0.44s ===============================
   

See also

Hypothesis for the Scientific Stack