Merge pull request #379 from johnnonweiler/266-remove-imports-from-wi…

…thin-tests

Move imports outside of test method code

_episodes/21-automatically-testing-software.md

@@ -355,10 +355,10 @@ Look at `tests/test_models.py`:
 import numpy as np
 import numpy.testing as npt
 
+from inflammation.models import daily_mean
 
 def test_daily_mean_zeros():
     """Test that mean function works for an array of zeros."""
-    from inflammation.models import daily_mean
 
     test_input = np.array([[0, 0],
                            [0, 0],
@@ -371,7 +371,6 @@ def test_daily_mean_zeros():
 
 def test_daily_mean_integers():
     """Test that mean function works for an array of positive integers."""
-    from inflammation.models import daily_mean
 
     test_input = np.array([[1, 2],
                            [3, 4],
@@ -544,14 +543,14 @@ do we think these results are easy to understand?
 > Once added, run all the tests again with `python -m pytest tests/test_models.py`,
 > and you should also see your new tests pass.
 >
-> 
+>
 > > ## Solution
 > >
 > > ~~~
+> > from inflammation.models import daily_max, daily_mean, daily_min
 > > ...
 > > def test_daily_max():
 > >     """Test that max function works for an array of positive integers."""
-> >     from inflammation.models import daily_max
 > >
 > >     test_input = np.array([[4, 2, 5],
 > >                            [1, 6, 2],
@@ -563,7 +562,6 @@ do we think these results are easy to understand?
 > >
 > > def test_daily_min():
 > >     """Test that min function works for an array of positive and negative integers."""
-> >     from inflammation.models import daily_min
 > >
 > >     test_input = np.array([[ 4, -2, 5],
 > >                            [ 1, -6, 2],
@@ -593,10 +591,10 @@ Add this test in `tests/test_models.py`:
 
 ~~~
 import pytest
+from inflammation.models import daily_min
 ...
 def test_daily_min_string():
     """Test for TypeError when passing strings"""
-    from inflammation.models import daily_min
 
     with pytest.raises(TypeError):
         error_expected = daily_min([['Hello', 'there'], ['General', 'Kenobi']])

_episodes/22-scaling-up-unit-testing.md

@@ -38,6 +38,8 @@ the `test_daily_mean_zeros()` and `test_daily_mean_integers()`
 into a single test function:
 
 ~~~
+from inflammation.models import daily_mean
+
 @pytest.mark.parametrize(
     "test, expected",
     [
@@ -46,7 +48,6 @@ into a single test function:
     ])
 def test_daily_mean(test, expected):
     """Test mean function works for array of zeroes and positive integers."""
-    from inflammation.models import daily_mean
     npt.assert_array_equal(daily_mean(np.array(test)), np.array(expected))
 ~~~
 {: .language-python}
@@ -85,6 +86,7 @@ and adding more tests scales better as our code becomes more complex.
 > 
 > > ## Solution
 > > ~~~
+> > from inflammation.models import daily_max, daily_min
 > > ...
 > > @pytest.mark.parametrize(
 > >     "test, expected",
@@ -95,7 +97,6 @@ and adding more tests scales better as our code becomes more complex.
 > >     ])
 > > def test_daily_max(test, expected):
 > >     """Test max function works for zeroes, positive integers, mix of positive/negative integers."""
-> >     from inflammation.models import daily_max
 > >     npt.assert_array_equal(daily_max(np.array(test)), np.array(expected))
 > >
 > >
@@ -108,7 +109,6 @@ and adding more tests scales better as our code becomes more complex.
 > >     ])
 > > def test_daily_min(test, expected):
 > >     """Test min function works for zeroes, positive integers, mix of positive/negative integers."""
-> >     from inflammation.models import daily_min
 > >     npt.assert_array_equal(daily_min(np.array(test)), np.array(expected))
 > > ...
 > > ~~~

_episodes/24-diagnosing-issues-improving-robustness.md

@@ -113,6 +113,8 @@ Let us now add a new test in `tests/test_models.py`
 to check that the normalisation function is correct for some test data.
 
 ~~~
+from inflammation.models import patient_normalise
+
 @pytest.mark.parametrize(
     "test, expected",
     [
@@ -121,7 +123,7 @@ to check that the normalisation function is correct for some test data.
 def test_patient_normalise(test, expected):
     """Test normalisation works for arrays of one and positive integers.
        Test with a relative and absolute tolerance of 0.01."""
-    from inflammation.models import patient_normalise
+
     result = patient_normalise(np.array(test))
     npt.assert_allclose(result, np.array(expected), rtol=1e-2, atol=1e-2)
 ~~~
@@ -135,14 +137,15 @@ and are only concerned with a certain degree of precision,
 like the test case above.
 
 > ## Relative and absolute tolerance
-> **Relative tolerance** in unit testing means that the acceptable difference between the expected and actual results 
-> depends on the size of the expected result itself. So, if your expected result is 100, 
+>
+> **Relative tolerance** in unit testing means that the acceptable difference between the expected and actual results
+> depends on the size of the expected result itself. So, if your expected result is 100,
 > a relative tolerance of 0.1 (or 10%) means the actual result can be anywhere from 90 to 110 and still be considered correct.
-> 
-> **Absolute tolerance**, on the other hand, 
-> sets a fixed allowable difference regardless of the magnitude of the expected result. 
-> For example, if you set an absolute tolerance of 5, 
-> it means the actual result can be within 5 units of the expected result, 
+>
+> **Absolute tolerance**, on the other hand,
+> sets a fixed allowable difference regardless of the magnitude of the expected result.
+> For example, if you set an absolute tolerance of 5,
+> it means the actual result can be within 5 units of the expected result,
 > regardless of whether the expected result is 10 or 1000.
 {: .callout}
 
@@ -467,9 +470,12 @@ def patient_normalise(data):
 > and add them to the parametrised tests.
 > After you have finished remember to commit your changes.
 >
-> 
+>
 > > ## Possible Solution
+> >
 > > ~~~
+> > from inflammation.models import patient_normalise
+> >
 > > @pytest.mark.parametrize(
 > >     "test, expected",
 > >     [
@@ -500,7 +506,7 @@ def patient_normalise(data):
 > >     ])
 > > def test_patient_normalise(test, expected):
 > >     """Test normalisation works for arrays of one and positive integers."""
-> >     from inflammation.models import patient_normalise
+> >
 > >     result = patient_normalise(np.array(test))
 > >     npt.assert_allclose(result, np.array(expected), rtol=1e-2, atol=1e-2)
 > > ...
@@ -563,6 +569,8 @@ and is used to indicate that the function received an argument of the right type
 but of an inappropriate value.
 
 ~~~
+from inflammation.models import patient_normalise
+
 @pytest.mark.parametrize(
     "test, expected, expect_raises",
     [
@@ -581,7 +589,6 @@ but of an inappropriate value.
     ])
 def test_patient_normalise(test, expected, expect_raises):
     """Test normalisation works for arrays of one and positive integers."""
-    from inflammation.models import patient_normalise
 
     if expect_raises is not None:
         with pytest.raises(expect_raises):
@@ -639,6 +646,7 @@ Be sure to commit your changes so far and push them to GitHub.
 > > In `test/test_models.py`:
 > >
 > > ~~~
+> > from inflammation.models import patient_normalise
 > > ...
 > > @pytest.mark.parametrize(
 > >     "test, expected, expect_raises",
@@ -662,7 +670,6 @@ Be sure to commit your changes so far and push them to GitHub.
 > >     ])
 > > def test_patient_normalise(test, expected, expect_raises):
 > >     """Test normalisation works for arrays of one and positive integers."""
-> >     from inflammation.models import patient_normalise
 > >     if isinstance(test, list):
 > >         test = np.array(test)
 > >     if expect_raises is not None:

_extras/databases.md

@@ -169,11 +169,12 @@ but it allows us not to worry about **migrations**.
 from sqlalchemy import create_engine
 from sqlalchemy.orm import sessionmaker
 
+from inflammation.models import Base, Patient
+
 ...
 
 def test_sqlalchemy_patient_search():
     """Test that we can save and retrieve patient data from a database."""
-    from inflammation.models import Base, Patient
 
     # Setup a database connection - we are using a database stored in memory here
     engine = create_engine('sqlite:///:memory:', echo=True)
@@ -273,11 +274,11 @@ We then test that we can get the observations from a patient we have searched fo
 ~~~
 # file: tests/test_models.py
 
+from inflammation.models import Base, Observation, Patient
 ...
 
 def test_sqlalchemy_observations():
     """Test that we can save and retrieve inflammation observations from a database."""
-    from inflammation.models import Base, Observation, Patient
 
     # Setup a database connection - we are using a database stored in memory here
     engine = create_engine('sqlite:///:memory:', echo=True)
@@ -342,10 +343,10 @@ and test that we can turn them into a Numpy array.
 
 ~~~
 # file: tests/test_models.py
-
+from inflammation.models import Base, Observation, Patient
+...
 def test_sqlalchemy_observations_to_array():
     """Test that we can save and retrieve inflammation observations from a database."""
-    from inflammation.models import Base, Observation, Patient
 
     # Setup a database connection - we are using a database stored in memory here
     engine = create_engine('sqlite:///:memory:')

_extras/object-oriented-programming.md

@@ -803,44 +803,40 @@ before we can properly initialise a `Patient` model with their inflammation data
 > explain them and how you implemented them to your neighbour.
 > Would they have implemented that feature in the same way?
 >
-> 
+>
 > > ## Solution
 > > One example solution is shown below.
 > > You may start by writing some tests (that will initially fail),
 > > and then develop the code to satisfy the new requirements and pass the tests.
 > > ~~~
 > > # file: tests/test_patient.py
 > > """Tests for the Patient model."""
+> > from inflammation.models import Doctor, Patient, Person
 > >
 > > def test_create_patient():
 > >     """Check a patient is created correctly given a name."""
-> >     from inflammation.models import Patient
 > >     name = 'Alice'
 > >     p = Patient(name=name)
 > >     assert p.name == name
 > >
 > > def test_create_doctor():
 > >     """Check a doctor is created correctly given a name."""
-> >     from inflammation.models import Doctor
 > >     name = 'Sheila Wheels'
 > >     doc = Doctor(name=name)
 > >     assert doc.name == name
 > >
 > > def test_doctor_is_person():
 > >     """Check if a doctor is a person."""
-> >     from inflammation.models import Doctor, Person
 > >     doc = Doctor("Sheila Wheels")
 > >     assert isinstance(doc, Person)
 > >
 > > def test_patient_is_person():
 > >     """Check if a patient is a person. """
-> >     from inflammation.models import Patient, Person
 > >     alice = Patient("Alice")
 > >     assert isinstance(alice, Person)
 > >
 > > def test_patients_added_correctly():
 > >     """Check patients are being added correctly by a doctor. """
-> >     from inflammation.models import Doctor, Patient
 > >     doc = Doctor("Sheila Wheels")
 > >     alice = Patient("Alice")
 > >     doc.add_patient(alice)
@@ -849,7 +845,6 @@ before we can properly initialise a `Patient` model with their inflammation data
 > >
 > > def test_no_duplicate_patients():
 > >     """Check adding the same patient to the same doctor twice does not result in duplicates. """
-> >     from inflammation.models import Doctor, Patient
 > >     doc = Doctor("Sheila Wheels")
 > >     alice = Patient("Alice")
 > >     doc.add_patient(alice)