re-adds old nose lesson. needs to be updated to pytest from scipy version of this lesson... must find.

Author: katyhuff

05-nose.md

@@ -0,0 +1,124 @@
+---
+layout: page
+title: Testing
+subtitle: Running Tests with Nose
+minutes: 10
+---
+> ## Learning Objectives {.objectives}
+> 
+> -   Understand how to run a test suite using the nose framework
+> -   Understand how to read the output of a nose test suite
+
+
+We created a suite of tests for our mean function, but it was annoying to run 
+them one at a time. It would be a lot better if there were some way to run them
+all at once, just reporting which tests fail and which succeed.
+
+Thankfully, that exists. Recall our tests:
+
+~~~ {.python}
+from mean import *
+
+def test_ints():
+    num_list = [1,2,3,4,5]
+    obs = mean(num_list)
+    exp = 3
+    assert obs == exp
+
+def test_zero():
+    num_list=[0,2,4,6]
+    obs = mean(num_list)
+    exp = 3
+    assert obs == exp
+
+def test_double():
+    # This one will fail in Python 2
+    num_list=[1,2,3,4]
+    obs = mean(num_list)
+    exp = 2.5
+    assert obs == exp
+
+def test_long():
+    big = 100000000
+    obs = mean(range(1,big))
+    exp = big/2.0
+    assert obs == exp
+
+def test_complex():
+    # given that complex numbers are an unordered field
+    # the arithmetic mean of complex numbers is meaningless
+    num_list = [2 + 3j, 3 + 4j, -32 - 2j]
+    obs = mean(num_list)
+    exp = NotImplemented
+    assert obs == exp
+~~~
+
+Once these tests are written in a file called `test_mean.py`, the command
+"nosetests" can be called from the directory containing the tests:
+
+~~~ {.bash}
+$ nosetests
+~~~
+~~~ {.output}
+....F
+======================================================================
+FAIL: test_mean.test_complex
+----------------------------------------------------------------------
+Traceback (most recent call last):
+  File "/Users/khuff/anaconda/envs/py3k/lib/python3.3/site-packages/nose/case.py", line 198, in runTest
+    self.test(*self.arg)
+  File "/Users/khuff/repos/2015-06-04-berkeley/testing/test_mean.py", line 34, in test_complex
+    assert obs == exp
+AssertionError
+
+----------------------------------------------------------------------
+Ran 5 tests in 3.746s
+
+FAILED (failures=1)
+~~~
+
+In the above case, the python nose package 'sniffed-out' the tests in the
+directory and ran them together to produce a report of the sum of the files and
+functions matching the regular expression `[Tt]est[-_]*`.
+
+
+The major boon a testing framework provides is exactly that, a utility to find and run the
+tests automatically. With `nose`, this is the command-line tool called
+_nosetests_.  When _nosetests_ is run, it will search all the directories whose names start or
+end with the word _test_, find all of the Python modules in these directories
+whose names
+start or end with _test_, import them, and run all of the functions and classes
+whose names start or end with _test_. In fact, `nose` looks for any names
+that match the regular expression `'(?:^|[\\b_\\.-])[Tt]est'`.
+This automatic registration of test code saves tons of human time and allows us to
+focus on what is important: writing more tests.
+
+When you run _nosetests_, it will print a dot (`.`) on the screen for every test
+that passes,
+an `F` for every test that fails, and an `E` for every test were there was an
+unexpected error. In rarer situations you may also see an `S` indicating a
+skipped tests (because the test is not applicable on your system) or a `K` for a known
+failure (because the developers could not fix it promptly). After the dots, _nosetests_
+will print summary information. 
+
+
+> ## Fix The Failing Code {.challenge}
+>
+> Without changing the tests, alter the mean.py file from the previous section until it passes. 
+> When it passes, _nosetests_ will produce results like the following:
+>
+> ~~~ {.bash}
+> $ nosetests
+> ~~~
+> ~~~ {.output}
+> .....
+> 
+> Ran 5 tests in 3.746s
+>
+> OK
+> ~~~
+
+As we write more code, we would write more tests, and _nosetests_ would produce
+more dots.  Each passing test is a small, satisfying reward for having written
+quality scientific software. Now that you know how to write tests, let's go
+into what can go wrong.