Unit tests for functions in a Jupyter notebook?

jupyter, python, reproducible-research, testing, unit-testing

Solution

Python standard testing tools, such as doctest and unittest, can be used directly in a notebook.

Doctest

A notebook cell with a function and a test case in a docstring:

def add(a, b):
    '''
    This is a test:
    >>> add(2, 2)
    5
    '''
    return a + b

A notebook cell (the last one in the notebook) that runs all test cases in the docstrings:

import doctest
doctest.testmod(verbose=True)

Output:

Trying:
    add(2, 2)
Expecting:
    5
**********************************************************************
File "__main__", line 4, in __main__.add
Failed example:
    add(2, 2)
Expected:
    5
Got:
    4
1 items had no tests:
    __main__
**********************************************************************
1 items had failures:
   1 of   1 in __main__.add
1 tests in 2 items.
0 passed and 1 failed.
***Test Failed*** 1 failures.

Unittest

A notebook cell with a function:

def add(a, b):
    return a + b

A notebook cell (the last one in the notebook) that contains a test case. The last line in the cell runs the test case when the cell is executed:

import unittest

class TestNotebook(unittest.TestCase):
    
    def test_add(self):
        self.assertEqual(add(2, 2), 5)
        

unittest.main(argv=[''], verbosity=2, exit=False)

Output:

test_add (__main__.TestNotebook) ... FAIL

======================================================================
FAIL: test_add (__main__.TestNotebook)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "<ipython-input-15-4409ad9ffaea>", line 6, in test_add
    self.assertEqual(add(2, 2), 5)
AssertionError: 4 != 5

----------------------------------------------------------------------
Ran 1 test in 0.001s

FAILED (failures=1)

Debugging a Failed Test

While debugging a failed test, it is often useful to halt the test case execution at some point and run a debugger. For this, insert the following code just before the line at which you want the execution to halt:

import pdb; pdb.set_trace()

For example:

def add(a, b):
    '''
    This is the test:
    >>> add(2, 2)
    5
    '''
    import pdb; pdb.set_trace()
    return a + b

For this example, the next time you run the doctest, the execution will halt just before the return statement and the Python debugger (pdb) will start. You will get a pdb prompt directly in the notebook, which will allow you to inspect the values of `a` and `b`, step over lines, etc.

Note: Starting with Python 3.7, the built-in `breakpoint()` can be used instead of `import pdb; pdb.set_trace()`.

I created a Jupyter notebook for experimenting with the techniques I have just described. You can try it out with

Problem

I have a Jupyter notebook that I plan to run repeatedly. It has functions in it, the structure of the code is this: ``` def construct_url(data): ... return url def scrape_url(url): ... # fetch url, extract data return parsed_data for i in mylist: url = construct_url(i) data = scrape_url(url) ... # use the data to do analysis ``` I'd like to write tests for `construct_url` and `scrape_url`. What's the most sensible way to do this? Some approaches I've considered: - Move the functions out into a utility file, and write tests for that utility file in some standard Python testing library. Possibly the best option, though it means that not all of the code is visible in the notebook. - Write asserts within the notebook itself, using test data (adds noise to the notebook). - Use specialised Jupyter testing to test the content of the cells (don't think this works, because the content of the cells is going to change).

Original source

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