PYTHON TESTING

JohnMonday, April 10, 2023

Type of testing

• Unit testing: Unit testing is testing of the smallest possible pieces of a program. it's the foundation upon which everything else is based

• Integration testing: tests encompass interactions between related units.

• System testing: system tests are an extreme form of integration tests.

UNITTEST MODULE

unittest introduction

• the batteries-included test module standard library.

• Similar usage as JUnit, nUnit, CppUnit series of tools.

Unittest package

Import unittestFrom unittest import TestCase,mainclass two_failing_tests(TestCase):

def test_assertTrue(self):self.assertTrue(1 == 1 + 1)

def test_assertEqual(self):self.assertEqual(1, 1 + 1)

if __name__ == '__main__':main()

Assert method• assertTrue: will succeed if expression is true• assertFalse: will succeed if expression is false• assertEqual, assertNotEqual• assertAlmostEqual: use this one compare

comparing floating point numbers. For example 3==3.00

• assertNotAlmostEqual• assertRaises• Final one: fail

PART 1: INTRODUCE DOCTEST MODULE

Doctest: the easiest Testing tool

• Doctest will be the mainstay of your testing toolkit

• doctest tests are written in plain text. • Doctest extracts the tests and ignores the

rest of the text• So the tests can be embedded in human-

readable explanations or discussions.

creating and running your first doctest• Open a new text file in your editor, and name it test.txt.• Insert the following text into the file: This is a simple doctest that checks some of Python's arithmeticoperations.>>> 2 + 24>>> 3 * 310• Run command: python -m doctest test.txt• Or you can write a small python code file:

import doctestdoctest.testfile(“test.txt")

• You can simply add IDLE input and output as test here

Directives:

• +SKIP to skip one test>>> 'This test would fail.' # doctest: +SKIP• +ELLIPSIS: can use … match any substring in

the actual outputfunc(56, "hello") # doctest: +ELLIPSIS<mocker.Mock object at ...>• More directives see here

Embedding doctests in Python docstringsdef testable(x):r"""The `testable` function returns the square root of itsparameter, or 3, whichever is larger.>>> testable(7)3.0>>> testable(16)4.0>>> testable(9)3.0>>> testable(10) == 10 ** 0.5True"""if x < 9: return 3.0return x ** 0.5

•Run command line: python m doctest v test.py‑ ‑•If you want to run the test in code. Add cose like:if __name__ == "__main__": import doctest doctest.testmod()

Tips

• Write your test before code development• reload(module) if your module is changed.

reload array

PART 2: INTRO TO PYTHON MOCKER AND UNITTEST

Install mocker first

• pip install mocker • Or python easy_install.py mocker• Or download it by yourself

http://labix.org/mocker

What is Mock object?

• Mock objects imitate the real objects that make up your program

• So we can decouple the multiplication class from others

Step by step

1. Create the mocking context: mocker = Mocker().

2. Create mocking object under this context: a = mocker.mock()

3. demonstrate how you expect the mock objects to be used :

func(56, "hello") # doctest: +ELLIPSIS<mocker.Mock object at ...>>>> mocker.result(11)

4. Here we expect func(56,”hello”) will output 11

6. Replay mode: mocker.replay(). Once enter this mode, the first time call func(56,”hello”). It will return 11 instead of call this func.

7. mocker.restore() : back the point not set mock.

8. mocker.verify(): check that the actual usage of the mocks was as expected. For example: check if func(56,”hello”) is 11

Function test

Parameter name in Mock

• ANY: any single object.i.e.func(a)• ARGS: any more arguments. i.e. func(a,b)• KWARGS: any more keyword arguments i.e.

func(a=1,b=2)• IS: func(7, IS(param)) # doctest: +ELLIPSIS• IN:func(7, IN([45, 68, 19])) # doctest:

+ELLIPSIS

CONTAINS: if the list contain this vlaue>>> from mocker import Mocker, CONTAINS>>> mocker = Mocker()>>> func = mocker.mock()>>> func(7, CONTAINS(45)) # doctest: +ELLIPSIS<mocker.Mock object at ...>>>> mocker.result(5)>>> mocker.replay()>>> func(7, [12, 31, 45, 18])5>>> mocker.restore()>>> mocker.verify()

MATCH: if match,it return true>>> from mocker import Mocker, MATCH>>> def is_odd(val):... return val % 2 == 1>>> mocker = Mocker()>>> func = mocker.mock()>>> func(7, MATCH(is_odd)) # doctest: +ELLIPSIS<mocker.Mock object at ...>>>> mocker.result(5)>>> mocker.replay()>>> func(7, 1001)5>>> mocker.restore()>>> mocker.verify()

mocker.count

• Mocker.count to specify the expected number of repetitions

• count(3): repeat 3 times• count(1,3): repeat times is between 1 and 3.• count(1,None): repeat at least 1 time, no

maximum.

Package test• Use replace to temporarily replace the libfrom time import time>>> from mocker import Mocker>>> mocker = Mocker()>>> mock_time = mocker.replace('time.time')>>> mock_time() # doctest: +ELLIPSIS<mocker.Mock object at ...>>>> mocker.result(1.3)>>> mocker.replay()>>> '%1.3g' % time()'1.3‘>>> mocker.restore()>>> mocker.verify()

Class test• Let self be a mock object>>> from testable import testable>>> from mocker import Mocker>>> mocker = Mocker()>>> target = mocker.mock()>>> target.method1(12) # doctest: +ELLIPSIS<mocker.Mock object at ...>>>> mocker.result(5)>>> target.method2(12) # doctest: +ELLIPSIS<mocker.Mock object at ...>>>> mocker.result(7)

PART 3: PYTHON TOOL NOSE

What is nose?

• A tool for finding and running all of your tests• presents with a nice report after tests finish.• Nose understands doctest and unittest tests• Install nose from PYPI (use easy_install or pip)• After install it, run command line: nosetests

Recommendation how to organize the source code folder• Nose recognizes test files based on their names– Any file whose name

contains test or Test containunittest TestCases

– Nose find doctest tests eitherembedded in docstrings or separate test files

• Reorgnize your folder. Change to the dir. Run command line:nosetests --with-doctest --doctest-extension=txt -v

Options for nosetests

• Create a configuration file called nose.cfg or .noserc in $HOME dir(For windows, the $HOME means C:\Users\users)

• Place following inside it:[nosetests]with-doctest=1doctest-extension=txtinclude="(?:^[Dd]oc)“

• Run nosetests –v.

PART 4: TESTING WEB APPLICATION FRONTENDS USING TWILL

Brief intro

• twill allows users to browse the Web from a command-line interface.

• twill supports automated Web testing • Twill has a simple Python interface.• Use pip install twill package first• Use command: twill-sh to start the shell

A simple example• Create slashdot.twill file contain code:code 200 follow Science code 200 formvalue 2 fhfilter "aardvark" submit code 200 find aardvark code 200follow Sciencecode 200formvalue 2 fhfilter "aardvark"submitcode 200find aardvark

• Run commandl line: twill-sh -u http://slashdot.org/ slashdot.twill

You can also test interactively

• >> go http://slashdot.org/ • >> code 200 • >> follow Science • ….

Use twill in python

Import twillbrowser = twill.get_browser()Browser methods include: go, reload,back,get_code,get_html,get_title,get_url,find_link,follow_link,set_agent_string,get_all_forms,get_form,get_form_field,clicked,submit,save_cookies,load_cookies,clear_cookies

PART 5: OTHER TESTING TOOLS AND TECHNIQUES

Code coverage

• A code coverage keeps track of which lines of code are (and aren't) executed while tests are running

• Give you a report describing how well your tests cover the whole body of code

Attention: Code coverage is a tool to give you insight into what your tests are doing, and what they may be overlooking. It's not the definition of a good test suite.

1. Install PYPI package coverage (pip install coverage)

2. When run your nose. Use option –with-coverage –-cover-erage

3. From the example, we saw line 16,19-20 of toy.py do not executes.

Automated continuous integration

• automated continuous integration system compiles your code (if need be) and runs your tests many times, in many different environments.

• Buildbot is a popular automated continuous integration tool.

Reference

• Book << Python Testing:Beginner's Guide>>