|Authors:||Lea Wiemann <LeWiemann@gmail.com>; David Goodger <firstname.lastname@example.org>|
|Copyright:||This document has been placed in the public domain.|
When adding new functionality (or fixing bugs), be sure to add test cases to the test suite. Practise test-first programming; it’s fun, it’s addictive, and it works!
This document describes how to run the Docutils test suite, how the tests are organized and how to add new tests or modify existing tests.
Before checking in any changes, run the entire Docutils test suite to be sure that you haven’t broken anything. From a shell:
cd docutils/test ./alltests.py
The Docutils 0.10 release supports Python 2.4 or later. Therefore, you should actually have Pythons 2.4, as well as the latest Python (3.2 at the time of this writing) installed and always run the tests on all of them. (A good way to do that is to always run the test suite through a short script that runs alltests.py under each version of Python.) If you can’t afford installing 3 or more Python versions, the edge cases (2.4, and 3.2) should cover most of it.
Good resources covering the differences between Python versions:
Unit tests test single functions or modules (i.e. whitebox testing).
If you are implementing a new feature, be sure to write a test case covering its functionality. It happens very frequently that your implementation (or even only a part of it) doesn’t work with an older (or even newer) Python version, and the only reliable way to detect those cases is using tests.
Often, it’s easier to write the test first and then implement the functionality required to make the test pass.
When writing new tests, it very often helps to see how a similar test is implemented. For example, the files in the test_parsers/test_rst/ directory all look very similar. So when adding a test, you don’t have to reinvent the wheel.
If there is no similar test, you can write a new test from scratch using Python’s unittest module. For an example, please have a look at the following imaginary test_square.py:
#! /usr/bin/env python # $Id$ # Author: Your Name <email@example.com> # Copyright: This module has been placed in the public domain. """ Test module for docutils.square. """ import unittest import docutils.square class SquareTest(unittest.TestCase): def test_square(self): self.assertEqual(docutils.square.square(0), 0) self.assertEqual(docutils.square.square(5), 25) self.assertEqual(docutils.square.square(7), 49) def test_square_root(self): self.assertEqual(docutils.square.sqrt(49), 7) self.assertEqual(docutils.square.sqrt(0), 0) self.assertRaises(docutils.square.SquareRootError, docutils.square.sqrt, 20) if __name__ == '__main__': unittest.main()
For more details on how to write tests, please refer to the documentation of the unittest module.
The directory test/functional/ contains data for functional tests.
Performing functional testing means testing the Docutils system as a whole (i.e. blackbox testing).
- functional/ The main data directory.
- input/ The input files.
- some_test.txt, for example.
- output/ The actual output.
- some_test.html, for example.
- expected/ The expected output.
- some_test.html, for example.
- tests/ The config files for processing the input files.
- some_test.py, for example.
- _default.py, the default configuration file.
- input/ The input files.
When running test_functional.py, all config files in functional/tests/ are processed. (Config files whose names begin with an underscore are ignored.) The current working directory is always Docutils’ main test directory (test/).
For example, functional/tests/some_test.py could read like this:
# Source and destination file names. test_source = "some_test.txt" test_destination = "some_test.html" # Keyword parameters passed to publish_file. reader_name = "standalone" parser_name = "rst" writer_name = "html" settings_overrides['output-encoding'] = 'utf-8' # Relative to main ``test/`` directory. settings_overrides['stylesheet_path'] = '../docutils/writers/html4css1/html4css1.css'
The two variables test_source and test_destination contain the input file name (relative to functional/input/) and the output file name (relative to functional/output/ and functional/expected/). Note that the file names can be chosen arbitrarily. However, the file names in functional/output/ must match the file names in functional/expected/.
If defined, _test_more must be a function with the following signature:
def _test_more(expected_dir, output_dir, test_case, parameters):
This function is called from the test case to perform tests beyond the simple comparison of expected and actual output files.
test_source and test_destination are removed from the namespace, as are all variables whose names begin with an underscore (“_”). The remaining names are passed as keyword arguments to docutils.core.publish_file, so you can set reader, parser, writer and anything else you want to configure. Note that settings_overrides is already initialized as a dictionary before the execution of the config file.
In order to create a new test, put the input test file into functional/input/. Then create a config file in functional/tests/ which sets at least input and output file names, reader, parser and writer.
Now run test_functional.py. The test will fail, of course, because you do not have an expected output yet. However, an output file will have been generated in functional/output/. Check this output file for validity and correctness. Then copy the file to functional/expected/.
If you rerun test_functional.py now, it should pass.
If you run test_functional.py later and the actual output doesn’t match the expected output anymore, the test will fail.
If this is the case and you made an intentional change, check the actual output for validity and correctness, copy it to functional/expected/ (overwriting the old expected output), and commit the change.