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Merge pull request #118 from guibog/master
On unit test, doctest and web frameworks
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@@ -21,10 +21,10 @@ documented in `PEP-3333 <http://www.python.org/dev/peps/pep-3333/>`_.
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Frameworks
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::::::::::
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Broadly speaking, a web framework is a set of libraries upon which you can
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build custom code to implement a web application (i.e. an interactive web
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site). Most web frameworks include patterns and utilities to accomplish at
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least the following:
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Broadly speaking, a web framework consist of a set of libraries and a main
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handler within which you can build custom code to implement a web application
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(i.e. an interactive web site). Most web frameworks include patterns and
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utilities to accomplish at least the following:
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URL Routing
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Matches an incoming HTTP request to a particular piece of Python code to
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@@ -33,7 +33,7 @@ Inline comments are used for individual lines and should be used sparingly.: ::
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But sometimes, this is useful: ::
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x = x + 1 # Compensate for border
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Doc Strings
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Docstrings
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-----------
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PEP 257 is the primary reference for docstrings. (http://www.python.org/dev/peps/pep-0257/)
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+91
-1
@@ -3,6 +3,69 @@ Testing Your Code
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Testing your code is very important.
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Getting used to writting the testing code and the running code in parallel is
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now considered a good habit. Used wisely, this method helps you define more
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precisely your code's intent and have a more decoupled architecture.
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Some general rules of testing:
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- A testing unit should focus on one tiny bit of functionality and prove it
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correct.
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- Each test unit must be fully independent. Each of them must be able to run
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alone, and also within the test suite, regardless of the order they are called.
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The implication of this rule is that each test must be loaded with a fresh
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dataset and may have to do some cleanup afterwards. This is usually
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handled by setUp() and tearDown() methods.
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- Try hard to make tests that run fast. If one single test needs more than a
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few millisecond to run, development will be slowed down or the tests will not
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be run as often as desirable. I some cases, test can't be fast because they
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need a complex data structure to work on, and this data structure must be loaded
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every time the test runs. Keep this heavier tests in a separate test suite
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that is run by some scheduled task, and run all other tests as often as needed.
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- Learn your tools and learn how to run a single test or a test case. Then,
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when developing a function inside a module, run this function's tests very
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often, ideally automatically when you save the code.
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- Always run the full test suite before a coding session, and run it again
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after. This will give you more confidence that you did not break anything in
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the rest of the code.
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- It is a good idea to implement a hook that runs all test before pushing code
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to a shared repository.
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- If you are in the middle of a development and have to interrupt your work, it
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is a good idea to write a broken unit test about what you want to develop next.
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When comming back to work, you will have a pointer to where you were and get
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faster on tracks.
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- The first step when you are debugging your code is to write a new test pinpointing
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the bug. While it is not always possible to do, those bug catching test are among
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the most valuable piece of code in your project.
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- Use long and descriptive names for testing functions. The style guide here is
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slighlty different than that of running code, where short names are often
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preferred. The reason is testing functions are never called explicitely.
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``square()`` or even ``sqr()`` is ok in running code, but in testing code you
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would has names such as ``test_square_of_number_2()``,
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``test_square_negative_number()``. These function names are displayed when a
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test fail, and should be as descriptive as possible.
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- When something goes wrong or has to be changed, and if your code has a good
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set of tests, you or other maintainers will rely largely on the testing suite
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to fix the problem or modify a given behavior. Therefore the testing code will
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be read as much as or even more than the running code. A unit test whose
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purpose is unclear is not very helpful is this case.
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- Another use of the testing code is as an introduction to new developpers. When
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someone will have to work on the code base, runnning and reading the related
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testing code is often the best they can do. They will or should discover the
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hot spots, where most difficulties arise, and the corner cases. If they have to
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add some functionality, the first step should be to add a test and, by this mean,
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ensure the new functionality is not already a working path that has not been
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plugged in the interface.
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The Basics
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::::::::::
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@@ -37,9 +100,36 @@ Doctest
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-------
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The doctest module searches for pieces of text that look like interactive Python
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sessions, and then executes those sessions to verify that they work exactly as
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sessions in docstrings, and then executes those sessions to verify that they work exactly as
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shown.
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Doctests have a different use case than proper unit tests: they are usually less
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detailed and don't catch special cases or obscure regression bugs. They are
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useful as an expressive documentation of the main use cases of a module and
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its components. However, doctests should run automatically each time
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the full test suite runs.
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A simple doctest in a function:
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::
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def square(x):
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"""Squares x.
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>>> square(2)
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4
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>>> square(-2)
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4
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"""
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return x * x
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if __name__ == '__main__':
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import doctest
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doctest.testmod()
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When running this module from the command line as in ``python module.py``, the doctests
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will run and complain if anything is not behaving as described in the docstrings.
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Tools
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:::::
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