# testtools for test authors

If you are writing tests for a Python project and you (rather wisely) want to use testtools to do so, this is the manual for you.

We assume that you already know Python and that you know something about automated testing already.

If you are a test author of an unusually large or unusually unusual test suite, you might be interested in testtools for framework folk.

You might also be interested in the testtools API docs.

## Introduction

testtools is a set of extensions to Python’s standard unittest module. Writing tests with testtools is very much like writing tests with standard Python, or with Twisted’s “trial”, or nose, except a little bit easier and more enjoyable.

Below, we’ll try to give some examples of how to use testtools in its most basic way, as well as a sort of feature-by-feature breakdown of the cool bits that you could easily miss.

## The basics

Here’s what a basic testtools unit tests look like:

    from testtools import TestCase
    from myproject import silly

    class TestSillySquare(TestCase):
        """Tests for silly square function."""

        def test_square(self):
            # 'square' takes a number and multiplies it by itself.
            result = silly.square(7)
            self.assertEqual(result, 49)

        def test_square_bad_input(self):
            # 'square' raises a TypeError if it's given bad input, say a
            # string.
            self.assertRaises(TypeError, silly.square, "orange")

Here you have a class that inherits from `testtools.TestCase` and bundles together a bunch of related tests. The tests themselves are methods on that class that begin with `test_`.

### Running your tests

You can run these tests in many ways. testtools provides a very basic mechanism for doing so:

    $ python -m testtools.run exampletest
    Tests running...
    Ran 2 tests in 0.000s

    OK

where ‘exampletest’ is a module that contains unit tests. By default, `testtools.run` will not recursively search the module or package for unit tests. To do this, run:

    $ python -m testtools.run discover packagecontainingtests

For more information see the Python unittest documentation, and:

    python -m testtools.run --help

which describes the options available to `testtools.run`.

As your testing needs grow and evolve, you will probably want to use a more sophisticated test runner. There are many of these for Python, and almost all of them will happily run testtools tests. In particular:

- testrepository

- Trial

- nose

- zope.testrunner (aka zope.testing)

From now on, we’ll assume that you know how to run your tests.

## Assertions

The core of automated testing is making assertions about the way things are, and getting a nice, helpful, informative error message when things are not as they ought to be.

All of the assertions that you can find in Python standard unittest can be found in testtools (remember, testtools extends unittest). testtools changes the behaviour of some of those assertions slightly and adds some new assertions that you will almost certainly find useful.

### Improved assertRaises

`TestCase.assertRaises` returns the caught exception. This is useful for asserting more things about the exception than just the type:

    def test_square_bad_input(self):
        # 'square' raises a TypeError if it's given bad input, say a
        # string.
        e = self.assertRaises(TypeError, silly.square, "orange")
        self.assertEqual("orange", e.bad_value)
        self.assertEqual("Cannot square 'orange', not a number.", str(e))

### ExpectedException

If you are using a version of Python that supports the `with` context manager syntax, you might prefer to use that syntax to ensure that code raises particular errors. `ExpectedException` does just that. For example:

    def test_square_root_bad_input_2(self):
        # 'square' raises a TypeError if it's given bad input.
        with ExpectedException(TypeError, "Cannot square.*"):
            silly.square('orange')

The first argument to `ExpectedException` is the type of exception you expect to see raised. The second argument is optional, and can be either a regular expression or a matcher. If it is a regular expression, the `str()` of the raised exception must match the regular expression. If it is a matcher, then the raised exception object must match it. The optional third argument `msg` will cause the raised error to be annotated with that message.

### assertIn, assertNotIn

These two assertions check whether a value is in a sequence and whether a value is not in a sequence. They are “assert” versions of the `in` and `not in` operators. For example:

    def test_assert_in_example(self):
        self.assertIn('a', 'cat')
        self.assertNotIn('o', 'cat')
        self.assertIn(5, list_of_primes_under_ten)
        self.assertNotIn(12, list_of_primes_under_ten)

### assertIs, assertIsNot

These two assertions check whether values are identical to one another. This is sometimes useful when you want to test something more strict than mere equality. For example:

    def test_assert_is_example(self):
        foo = [None]
        foo_alias = foo
        bar = [None]
        self.assertIs(foo, foo_alias)
        self.assertIsNot(foo, bar)
        self.assertEqual(foo, bar) # They are equal, but not identical

### assertIsInstance

As much as we love duck-typing and polymorphism, sometimes you need to check whether or not a value is of a given type. This method does that. For example:

    def test_assert_is_instance_example(self):
        now = datetime.now()
        self.assertIsInstance(now, datetime)

Note that there is no `assertIsNotInstance` in testtools currently.

### expectFailure

Sometimes it’s useful to write tests that fail. For example, you might want to turn a bug report into a unit test, but you don’t know how to fix the bug yet. Or perhaps you want to document a known, temporary deficiency in a dependency.

testtools gives you the `TestCase.expectFailure` to help with this. You use it to say that you expect this assertion to fail. When the test runs and the assertion fails, testtools will report it as an “expected failure”.

Here’s an example:

    def test_expect_failure_example(self):
        self.expectFailure(
            "cats should be dogs", self.assertEqual, 'cats', 'dogs')

As long as ‘cats’ is not equal to ‘dogs’, the test will be reported as an expected failure.

If ever by some miracle ‘cats’ becomes ‘dogs’, then testtools will report an “unexpected success”. Unlike standard unittest, testtools treats this as something that fails the test suite, like an error or a failure.

## Matchers

The built-in assertion methods are very useful, they are the bread and butter of writing tests. However, soon enough you will probably want to write your own assertions. Perhaps there are domain specific things that you want to check (e.g. assert that two widgets are aligned parallel to the flux grid), or perhaps you want to check something that could almost but not quite be found in some other standard library (e.g. assert that two paths point to the same file).

When you are in such situations, you could either make a base class for your project that inherits from `testtools.TestCase` and make sure that all of your tests derive from that, or you could use the testtools `Matcher` system.

### Using Matchers

Here’s a really basic example using stock matchers found in testtools:

    import testtools
    from testtools.matchers import Equals

    class TestSquare(TestCase):
        def test_square(self):
           result = square(7)
           self.assertThat(result, Equals(49))

The line `self.assertThat(result, Equals(49))` is equivalent to `self.assertEqual(result, 49)` and means “assert that `result` equals 49”. The difference is that `assertThat` is a more general method that takes some kind of observed value (in this case, `result`) and any matcher object (here, `Equals(49)`).

The matcher object could be absolutely anything that implements the Matcher protocol. This means that you can make more complex matchers by combining existing ones:

    def test_square_silly(self):
        result = square(7)
        self.assertThat(result, Not(Equals(50)))

Which is roughly equivalent to:

    def test_square_silly(self):
        result = square(7)
        self.assertNotEqual(result, 50)

### `assert_that` Function

In addition to `self.assertThat`, testtools also provides the `assert_that` function in `testtools.assertions` This behaves like the method version does:

    class TestSquare(TestCase):

        def test_square():
            result = square(7)
            assert_that(result, Equals(49))

        def test_square_silly():
            result = square(7)
            assert_that(result, Not(Equals(50)))

#### Delayed Assertions

A failure in the `self.assertThat` method will immediately fail the test: No more test code will be run after the assertion failure.

The `expectThat` method behaves the same as `assertThat` with one exception: when failing the test it does so at the end of the test code rather than when the mismatch is detected. For example:

    import subprocess

    from testtools import TestCase
    from testtools.matchers import Equals

    class SomeProcessTests(TestCase):

        def test_process_output(self):
            process = subprocess.Popen(
              ["my-app", "/some/path"],
              stdout=subprocess.PIPE,
              stderr=subprocess.PIPE
            )

            stdout, stderrr = process.communicate()

            self.expectThat(process.returncode, Equals(0))
            self.expectThat(stdout, Equals("Expected Output"))
            self.expectThat(stderr, Equals(""))

In this example, should the `expectThat` call fail, the failure will be recorded in the test result, but the test will continue as normal. If all three assertions fail, the test result will have three failures recorded, and the failure details for each failed assertion will be attached to the test result.

### Stock matchers

testtools comes with many matchers built in. They can all be found in and imported from the `testtools.matchers` module.

#### Equals

Matches if two items are equal. For example:

    def test_equals_example(self):
        self.assertThat([42], Equals([42]))

#### Is

Matches if two items are identical. For example:

    def test_is_example(self):
        foo = object()
        self.assertThat(foo, Is(foo))

#### IsInstance

Adapts isinstance() to use as a matcher. For example:

    def test_isinstance_example(self):
        class MyClass:pass
        self.assertThat(MyClass(), IsInstance(MyClass))
        self.assertThat(MyClass(), IsInstance(MyClass, str))

#### The raises helper

Matches if a callable raises a particular type of exception. For example:

    def test_raises_example(self):
        self.assertThat(lambda: 1/0, raises(ZeroDivisionError))

This is actually a convenience function that combines two other matchers: Raises and MatchesException.

#### The IsDeprecated helper

Matches if a callable produces a warning whose message matches the specified matcher. For example:

    def old_func(x):
        warnings.warn('old_func is deprecated use new_func instead')
        return new_func(x)

    def test_warning_example(self):
        self.assertThat(
          lambda: old_func(42),
          IsDeprecated(Contains('old_func is deprecated')))

This is just a convenience function that combines Warnings and WarningMessage.

#### DocTestMatches

Matches a string as if it were the output of a doctest example. Very useful for making assertions about large chunks of text. For example:

    import doctest

    def test_doctest_example(self):
        output = "Colorless green ideas"
        self.assertThat(
            output,
            DocTestMatches("Colorless ... ideas", doctest.ELLIPSIS))

We highly recommend using the following flags:

    doctest.ELLIPSIS | doctest.NORMALIZE_WHITESPACE | doctest.REPORT_NDIFF

#### GreaterThan

Matches if the given thing is greater than the thing in the matcher. For example:

    def test_greater_than_example(self):
        self.assertThat(3, GreaterThan(2))

#### LessThan

Matches if the given thing is less than the thing in the matcher. For example:

    def test_less_than_example(self):
        self.assertThat(2, LessThan(3))

#### StartsWith, EndsWith

These matchers check to see if a string starts with or ends with a particular substring. For example:

    def test_starts_and_ends_with_example(self):
        self.assertThat('underground', StartsWith('und'))
        self.assertThat('underground', EndsWith('und'))

#### Contains

This matcher checks to see if the given thing contains the thing in the matcher. For example:

    def test_contains_example(self):
        self.assertThat('abc', Contains('b'))

#### MatchesException

Matches an exc_info tuple if the exception is of the correct type. For example:

    def test_matches_exception_example(self):
        try:
            raise RuntimeError('foo')
        except RuntimeError:
            exc_info = sys.exc_info()
        self.assertThat(exc_info, MatchesException(RuntimeError))
        self.assertThat(exc_info, MatchesException(RuntimeError('bar')))

Most of the time, you will want to uses The raises helper instead.

#### WarningMessage

Match against various attributes (category, message and filename to name a few) of a warning.WarningMessage, which can be captured by Warnings.

#### NotEquals

Matches if something is not equal to something else. Note that this is subtly different to `Not(Equals(x))`. `NotEquals(x)` will match if `y != x`, `Not(Equals(x))` will match if `not y == x`.

You only need to worry about this distinction if you are testing code that relies on badly written overloaded equality operators.

#### KeysEqual

Matches if the keys of one dict are equal to the keys of another dict. For example:

    def test_keys_equal(self):
        x = {'a': 1, 'b': 2}
        y = {'a': 2, 'b': 3}
        self.assertThat(x, KeysEqual(y))

#### MatchesRegex

Matches a string against a regular expression, which is a wonderful thing to be able to do, if you think about it:

    def test_matches_regex_example(self):
        self.assertThat('foo', MatchesRegex('fo+'))

#### HasLength

Check the length of a collection. The following assertion will fail:

    self.assertThat([1, 2, 3], HasLength(2))

But this one won’t:

    self.assertThat([1, 2, 3], HasLength(3))

### File- and path-related matchers

testtools also has a number of matchers to help with asserting things about the state of the filesystem.

#### PathExists

Matches if a path exists:

    self.assertThat('/', PathExists())

#### DirExists

Matches if a path exists and it refers to a directory:

    # This will pass on most Linux systems.
    self.assertThat('/home/', DirExists())
    # This will not
    self.assertThat('/home/jml/some-file.txt', DirExists())

#### FileExists

Matches if a path exists and it refers to a file (as opposed to a directory):

    # This will pass on most Linux systems.
    self.assertThat('/bin/true', FileExists())
    # This will not.
    self.assertThat('/home/', FileExists())

#### DirContains

Matches if the given directory contains the specified files and directories. Say we have a directory `foo` that has the files `a`, `b` and `c`, then:

    self.assertThat('foo', DirContains(['a', 'b', 'c']))

will match, but:

    self.assertThat('foo', DirContains(['a', 'b']))

will not.

The matcher sorts both the input and the list of names we get back from the filesystem.

You can use this in a more advanced way, and match the sorted directory listing against an arbitrary matcher:

    self.assertThat('foo', DirContains(matcher=Contains('a')))

#### FileContains

Matches if the given file has the specified contents. Say there’s a file called `greetings.txt` with the contents, `Hello World!`:

    self.assertThat('greetings.txt', FileContains("Hello World!"))

will match.

You can also use this in a more advanced way, and match the contents of the file against an arbitrary matcher:

    self.assertThat('greetings.txt', FileContains(matcher=Contains('!')))

#### HasPermissions

Used for asserting that a file or directory has certain permissions. Uses octal-mode permissions for both input and matching. For example:

    self.assertThat('/tmp', HasPermissions('1777'))
    self.assertThat('id_rsa', HasPermissions('0600'))

This is probably more useful on UNIX systems than on Windows systems.

#### SamePath

Matches if two paths actually refer to the same thing. The paths don’t have to exist, but if they do exist, `SamePath` will resolve any symlinks.:

    self.assertThat('somefile', SamePath('childdir/../somefile'))

#### TarballContains

Matches the contents of a tarball. In many ways, much like `DirContains`, but instead of matching on `os.listdir` matches on `TarFile.getnames`.

### Combining matchers

One great thing about matchers is that you can readily combine existing matchers to get variations on their behaviour or to quickly build more complex assertions.

Below are a few of the combining matchers that come with testtools.

#### Always

testtools.matchers.Always()

  Always match.

  That is:

      self.assertThat(x, Always())

  Will always match and never fail, no matter what `x` is. Most useful when passed to other higher-order matchers (e.g. `MatchesListwise`).

#### Never

testtools.matchers.Never()

  Never match.

  That is:

      self.assertThat(x, Never())

  Will never match and always fail, no matter what `x` is. Included for completeness with `Always()`, but if you find a use for this, let us know!

#### Not

Negates another matcher. For example:

    def test_not_example(self):
        self.assertThat([42], Not(Equals("potato")))
        self.assertThat([42], Not(Is([42])))

If you find yourself using `Not` frequently, you may wish to create a custom matcher for it. For example:

    IsNot = lambda x: Not(Is(x))

    def test_not_example_2(self):
        self.assertThat([42], IsNot([42]))

#### Annotate

Used to add custom notes to a matcher. For example:

    def test_annotate_example(self):
        result = 43
        self.assertThat(
            result, Annotate("Not the answer to the Question!", Equals(42)))

Since the annotation is only ever displayed when there is a mismatch (e.g. when `result` does not equal 42), it’s a good idea to phrase the note negatively, so that it describes what a mismatch actually means.

As with Not, you may wish to create a custom matcher that describes a common operation. For example:

    PoliticallyEquals = lambda x: Annotate("Death to the aristos!", Equals(x))

    def test_annotate_example_2(self):
        self.assertThat("orange", PoliticallyEquals("yellow"))

You can have assertThat perform the annotation for you as a convenience:

    def test_annotate_example_3(self):
        self.assertThat("orange", Equals("yellow"), "Death to the aristos!")

#### AfterPreprocessing

Used to make a matcher that applies a function to the matched object before matching. This can be used to aid in creating trivial matchers as functions, for example:

    def test_after_preprocessing_example(self):
        def PathHasFileContent(content):
            def _read(path):
                return open(path).read()
            return AfterPreprocessing(_read, Equals(content))
        self.assertThat('/tmp/foo.txt', PathHasFileContent("Hello world!"))

#### MatchesAll

Combines many matchers to make a new matcher. The new matcher will only match things that match every single one of the component matchers.

It’s much easier to understand in Python than in English:

    def test_matches_all_example(self):
        has_und_at_both_ends = MatchesAll(StartsWith("und"), EndsWith("und"))
        # This will succeed.
        self.assertThat("underground", has_und_at_both_ends)
        # This will fail.
        self.assertThat("found", has_und_at_both_ends)
        # So will this.
        self.assertThat("undead", has_und_at_both_ends)

At this point some people ask themselves, “why bother doing this at all? why not just have two separate assertions?”. It’s a good question.

The first reason is that when a `MatchesAll` gets a mismatch, the error will include information about all of the bits that mismatched. When you have two separate assertions, as below:

    def test_two_separate_assertions(self):
         self.assertThat("foo", StartsWith("und"))
         self.assertThat("foo", EndsWith("und"))

Then you get absolutely no information from the second assertion if the first assertion fails. Tests are largely there to help you debug code, so having more information in error messages is a big help.

The second reason is that it is sometimes useful to give a name to a set of matchers. `has_und_at_both_ends` is a bit contrived, of course, but it is clear. The `FileExists` and `DirExists` matchers included in testtools are perhaps better real examples.

If you want only the first mismatch to be reported, pass `first_only=True` as a keyword parameter to `MatchesAll`.

#### MatchesAny

Like MatchesAll, `MatchesAny` combines many matchers to make a new matcher. The difference is that the new matchers will match a thing if it matches any of the component matchers.

For example:

    def test_matches_any_example(self):
        self.assertThat(42, MatchesAny(Equals(5), Not(Equals(6))))

#### AllMatch

Matches many values against a single matcher. Can be used to make sure that many things all meet the same condition:

    def test_all_match_example(self):
        self.assertThat([2, 3, 5, 7], AllMatch(LessThan(10)))

If the match fails, then all of the values that fail to match will be included in the error message.

In some ways, this is the converse of MatchesAll.

#### MatchesListwise

Where `MatchesAny` and `MatchesAll` combine many matchers to match a single value, `MatchesListwise` combines many matches to match many values.

For example:

    def test_matches_listwise_example(self):
        self.assertThat(
            [1, 2, 3], MatchesListwise(map(Equals, [1, 2, 3])))

This is useful for writing custom, domain-specific matchers.

If you want only the first mismatch to be reported, pass `first_only=True` to `MatchesListwise`.

#### MatchesSetwise

Combines many matchers to match many values, without regard to their order.

Here’s an example:

    def test_matches_setwise_example(self):
        self.assertThat(
            [1, 2, 3], MatchesSetwise(Equals(2), Equals(3), Equals(1)))

Much like `MatchesListwise`, best used for writing custom, domain-specific matchers.

#### MatchesStructure

Creates a matcher that matches certain attributes of an object against a pre-defined set of matchers.

It’s much easier to understand in Python than in English:

    def test_matches_structure_example(self):
        foo = Foo()
        foo.a = 1
        foo.b = 2
        matcher = MatchesStructure(a=Equals(1), b=Equals(2))
        self.assertThat(foo, matcher)

Since all of the matchers used were `Equals`, we could also write this using the `byEquality` helper:

    def test_matches_structure_example(self):
        foo = Foo()
        foo.a = 1
        foo.b = 2
        matcher = MatchesStructure.byEquality(a=1, b=2)
        self.assertThat(foo, matcher)

`MatchesStructure.fromExample` takes an object and a list of attributes and creates a `MatchesStructure` matcher where each attribute of the matched object must equal each attribute of the example object. For example:

    matcher = MatchesStructure.fromExample(foo, 'a', 'b')

is exactly equivalent to `matcher` in the previous example.

#### MatchesPredicate

Sometimes, all you want to do is create a matcher that matches if a given function returns True, and mismatches if it returns False.

For example, you might have an `is_prime` function and want to make a matcher based on it:

    def test_prime_numbers(self):
        IsPrime = MatchesPredicate(is_prime, '%s is not prime.')
        self.assertThat(7, IsPrime)
        self.assertThat(1983, IsPrime)
        # This will fail.
        self.assertThat(42, IsPrime)

Which will produce the error message:

    Traceback (most recent call last):
      File "...", line ..., in test_prime_numbers
        self.assertThat(42, IsPrime)
    MismatchError: 42 is not prime.

#### MatchesPredicateWithParams

Sometimes you can’t use a trivial predicate and instead need to pass in some parameters each time. In that case, MatchesPredicateWithParams is your go-to tool for creating ad hoc matchers. MatchesPredicateWithParams takes a predicate function and message and returns a factory to produce matchers from that. The predicate needs to return a boolean (or any truthy object), and accept the object to match + whatever was passed into the factory.

For example, you might have an `divisible` function and want to make a matcher based on it:

    def test_divisible_numbers(self):
        IsDivisibleBy = MatchesPredicateWithParams(
            divisible, '{0} is not divisible by {1}')
        self.assertThat(7, IsDivisibleBy(1))
        self.assertThat(7, IsDivisibleBy(7))
        self.assertThat(7, IsDivisibleBy(2))
        # This will fail.

Which will produce the error message:

    Traceback (most recent call last):
      File "...", line ..., in test_divisible
        self.assertThat(7, IsDivisibleBy(2))
    MismatchError: 7 is not divisible by 2.

#### Raises

Takes whatever the callable raises as an exc_info tuple and matches it against whatever matcher it was given. For example, if you want to assert that a callable raises an exception of a given type:

    def test_raises_example(self):
        self.assertThat(
            lambda: 1/0, Raises(MatchesException(ZeroDivisionError)))

Although note that this could also be written as:

    def test_raises_example_convenient(self):
        self.assertThat(lambda: 1/0, raises(ZeroDivisionError))

See also MatchesException and the raises helper

#### Warnings

Captures all warnings produced by a callable as a list of warning.WarningMessage and matches against it. For example, if you want to assert that a callable emits exactly one warning:

    def soon_to_be_old_func():
        warnings.warn('soon_to_be_old_func will be deprecated next version',
                      PendingDeprecationWarning, 2)

    def test_warnings_example(self):
        self.assertThat(
            soon_to_be_old_func,
            Warnings(HasLength(1)))

Deprecating something and making an assertion about the deprecation message is a very common test with which the IsDeprecated helper can assist. For making more specific matches against warnings WarningMessage can construct a matcher that can be combined with Warnings.

### Writing your own matchers

Combining matchers is fun and can get you a very long way indeed, but sometimes you will have to write your own. Here’s how.

You need to make two closely-linked objects: a `Matcher` and a `Mismatch`. The `Matcher` knows how to actually make the comparison, and the `Mismatch` knows how to describe a failure to match.

Here’s an example matcher:

    class IsDivisibleBy(object):
        """Match if a number is divisible by another number."""
        def __init__(self, divider):
            self.divider = divider
        def __str__(self):
            return 'IsDivisibleBy(%s)' % (self.divider,)
        def match(self, actual):
            remainder = actual % self.divider
            if remainder != 0:
                return IsDivisibleByMismatch(actual, self.divider, remainder)
            else:
                return None

The matcher has a constructor that takes parameters that describe what you actually expect, in this case a number that other numbers ought to be divisible by. It has a `__str__` method, the result of which is displayed on failure by `assertThat` and a `match` method that does the actual matching.

`match` takes something to match against, here `actual`, and decides whether or not it matches. If it does match, then `match` must return `None`. If it does not match, then `match` must return a `Mismatch` object. `assertThat` will call `match` and then fail the test if it returns a non-None value. For example:

    def test_is_divisible_by_example(self):
        # This succeeds, since IsDivisibleBy(5).match(10) returns None.
        self.assertThat(10, IsDivisibleBy(5))
        # This fails, since IsDivisibleBy(7).match(10) returns a mismatch.
        self.assertThat(10, IsDivisibleBy(7))

The mismatch is responsible for what sort of error message the failing test generates. Here’s an example mismatch:

    class IsDivisibleByMismatch(object):
        def __init__(self, number, divider, remainder):
            self.number = number
            self.divider = divider
            self.remainder = remainder

        def describe(self):
            return "%r is not divisible by %r, %r remains" % (
                self.number, self.divider, self.remainder)

        def get_details(self):
            return {}

The mismatch takes information about the mismatch, and provides a `describe` method that assembles all of that into a nice error message for end users. You can use the `get_details` method to provide extra, arbitrary data with the mismatch (e.g. the contents of a log file). Most of the time it’s fine to just return an empty dict. You can read more about Details elsewhere in this document.

Sometimes you don’t need to create a custom mismatch class. In particular, if you don’t care when the description is calculated, then you can just do that in the Matcher itself like this:

    def match(self, actual):
        remainder = actual % self.divider
        if remainder != 0:
            return Mismatch(
                "%r is not divisible by %r, %r remains" % (
                    actual, self.divider, remainder))
        else:
            return None

When writing a `describe` method or constructing a `Mismatch` object the code should ensure it only emits printable unicode. As this output must be combined with other text and forwarded for presentation, letting through non-ascii bytes of ambiguous encoding or control characters could throw an exception or mangle the display. In most cases simply avoiding the `%s` format specifier and using `%r` instead will be enough. For examples of more complex formatting see the `testtools.matchers` implementatons.

## Details

As we may have mentioned once or twice already, one of the great benefits of automated tests is that they help find, isolate and debug errors in your system.

Frequently however, the information provided by a mere assertion failure is not enough. It’s often useful to have other information: the contents of log files; what queries were run; benchmark timing information; what state certain subsystem components are in and so forth.

testtools calls all of these things “details” and provides a single, powerful mechanism for including this information in your test run.

Here’s an example of how to add them:

    from testtools import TestCase
    from testtools.content import text_content

    class TestSomething(TestCase):

        def test_thingy(self):
            self.addDetail('arbitrary-color-name', text_content("blue"))
            1 / 0 # Gratuitous error!

A detail an arbitrary piece of content given a name that’s unique within the test. Here the name is `arbitrary-color-name` and the content is `text_content("blue")`. The name can be any text string, and the content can be any `testtools.content.Content` object.

When the test runs, testtools will show you something like this:

    ======================================================================
    ERROR: exampletest.TestSomething.test_thingy
    ----------------------------------------------------------------------
    arbitrary-color-name: {{{blue}}}

    Traceback (most recent call last):
      File "exampletest.py", line 8, in test_thingy
        1 / 0 # Gratuitous error!
    ZeroDivisionError: integer division or modulo by zero
    ------------
    Ran 1 test in 0.030s

As you can see, the detail is included as an attachment, here saying that our arbitrary-color-name is “blue”.

### Content

For the actual content of details, testtools uses its own MIME-based Content object. This allows you to attach any information that you could possibly conceive of to a test, and allows testtools to use or serialize that information.

The basic `testtools.content.Content` object is constructed from a `testtools.content.ContentType` and a nullary callable that must return an iterator of chunks of bytes that the content is made from.

So, to make a Content object that is just a simple string of text, you can do:

    from testtools.content import Content
    from testtools.content_type import ContentType

    text = Content(ContentType('text', 'plain'), lambda: ["some text"])

Because adding small bits of text content is very common, there’s also a convenience method:

    text = text_content("some text")

To make content out of an image stored on disk, you could do something like:

    image = Content(ContentType('image', 'png'), lambda: open('foo.png').read())

Or you could use the convenience function:

    image = content_from_file('foo.png', ContentType('image', 'png'))

The `lambda` helps make sure that the file is opened and the actual bytes read only when they are needed – by default, when the test is finished. This means that tests can construct and add Content objects freely without worrying too much about how they affect run time.

### A realistic example

A very common use of details is to add a log file to failing tests. Say your project has a server represented by a class `SomeServer` that you can start up and shut down in tests, but runs in another process. You want to test interaction with that server, and whenever the interaction fails, you want to see the client-side error and the logs from the server-side. Here’s how you might do it:

    from testtools import TestCase
    from testtools.content import attach_file, Content
    from testtools.content_type import UTF8_TEXT

    from myproject import SomeServer

    class SomeTestCase(TestCase):

        def setUp(self):
            super(SomeTestCase, self).setUp()
            self.server = SomeServer()
            self.server.start_up()
            self.addCleanup(self.server.shut_down)
            self.addCleanup(attach_file, self.server.logfile, self)

        def attach_log_file(self):
            self.addDetail(
                'log-file',
                Content(UTF8_TEXT,
                        lambda: open(self.server.logfile, 'r').readlines()))

        def test_a_thing(self):
            self.assertEqual("cool", self.server.temperature)

This test will attach the log file of `SomeServer` to each test that is run. testtools will only display the log file for failing tests, so it’s not such a big deal.

If the act of adding at detail is expensive, you might want to use addOnException so that you only do it when a test actually raises an exception.

## Controlling test execution

### addCleanup

`TestCase.addCleanup` is a robust way to arrange for a clean up function to be called before `tearDown`. This is a powerful and simple alternative to putting clean up logic in a try/finally block or `tearDown` method. For example:

    def test_foo(self):
        foo.lock()
        self.addCleanup(foo.unlock)
        ...

This is particularly useful if you have some sort of factory in your test:

    def make_locked_foo(self):
        foo = Foo()
        foo.lock()
        self.addCleanup(foo.unlock)
        return foo

    def test_frotz_a_foo(self):
        foo = self.make_locked_foo()
        foo.frotz()
        self.assertEqual(foo.frotz_count, 1)

Any extra arguments or keyword arguments passed to `addCleanup` are passed to the callable at cleanup time.

Cleanups can also report multiple errors, if appropriate by wrapping them in a `testtools.MultipleExceptions` object:

    raise MultipleExceptions(exc_info1, exc_info2)

### Fixtures

Tests often depend on a system being set up in a certain way, or having certain resources available to them. Perhaps a test needs a connection to the database or access to a running external server.

One common way of doing this is to do:

    class SomeTest(TestCase):
        def setUp(self):
            super(SomeTest, self).setUp()
            self.server = Server()
            self.server.setUp()
            self.addCleanup(self.server.tearDown)

testtools provides a more convenient, declarative way to do the same thing:

    class SomeTest(TestCase):
        def setUp(self):
            super(SomeTest, self).setUp()
            self.server = self.useFixture(Server())

`useFixture(fixture)` calls `setUp` on the fixture, schedules a clean up to clean it up, and schedules a clean up to attach all details held by the fixture to the test case. The fixture object must meet the `fixtures.Fixture` protocol (version 0.3.4 or newer, see fixtures).

If you have anything beyond the most simple test set up, we recommend that you put this set up into a `Fixture` class. Once there, the fixture can be easily re-used by other tests and can be combined with other fixtures to make more complex resources.

### Skipping tests

Many reasons exist to skip a test: a dependency might be missing; a test might be too expensive and thus should not berun while on battery power; or perhaps the test is testing an incomplete feature.

`TestCase.skipTest` is a simple way to have a test stop running and be reported as a skipped test, rather than a success, error or failure. For example:

    def test_make_symlink(self):
        symlink = getattr(os, 'symlink', None)
        if symlink is None:
            self.skipTest("No symlink support")
        symlink(whatever, something_else)

Using `skipTest` means that you can make decisions about what tests to run as late as possible, and close to the actual tests. Without it, you might be forced to use convoluted logic during test loading, which is a bit of a mess.

#### Legacy skip support

If you are using this feature when running your test suite with a legacy `TestResult` object that is missing the `addSkip` method, then the `addError` method will be invoked instead. If you are using a test result from testtools, you do not have to worry about this.

In older versions of testtools, `skipTest` was known as `skip`. Since Python 2.7 added `skipTest` support, the `skip` name is now deprecated.

### addOnException

Sometimes, you might wish to do something only when a test fails. Perhaps you need to run expensive diagnostic routines or some such. `TestCase.addOnException` allows you to easily do just this. For example:

    class SomeTest(TestCase):
        def setUp(self):
            super(SomeTest, self).setUp()
            self.server = self.useFixture(SomeServer())
            self.addOnException(self.attach_server_diagnostics)

        def attach_server_diagnostics(self, exc_info):
            self.server.prep_for_diagnostics() # Expensive!
            self.addDetail('server-diagnostics', self.server.get_diagnostics)

        def test_a_thing(self):
            self.assertEqual('cheese', 'chalk')

In this example, `attach_server_diagnostics` will only be called when a test fails. It is given the exc_info tuple of the error raised by the test, just in case it is needed.

### Twisted support

testtools provides support for running Twisted tests – tests that return a Deferred and rely on the Twisted reactor. See Twisted support.

### force_failure

Setting the `testtools.TestCase.force_failure` instance variable to `True` will cause the test to be marked as a failure, but won’t stop the test code from running (see Delayed Test Failure).

## Test helpers

testtools comes with a few little things that make it a little bit easier to write tests.

### TestCase.patch

`patch` is a convenient way to monkey-patch a Python object for the duration of your test. It’s especially useful for testing legacy code. e.g.:

    def test_foo(self):
        my_stream = StringIO()
        self.patch(sys, 'stderr', my_stream)
        run_some_code_that_prints_to_stderr()
        self.assertEqual('', my_stream.getvalue())

The call to `patch` above masks `sys.stderr` with `my_stream` so that anything printed to stderr will be captured in a StringIO variable that can be actually tested. Once the test is done, the real `sys.stderr` is restored to its rightful place.

### Creation methods

Often when writing unit tests, you want to create an object that is a completely normal instance of its type. You don’t want there to be anything special about its properties, because you are testing generic behaviour rather than specific conditions.

A lot of the time, test authors do this by making up silly strings and numbers and passing them to constructors (e.g. 42, ‘foo’, “bar” etc), and that’s fine. However, sometimes it’s useful to be able to create arbitrary objects at will, without having to make up silly sample data.

To help with this, `testtools.TestCase` implements creation methods called `getUniqueString` and `getUniqueInteger`. They return strings and integers that are unique within the context of the test that can be used to assemble more complex objects. Here’s a basic example where `getUniqueString` is used instead of saying “foo” or “bar” or whatever:

    class SomeTest(TestCase):

        def test_full_name(self):
            first_name = self.getUniqueString()
            last_name = self.getUniqueString()
            p = Person(first_name, last_name)
            self.assertEqual(p.full_name, "%s %s" % (first_name, last_name))

And here’s how it could be used to make a complicated test:

    class TestCoupleLogic(TestCase):

        def make_arbitrary_person(self):
            return Person(self.getUniqueString(), self.getUniqueString())

        def test_get_invitation(self):
            a = self.make_arbitrary_person()
            b = self.make_arbitrary_person()
            couple = Couple(a, b)
            event_name = self.getUniqueString()
            invitation = couple.get_invitation(event_name)
            self.assertEqual(
                invitation,
                "We invite %s and %s to %s" % (
                    a.full_name, b.full_name, event_name))

Essentially, creation methods like these are a way of reducing the number of assumptions in your tests and communicating to test readers that the exact details of certain variables don’t actually matter.

See pages 419-423 of xUnit Test Patterns by Gerard Meszaros for a detailed discussion of creation methods.

`testcase.generate_unique_text()` is similar to `getUniqueString`, except it generates text that contains unicode characters. The value will be a `unicode` object in Python 2 and a `str` object in Python 3.

### Test attributes

Inspired by the `nosetests` `attr` plugin, testtools provides support for marking up test methods with attributes, which are then exposed in the test id and can be used when filtering tests by id. (e.g. via `--load-list`):

    from testtools.testcase import attr, WithAttributes

    class AnnotatedTests(WithAttributes, TestCase):

        @attr('simple')
        def test_one(self):
            pass

        @attr('more', 'than', 'one')
        def test_two(self):
            pass

        @attr('or')
        @attr('stacked')
        def test_three(self):
            pass

## General helpers

### Nullary callables

Sometimes you want to be able to pass around a function with the arguments already specified. The normal way of doing this in Python is:

    nullary = lambda: f(*args, **kwargs)
    nullary()

Which is mostly good enough, but loses a bit of debugging information. If you take the `repr()` of `nullary`, you’re only told that it’s a lambda, and you get none of the juicy meaning that you’d get from the `repr()` of `f`.

The solution is to use `Nullary` instead:

    nullary = Nullary(f, *args, **kwargs)
    nullary()

Here, `repr(nullary)` will be the same as `repr(f)`.