/usr/lib64/python3.9/unittest/__pycache__
Edit: /usr/lib64/python3.9/unittest/__pycache__/mock.cpython-39.pyc (78019B)
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Create a new `Mock` object. `Mock` takes several optional arguments
that specify the behaviour of the Mock object:
* `spec`: This can be either a list of strings or an existing object (a
class or instance) that acts as the specification for the mock object. If
you pass in an object then a list of strings is formed by calling dir on
the object (excluding unsupported magic attributes and methods). Accessing
any attribute not in this list will raise an `AttributeError`.
If `spec` is an object (rather than a list of strings) then
`mock.__class__` returns the class of the spec object. This allows mocks
to pass `isinstance` tests.
* `spec_set`: A stricter variant of `spec`. If used, attempting to *set*
or get an attribute on the mock that isn't on the object passed as
`spec_set` will raise an `AttributeError`.
* `side_effect`: A function to be called whenever the Mock is called. See
the `side_effect` attribute. Useful for raising exceptions or
dynamically changing return values. The function is called with the same
arguments as the mock, and unless it returns `DEFAULT`, the return
value of this function is used as the return value.
If `side_effect` is an iterable then each call to the mock will return
the next value from the iterable. If any of the members of the iterable
are exceptions they will be raised instead of returned.
* `return_value`: The value returned when the mock is called. By default
this is a new Mock (created on first access). See the
`return_value` attribute.
* `wraps`: Item for the mock object to wrap. If `wraps` is not None then
calling the Mock will pass the call through to the wrapped object
(returning the real result). Attribute access on the mock will return a
Mock object that wraps the corresponding attribute of the wrapped object
(so attempting to access an attribute that doesn't exist will raise an
`AttributeError`).
If the mock has an explicit `return_value` set then calls are not passed
to the wrapped object and the `return_value` is returned instead.
* `name`: If the mock has a name then it will be used in the repr of the
mock. This can be useful for debugging. The name is propagated to child
mocks.
Mocks can also be called with arbitrary keyword arguments. These will be
used to set attributes on the mock after it is created.
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patch the named member (`attribute`) on an object (`target`) with a mock
object.
`patch.object` can be used as a decorator, class decorator or a context
manager. Arguments `new`, `spec`, `create`, `spec_set`,
`autospec` and `new_callable` have the same meaning as for `patch`. Like
`patch`, `patch.object` takes arbitrary keyword arguments for configuring
the mock object it creates.
When used as a class decorator `patch.object` honours `patch.TEST_PREFIX`
for choosing which methods to wrap.
z3 must be the actual object to be patched, not a strc s S r/ r r r r r r 5 r! z _patch_object..)r1 strr rV )
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t|| |
|||||i } | | _| j| qt| S )a Perform multiple patches in a single call. It takes the object to be
patched (either as an object or a string to fetch the object by importing)
and keyword arguments for the patches::
with patch.multiple(settings, FIRST_PATCH='one', SECOND_PATCH='two'):
...
Use `DEFAULT` as the value if you want `patch.multiple` to create
mocks for you. In this case the created mocks are passed into a decorated
function by keyword, and a dictionary is returned when `patch.multiple` is
used as a context manager.
`patch.multiple` can be used as a decorator, class decorator or a context
manager. The arguments `spec`, `spec_set`, `create`,
`autospec` and `new_callable` have the same meaning as for `patch`. These
arguments will be applied to *all* patches done by `patch.multiple`.
When used as a class decorator `patch.multiple` honours `patch.TEST_PREFIX`
for choosing which methods to wrap.
c s t S r/ r r r r r r S r! z!_patch_multiple..c s S r/ r r r r r r U r! z=Must supply at least one keyword argument with patch.multipler r N) r1 r r< rY r rV r^ r[ r )
rS r rY r rZ rX rC rW r rU r r_ Z this_patcherr r r _patch_multiple< s, r c
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`patch` acts as a function decorator, class decorator or a context
manager. Inside the body of the function or with statement, the `target`
is patched with a `new` object. When the function/with statement exits
the patch is undone.
If `new` is omitted, then the target is replaced with an
`AsyncMock if the patched object is an async function or a
`MagicMock` otherwise. If `patch` is used as a decorator and `new` is
omitted, the created mock is passed in as an extra argument to the
decorated function. If `patch` is used as a context manager the created
mock is returned by the context manager.
`target` should be a string in the form `'package.module.ClassName'`. The
`target` is imported and the specified object replaced with the `new`
object, so the `target` must be importable from the environment you are
calling `patch` from. The target is imported when the decorated function
is executed, not at decoration time.
The `spec` and `spec_set` keyword arguments are passed to the `MagicMock`
if patch is creating one for you.
In addition you can pass `spec=True` or `spec_set=True`, which causes
patch to pass in the object being mocked as the spec/spec_set object.
`new_callable` allows you to specify a different class, or callable object,
that will be called to create the `new` object. By default `AsyncMock` is
used for async functions and `MagicMock` for the rest.
A more powerful form of `spec` is `autospec`. If you set `autospec=True`
then the mock will be created with a spec from the object being replaced.
All attributes of the mock will also have the spec of the corresponding
attribute of the object being replaced. Methods and functions being
mocked will have their arguments checked and will raise a `TypeError` if
they are called with the wrong signature. For mocks replacing a class,
their return value (the 'instance') will have the same spec as the class.
Instead of `autospec=True` you can pass `autospec=some_object` to use an
arbitrary object as the spec instead of the one being replaced.
By default `patch` will fail to replace attributes that don't exist. If
you pass in `create=True`, and the attribute doesn't exist, patch will
create the attribute for you when the patched function is called, and
delete it again afterwards. This is useful for writing tests against
attributes that your production code creates at runtime. It is off by
default because it can be dangerous. With it switched on you can write
passing tests against APIs that don't actually exist!
Patch can be used as a `TestCase` class decorator. It works by
decorating each test method in the class. This reduces the boilerplate
code when your test methods share a common patchings set. `patch` finds
tests by looking for method names that start with `patch.TEST_PREFIX`.
By default this is `test`, which matches the way `unittest` finds tests.
You can specify an alternative prefix by setting `patch.TEST_PREFIX`.
Patch can be used as a context manager, with the with statement. Here the
patching applies to the indented block after the with statement. If you
use "as" then the patched object will be bound to the name after the
"as"; very useful if `patch` is creating a mock object for you.
`patch` takes arbitrary keyword arguments. These will be passed to
`AsyncMock` if the patched object is asynchronous, to `MagicMock`
otherwise or to `new_callable` if specified.
`patch.dict(...)`, `patch.multiple(...)` and `patch.object(...)` are
available for alternate use-cases.
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Patch a dictionary, or dictionary like object, and restore the dictionary
to its original state after the test.
`in_dict` can be a dictionary or a mapping like container. If it is a
mapping then it must at least support getting, setting and deleting items
plus iterating over keys.
`in_dict` can also be a string specifying the name of the dictionary, which
will then be fetched by importing it.
`values` can be a dictionary of values to set in the dictionary. `values`
can also be an iterable of `(key, value)` pairs.
If `clear` is True then the dictionary will be cleared before the new
values are set.
`patch.dict` can also be called with arbitrary keyword arguments to set
values in the dictionary::
with patch.dict('sys.modules', mymodule=Mock(), other_module=Mock()):
...
`patch.dict` can be used as a context manager, decorator or class
decorator. When used as a class decorator `patch.dict` honours
`patch.TEST_PREFIX` for choosing which methods to wrap.
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MagicMock is a subclass of Mock with default implementations
of most of the magic methods. You can use MagicMock without having to
configure the magic methods yourself.
If you use the `spec` or `spec_set` arguments then *only* magic
methods that exist in the spec will be created.
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Fc C s | || | dS r r r r r r r + s zMagicMock.mock_add_specN)Fr r r r r r s
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Assert that the mock was awaited at least once.
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Assert that the mock was awaited exactly once and with the specified
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Assert the mock has been awaited with the specified calls.
The :attr:`await_args_list` list is checked for the awaits.
If `any_order` is False (the default) then the awaits must be
sequential. There can be extra calls before or after the
specified awaits.
If `any_order` is True then the awaits can be in any order, but
they must all appear in :attr:`await_args_list`.
c s g | ]} |qS r r. r/ r r r r r! z4AsyncMockMixin.assert_has_awaits..c s s | ]}t |tr|V qd S r/ r1 r r r r r2 r! z3AsyncMockMixin.assert_has_awaits..Nc 3 s | ]} |V qd S r/ r. r/ r r r r2 r! zAwaits not found.z,Error processing expected awaits.
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Enhance :class:`Mock` with features allowing to mock
an async function.
The :class:`AsyncMock` object will behave so the object is
recognized as an async function, and the result of a call is an awaitable:
>>> mock = AsyncMock()
>>> iscoroutinefunction(mock)
True
>>> inspect.isawaitable(mock())
True
The result of ``mock()`` is an async function which will have the outcome
of ``side_effect`` or ``return_value``:
- if ``side_effect`` is a function, the async function will return the
result of that function,
- if ``side_effect`` is an exception, the async function will raise the
exception,
- if ``side_effect`` is an iterable, the async function will return the
next value of the iterable, however, if the sequence of result is
exhausted, ``StopIteration`` is raised immediately,
- if ``side_effect`` is not defined, the async function will return the
value defined by ``return_value``, hence, by default, the async function
returns a new :class:`AsyncMock` object.
If the outcome of ``side_effect`` or ``return_value`` is an async function,
the mock async function obtained when the mock object is called will be this
async function itself (and not an async function returning an async
function).
The test author can also specify a wrapped object with ``wraps``. In this
case, the :class:`Mock` object behavior is the same as with an
:class:`.Mock` object: the wrapped object may have methods
defined as async function functions.
Based on Martin Richard's asynctest project.
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A tuple for holding the results of a call to a mock, either in the form
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_Call(('name', (), {})) == ('name',)
_Call(('name', (1,), {})) == ('name', (1,))
_Call(((), {'a': 'b'})) == ({'a': 'b'},)
The `_Call` object provides a useful shortcut for comparing with call::
_Call(((1, 2), {'a': 3})) == call(1, 2, a=3)
_Call(('foo', (1, 2), {'a': 3})) == call.foo(1, 2, a=3)
If the _Call has no name then it will match any name.
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||d t|tr^t | | | q^| S )aI Create a mock object using another object as a spec. Attributes on the
mock will use the corresponding attribute on the `spec` object as their
spec.
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to check that they are called with the correct signature.
If `spec_set` is True then attempting to set attributes that don't exist
on the spec object will raise an `AttributeError`.
If a class is used as a spec then the return value of the mock (the
instance of the class) will have the same spec. You can use a class as the
spec for an instance object by passing `instance=True`. The returned mock
will only be callable if instances of the mock are callable.
`create_autospec` also takes arbitrary keyword arguments that are passed to
the constructor of the created mock.r r NTr zJInstance can not be True when create_autospec is mocking an async functionr r )r r r r rv r )rK rz r r )r r r r )rJ ) r[ r1 r$ r. rk r r' Zisdatadescriptor RuntimeErrorr rX r r` r r6 ri r rL r~ r rv r r r& r: r r5
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Return whether we should skip the first argument on spec's `entry`
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A helper function to create a mock to replace the use of `open`. It works
for `open` called directly or used as a context manager.
The `mock` argument is the mock object to configure. If `None` (the
default) then a `MagicMock` will be created for you, with the API limited
to methods or attributes available on standard file handles.
`read_data` is a string for the `read`, `readline` and `readlines` of the
file handle to return. This is an empty string by default.
Nc s( j jd urj jS d j | i |S r ) readlinesrv ra _statehandler r _readlines_side_effect
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A mock intended to be used as a property, or other descriptor, on a class.
`PropertyMock` provides `__get__` and `__set__` methods so you can specify
a return value when it is fetched.
Fetching a `PropertyMock` instance from an object calls the mock, with
no args. Setting it calls the mock with the value being set.
c K s t f i |S r/ )r )rA rC r r r r s z PropertyMock._get_child_mockNc C s | S r/ r )rA r) Zobj_typer r r r s zPropertyMock.__get__c C s | | d S r/ r )rA r) r r r r r ! s zPropertyMock.__set__)N)rM rP r rN r r r r r r r r s
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Given an input Mock, seals it to ensure no further mocks will be generated
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Wraps an iterator in an asynchronous iterator.
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