def register_testcases(metafunc, argnames, argvals):
"""
Add custom parametrization test cases. Based on metafunc's parametrize method.
"""
from _pytest.python import CallSpec2, _find_parametrized_scope
from _pytest.mark import ParameterSet
from _pytest.fixtures import scope2index
parameter_sets = [ParameterSet(values=val, marks=[], id=None) for val in argvals]
metafunc._validate_if_using_arg_names(argnames, False)
arg_value_types = metafunc._resolve_arg_value_types(argnames, False)
ids = [testcase_id(param_set) for param_set in parameter_sets]
scope = _find_parametrized_scope(argnames, metafunc._arg2fixturedefs, False)
scopenum = scope2index(scope, descr=f"parametrizex() call in {metafunc.function.__name__}")
calls = []
for callspec in metafunc._calls or [CallSpec2(metafunc)]:
for param_index, (param_id, param_set) in enumerate(zip(ids, parameter_sets)):
newcallspec = callspec.copy()
newcallspec.setmulti2(
arg_value_types,
argnames,
param_set.values,
param_id,
param_set.marks,
scopenum,
param_index,
)
calls.append(newcallspec)
metafunc._calls = calls
def test_parameterset_extractfrom(argval, expected):
from _pytest.deprecated import MARK_PARAMETERSET_UNPACKING
warn_called = []
class DummyItem:
def warn(self, warning):
warn_called.append(warning)
extracted = ParameterSet.extract_from(argval, belonging_definition=DummyItem())
assert extracted == expected
assert warn_called == [MARK_PARAMETERSET_UNPACKING]
def test_parameterset_extractfrom(argval, expected):
from _pytest.deprecated import MARK_PARAMETERSET_UNPACKING
warn_called = []
class DummyItem:
def warn(self, warning):
warn_called.append(warning)
extracted = ParameterSet.extract_from(argval, belonging_definition=DummyItem())
assert extracted == expected
assert warn_called == [MARK_PARAMETERSET_UNPACKING]
def _fixture_ids(self, fixturename):
fixturedef = self.fixture_definition(fixturename)
metafunc = self.context_item._pyfuncitem.callspec.metafunc
# TODO figure out how to avoid using internal things
try:
argnames, parameters = ParameterSet._for_parametrize(
fixturedef.argname,
fixturedef.params,
metafunc.function,
self.config,
function_definition=metafunc.definition,
)
except TypeError:
argnames, parameters = ParameterSet._for_parametrize(
fixturedef.argname,
fixturedef.params,
metafunc.function,
self.config,
nodeid=self.context_item.nodeid,
)
try:
ids = metafunc._resolve_arg_ids(
argnames,
fixturedef.ids,
parameters,
item=self.context_item,
)
except TypeError:
ids = metafunc._resolve_arg_ids(
argnames,
fixturedef.ids,
parameters,
nodeid=self.context_item.nodeid,
)
return ids
def param(
*values: _T,
marks: Union[MarkDecorator, Collection[Union[MarkDecorator, Mark]]] = (),
id: Optional[str] = None, # noqa: A002 # pylint: disable=redefined-builtin
idx: Optional[int] = None,
key: Optional[Callable[[Tuple[_T, ...]], str]] = None,
) -> ParameterSet:
r"""
Specify a parameter in `pytest.mark.parametrize <https://docs.pytest.org/en/stable/parametrize.html>`__
calls or :ref:`parametrized fixtures <fixture-parametrize-marks>`.
**Examples:**
.. code-block:: python
@pytest.mark.parametrize("test_input, expected", [
("3+5", 8),
param("6*9", 42, marks=pytest.mark.xfail),
param("2**2", 4, idx=0),
param("3**2", 9, id="3^2"),
param("sqrt(9)", 3, key=itemgetter(0)),
])
def test_eval(test_input, expected):
assert eval (test_input) == expected
.. versionadded:: 0.4.0
:param \*values: Variable args of the values of the parameter set, in order.
:param marks: A single mark or a list of marks to be applied to this parameter set.
:param id: The id to attribute to this parameter set.
:param idx: The index of the value in ``*values`` to use as the id.
:param key: A callable which is given ``values`` (as a :class:`tuple`) and returns the value to use as the id.
:rtype:
.. clearpage::
""" # noqa: D400
if len([x for x in (id, idx, key) if x is not None]) > 1:
raise ValueError("'id', 'idx' and 'key' are mutually exclusive.")
if idx is not None:
# pytest will catch the type error later on
id = cast(str, values[idx]) # noqa: A001 # pylint: disable=redefined-builtin
elif key is not None:
id = key(values) # noqa: A001 # pylint: disable=redefined-builtin
return ParameterSet.param(*values, marks=marks, id=id)
def test_parameterset_extractfrom(argval, expected):
extracted = ParameterSet.extract_from(argval)
assert extracted == expected
def assert_test_is_not_selected(keyword):
reprec = testdir.inline_run("-k", keyword, p)
passed, skipped, failed = reprec.countoutcomes()
dlist = reprec.getcalls("pytest_deselected")
assert passed + skipped + failed == 0
deselected_tests = dlist[0].items
assert len(deselected_tests) == 1
assert_test_is_not_selected("__")
assert_test_is_not_selected("()")
@pytest.mark.parametrize('argval, expected', [
(pytest.mark.skip()(
(1, 2)), ParameterSet(values=(1, 2), marks=[pytest.mark.skip],
id=None)),
(pytest.mark.xfail(pytest.mark.skip()((1, 2))),
ParameterSet(
values=(1, 2), marks=[pytest.mark.xfail, pytest.mark.skip], id=None)),
])
@pytest.mark.filterwarnings('ignore')
def test_parameterset_extractfrom(argval, expected):
extracted = ParameterSet.extract_from(argval)
assert extracted == expected
def test_legacy_transfer():
class FakeModule(object):
pytestmark = []
class FakeClass(object):
def parametrize(self, argnames, argvalues, indirect=False, ids=None, scope=None):
""" Add new invocations to the underlying test function using the list
of argvalues for the given argnames. Parametrization is performed
during the collection phase. If you need to setup expensive resources
see about setting indirect to do it rather at test setup time.
:arg argnames: a comma-separated string denoting one or more argument
names, or a list/tuple of argument strings.
:arg argvalues: The list of argvalues determines how often a
test is invoked with different argument values. If only one
argname was specified argvalues is a list of values. If N
argnames were specified, argvalues must be a list of N-tuples,
where each tuple-element specifies a value for its respective
argname.
:arg indirect: The list of argnames or boolean. A list of arguments'
names (subset of argnames). If True the list contains all names from
the argnames. Each argvalue corresponding to an argname in this list will
be passed as request.param to its respective argname fixture
function so that it can perform more expensive setups during the
setup phase of a test rather than at collection time.
:arg ids: list of string ids, or a callable.
If strings, each is corresponding to the argvalues so that they are
part of the test id. If None is given as id of specific test, the
automatically generated id for that argument will be used.
If callable, it should take one argument (a single argvalue) and return
a string or return None. If None, the automatically generated id for that
argument will be used.
If no ids are provided they will be generated automatically from
the argvalues.
:arg scope: if specified it denotes the scope of the parameters.
The scope is used for grouping tests by parameter instances.
It will also override any fixture-function defined scope, allowing
to set a dynamic scope using test context or configuration.
"""
from _pytest.fixtures import scope2index
from _pytest.mark import ParameterSet
from py.io import saferepr
argnames, parameters = ParameterSet._for_parametrize(
argnames, argvalues, self.function, self.config
)
del argvalues
default_arg_names = set(get_default_arg_names(self.function))
if scope is None:
scope = _find_parametrized_scope(argnames, self._arg2fixturedefs, indirect)
scopenum = scope2index(scope, descr="call to {}".format(self.parametrize))
valtypes = {}
for arg in argnames:
if arg not in self.fixturenames:
if arg in default_arg_names:
raise ValueError(
"%r already takes an argument %r with a default value"
% (self.function, arg)
)
else:
if isinstance(indirect, (tuple, list)):
name = "fixture" if arg in indirect else "argument"
else:
name = "fixture" if indirect else "argument"
raise ValueError("%r uses no %s %r" % (self.function, name, arg))
if indirect is True:
valtypes = dict.fromkeys(argnames, "params")
elif indirect is False:
valtypes = dict.fromkeys(argnames, "funcargs")
elif isinstance(indirect, (tuple, list)):
valtypes = dict.fromkeys(argnames, "funcargs")
for arg in indirect:
if arg not in argnames:
raise ValueError(
"indirect given to %r: fixture %r doesn't exist"
% (self.function, arg)
)
valtypes[arg] = "params"
idfn = None
if callable(ids):
idfn = ids
ids = None
if ids:
if len(ids) != len(parameters):
raise ValueError(
"%d tests specified with %d ids" % (len(parameters), len(ids))
)
for id_value in ids:
if id_value is not None and not isinstance(id_value, six.string_types):
msg = "ids must be list of strings, found: %s (type: %s)"
raise ValueError(
msg % (saferepr(id_value), type(id_value).__name__)
)
ids = idmaker(argnames, parameters, idfn, ids, self.config)
newcalls = []
for callspec in self._calls or [CallSpec2(self)]:
elements = zip(ids, parameters, count())
for a_id, param, param_index in elements:
if len(param.values) != len(argnames):
raise ValueError(
'In "parametrize" the number of values ({}) must be '
"equal to the number of names ({})".format(
param.values, argnames
)
)
newcallspec = callspec.copy()
newcallspec.setmulti2(
valtypes,
argnames,
param.values,
a_id,
param.marks,
scopenum,
param_index,
)
newcalls.append(newcallspec)
self._calls = newcalls
def parametrize(self, argnames, argvalues, indirect=False, ids=None,
scope=None):
""" Add new invocations to the underlying test function using the list
of argvalues for the given argnames. Parametrization is performed
during the collection phase. If you need to setup expensive resources
see about setting indirect to do it rather at test setup time.
:arg argnames: a comma-separated string denoting one or more argument
names, or a list/tuple of argument strings.
:arg argvalues: The list of argvalues determines how often a
test is invoked with different argument values. If only one
argname was specified argvalues is a list of values. If N
argnames were specified, argvalues must be a list of N-tuples,
where each tuple-element specifies a value for its respective
argname.
:arg indirect: The list of argnames or boolean. A list of arguments'
names (subset of argnames). If True the list contains all names from
the argnames. Each argvalue corresponding to an argname in this list will
be passed as request.param to its respective argname fixture
function so that it can perform more expensive setups during the
setup phase of a test rather than at collection time.
:arg ids: list of string ids, or a callable.
If strings, each is corresponding to the argvalues so that they are
part of the test id. If None is given as id of specific test, the
automatically generated id for that argument will be used.
If callable, it should take one argument (a single argvalue) and return
a string or return None. If None, the automatically generated id for that
argument will be used.
If no ids are provided they will be generated automatically from
the argvalues.
:arg scope: if specified it denotes the scope of the parameters.
The scope is used for grouping tests by parameter instances.
It will also override any fixture-function defined scope, allowing
to set a dynamic scope using test context or configuration.
"""
from _pytest.fixtures import scope2index
from _pytest.mark import ParameterSet
from py.io import saferepr
argnames, parameters = ParameterSet._for_parameterize(
argnames, argvalues, self.function)
del argvalues
if scope is None:
scope = _find_parametrized_scope(argnames, self._arg2fixturedefs, indirect)
scopenum = scope2index(scope, descr='call to {0}'.format(self.parametrize))
valtypes = {}
for arg in argnames:
if arg not in self.fixturenames:
if isinstance(indirect, (tuple, list)):
name = 'fixture' if arg in indirect else 'argument'
else:
name = 'fixture' if indirect else 'argument'
raise ValueError(
"%r uses no %s %r" % (
self.function, name, arg))
if indirect is True:
valtypes = dict.fromkeys(argnames, "params")
elif indirect is False:
valtypes = dict.fromkeys(argnames, "funcargs")
elif isinstance(indirect, (tuple, list)):
valtypes = dict.fromkeys(argnames, "funcargs")
for arg in indirect:
if arg not in argnames:
raise ValueError("indirect given to %r: fixture %r doesn't exist" % (
self.function, arg))
valtypes[arg] = "params"
idfn = None
if callable(ids):
idfn = ids
ids = None
if ids:
if len(ids) != len(parameters):
raise ValueError('%d tests specified with %d ids' % (
len(parameters), len(ids)))
for id_value in ids:
if id_value is not None and not isinstance(id_value, six.string_types):
msg = 'ids must be list of strings, found: %s (type: %s)'
raise ValueError(msg % (saferepr(id_value), type(id_value).__name__))
ids = idmaker(argnames, parameters, idfn, ids, self.config)
newcalls = []
for callspec in self._calls or [CallSpec2(self)]:
elements = zip(ids, parameters, count())
for a_id, param, param_index in elements:
if len(param.values) != len(argnames):
raise ValueError(
'In "parametrize" the number of values ({0}) must be '
'equal to the number of names ({1})'.format(
param.values, argnames))
newcallspec = callspec.copy(self)
newcallspec.setmulti2(valtypes, argnames, param.values, a_id,
param.marks, scopenum, param_index)
newcalls.append(newcallspec)
self._calls = newcalls
def parametrize(self,
argnames,
argvalues,
indirect=False,
ids=None,
scope=None):
""" Add new invocations to the underlying test function using the list
of argvalues for the given argnames. Parametrization is performed
during the collection phase. If you need to setup expensive resources
see about setting indirect to do it rather at test setup time.
:arg argnames: a comma-separated string denoting one or more argument
names, or a list/tuple of argument strings.
:arg argvalues: The list of argvalues determines how often a
test is invoked with different argument values. If only one
argname was specified argvalues is a list of values. If N
argnames were specified, argvalues must be a list of N-tuples,
where each tuple-element specifies a value for its respective
argname.
:arg indirect: The list of argnames or boolean. A list of arguments'
names (subset of argnames). If True the list contains all names from
the argnames. Each argvalue corresponding to an argname in this list will
be passed as request.param to its respective argname fixture
function so that it can perform more expensive setups during the
setup phase of a test rather than at collection time.
:arg ids: list of string ids, or a callable.
If strings, each is corresponding to the argvalues so that they are
part of the test id. If None is given as id of specific test, the
automatically generated id for that argument will be used.
If callable, it should take one argument (a single argvalue) and return
a string or return None. If None, the automatically generated id for that
argument will be used.
If no ids are provided they will be generated automatically from
the argvalues.
:arg scope: if specified it denotes the scope of the parameters.
The scope is used for grouping tests by parameter instances.
It will also override any fixture-function defined scope, allowing
to set a dynamic scope using test context or configuration.
"""
from _pytest.fixtures import scope2index
from _pytest.mark import MARK_GEN, ParameterSet
from py.io import saferepr
if not isinstance(argnames, (tuple, list)):
argnames = [x.strip() for x in argnames.split(",") if x.strip()]
force_tuple = len(argnames) == 1
else:
force_tuple = False
parameters = [
ParameterSet.extract_from(x, legacy_force_tuple=force_tuple)
for x in argvalues
]
del argvalues
if not parameters:
fs, lineno = getfslineno(self.function)
reason = "got empty parameter set %r, function %s at %s:%d" % (
argnames, self.function.__name__, fs, lineno)
mark = MARK_GEN.skip(reason=reason)
parameters.append(
ParameterSet(
values=(NOTSET, ) * len(argnames),
marks=[mark],
id=None,
))
if scope is None:
scope = _find_parametrized_scope(argnames, self._arg2fixturedefs,
indirect)
scopenum = scope2index(scope,
descr='call to {0}'.format(self.parametrize))
valtypes = {}
for arg in argnames:
if arg not in self.fixturenames:
if isinstance(indirect, (tuple, list)):
name = 'fixture' if arg in indirect else 'argument'
else:
name = 'fixture' if indirect else 'argument'
raise ValueError("%r uses no %s %r" %
(self.function, name, arg))
if indirect is True:
valtypes = dict.fromkeys(argnames, "params")
elif indirect is False:
valtypes = dict.fromkeys(argnames, "funcargs")
elif isinstance(indirect, (tuple, list)):
valtypes = dict.fromkeys(argnames, "funcargs")
for arg in indirect:
if arg not in argnames:
raise ValueError(
"indirect given to %r: fixture %r doesn't exist" %
(self.function, arg))
valtypes[arg] = "params"
idfn = None
if callable(ids):
idfn = ids
ids = None
if ids:
if len(ids) != len(parameters):
raise ValueError('%d tests specified with %d ids' %
(len(parameters), len(ids)))
for id_value in ids:
if id_value is not None and not isinstance(
id_value, py.builtin._basestring):
msg = 'ids must be list of strings, found: %s (type: %s)'
raise ValueError(
msg % (saferepr(id_value), type(id_value).__name__))
ids = idmaker(argnames, parameters, idfn, ids, self.config)
newcalls = []
for callspec in self._calls or [CallSpec2(self)]:
elements = zip(ids, parameters, count())
for a_id, param, param_index in elements:
if len(param.values) != len(argnames):
raise ValueError(
'In "parametrize" the number of values ({0}) must be '
'equal to the number of names ({1})'.format(
param.values, argnames))
newcallspec = callspec.copy(self)
newcallspec.setmulti(valtypes, argnames, param.values, a_id,
param.deprecated_arg_dict, scopenum,
param_index)
newcalls.append(newcallspec)
self._calls = newcalls
def parametrize(self, argnames, argvalues, indirect=False, ids=None, scope=None):
""" Add new invocations to the underlying test function using the list
of argvalues for the given argnames. Parametrization is performed
during the collection phase. If you need to setup expensive resources
see about setting indirect to do it rather at test setup time.
:arg argnames: a comma-separated string denoting one or more argument
names, or a list/tuple of argument strings.
:arg argvalues: The list of argvalues determines how often a
test is invoked with different argument values. If only one
argname was specified argvalues is a list of values. If N
argnames were specified, argvalues must be a list of N-tuples,
where each tuple-element specifies a value for its respective
argname.
:arg indirect: The list of argnames or boolean. A list of arguments'
names (subset of argnames). If True the list contains all names from
the argnames. Each argvalue corresponding to an argname in this list will
be passed as request.param to its respective argname fixture
function so that it can perform more expensive setups during the
setup phase of a test rather than at collection time.
:arg ids: list of string ids, or a callable.
If strings, each is corresponding to the argvalues so that they are
part of the test id. If None is given as id of specific test, the
automatically generated id for that argument will be used.
If callable, it should take one argument (a single argvalue) and return
a string or return None. If None, the automatically generated id for that
argument will be used.
If no ids are provided they will be generated automatically from
the argvalues.
:arg scope: if specified it denotes the scope of the parameters.
The scope is used for grouping tests by parameter instances.
It will also override any fixture-function defined scope, allowing
to set a dynamic scope using test context or configuration.
"""
from _pytest.fixtures import scope2index
from _pytest.mark import ParameterSet
argnames, parameters = ParameterSet._for_parametrize(
argnames,
argvalues,
self.function,
self.config,
function_definition=self.definition,
)
del argvalues
if scope is None:
scope = _find_parametrized_scope(argnames, self._arg2fixturedefs, indirect)
self._validate_if_using_arg_names(argnames, indirect)
arg_values_types = self._resolve_arg_value_types(argnames, indirect)
ids = self._resolve_arg_ids(argnames, ids, parameters, item=self.definition)
scopenum = scope2index(
scope, descr="parametrize() call in {}".format(self.function.__name__)
)
# create the new calls: if we are parametrize() multiple times (by applying the decorator
# more than once) then we accumulate those calls generating the cartesian product
# of all calls
newcalls = []
for callspec in self._calls or [CallSpec2(self)]:
for param_index, (param_id, param_set) in enumerate(zip(ids, parameters)):
newcallspec = callspec.copy()
newcallspec.setmulti2(
arg_values_types,
argnames,
param_set.values,
param_id,
param_set.marks,
scopenum,
param_index,
)
newcalls.append(newcallspec)
self._calls = newcalls
def test_parameterset_extractfrom(argval, expected):
extracted = ParameterSet.extract_from(argval)
assert extracted == expected
def parametrize(self, argnames, argvalues, indirect=False, ids=None, scope=None):
""" Add new invocations to the underlying test function using the list
of argvalues for the given argnames. Parametrization is performed
during the collection phase. If you need to setup expensive resources
see about setting indirect to do it rather at test setup time.
:arg argnames: a comma-separated string denoting one or more argument
names, or a list/tuple of argument strings.
:arg argvalues: The list of argvalues determines how often a
test is invoked with different argument values. If only one
argname was specified argvalues is a list of values. If N
argnames were specified, argvalues must be a list of N-tuples,
where each tuple-element specifies a value for its respective
argname.
:arg indirect: The list of argnames or boolean. A list of arguments'
names (subset of argnames). If True the list contains all names from
the argnames. Each argvalue corresponding to an argname in this list will
be passed as request.param to its respective argname fixture
function so that it can perform more expensive setups during the
setup phase of a test rather than at collection time.
:arg ids: list of string ids, or a callable.
If strings, each is corresponding to the argvalues so that they are
part of the test id. If None is given as id of specific test, the
automatically generated id for that argument will be used.
If callable, it should take one argument (a single argvalue) and return
a string or return None. If None, the automatically generated id for that
argument will be used.
If no ids are provided they will be generated automatically from
the argvalues.
:arg scope: if specified it denotes the scope of the parameters.
The scope is used for grouping tests by parameter instances.
It will also override any fixture-function defined scope, allowing
to set a dynamic scope using test context or configuration.
"""
from _pytest.fixtures import scope2index
from _pytest.mark import ParameterSet
argnames, parameters = ParameterSet._for_parametrize(
argnames, argvalues, self.function, self.config
)
del argvalues
if scope is None:
scope = _find_parametrized_scope(argnames, self._arg2fixturedefs, indirect)
self._validate_if_using_arg_names(argnames, indirect)
arg_values_types = self._resolve_arg_value_types(argnames, indirect)
ids = self._resolve_arg_ids(argnames, ids, parameters)
scopenum = scope2index(scope, descr="call to {}".format(self.parametrize))
# create the new calls: if we are parametrize() multiple times (by applying the decorator
# more than once) then we accumulate those calls generating the cartesian product
# of all calls
newcalls = []
for callspec in self._calls or [CallSpec2(self)]:
for param_index, (param_id, param_set) in enumerate(zip(ids, parameters)):
newcallspec = callspec.copy()
newcallspec.setmulti2(
arg_values_types,
argnames,
param_set.values,
param_id,
param_set.marks,
scopenum,
param_index,
)
newcalls.append(newcallspec)
self._calls = newcalls