Make it possible to use *args in argument clinic

This commit is contained in:
Dave Halter
2018-09-03 19:12:36 +02:00
parent 39f1dfc85e
commit 35ce54630e
2 changed files with 39 additions and 27 deletions

View File

@@ -45,23 +45,27 @@ def repack_with_argument_clinic(string, keep_arguments_param=False):
clinic_args = list(_parse_argument_clinic(string))
def decorator(func):
def wrapper(*args, **kwargs):
def wrapper(context, *args, **kwargs):
if keep_arguments_param:
arguments = kwargs['arguments']
else:
arguments = kwargs.pop('arguments')
try:
args += tuple(_iterate_argument_clinic(arguments, clinic_args))
args += tuple(_iterate_argument_clinic(
context.evaluator,
arguments,
clinic_args
))
except ValueError:
return NO_CONTEXTS
else:
return func(*args, **kwargs)
return func(context, *args, **kwargs)
return wrapper
return decorator
def _iterate_argument_clinic(arguments, parameters):
def _iterate_argument_clinic(evaluator, arguments, parameters):
"""Uses a list with argument clinic information (see PEP 436)."""
iterator = PushBackIterator(arguments.unpack())
for i, (name, optional, allow_kwargs, stars) in enumerate(parameters):

View File

@@ -66,7 +66,6 @@ class StdlibPlugin(BasePlugin):
if module_name == 'builtins' and context.py__name__() == '__get__':
if context.class_context.py__name__() == 'property':
return builtins_property(
self._evaluator,
context,
arguments=arguments
)
@@ -78,7 +77,7 @@ class StdlibPlugin(BasePlugin):
except KeyError:
pass
else:
return func(self._evaluator, context, arguments=arguments)
return func(context, arguments=arguments)
return callback(context, arguments=arguments)
return wrapper
@@ -93,14 +92,15 @@ def _follow_param(evaluator, arguments, index):
return lazy_context.infer()
def argument_clinic(string, want_obj=False, want_context=False, want_arguments=False):
def argument_clinic(string, want_obj=False, want_context=False,
want_arguments=False, want_evaluator=False):
"""
Works like Argument Clinic (PEP 436), to validate function params.
"""
def f(func):
@repack_with_argument_clinic(string, keep_arguments_param=True)
def wrapper(evaluator, obj, *args, **kwargs):
def wrapper(obj, *args, **kwargs):
arguments = kwargs.pop('arguments')
assert not kwargs # Python 2...
debug.dbg('builtin start %s' % obj, color='MAGENTA')
@@ -109,9 +109,11 @@ def argument_clinic(string, want_obj=False, want_context=False, want_arguments=F
kwargs['context'] = arguments.context
if want_obj:
kwargs['obj'] = obj
if want_evaluator:
kwargs['evaluator'] = obj.evaluator
if want_arguments:
kwargs['arguments'] = arguments
result = func(evaluator, *args, **kwargs)
result = func(*args, **kwargs)
debug.dbg('builtin end: %s', result, color='MAGENTA')
return result
@@ -120,7 +122,7 @@ def argument_clinic(string, want_obj=False, want_context=False, want_arguments=F
@argument_clinic('obj, type, /', want_obj=True, want_arguments=True)
def builtins_property(evaluator, objects, types, obj, arguments):
def builtins_property(objects, types, obj, arguments):
print(obj)
print(obj.instance.var_args)
property_args = obj.instance.var_args.unpack()
@@ -134,8 +136,8 @@ def builtins_property(evaluator, objects, types, obj, arguments):
return NO_CONTEXTS
@argument_clinic('iterator[, default], /')
def builtins_next(evaluator, iterators, defaults):
@argument_clinic('iterator[, default], /', want_evaluator=True)
def builtins_next(iterators, defaults, evaluator):
"""
TODO this function is currently not used. It's a stab at implementing next
in a different way than fake objects. This would be a bit more flexible.
@@ -159,7 +161,7 @@ def builtins_next(evaluator, iterators, defaults):
@argument_clinic('object, name[, default], /')
def builtins_getattr(evaluator, objects, names, defaults=None):
def builtins_getattr(objects, names, defaults=None):
# follow the first param
for obj in objects:
for name in names:
@@ -172,7 +174,7 @@ def builtins_getattr(evaluator, objects, names, defaults=None):
@argument_clinic('object[, bases, dict], /')
def builtins_type(evaluator, objects, bases, dicts):
def builtins_type(objects, bases, dicts):
if bases or dicts:
# It's a type creation... maybe someday...
return NO_CONTEXTS
@@ -188,7 +190,7 @@ class SuperInstance(AbstractInstanceContext):
@argument_clinic('[type[, obj]], /', want_context=True)
def builtins_super(evaluator, types, objects, context):
def builtins_super(types, objects, context):
# TODO make this able to detect multiple inheritance super
if isinstance(context, FunctionExecutionContext):
if isinstance(context.var_args, InstanceArguments):
@@ -199,7 +201,7 @@ def builtins_super(evaluator, types, objects, context):
@argument_clinic('sequence, /', want_obj=True, want_arguments=True)
def builtins_reversed(evaluator, sequences, obj, arguments):
def builtins_reversed(sequences, obj, arguments):
# While we could do without this variable (just by using sequences), we
# want static analysis to work well. Therefore we need to generated the
# values again.
@@ -215,13 +217,18 @@ def builtins_reversed(evaluator, sequences, obj, arguments):
# necessary, because `reversed` is a function and autocompletion
# would fail in certain cases like `reversed(x).__iter__` if we
# just returned the result directly.
seq = iterable.FakeSequence(evaluator, u'list', rev)
seq = iterable.FakeSequence(obj.evaluator, u'list', rev)
arguments = ValuesArguments([ContextSet(seq)])
return ContextSet(CompiledInstance(evaluator, evaluator.builtins_module, obj, arguments))
return ContextSet(CompiledInstance(
obj.evaluator,
obj.evaluator.builtins_module,
obj,
arguments
))
@argument_clinic('obj, type, /', want_arguments=True)
def builtins_isinstance(evaluator, objects, types, arguments):
@argument_clinic('obj, type, /', want_arguments=True, want_evaluator=True)
def builtins_isinstance(objects, types, arguments, evaluator):
bool_results = set()
for o in objects:
cls = o.py__class__()
@@ -262,7 +269,7 @@ def builtins_isinstance(evaluator, objects, types, arguments):
)
def collections_namedtuple(evaluator, obj, arguments):
def collections_namedtuple(obj, arguments):
"""
Implementation of the namedtuple function.
@@ -270,6 +277,7 @@ def collections_namedtuple(evaluator, obj, arguments):
evaluating the result.
"""
evaluator = obj.evaluator
collections_context = obj.parent_context
_class_template_set = collections_context.py__getattribute__(u'_class_template')
if not _class_template_set:
@@ -358,7 +366,7 @@ class MergedPartialArguments(AbstractArguments):
yield key_lazy_context
def functools_partial(evaluator, obj, arguments):
def functools_partial(obj, arguments):
return ContextSet.from_iterable(
PartialObject(instance, arguments)
for instance in obj.py__call__(arguments)
@@ -366,12 +374,12 @@ def functools_partial(evaluator, obj, arguments):
@argument_clinic('first, /')
def _return_first_param(evaluator, firsts):
def _return_first_param(firsts):
return firsts
@argument_clinic('seq')
def _random_choice(evaluator, sequences):
def _random_choice(sequences):
return ContextSet.from_sets(
lazy_context.infer()
for sequence in sequences
@@ -390,7 +398,7 @@ class ItemGetterCallable(object):
@argument_clinic('*args, /', want_obj=True, want_arguments=True)
def _operator_itemgetter(evaluator, args_context_set, obj, arguments):
def _operator_itemgetter(args_context_set, obj, arguments):
final = obj.py__call__(arguments)
print(final)
return final
@@ -410,8 +418,8 @@ _implemented = {
'deepcopy': _return_first_param,
},
'json': {
'load': lambda evaluator, obj, arguments: NO_CONTEXTS,
'loads': lambda evaluator, obj, arguments: NO_CONTEXTS,
'load': lambda obj, arguments: NO_CONTEXTS,
'loads': lambda obj, arguments: NO_CONTEXTS,
},
'collections': {
'namedtuple': collections_namedtuple,