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):
if stars == 1:
lazy_contexts = []
for key, argument in iterator:
if key is not None:
iterator.push_back((key, argument))
break
lazy_contexts.append(argument)
yield ContextSet([iterable.FakeSequence(evaluator, u'tuple', lazy_contexts)])
lazy_contexts
continue
elif stars == 2:
raise NotImplementedError()
key, argument = next(iterator, (None, None))
if key is not None:
debug.warning('Keyword arguments in argument clinic are currently not supported.')
raise ParamIssue
if argument is None and not optional:
debug.warning('TypeError: %s expected at least %s arguments, got %s',
name, len(parameters), i)
raise ParamIssue
context_set = NO_CONTEXTS if argument is None else argument.infer()
if not context_set and not optional:
# For the stdlib we always want values. If we don't get them,
# that's ok, maybe something is too hard to resolve, however,
# we will not proceed with the evaluation of that function.
debug.warning('argument_clinic "%s" not resolvable.', name)
raise ParamIssue
yield context_set
def _create_default_param(execution_context, param):
if param.star_count == 1:
result_arg = LazyKnownContext(
iterable.FakeSequence(execution_context.evaluator, u'tuple', []))
elif param.star_count == 2:
result_arg = LazyKnownContext(
iterable.FakeDict(execution_context.evaluator, {}))
elif param.default is None:
result_arg = LazyUnknownContext()
else:
result_arg = LazyTreeContext(execution_context.parent_context,
param.default)
return ExecutedParam(execution_context, param, result_arg)
def py__call__(self, item_context_set):
context_set = NO_CONTEXTS
for args_context in self._args_context_set:
lazy_contexts = list(args_context.py__iter__())
if len(lazy_contexts) == 1:
# TODO we need to add the contextualized context.
context_set |= item_context_set.get_item(lazy_contexts[0].infer(), None)
else:
context_set |= ContextSet([iterable.FakeSequence(
self._wrapped_context.evaluator,
'list',
[
LazyKnownContexts(item_context_set.get_item(lazy_context.infer(), None))
for lazy_context in lazy_contexts
],
)])
return context_set
def builtins_reversed(evaluator, 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.
key, lazy_context = next(arguments.unpack())
cn = None
if isinstance(lazy_context, LazyTreeContext):
# TODO access private
cn = ContextualizedNode(lazy_context._context, lazy_context.data)
ordered = list(sequences.iterate(cn))
rev = list(reversed(ordered))
# Repack iterator values and then run it the normal way. This is
# 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)
arguments = ValuesArguments([ContextSet(seq)])
return ContextSet(CompiledInstance(evaluator, evaluator.builtins_module, obj, arguments))
def get_params(execution_context, var_args):
result_params = []
param_dict = {}
funcdef = execution_context.tree_node
parent_context = execution_context.parent_context
for param in funcdef.get_params():
param_dict[param.name.value] = param
unpacked_va = list(var_args.unpack(funcdef))
var_arg_iterator = PushBackIterator(iter(unpacked_va))
non_matching_keys = defaultdict(lambda: [])
keys_used = {}
keys_only = False
had_multiple_value_error = False
for param in funcdef.get_params():
# The value and key can both be null. There, the defaults apply.
# args / kwargs will just be empty arrays / dicts, respectively.
# Wrong value count is just ignored. If you try to test cases that are
# not allowed in Python, Jedi will maybe not show any completions.
key, argument = next(var_arg_iterator, (None, None))
while key is not None:
keys_only = True
try:
key_param = param_dict[key]
except KeyError:
non_matching_keys[key] = argument
else:
if key in keys_used:
had_multiple_value_error = True
m = (
"TypeError: %s() got multiple values for keyword argument '%s'."
% (funcdef.name, key))
for node in var_args.get_calling_nodes():
analysis.add(parent_context,
'type-error-multiple-values',
node,
message=m)
else:
keys_used[key] = ExecutedParam(execution_context,
key_param, argument)
key, argument = next(var_arg_iterator, (None, None))
try:
result_params.append(keys_used[param.name.value])
continue
except KeyError:
pass
if param.star_count == 1:
# *args param
lazy_context_list = []
if argument is not None:
lazy_context_list.append(argument)
for key, argument in var_arg_iterator:
# Iterate until a key argument is found.
if key:
var_arg_iterator.push_back((key, argument))
break
lazy_context_list.append(argument)
seq = iterable.FakeSequence(execution_context.evaluator, u'tuple',
lazy_context_list)
result_arg = LazyKnownContext(seq)
elif param.star_count == 2:
# **kwargs param
dct = iterable.FakeDict(execution_context.evaluator,
dict(non_matching_keys))
result_arg = LazyKnownContext(dct)
non_matching_keys = {}
else:
# normal param
if argument is None:
# No value: Return an empty container
if param.default is None:
result_arg = LazyUnknownContext()
if not keys_only:
for node in var_args.get_calling_nodes():
m = _error_argument_count(funcdef,
len(unpacked_va))
analysis.add(parent_context,
'type-error-too-few-arguments',
node,
message=m)
else:
result_arg = LazyTreeContext(parent_context, param.default)
else:
result_arg = argument
result_params.append(
ExecutedParam(execution_context, param, result_arg))
if not isinstance(result_arg, LazyUnknownContext):
keys_used[param.name.value] = result_params[-1]
if keys_only:
# All arguments should be handed over to the next function. It's not
# about the values inside, it's about the names. Jedi needs to now that
# there's nothing to find for certain names.
for k in set(param_dict) - set(keys_used):
param = param_dict[k]
if not (non_matching_keys or had_multiple_value_error
or param.star_count or param.default):
# add a warning only if there's not another one.
for node in var_args.get_calling_nodes():
m = _error_argument_count(funcdef, len(unpacked_va))
analysis.add(parent_context,
'type-error-too-few-arguments',
node,
message=m)
for key, lazy_context in non_matching_keys.items():
m = "TypeError: %s() got an unexpected keyword argument '%s'." \
% (funcdef.name, key)
_add_argument_issue(parent_context,
'type-error-keyword-argument',
lazy_context,
message=m)
remaining_arguments = list(var_arg_iterator)
if remaining_arguments:
m = _error_argument_count(funcdef, len(unpacked_va))
# Just report an error for the first param that is not needed (like
# cPython).
first_key, lazy_context = remaining_arguments[0]
if var_args.get_calling_nodes():
# There might not be a valid calling node so check for that first.
_add_argument_issue(parent_context,
'type-error-too-many-arguments',
lazy_context,
message=m)
return result_params
