def builtins_reversed(evaluator, sequences, obj):
# Unpack the iterator values
objects = tuple(iterable.get_iterator_types(sequences))
rev = [iterable.AlreadyEvaluated([o]) for o in reversed(objects)]
# 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.
rev = iterable.AlreadyEvaluated(
[iterable.FakeSequence(evaluator, rev, 'list')])
return [er.Instance(evaluator, obj, param.Arguments(evaluator, [rev]))]
def create_default_param(parent_context, param):
if param.stars == 1:
result_arg = context.LazyKnownContext(
iterable.FakeSequence(parent_context.evaluator, 'tuple', []))
elif param.stars == 2:
result_arg = context.LazyKnownContext(
iterable.FakeDict(parent_context.evaluator, {}))
elif param.default is None:
result_arg = context.LazyUnknownContext()
else:
result_arg = context.LazyTreeContext(parent_context, param.default)
return ExecutedParam(parent_context, param, None, result_arg)
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.
first_arg = next(arguments.as_tuple())[0]
ordered = list(iterable.py__iter__(evaluator, sequences, first_arg))
rev = [iterable.AlreadyEvaluated(o) for o in 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.
rev = iterable.AlreadyEvaluated(
[iterable.FakeSequence(evaluator, rev, 'list')]
)
return set([er.Instance(evaluator, obj, param.Arguments(evaluator, [rev]))])
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())
ordered = list(iterable.py__iter__(evaluator, sequences,
lazy_context.data))
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, 'list', rev)
arguments = param.ValuesArguments([[seq]])
return set(
[CompiledInstance(evaluator, evaluator.BUILTINS, 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.params:
param_dict[param.name.value] = param
unpacked_va = list(var_args.unpack(funcdef))
var_arg_iterator = common.PushBackIterator(iter(unpacked_va))
non_matching_keys = defaultdict(lambda: [])
keys_used = {}
keys_only = False
had_multiple_value_error = False
for param in funcdef.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, 'tuple', lazy_context_list)
result_arg = context.LazyKnownContext(seq)
elif param.star_count == 2:
# **kwargs param
dct = iterable.FakeDict(execution_context.evaluator, dict(non_matching_keys))
result_arg = context.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 = context.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 = context.LazyTreeContext(parent_context, param.default)
else:
result_arg = argument
result_params.append(ExecutedParam(execution_context, param, result_arg))
if not isinstance(result_arg, context.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
def get_params(evaluator, func, var_args):
param_names = []
param_dict = {}
for param in func.params:
param_dict[str(param.get_name())] = param
unpacked_va = list(var_args.unpack(func))
from jedi.evaluate.representation import InstanceElement
if isinstance(func, InstanceElement):
# Include self at this place.
unpacked_va.insert(
0, (None, [iterable.AlreadyEvaluated([func.instance])]))
var_arg_iterator = common.PushBackIterator(iter(unpacked_va))
non_matching_keys = defaultdict(lambda: [])
keys_used = {}
keys_only = False
had_multiple_value_error = False
for param in func.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.
default = [] if param.default is None else [param.default]
key, va_values = next(var_arg_iterator, (None, default))
while key is not None:
keys_only = True
k = unicode(key)
try:
key_param = param_dict[unicode(key)]
except KeyError:
non_matching_keys[key] += va_values
else:
param_names.append(
ExecutedParam(key_param, var_args, va_values).name)
if k in keys_used:
had_multiple_value_error = True
m = (
"TypeError: %s() got multiple values for keyword argument '%s'."
% (func.name, k))
calling_va = _get_calling_var_args(evaluator, var_args)
if calling_va is not None:
analysis.add(evaluator,
'type-error-multiple-values',
calling_va,
message=m)
else:
try:
keys_used[k] = param_names[-1]
except IndexError:
# TODO this is wrong stupid and whatever.
pass
key, va_values = next(var_arg_iterator, (None, ()))
values = []
if param.stars == 1:
# *args param
lst_values = [iterable.MergedNodes(va_values)] if va_values else []
for key, va_values in var_arg_iterator:
# Iterate until a key argument is found.
if key:
var_arg_iterator.push_back((key, va_values))
break
if va_values:
lst_values.append(iterable.MergedNodes(va_values))
seq = iterable.FakeSequence(evaluator, lst_values, 'tuple')
values = [iterable.AlreadyEvaluated([seq])]
elif param.stars == 2:
# **kwargs param
dct = iterable.FakeDict(evaluator, dict(non_matching_keys))
values = [iterable.AlreadyEvaluated([dct])]
non_matching_keys = {}
else:
# normal param
if va_values:
values = va_values
else:
# No value: Return an empty container
values = []
if not keys_only:
calling_va = var_args.get_calling_var_args()
if calling_va is not None:
m = _error_argument_count(func, len(unpacked_va))
analysis.add(evaluator,
'type-error-too-few-arguments',
calling_va,
message=m)
# Now add to result if it's not one of the previously covered cases.
if (not keys_only or param.stars == 2):
param_names.append(ExecutedParam(param, var_args, values).name)
keys_used[unicode(param.get_name())] = param_names[-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]
values = [] if param.default is None else [param.default]
param_names.append(ExecutedParam(param, var_args, values).name)
if not (non_matching_keys or had_multiple_value_error
or param.stars or param.default):
# add a warning only if there's not another one.
calling_va = _get_calling_var_args(evaluator, var_args)
if calling_va is not None:
m = _error_argument_count(func, len(unpacked_va))
analysis.add(evaluator,
'type-error-too-few-arguments',
calling_va,
message=m)
for key, va_values in non_matching_keys.items():
m = "TypeError: %s() got an unexpected keyword argument '%s'." \
% (func.name, key)
for value in va_values:
analysis.add(evaluator,
'type-error-keyword-argument',
value.parent,
message=m)
remaining_params = list(var_arg_iterator)
if remaining_params:
m = _error_argument_count(func, len(unpacked_va))
# Just report an error for the first param that is not needed (like
# cPython).
first_key, first_values = remaining_params[0]
for v in first_values:
if first_key is not None:
# Is a keyword argument, return the whole thing instead of just
# the value node.
v = v.parent
try:
non_kw_param = keys_used[first_key]
except KeyError:
pass
else:
origin_args = non_kw_param.parent.var_args.argument_node
# TODO calculate the var_args tree and check if it's in
# the tree (if not continue).
# print('\t\tnonkw', non_kw_param.parent.var_args.argument_node, )
if origin_args not in [
f.parent.parent for f in first_values
]:
continue
analysis.add(evaluator,
'type-error-too-many-arguments',
v,
message=m)
return param_names
