from collections import defaultdict from itertools import chain from jedi._compatibility import unicode, zip_longest from jedi import debug from jedi import common from jedi.parser import tree from jedi.evaluate import iterable from jedi.evaluate import analysis from jedi.evaluate import precedence from jedi.evaluate.helpers import FakeName from jedi.cache import underscore_memoization class Arguments(tree.Base): def __init__(self, evaluator, argument_node, trailer=None): """ The argument_node is either a parser node or a list of evaluated objects. Those evaluated objects may be lists of evaluated objects themselves (one list for the first argument, one for the second, etc). :param argument_node: May be an argument_node or a list of nodes. """ self.argument_node = argument_node self._evaluator = evaluator self.trailer = trailer # Can be None, e.g. in a class definition. def _split(self): if isinstance(self.argument_node, (tuple, list)): for el in self.argument_node: yield 0, el else: if not tree.is_node(self.argument_node, 'arglist'): yield 0, self.argument_node return iterator = iter(self.argument_node.children) for child in iterator: if child == ',': continue elif child in ('*', '**'): yield len(child.value), next(iterator) else: yield 0, child def get_parent_until(self, *args, **kwargs): if self.trailer is None: try: element = self.argument_node[0] from jedi.evaluate.iterable import AlreadyEvaluated if isinstance(element, AlreadyEvaluated): element = self._evaluator.eval_element(element)[0] except IndexError: return None else: return element.get_parent_until(*args, **kwargs) else: return self.trailer.get_parent_until(*args, **kwargs) def as_tuple(self): for stars, argument in self._split(): if tree.is_node(argument, 'argument'): argument, default = argument.children[::2] else: default = None yield argument, default, stars def unpack(self, func=None): named_args = [] for stars, el in self._split(): if stars == 1: arrays = self._evaluator.eval_element(el) iterators = [_iterate_star_args(self._evaluator, a, el, func) for a in arrays] iterators = list(iterators) for values in list(zip_longest(*iterators)): yield None, [v for v in values if v is not None] elif stars == 2: arrays = self._evaluator.eval_element(el) dicts = [_star_star_dict(self._evaluator, a, el, func) for a in arrays] for dct in dicts: for key, values in dct.items(): yield key, values else: if tree.is_node(el, 'argument'): c = el.children if len(c) == 3: # Keyword argument. named_args.append((c[0].value, (c[2],))) else: # Generator comprehension. # Include the brackets with the parent. comp = iterable.GeneratorComprehension( self._evaluator, self.argument_node.parent) yield None, (iterable.AlreadyEvaluated([comp]),) elif isinstance(el, (list, tuple)): yield None, el else: yield None, (el,) # Reordering var_args is necessary, because star args sometimes appear # after named argument, but in the actual order it's prepended. for key_arg in named_args: yield key_arg def _reorder_var_args(var_args): named_index = None new_args = [] for i, stmt in enumerate(var_args): if isinstance(stmt, tree.ExprStmt): if named_index is None and stmt.assignment_details: named_index = i if named_index is not None: expression_list = stmt.expression_list() if expression_list and expression_list[0] == '*': new_args.insert(named_index, stmt) named_index += 1 continue new_args.append(stmt) return new_args def eval_argument_clinic(self, arguments): """Uses a list with argument clinic information (see PEP 436).""" iterator = self.unpack() for i, (name, optional, allow_kwargs) in enumerate(arguments): key, va_values = next(iterator, (None, [])) if key is not None: raise NotImplementedError if not va_values and not optional: debug.warning('TypeError: %s expected at least %s arguments, got %s', name, len(arguments), i) raise ValueError values = list(chain.from_iterable(self._evaluator.eval_element(el) for el in va_values)) if not values 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 ValueError yield values def scope(self): # Returns the scope in which the arguments are used. return (self.trailer or self.argument_node).get_parent_until(tree.IsScope) def eval_args(self): # TODO this method doesn't work with named args and a lot of other # things. Use unpack. return [self._evaluator.eval_element(el) for stars, el in self._split()] def __repr__(self): return '<%s: %s>' % (type(self).__name__, self.argument_node) def get_calling_var_args(self): if tree.is_node(self.argument_node, 'arglist', 'argument') \ or self.argument_node == () and self.trailer is not None: return _get_calling_var_args(self._evaluator, self) else: return None class ExecutedParam(tree.Param): """Fake a param and give it values.""" def __init__(self, original_param, var_args, values): self._original_param = original_param self.var_args = var_args self._values = values def eval(self, evaluator): types = [] for v in self._values: types += evaluator.eval_element(v) return types @property def position_nr(self): # Need to use the original logic here, because it uses the parent. return self._original_param.position_nr @property @underscore_memoization def name(self): return FakeName(str(self._original_param.name), self, self.start_pos) def __getattr__(self, name): return getattr(self._original_param, name) def _get_calling_var_args(evaluator, var_args): old_var_args = None while var_args != old_var_args: old_var_args = var_args for name, default, stars in reversed(list(var_args.as_tuple())): if not stars or not isinstance(name, tree.Name): continue names = evaluator.goto(name) if len(names) != 1: break param = names[0].get_definition() if not isinstance(param, ExecutedParam): if isinstance(param, tree.Param): # There is no calling var_args in this case - there's just # a param without any input. return None break # We never want var_args to be a tuple. This should be enough for # now, we can change it later, if we need to. if isinstance(param.var_args, Arguments): var_args = param.var_args return var_args.argument_node or var_args.trailer def get_params(evaluator, func, var_args): param_names = [] param_dict = {} for param in func.params: param_dict[str(param.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.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 def _iterate_star_args(evaluator, array, input_node, func=None): from jedi.evaluate.representation import Instance if isinstance(array, iterable.Array): for field_stmt in array: # yield from plz! yield field_stmt elif isinstance(array, iterable.Generator): for field_stmt in array.iter_content(): yield iterable.AlreadyEvaluated([field_stmt]) elif isinstance(array, Instance) and array.name.get_code() == 'tuple': debug.warning('Ignored a tuple *args input %s' % array) else: if func is not None: m = "TypeError: %s() argument after * must be a sequence, not %s" \ % (func.name.value, array) analysis.add(evaluator, 'type-error-star', input_node, message=m) def _star_star_dict(evaluator, array, input_node, func): dct = defaultdict(lambda: []) from jedi.evaluate.representation import Instance if isinstance(array, Instance) and array.name.get_code() == 'dict': # For now ignore this case. In the future add proper iterators and just # make one call without crazy isinstance checks. return {} if isinstance(array, iterable.FakeDict): return array._dct elif isinstance(array, iterable.Array) and array.type == 'dict': # TODO bad call to non-public API for key_node, values in array._items(): for key in evaluator.eval_element(key_node): if precedence.is_string(key): dct[key.obj] += values else: if func is not None: m = "TypeError: %s argument after ** must be a mapping, not %s" \ % (func.name.value, array) analysis.add(evaluator, 'type-error-star-star', input_node, message=m) return dict(dct) def _error_argument_count(func, actual_count): default_arguments = sum(1 for p in func.params if p.default or p.stars) if default_arguments == 0: before = 'exactly ' else: before = 'from %s to ' % (len(func.params) - default_arguments) return ('TypeError: %s() takes %s%s arguments (%s given).' % (func.name, before, len(func.params), actual_count))