text: 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
  
  
  def try_iter_content(types, depth=0):
      """Helper method for static analysis."""
      if depth > 10:
          # It's possible that a loop has references on itself (especially with
          # CompiledObject). Therefore don't loop infinitely.
          return
  
      for typ in types:
          try:
              f = typ.py__iter__
          except AttributeError:
              pass
          else:
              for iter_types in f():
                  try_iter_content(iter_types, depth + 1)
  
  
  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') or (
                      # in python 3.5 **arg is an argument, not arglist
                      (tree.is_node(self.argument_node, 'argument') and
                       self.argument_node.children[0] in ('*', '**')))):
                  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)
                  elif tree.is_node(child, 'argument') and \
                          child.children[0] in ('*', '**'):
                      assert len(child.children) == 2
                      yield len(child.children[0].value), child.children[1]
                  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 = list(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 = set(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
  
      def eval_all(self, func=None):
          """
          Evaluates all arguments as a support for static analysis
          (normally Jedi).
          """
          for key, element_values in self.unpack():
              for element in element_values:
                  types = self._evaluator.eval_element(element)
                  try_iter_content(types)
  
  
  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 = set()
          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):
          # TODO ._items is not the call we want here. Replace in the future.
          for node in array._items():
              yield node
      elif isinstance(array, iterable.Generator):
          for types in array.py__iter__():
              yield iterable.AlreadyEvaluated(types)
      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, value in array._items():
              for key in evaluator.eval_element(key_node):
                  if precedence.is_string(key):
                      dct[key.obj].append(value)
  
      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))
  