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


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, context, argument_node, trailer):
        """
        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._context = context
        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(self._context, 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(self._context, 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(self._context, 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(self._context, 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(self._context, 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(self._context, 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
        self.string_name = self._original_param.name.value

    def infer(self, evaluator):
        types = set()
        for v in self._values:
            # TODO this context selection seems wrong. Fix it once we change
            # the way executed params work.
            types |= evaluator.eval_element(self.var_args._context, 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

    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):
    result_params = []
    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:
                result_params.append(ExecutedParam(key_param, var_args, va_values))

            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] = result_params[-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):
            result_params.append(ExecutedParam(param, var_args, values))
            keys_used[unicode(param.name)] = 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]
            values = [] if param.default is None else [param.default]
            result_params.append(ExecutedParam(param, var_args, values))

            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 result_params


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))