Instruction:
Can you tell what is the following Python 3 function doing
def _add_prefix(self, split_names, start_node, group_type_name):
        root = self._root_instance

        # If the start node of our insertion is root or one below root
        # we might need to add prefixes.
        # In case of derived parameters and results we also need to add prefixes containing the
        # subbranch and the current run in case of a single run.
        # For instance, a prefix could be 'results.runs.run_00000007'.
        prepend = []
        if start_node.v_depth < 3 and not group_type_name == GROUP:
            if start_node.v_depth == 0:

                if group_type_name == DERIVED_PARAMETER_GROUP:
                    if split_names[0] == 'derived_parameters':
                        return split_names
                    else:
                        prepend += ['derived_parameters']

                elif group_type_name == RESULT_GROUP:
                    if split_names[0] == 'results':
                        return split_names
                    else:
                        prepend += ['results']

                elif group_type_name == CONFIG_GROUP:
                    if split_names[0] == 'config':
                        return split_names
                    else:
                        prepend += ['config']

                elif group_type_name == PARAMETER_GROUP:
                    if split_names[0] == 'parameters':
                        return split_names[0]
                    else:
                        prepend += ['parameters']
                else:
                    raise RuntimeError('Why are you here?')

            # Check if we have to add a prefix containing the current run
            if root._is_run and root._auto_run_prepend:
                dummy = root.f_wildcard('$', -1)
                crun = root.f_wildcard('$')
                if any(name in root._run_information for name in split_names):
                    pass
                elif any(name == dummy for name in split_names):
                    pass
                elif (group_type_name == RESULT_GROUP or
                        group_type_name == DERIVED_PARAMETER_GROUP):

                    if start_node.v_depth == 0:
                        prepend += ['runs', crun]

                    elif start_node.v_depth == 1:

                        if len(split_names) == 1 and split_names[0] == 'runs':
                            return split_names
                        else:
                            prepend += ['runs', crun]

                    elif start_node.v_depth == 2 and start_node.v_name == 'runs':
                        prepend += [crun]

        if prepend:
            split_names = prepend + split_names

        return split_names

Response: Adds the correct sub branch prefix to a given name.


Instruction:
Write a Python 3 script for
determining types for generic additions

Response:
def _determine_types(start_node, first_name, add_leaf, add_link):
        """Determines types for generic additions"""
        if start_node.v_is_root:
            where = first_name
        else:
            where = start_node._branch

        if where in SUBTREE_MAPPING:
            type_tuple = SUBTREE_MAPPING[where]
        else:
            type_tuple = (GROUP, LEAF)

        if add_link:
            return type_tuple[0], LINK
        if add_leaf:
            return type_tuple
        else:
            return type_tuple[0], type_tuple[0]


Instruction:
Can you generate the documentation for the following Python 3 function
def _add_generic(self, start_node, type_name, group_type_name, args, kwargs,
                     add_prefix=True, check_naming=True):
        """Adds a given item to the tree irrespective of the subtree.

        Infers the subtree from the arguments.

        :param start_node: The parental node the adding was initiated from

        :param type_name:

            The type of the new instance. Whether it is a parameter, parameter group, config,
            config group, etc. See the name of the corresponding constants at the top of this
            python module.

        :param group_type_name:

            Type of the subbranch. i.e. whether the item is added to the 'parameters',
            'results' etc. These subbranch types are named as the group names
            (e.g. 'PARAMETER_GROUP') in order to have less constants.
            For all constants used see beginning of this python module.

        :param args:

            Arguments specifying how the item is added.

            If len(args)==1 and the argument is the a given instance of a result or parameter,
            this one is added to the tree.

            Otherwise it is checked if the first argument is a class specifying how to
            construct a new item and the second argument is the name of the new class.

            If the first argument is not a class but a string, the string is assumed to be
            the name of the new instance.

            Additional args are later on used for the construction of the instance.

        :param kwargs:

            Additional keyword arguments that might be handed over to the instance constructor.

        :param add_prefix:

            If a prefix group, i.e. `results`, `config`, etc. should be added

        :param check_naming:

            If it should be checked for correct namings, can be set to ``False`` if data is loaded
            and we know that all names are correct.

        :return: The new added instance

        """
        args = list(args)
        create_new = True
        name = ''
        instance = None
        constructor = None

        add_link = type_name == LINK

        # First check if the item is already a given instance or we want to add a link
        if add_link:
            name = args[0]
            instance = args[1]
            create_new = False
        elif len(args) == 1 and len(kwargs) == 0:
            item = args[0]
            try:
                name = item.v_full_name
                instance = item

                create_new = False
            except AttributeError:
                pass

        # If the item is not an instance yet, check if args[0] is a class and args[1] is
        # a string describing the new name of the instance.
        # If args[0] is not a class it is assumed to be the name of the new instance.
        if create_new:
            if len(args) > 0 and inspect.isclass(args[0]):
                constructor = args.pop(0)
            if len(args) > 0 and isinstance(args[0], str):
                name = args.pop(0)
            elif 'name' in kwargs:
                name = kwargs.pop('name')
            elif 'full_name' in kwargs:
                name = kwargs.pop('full_name')
            else:
                raise ValueError('Could not determine a name of the new item you want to add. '
                                 'Either pass the name as positional argument or as a keyword '
                                 'argument `name`.')

        split_names = name.split('.')
        if check_naming:

            for idx, name in enumerate(split_names):
                translated_shortcut, name = self._translate_shortcut(name)
                replaced, name = self._replace_wildcards(name)
                if translated_shortcut or replaced:
                    split_names[idx] = name

            # First check if the naming of the new item is appropriate
            faulty_names = self._check_names(split_names, start_node)

            if faulty_names:
                full_name = '.'.join(split_names)
                raise ValueError(
                    'Your Parameter/Result/Node `%s` contains the following not admissible names: '
                    '%s please choose other names.' % (full_name, faulty_names))

            if add_link:
                if instance is None:
                    raise ValueError('You must provide an instance to link to!')
                if instance.v_is_root:
                    raise ValueError('You cannot create a link to the root node')
                if start_node.v_is_root and name in SUBTREE_MAPPING:
                    raise ValueError('`%s` is a reserved name for a group under root.' % name)
                if not self._root_instance.f_contains(instance, with_links=False, shortcuts=False):
                    raise ValueError('You can only link to items within the trajectory tree!')

        # Check if the name fulfils the prefix conditions, if not change the name accordingly.
        if add_prefix:
            split_names = self._add_prefix(split_names, start_node, group_type_name)

        if group_type_name == GROUP:
            add_leaf = type_name != group_type_name and not add_link
            # If this is equal we add a group node
            group_type_name, type_name = self._determine_types(start_node, split_names[0],
                                                               add_leaf, add_link)

        # Check if we are allowed to add the data
        if self._root_instance._is_run and type_name in SENSITIVE_TYPES:
            raise TypeError('You are not allowed to add config or parameter data or groups '
                            'during a single run.')

        return self._add_to_tree(start_node, split_names, type_name, group_type_name, instance,
                                 constructor, args, kwargs)

Response: Internal function to add a generic item to the tree.


Instruction:
Write a Python 3 script to
replace the $ wildcards and returns True or False in case it was replaced

Response:
def _replace_wildcards(self, name, run_idx=None):
        """Replaces the $ wildcards and returns True/False in case it was replaced"""
        if self._root_instance.f_is_wildcard(name):
            return True, self._root_instance.f_wildcard(name, run_idx)
        else:
            return False, name


Instruction:
Here you have a function in Python 3, explain what it does
def _add_to_tree(self, start_node, split_names, type_name, group_type_name,
                     instance, constructor, args, kwargs):
        """Adds a new item to the tree.

        The item can be an already given instance or it is created new.

        :param start_node:

            Parental node the adding of the item was initiated from.

        :param split_names:

            List of names of the new item

        :param type_name:

            Type of item 'RESULT', 'RESULT_GROUP', 'PARAMETER', etc. See name of constants
            at beginning of the python module.

        :param group_type_name:

            Name of the subbranch the item is added to 'RESULT_GROUP', 'PARAMETER_GROUP' etc.
            See name of constants at beginning of this python module.

        :param instance:

            Here an already given instance can be passed. If instance should be created new
            pass None.

        :param constructor:

            If instance should be created new pass a constructor class. If None is passed
            the standard constructor for the instance is chosen.

        :param args:

            Additional arguments passed to instance construction

        :param kwargs:

            Additional keyword arguments passed to instance construction

        :return: The new added instance

        :raises: ValueError if naming of the new item is invalid

        """

        # Then walk iteratively from the start node as specified by the new name and create
        # new empty groups on the fly
        try:
            act_node = start_node
            last_idx = len(split_names) - 1
            add_link = type_name == LINK
            link_added = False
            # last_name = start_node.v_crun
            for idx, name in enumerate(split_names):
                if name not in act_node._children:
                    if idx == last_idx:
                        if add_link:
                            new_node = self._create_link(act_node, name, instance)
                            link_added = True
                        elif group_type_name != type_name:
                            # We are at the end of the chain and we add a leaf node

                            new_node = self._create_any_param_or_result(act_node,
                                                                        name,
                                                                        type_name,
                                                                        instance,
                                                                        constructor,
                                                                        args, kwargs)

                            self._flat_leaf_storage_dict[new_node.v_full_name] = new_node
                        else:
                            # We add a group as desired
                            new_node = self._create_any_group(act_node, name,
                                                              group_type_name,
                                                              instance,
                                                              constructor,
                                                              args, kwargs)
                    else:
                        # We add a group on the fly
                        new_node = self._create_any_group(act_node, name,
                                                          group_type_name)

                    if name in self._root_instance._run_information:
                        self._root_instance._run_parent_groups[act_node.v_full_name] = act_node
                    if self._root_instance._is_run:
                        if link_added:
                            self._root_instance._new_links[(act_node.v_full_name, name)] = \
                                (act_node, new_node)
                        else:
                            self._root_instance._new_nodes[(act_node.v_full_name, name)] = \
                                (act_node, new_node)
                else:
                    if name in act_node._links:
                        raise AttributeError('You cannot hop over links when adding '
                                             'data to the tree. '
                                             'There is a link called `%s` under `%s`.' %
                                             (name, act_node.v_full_name))
                    if idx == last_idx:
                        if self._root_instance._no_clobber:
                            self._logger.warning('You already have a group/instance/link `%s` '
                                                 'under `%s`. '
                                                 'However, you set `v_no_clobber=True`, '
                                                 'so I will ignore your addition of '
                                                 'data.' % (name, act_node.v_full_name))
                        else:
                            raise AttributeError('You already have a group/instance/link `%s` '
                                                 'under `%s`' % (name, act_node.v_full_name))
                act_node = act_node._children[name]
            return act_node
        except:
            self._logger.error('Failed adding `%s` under `%s`.' %
                               (name, start_node.v_full_name))
            raise

Response: Add a new item to the tree.


Instruction:
Can you tell what is the following Python 3 function doing
def _create_link(self, act_node, name, instance):

        act_node._links[name] = instance
        act_node._children[name] = instance

        full_name = instance.v_full_name
        if full_name not in self._root_instance._linked_by:
            self._root_instance._linked_by[full_name] = {}
        linking = self._root_instance._linked_by[full_name]
        if act_node.v_full_name not in linking:
            linking[act_node.v_full_name] = (act_node, set())
        linking[act_node.v_full_name][1].add(name)

        if name not in self._links_count:
            self._links_count[name] = 0
        self._links_count[name] = self._links_count[name] + 1

        self._logger.debug('Added link `%s` under `%s` pointing '
                           'to `%s`.' % (name, act_node.v_full_name,
                                         instance.v_full_name))
        return instance

Response: Creates a link and checks if names are appropriate


Instruction:
Write a Python 3 script to
check if a list contains invalid names.

Response:
def _check_names(self, split_names, parent_node=None):
        """Checks if a list contains strings with invalid names.

        Returns a description of the name violations. If names are correct the empty
        string is returned.

        :param split_names: List of strings

        :param parent_node:

            The parental node from where to start (only applicable for node names)

        """

        faulty_names = ''

        if parent_node is not None and parent_node.v_is_root and split_names[0] == 'overview':
            faulty_names = '%s `overview` cannot be added directly under the root node ' \
                           'this is a reserved keyword,' % (faulty_names)

        for split_name in split_names:

            if len(split_name) == 0:
                faulty_names = '%s `%s` contains no characters, please use at least 1,' % (
                    faulty_names, split_name)

            elif split_name.startswith('_'):
                faulty_names = '%s `%s` starts with a leading underscore,' % (
                    faulty_names, split_name)

            elif re.match(CHECK_REGEXP, split_name) is None:
                faulty_names = '%s `%s` contains non-admissible characters ' \
                               '(use only [A-Za-z0-9_-]),' % \
                               (faulty_names, split_name)

            elif '$' in split_name:
                if split_name not in self._root_instance._wildcard_keys:
                    faulty_names = '%s `%s` contains `$` but has no associated ' \
                                   'wildcard function,' % (faulty_names, split_name)

            elif split_name in self._not_admissible_names:
                warnings.warn('`%s` is a method/attribute of the '
                              'trajectory/treenode/naminginterface, you may not be '
                              'able to access it via natural naming but only by using '
                              '`[]` square bracket notation. ' % split_name,
                              category=SyntaxWarning)

            elif split_name in self._python_keywords:
                warnings.warn('`%s` is a python keyword, you may not be '
                              'able to access it via natural naming but only by using '
                              '`[]` square bracket notation. ' % split_name,
                              category=SyntaxWarning)

        name = split_names[-1]
        if len(name) >= pypetconstants.HDF5_STRCOL_MAX_NAME_LENGTH:
            faulty_names = '%s `%s` is too long the name can only have %d characters but it has ' \
                           '%d,' % \
                           (faulty_names, name, len(name),
                            pypetconstants.HDF5_STRCOL_MAX_NAME_LENGTH)

        return faulty_names


Instruction:
Given the following Python 3 function, write the documentation
def _set_details_tree_node(self, parent_node, name, instance):
        depth = parent_node._depth + 1
        if parent_node.v_is_root:
            branch = name  # We add below root
        else:
            branch = parent_node._branch
        if name in self._root_instance._run_information:
            run_branch = name
        else:
            run_branch = parent_node._run_branch

        instance._set_details(depth, branch, run_branch)

Response: Sets the details of a given instance based on parent_node and name.


Instruction:
Write a Python 3 function that can
return an iterator over nodes hanging below a given start node.

Response:
def _iter_nodes(self, node, recursive=False, max_depth=float('inf'),
                    with_links=True, in_search=False, predicate=None):
        """Returns an iterator over nodes hanging below a given start node.

        :param node:

            Start node

        :param recursive:

            Whether recursively also iterate over the children of the start node's children

        :param max_depth:

            Maximum depth to search for

        :param in_search:

            if it is used during get search and if detailed info should be returned

        :param with_links:

            If links should be considered

        :param predicate:

            A predicate to filter nodes

        :return: Iterator

        """
        def _run_predicate(x, run_name_set):
            branch = x.v_run_branch
            return branch == 'trajectory' or branch in run_name_set

        if max_depth is None:
            max_depth = float('inf')

        if predicate is None:
            predicate = lambda x: True
        elif isinstance(predicate, (tuple, list)):
            # Create a predicate from a list of run names or run indices
            run_list = predicate
            run_name_set = set()
            for item in run_list:
                if item == -1:
                    run_name_set.add(self._root_instance.f_wildcard('$', -1))
                elif isinstance(item, int):
                    run_name_set.add(self._root_instance.f_idx_to_run(item))
                else:
                    run_name_set.add(item)
            predicate = lambda x: _run_predicate(x, run_name_set)

        if recursive:
            return NaturalNamingInterface._recursive_traversal_bfs(node,
                                            self._root_instance._linked_by,
                                            max_depth, with_links,
                                            in_search, predicate)
        else:
            iterator = (x for x in self._make_child_iterator(node, with_links) if
                        predicate(x[2]))
            if in_search:
                return iterator # Here we return tuples: (depth, name, object)
            else:
                return (x[2] for x in iterator)


Instruction:
Implement a function in Python 3 to
return a dictionary with pairings of full names as keys and instances as values.

Response:
def _to_dict(self, node, fast_access=True, short_names=False, nested=False,
                 copy=True, with_links=True):
        """ Returns a dictionary with pairings of (full) names as keys and instances as values.

        :param fast_access:

            If true parameter or result values are returned instead of the
            instances.

        :param short_names:

            If true keys are not full names but only the names.
            Raises a ValueError if the names are not unique.

        :param nested:

            If true returns a nested dictionary.

        :param with_links:

            If links should be considered

        :return: dictionary

        :raises: ValueError

        """

        if (fast_access or short_names or nested) and not copy:
            raise ValueError('You can not request the original data with >>fast_access=True<< or'
                             ' >>short_names=True<< of >>nested=True<<.')

        if nested and short_names:
            raise ValueError('You cannot use short_names and nested at the '
                             'same time.')

        # First, let's check if we can return the `flat_leaf_storage_dict` or a copy of that, this
        # is faster than creating a novel dictionary by tree traversal.
        if node.v_is_root:
            temp_dict = self._flat_leaf_storage_dict

            if not fast_access and not short_names:
                if copy:
                    return temp_dict.copy()
                else:
                    return temp_dict

            else:
                iterator = temp_dict.values()
        else:
            iterator = node.f_iter_leaves(with_links=with_links)

        # If not we need to build the dict by iterating recursively over all leaves:
        result_dict = {}
        for val in iterator:
            if short_names:
                new_key = val.v_name
            else:
                new_key = val.v_full_name

            if new_key in result_dict:
                raise ValueError('Your short names are not unique. '
                                 'Duplicate key `%s`!' % new_key)

            new_val = self._apply_fast_access(val, fast_access)
            result_dict[new_key] = new_val

        if nested:
            if node.v_is_root:
                nest_dict = result_dict
            else:
                # remove the name of the current node
                # such that the nested dictionary starts with the children
                strip = len(node.v_full_name) + 1
                nest_dict = {key[strip:]: val for key, val in result_dict.items()}
            result_dict = nest_dictionary(nest_dict, '.')

        return result_dict


Instruction:
Explain what the following Python 3 code does
def _make_child_iterator(node, with_links, current_depth=0):
        cdp1 = current_depth + 1
        if with_links:
            iterator = ((cdp1, x[0], x[1]) for x in node._children.items())
        else:
            leaves = ((cdp1, x[0], x[1]) for x in node._leaves.items())
            groups = ((cdp1, y[0], y[1]) for y in node._groups.items())
            iterator = itools.chain(groups, leaves)
        return iterator

Response: Returns an iterator over a node s children.


Instruction:
How would you explain what the following Python 3 function does
def _recursive_traversal_bfs(node, linked_by=None,
                                 max_depth=float('inf'),
                                 with_links=True, in_search=False, predicate=None):
        """Iterator function traversing the tree below `node` in breadth first search manner.

        If `run_name` is given only sub branches of this run are considered and the rest is
        blinded out.

        """

        if predicate is None:
            predicate = lambda x: True

        iterator_queue = IteratorChain([(0, node.v_name, node)])
        #iterator_queue = iter([(0, node.v_name, node)])
        start = True
        visited_linked_nodes = set([])

        while True:
            try:
                depth, name, item = next(iterator_queue)
                full_name = item._full_name
                if start or predicate(item):
                    if full_name in visited_linked_nodes:
                        if in_search:
                            # We need to return the node again to check if a link to the node
                            # has to be found
                            yield depth, name, item
                    elif depth <= max_depth:
                        if start:
                            start = False
                        else:
                            if in_search:
                                yield depth, name, item
                            else:
                                yield item

                        if full_name in linked_by:
                            visited_linked_nodes.add(full_name)

                        if not item._is_leaf and depth < max_depth:
                            child_iterator = NaturalNamingInterface._make_child_iterator(item,
                                                                        with_links,
                                                                        current_depth=depth)
                            iterator_queue.add(child_iterator)
                            #iterator_queue = itools.chain(iterator_queue, child_iterator)
            except StopIteration:
                break

Response: Iterator function traversing the tree below node in breadth first search manner.


Instruction:
Write a Python 3 function for
fasting search for a node in the tree.

Response:
def _very_fast_search(self, node, key, max_depth, with_links, crun):
        """Fast search for a node in the tree.

        The tree is not traversed but the reference dictionaries are searched.

        :param node:

            Parent node to start from

        :param key:

            Name of node to find

        :param max_depth:

            Maximum depth.

        :param with_links:

            If we work with links than we can only be sure to found the node in case we
            have a single match. Otherwise the other match might have been linked as well.

        :param crun:

            If given only nodes belonging to this particular run are searched and the rest
            is blinded out.

        :return: The found node and its depth

        :raises:

            TooManyGroupsError:

                If search cannot performed fast enough, an alternative search method is needed.

            NotUniqueNodeError:

                If several nodes match the key criterion

        """

        if key in self._links_count:
            return

        parent_full_name = node.v_full_name
        starting_depth = node.v_depth
        candidate_dict = self._get_candidate_dict(key, crun)

        # If there are to many potential candidates sequential search might be too slow
        if with_links:
            upper_bound = 1
        else:
            upper_bound = FAST_UPPER_BOUND
        if len(candidate_dict) > upper_bound:
            raise pex.TooManyGroupsError('Too many nodes')

        # Next check if the found candidates could be reached from the parent node
        result_node = None
        for goal_name in candidate_dict:

            # Check if we have found a matching node
            if goal_name.startswith(parent_full_name):
                candidate = candidate_dict[goal_name]
                if candidate.v_depth - starting_depth <= max_depth:
                    # In case of several solutions raise an error:
                    if result_node is not None:
                        raise pex.NotUniqueNodeError('Node `%s` has been found more than once, '
                                                     'full name of first occurrence is `%s` and of'
                                                     'second `%s`'
                                                     % (key, goal_name, result_node.v_full_name))
                    result_node = candidate

        if result_node is not None:
            return result_node, result_node.v_depth


Instruction:
Given the following Python 3 function, write the documentation
def _search(self, node, key, max_depth=float('inf'), with_links=True, crun=None):

        # If we find it directly there is no need for an exhaustive search
        if key in node._children and (with_links or key not in node._links):
            return node._children[key], 1

        # First the very fast search is tried that does not need tree traversal.
        try:
            result = self._very_fast_search(node, key, max_depth, with_links, crun)
            if result:
                return result
        except pex.TooManyGroupsError:
            pass
        except pex.NotUniqueNodeError:
            pass

        # Slowly traverse the entire tree
        nodes_iterator = self._iter_nodes(node, recursive=True,
                                          max_depth=max_depth, in_search=True,
                                          with_links=with_links)
        result_node = None
        result_depth = float('inf')
        for depth, name, child in nodes_iterator:

            if depth > result_depth:
                # We can break here because we enter a deeper stage of the tree and we
                # cannot find matching node of the same depth as the one we found
                break

            if key == name:
                # If result_node is not None means that we care about uniqueness and the search
                # has found more than a single solution.
                if result_node is not None:
                    raise pex.NotUniqueNodeError('Node `%s` has been found more than once within '
                                                 'the same depth %d. '
                                                 'Full name of first occurrence is `%s` and of '
                                                 'second `%s`'
                                                 % (key, child.v_depth, result_node.v_full_name,
                                                    child.v_full_name))

                result_node = child
                result_depth = depth

        return result_node, result_depth

Response: Search the tree for an item in the tree below the given node.


Instruction:
Write a Python 3 script for
performing a backwards search from the terminal node back to the start node :param start_node: The node from where search starts, or here better way where backwards search should end. :param split_name: List of names :param max_depth: Maximum search depth where to look for :param shortcuts: If shortcuts are allowed

Response:
def _backwards_search(self, start_node, split_name, max_depth=float('inf'), shortcuts=True):
        """ Performs a backwards search from the terminal node back to the start node

        :param start_node:

            The node from where search starts, or here better way where backwards search should
            end.

        :param split_name:

            List of names

        :param max_depth:

            Maximum search depth where to look for

        :param shortcuts:

            If shortcuts are allowed

        """

        result_list = [] # Result list of all found items
        full_name_set = set() # Set containing full names of all found items to avoid finding items
        # twice due to links

        colon_name = '.'.join(split_name)
        key = split_name[-1]
        candidate_dict = self._get_candidate_dict(key, None, use_upper_bound=False)
        parent_full_name = start_node.v_full_name

        split_length = len(split_name)

        for candidate_name in candidate_dict:
            # Check if candidate startswith the parent's name
            candidate = candidate_dict[candidate_name]
            if key != candidate.v_name or candidate.v_full_name in full_name_set:
                # If this is not the case we do have link, that we need to skip
                continue

            if candidate_name.startswith(parent_full_name):
                if parent_full_name != '':
                    reduced_candidate_name = candidate_name[len(parent_full_name) + 1:]
                else:
                    reduced_candidate_name = candidate_name

                candidate_split_name = reduced_candidate_name.split('.')

                if len(candidate_split_name) > max_depth:
                    break

                if len(split_name) == 1 or reduced_candidate_name.endswith(colon_name):
                    result_list.append(candidate)
                    full_name_set.add(candidate.v_full_name)

                elif shortcuts:

                    candidate_set = set(candidate_split_name)
                    climbing = True
                    for name in split_name:
                        if name not in candidate_set:
                            climbing = False
                            break

                    if climbing:
                        count = 0
                        candidate_length = len(candidate_split_name)
                        for idx in range(candidate_length):

                            if idx + split_length - count > candidate_length:
                                break

                            if split_name[count] == candidate_split_name[idx]:
                                count += 1
                                if count == len(split_name):
                                    result_list.append(candidate)
                                    full_name_set.add(candidate.v_full_name)
                                    break

        return result_list


Instruction:
Explain what the following Python 3 code does
def _get_all(self, node, name, max_depth, shortcuts):

        if max_depth is None:
            max_depth = float('inf')

        if isinstance(name, list):
            split_name = name
        elif isinstance(name, tuple):
            split_name = list(name)
        elif isinstance(name, int):
            split_name = [name]
        else:
            split_name = name.split('.')

        for idx, key in enumerate(split_name):
            _, key = self._translate_shortcut(key)
            _, key = self._replace_wildcards(key)
            split_name[idx] = key

        return self._backwards_search(node, split_name, max_depth, shortcuts)

Response: Searches for all occurrences of name under node.


Instruction:
Implement a Python 3 function for
searching for an item with the given name.

Response:
def _get(self, node, name, fast_access,
             shortcuts, max_depth, auto_load, with_links):
        """Searches for an item (parameter/result/group node) with the given `name`.

        :param node: The node below which the search is performed

        :param name: Name of the item (full name or parts of the full name)

        :param fast_access: If the result is a parameter, whether fast access should be applied.

        :param max_depth:

            Maximum search depth relative to start node.

        :param auto_load:

            If data should be automatically loaded

        :param with_links

            If links should be considered

        :return:

            The found instance (result/parameter/group node) or if fast access is True and you
            found a parameter or result that supports fast access, the contained value is returned.

        :raises:

            AttributeError if no node with the given name can be found.
            Raises errors that are raised by the storage service if `auto_load=True` and
            item cannot be found.

        """
        if auto_load and not with_links:
            raise ValueError('If you allow auto-loading you mus allow links.')

        if isinstance(name, list):
            split_name = name
        elif isinstance(name, tuple):
            split_name = list(name)
        elif isinstance(name, int):
            split_name = [name]
        else:
            split_name = name.split('.')

        if node.v_is_root:
            # We want to add `parameters`, `config`, `derived_parameters` and `results`
            # on the fly if they don't exist
            if len(split_name) == 1 and split_name[0] == '':
                return node
            key = split_name[0]
            _, key = self._translate_shortcut(key)
            if key in SUBTREE_MAPPING and key not in node._children:
                node.f_add_group(key)

        if max_depth is None:
            max_depth = float('inf')

        if len(split_name) > max_depth and shortcuts:
            raise ValueError(
                'Name of node to search for (%s) is longer thant the maximum depth %d' %
                (str(name), max_depth))

        try_auto_load_directly1 = False
        try_auto_load_directly2 = False
        wildcard_positions = []

        root = self._root_instance
        # # Rename shortcuts and check keys:
        for idx, key in enumerate(split_name):
            translated_shortcut, key = self._translate_shortcut(key)
            if translated_shortcut:
                split_name[idx] = key

            if key[0] == '_':
                raise AttributeError('Leading underscores are not allowed '
                                     'for group or parameter '
                                     'names. Cannot return %s.' % key)

            is_wildcard = self._root_instance.f_is_wildcard(key)
            if (not is_wildcard and key not in self._nodes_and_leaves and
                    key not in self._links_count):
                try_auto_load_directly1 = True
                try_auto_load_directly2 = True

            if is_wildcard:
                wildcard_positions.append((idx, key))
                if root.f_wildcard(key) not in self._nodes_and_leaves:
                    try_auto_load_directly1 = True
                if root.f_wildcard(key, -1) not in self._nodes_and_leaves:
                    try_auto_load_directly2 = True

        run_idx = root.v_idx
        wildcard_exception = None # Helper variable to store the exception thrown in case
        # of using a wildcard, to be re-thrown later on.

        if try_auto_load_directly1 and try_auto_load_directly2 and not auto_load:
            for wildcard_pos, wildcard in wildcard_positions:
                split_name[wildcard_pos] = root.f_wildcard(wildcard, run_idx)
            raise AttributeError('%s is not part of your trajectory or it\'s tree. ' %
                                 str('.'.join(split_name)))

        if run_idx > -1:
            # If we count the wildcard we have to perform the search twice,
            # one with a run name and one with the dummy:
            with self._disable_logging:
                try:
                    for wildcard_pos, wildcard in wildcard_positions:
                        split_name[wildcard_pos] = root.f_wildcard(wildcard, run_idx)

                    result = self._perform_get(node, split_name, fast_access,
                                               shortcuts, max_depth, auto_load, with_links,
                                               try_auto_load_directly1)
                    return result
                except (pex.DataNotInStorageError, AttributeError) as exc:
                    wildcard_exception = exc

        if wildcard_positions:
            for wildcard_pos, wildcard in wildcard_positions:
                split_name[wildcard_pos] = root.f_wildcard(wildcard, -1)
        try:
            return self._perform_get(node, split_name, fast_access,
                                     shortcuts, max_depth, auto_load, with_links,
                                     try_auto_load_directly2)
        except (pex.DataNotInStorageError, AttributeError):
            # Re-raise the old error in case it was thronw already
            if wildcard_exception is not None:
                raise wildcard_exception
            else:
                raise


Instruction:
Implement a Python 3 function for
performing a search for an item in the given node.

Response:
def _perform_get(self, node, split_name, fast_access,
                     shortcuts, max_depth, auto_load, with_links,
                     try_auto_load_directly):
        """Searches for an item (parameter/result/group node) with the given `name`.

        :param node: The node below which the search is performed

        :param split_name: Name split into list according to '.'

        :param fast_access: If the result is a parameter, whether fast access should be applied.

        :param max_depth:

            Maximum search depth relative to start node.

        :param auto_load:

            If data should be automatically loaded

        :param with_links:

            If links should be considered.

        :param try_auto_load_directly:

            If one should skip search and directly try auto_loading

        :return:

            The found instance (result/parameter/group node) or if fast access is True and you
            found a parameter or result that supports fast access, the contained value is returned.

        :raises:

            AttributeError if no node with the given name can be found
            Raises errors that are raiesd by the storage service if `auto_load=True`

        """

        result = None
        name = '.'.join(split_name)

        if len(split_name) > max_depth:
            raise AttributeError('The node or param/result `%s`, cannot be found under `%s`'
                                 'The name you are looking for is larger than the maximum '
                                 'search depth.' %
                                 (name, node.v_full_name))

        if shortcuts and not try_auto_load_directly:
            first = split_name[0]

            if len(split_name) == 1 and first in node._children and (with_links or
                                                                    first not in node._links):
                result = node._children[first]
            else:

                result = self._check_flat_dicts(node, split_name)

                if result is None:
                    # Check in O(N) with `N` number of groups and nodes
                    # [Worst Case O(N), average case is better
                    # since looking into a single dict costs O(1)].
                    result = node
                    crun = None
                    for key in split_name:
                        if key in self._root_instance._run_information:
                            crun = key
                        result, depth = self._search(result, key, max_depth, with_links, crun)
                        max_depth -= depth
                        if result is None:
                            break

        elif not try_auto_load_directly:
            result = node
            for name in split_name:
                if name in result._children and (with_links or not name in result._links):
                    result = result._children[name]
                else:
                    raise AttributeError(
                        'You did not allow for shortcuts and `%s` was not directly '
                        'found  under node `%s`.' % (name, result.v_full_name))

        if result is None and auto_load:
            try:
                result = node.f_load_child('.'.join(split_name),
                                           load_data=pypetconstants.LOAD_DATA)
                if (self._root_instance.v_idx != -1 and
                            result.v_is_leaf and
                            result.v_is_parameter and
                            result.v_explored):
                    result._set_parameter_access(self._root_instance.v_idx)
            except:
                self._logger.error('Error while auto-loading `%s` under `%s`.' %
                                   (name, node.v_full_name))
                raise

        if result is None:
            raise AttributeError('The node or param/result `%s`, cannot be found under `%s`' %
                                 (name, node.v_full_name))
        if result.v_is_leaf:
            if auto_load and result.f_is_empty():

                try:
                    self._root_instance.f_load_item(result)
                    if (self._root_instance.v_idx != -1 and
                            result.v_is_parameter and
                            result.v_explored):
                        result._set_parameter_access(self._root_instance.v_idx)
                except:
                    self._logger.error('Error while auto-loading `%s` under `%s`. I found the '
                                       'item but I could not load the data.' %
                                       (name, node.v_full_name))
                    raise

            return self._apply_fast_access(result, fast_access)
        else:
            return result


Instruction:
Can you generate the documentation for the following Python 3 function
def _add_group_from_storage(self, args, kwargs):
        return self._nn_interface._add_generic(self,
                                                type_name=GROUP,
                                                group_type_name=GROUP,
                                                args=args,
                                                kwargs=kwargs,
                                                add_prefix=False,
                                                check_naming=False)

Response: Add a new group from storage service


Instruction:
Can you generate the documentation for the following Python 3 function
def _add_leaf_from_storage(self, args, kwargs):
        return self._nn_interface._add_generic(self,
                                                type_name=LEAF,
                                                group_type_name=GROUP,
                                                args=args, kwargs=kwargs,
                                                add_prefix=False,
                                                check_naming=False)

Response: Add a leaf from storage service to the network interface


Instruction:
Implement a Python 3 function for
returning a list of all children names

Response:
def f_dir_data(self):
        """Returns a list of all children names"""
        if (self._nn_interface is not None and
                    self._nn_interface._root_instance is not None
                        and self.v_root.v_auto_load):
            try:
                if self.v_is_root:
                    self.f_load(recursive=True, max_depth=1,
                                load_data=pypetconstants.LOAD_SKELETON,
                                with_meta_data=False,
                                with_run_information=False)
                else:
                    self.f_load(recursive=True, max_depth=1, load_data=pypetconstants.LOAD_SKELETON)
            except Exception as exc:
                pass
        return list(self._children.keys())


Instruction:
Create a Python 3 function for
creating a dummy object containing the whole tree to make unfolding easier.

Response:
def _debug(self):
        """Creates a dummy object containing the whole tree to make unfolding easier.

        This method is only useful for debugging purposes.
        If you use an IDE and want to unfold the trajectory tree, you always need to
        open the private attribute `_children`. Use to this function to create a new
        object that contains the tree structure in its attributes.

        Manipulating the returned object does not change the original tree!

        """

        class Bunch(object):
            """Dummy container class"""
            pass

        debug_tree = Bunch()

        if not self.v_annotations.f_is_empty():
            debug_tree.v_annotations = self.v_annotations
        if not self.v_comment == '':
            debug_tree.v_comment = self.v_comment

        for leaf_name in self._leaves:
            leaf = self._leaves[leaf_name]
            setattr(debug_tree, leaf_name, leaf)

        for link_name in self._links:
            linked_node = self._links[link_name]
            setattr(debug_tree, link_name, 'Link to `%s`' % linked_node.v_full_name)

        for group_name in self._groups:
            group = self._groups[group_name]
            setattr(debug_tree, group_name, group._debug())

        return debug_tree


Instruction:
Implement a function in Python 3 to
return the parent of the current node.

Response:
def f_get_parent(self):
        """Returns the parent of the node.

        Raises a TypeError if current node is root.

        """
        if self.v_is_root:
            raise TypeError('Root does not have a parent')
        elif self.v_location == '':
            return self.v_root
        else:
            return self.v_root.f_get(self.v_location, fast_access=False, shortcuts=False)


Instruction:
Can you generate the documentation for the following Python 3 function
def f_add_group(self, *args, **kwargs):

        return self._nn_interface._add_generic(self, type_name=GROUP,
                                               group_type_name=GROUP,
                                               args=args, kwargs=kwargs, add_prefix=False)

Response: Adds an empty generic group under the current node.


Instruction:
How would you code a function in Python 3 to
add a link to an existing node.

Response:
def f_add_link(self, name_or_item, full_name_or_item=None):
        """Adds a link to an existing node.

        Can be called as ``node.f_add_link(other_node)`` this will add a link the `other_node`
        with the link name as the name of the node.

        Or can be called as ``node.f_add_link(name, other_node)`` to add a link to the
        `other_node` and the given `name` of the link.

        In contrast to addition of groups and leaves,  colon separated names
        are **not** allowed, i.e. ``node.f_add_link('mygroup.mylink', other_node)``
        does not work.

        """
        if isinstance(name_or_item, str):
            name = name_or_item
            if isinstance(full_name_or_item, str):
                instance = self.v_root.f_get(full_name_or_item)
            else:
                instance =  full_name_or_item
        else:
            instance = name_or_item
            name = instance.v_name

        return self._nn_interface._add_generic(self, type_name=LINK,
                                               group_type_name=GROUP, args=(name, instance),
                                               kwargs={},
                                               add_prefix=False)


Instruction:
Given the following Python 3 function, write the documentation
def f_remove_link(self, name):
        if name not in self._links:
            raise ValueError('No link with name `%s` found under `%s`.' % (name, self._full_name))

        self._nn_interface._remove_link(self, name)

Response: Removes a link from the current group node with a given name.


Instruction:
How would you explain what the following Python 3 function does
def f_add_leaf(self, *args, **kwargs):

        return self._nn_interface._add_generic(self, type_name=LEAF,
                                               group_type_name=GROUP,
                                               args=args, kwargs=kwargs,
                                               add_prefix=False)

Response: Adds an empty generic leaf under the current node.


Instruction:
Explain what the following Python 3 code does
def f_remove_child(self, name, recursive=False, predicate=None):
        if name not in self._children:
            raise ValueError('Your group `%s` does not contain the child `%s`.' %
                             (self.v_full_name, name))
        else:
            child = self._children[name]
            if (name not in self._links and
                    not child.v_is_leaf and
                    child.f_has_children() and
                    not recursive):
                raise TypeError('Cannot remove child. It is a group with children. Use'
                                ' f_remove with ``recursive = True``')
            else:
                self._nn_interface._remove_subtree(self, name, predicate)

Response: Removes a child of the current group.


Instruction:
Given the following Python 3 function, write the documentation
def f_contains(self, item, with_links=True, shortcuts=False, max_depth=None):

        # Check if an instance or a name was supplied by the user
        try:
            search_string = item.v_full_name
            parent_full_name = self.v_full_name

            if not search_string.startswith(parent_full_name):
                return False

            if parent_full_name != '':
                search_string = search_string[len(parent_full_name) + 1:]
            else:
                search_string = search_string

            shortcuts = False # if we search for a particular item we do not allow shortcuts

        except AttributeError:
            search_string = item
            item = None

        if search_string == '':
            return False # To allow to search for nodes wit name = '', which are never part
            # of the trajectory

        try:
            result = self.f_get(search_string,
                                shortcuts=shortcuts, max_depth=max_depth, with_links=with_links)
        except AttributeError:
            return False

        if item is not None:
            return id(item) == id(result)
        else:
            return True

Response: Checks if the node contains a specific parameter or result.


Instruction:
How would you implement a function in Python 3 that
iterates over nodes in the search tree.

Response:
def f_iter_nodes(self, recursive=True, with_links=True, max_depth=None, predicate=None):
        """Iterates recursively (default) over nodes hanging below this group.

        :param recursive: Whether to iterate the whole sub tree or only immediate children.

        :param with_links: If links should be considered

        :param max_depth: Maximum depth in search tree relative to start node (inclusive)

        :param predicate:

            A predicate function that is applied for each node and only returns the node
            if it evaluates to ``True``. If ``False``
            and you iterate recursively also the children are spared.

            Leave to `None` if you don't want to filter and simply iterate over all nodes.

            For example, to iterate only over groups you could use:

            >>> traj.f_iter_nodes(recursive=True, predicate=lambda x: x.v_is_group)

            To blind out all runs except for a particular set, you can simply pass a tuple
            of run indices with -1 referring to the ``run_ALL`` node.

            For instance

            >>> traj.f_iter_nodes(recursive=True, predicate=(0,3,-1))

            Will blind out all nodes hanging below a group named ``run_XXXXXXXXX``
            (including the group) except ``run_00000000``, ``run_00000003``, and ``run_ALL``.

        :return: Iterator over nodes

        """
        return self._nn_interface._iter_nodes(self, recursive=recursive, with_links=with_links,
                                              max_depth=max_depth,
                                              predicate=predicate)


Instruction:
Explain what the following Python 3 code does
def f_iter_leaves(self, with_links=True):
        for node in self.f_iter_nodes(with_links=with_links):
            if node.v_is_leaf:
                yield node

Response: Iterates recursively over all leaves in the current group.


Instruction:
Can you implement a function in Python 3 that
searches for all occurrences of name under node.

Response:
def f_get_all(self, name, max_depth=None, shortcuts=True):
        """ Searches for all occurrences of `name` under `node`.

        Links are NOT considered since nodes are searched bottom up in the tree.

        :param node:

            Start node

        :param name:

            Name of what to look for, can be separated by colons, i.e.
            ``'mygroupA.mygroupB.myparam'``.

        :param max_depth:

            Maximum search depth relative to start node.
            `None` for no limit.

        :param shortcuts:

            If shortcuts are allowed, otherwise the stated name defines a
            consecutive name.For instance. ``'mygroupA.mygroupB.myparam'`` would
            also find ``mygroupA.mygroupX.mygroupB.mygroupY.myparam`` if shortcuts
            are allowed, otherwise not.

        :return:

            List of nodes that match the name, empty list if nothing was found.

        """
        return self._nn_interface._get_all(self, name, max_depth=max_depth, shortcuts=shortcuts)


Instruction:
Write a Python 3 function for
returning the default value for the given name if the name is not found in the trajectory.

Response:
def f_get_default(self, name, default=None, fast_access=True, with_links=True,
              shortcuts=True, max_depth=None, auto_load=False):
        """ Similar to `f_get`, but returns the default value if `name` is not found in the
        trajectory.

        This function uses the `f_get` method and will return the default value
        in case `f_get` raises an AttributeError or a DataNotInStorageError.
        Other errors are not handled.

        In contrast to `f_get`, fast access is True by default.

        """
        try:
            return self.f_get(name, fast_access=fast_access,
                           shortcuts=shortcuts,
                           max_depth=max_depth,
                           auto_load=auto_load,
                           with_links=with_links)

        except (AttributeError, pex.DataNotInStorageError):
            return default


Instruction:
Implement a function in Python 3 to
search and returns an item with the given name.

Response:
def f_get(self, name, fast_access=False, with_links=True,
              shortcuts=True, max_depth=None, auto_load=False):
        """Searches and returns an item (parameter/result/group node) with the given `name`.

        :param name: Name of the item (full name or parts of the full name)

        :param fast_access: Whether fast access should be applied.

        :param with_links:

            If links are considered. Cannot be set to ``False`` if ``auto_load`` is ``True``.

        :param shortcuts:

            If shortcuts are allowed and the trajectory can *hop* over nodes in the
            path.

        :param max_depth:

            Maximum depth relative to starting node (inclusive).
            `None` means no depth limit.

        :param auto_load:

            If data should be loaded from the storage service if it cannot be found in the
            current trajectory tree. Auto-loading will load group and leaf nodes currently
            not in memory and it will load data into empty leaves. Be aware that auto-loading
            does not work with shortcuts.

        :return:

            The found instance (result/parameter/group node) or if fast access is True and you
            found a parameter or result that supports fast access, the contained value is returned.

        :raises:

            AttributeError: If no node with the given name can be found

            NotUniqueNodeError

                In case of forward search if more than one candidate node is found within a
                particular depth of the tree. In case of backwards search if more than
                one candidate is found regardless of the depth.

            DataNotInStorageError:

                In case auto-loading fails

            Any exception raised by the StorageService in case auto-loading is enabled

        """
        return self._nn_interface._get(self, name, fast_access=fast_access,
                                       shortcuts=shortcuts,
                                       max_depth=max_depth,
                                       auto_load=auto_load,
                                       with_links=with_links)


Instruction:
How would you explain what the following Python 3 function does
def f_get_children(self, copy=True):
        if copy:
            return self._children.copy()
        else:
            return self._children

Response: Returns a dictionary of children.


Instruction:
Here you have a function in Python 3, explain what it does
def f_get_groups(self, copy=True):
        if copy:
            return self._groups.copy()
        else:
            return self._groups

Response: Returns a dictionary of groups hanging immediately below this group.


Instruction:
Here you have a function in Python 3, explain what it does
def f_get_leaves(self, copy=True):
        if copy:
            return self._leaves.copy()
        else:
            return self._leaves

Response: Returns a dictionary of all leaves hanging immediately below this group.


Instruction:
How would you implement a function in Python 3 that
returns a dictionary of nodes with their link keys.

Response:
def f_get_links(self, copy=True):
        """Returns a link dictionary.

        :param copy:

            Whether the group's original dictionary or a shallow copy is returned.
            If you want the real dictionary please do not modify it at all!

        :returns: Dictionary of nodes

        """
        if copy:
            return self._links.copy()
        else:
            return self._links


Instruction:
Make a summary of the following Python 3 code
def f_store_child(self, name, recursive=False, store_data=pypetconstants.STORE_DATA,
                      max_depth=None):
        """Stores a child or recursively a subtree to disk.

        :param name:

            Name of child to store. If grouped ('groupA.groupB.childC') the path along the way
            to last node in the chain is stored. Shortcuts are NOT allowed!

        :param recursive:

            Whether recursively all children's children should be stored too.

        :param store_data:

            For how to choose 'store_data' see :ref:`more-on-storing`.

        :param max_depth:

            In case `recursive` is `True`, you can specify the maximum depth to store
            data relative from current node. Leave `None` if you don't want to limit
            the depth.

        :raises: ValueError if the child does not exist.

        """
        if not self.f_contains(name, shortcuts=False):
            raise ValueError('Your group `%s` does not (directly) contain the child `%s`. '
                             'Please not that shortcuts are not allowed for `f_store_child`.' %
                             (self.v_full_name, name))

        traj = self._nn_interface._root_instance
        storage_service = traj.v_storage_service

        storage_service.store(pypetconstants.TREE, self, name,
                              trajectory_name=traj.v_name,
                              recursive=recursive,
                              store_data=store_data,
                              max_depth=max_depth)

Response: Stores a child or recursively a subtree to disk.


Instruction:
Write a Python 3 script for
storing a group node to disk.

Response:
def f_store(self, recursive=True, store_data=pypetconstants.STORE_DATA,
                max_depth=None):
        """Stores a group node to disk

        :param recursive:

            Whether recursively all children should be stored too. Default is ``True``.

        :param store_data:

            For how to choose 'store_data' see :ref:`more-on-storing`.

        :param max_depth:

            In case `recursive` is `True`, you can specify the maximum depth to store
            data relative from current node. Leave `None` if you don't want to limit
            the depth.

        """
        traj = self._nn_interface._root_instance
        storage_service = traj.v_storage_service

        storage_service.store(pypetconstants.GROUP, self,
                              trajectory_name=traj.v_name,
                              recursive=recursive,
                              store_data=store_data,
                              max_depth=max_depth)


Instruction:
Can you implement a function in Python 3 that
loads a child or recursively a subtree from disk.

Response:
def f_load_child(self, name, recursive=False, load_data=pypetconstants.LOAD_DATA,
                     max_depth=None):
        """Loads a child or recursively a subtree from disk.

        :param name:

            Name of child to load. If grouped ('groupA.groupB.childC') the path along the way
            to last node in the chain is loaded. Shortcuts are NOT allowed!

        :param recursive:

            Whether recursively all nodes below the last child should be loaded, too.
            Note that links are never evaluated recursively. Only the linked node
            will be loaded if it does not exist in the tree, yet. Any nodes or links
            of this linked node are not loaded.

        :param load_data:

            Flag how to load the data.
            For how to choose 'load_data' see :ref:`more-on-loading`.

        :param max_depth:

            In case `recursive` is `True`, you can specify the maximum depth to load
            load data relative from current node. Leave `None` if you don't want to limit
            the depth.

        :returns:

            The loaded child, in case of grouping ('groupA.groupB.childC') the last
            node (here 'childC') is returned.

        """

        traj = self._nn_interface._root_instance
        storage_service = traj.v_storage_service

        storage_service.load(pypetconstants.TREE, self, name,
                             trajectory_name=traj.v_name,
                             load_data=load_data,
                             recursive=recursive,
                             max_depth=max_depth)

        return self.f_get(name, shortcuts=False)


Instruction:
How would you code a function in Python 3 to
load a group from disk.

Response:
def f_load(self, recursive=True, load_data=pypetconstants.LOAD_DATA,
               max_depth=None):
        """Loads a group from disk.

        :param recursive:

            Default is ``True``.
            Whether recursively all nodes below the current node should be loaded, too.
            Note that links are never evaluated recursively. Only the linked node
            will be loaded if it does not exist in the tree, yet. Any nodes or links
            of this linked node are not loaded.

        :param load_data:

            Flag how to load the data.
            For how to choose 'load_data' see :ref:`more-on-loading`.

        :param max_depth:

            In case `recursive` is `True`, you can specify the maximum depth to load
            load data relative from current node.

        :returns:

            The node itself.

        """

        traj = self._nn_interface._root_instance
        storage_service = traj.v_storage_service

        storage_service.load(pypetconstants.GROUP, self,
                             trajectory_name=traj.v_name,
                             load_data=load_data,
                             recursive=recursive,
                             max_depth=max_depth)
        return self


Instruction:
How would you implement a function in Python 3 that
adds an empty parameter group under the current node.

Response:
def f_add_parameter_group(self, *args, **kwargs):
        """Adds an empty parameter group under the current node.

        Can be called with ``f_add_parameter_group('MyName', 'this is an informative comment')``
        or ``f_add_parameter_group(name='MyName', comment='This is an informative comment')``
        or with a given new group instance:
        ``f_add_parameter_group(ParameterGroup('MyName', comment='This is a comment'))``.

        Adds the full name of the current node as prefix to the name of the group.
        If current node is the trajectory (root), the prefix `'parameters'`
        is added to the full name.

        The `name` can also contain subgroups separated via colons, for example:
        `name=subgroup1.subgroup2.subgroup3`. These other parent groups will be automatically
        created.

        """
        return self._nn_interface._add_generic(self, type_name=PARAMETER_GROUP,
                                               group_type_name=PARAMETER_GROUP,
                                               args=args, kwargs=kwargs)


Instruction:
Can you generate the documentation for the following Python 3 function
def f_add_parameter(self, *args, **kwargs):
        return self._nn_interface._add_generic(self, type_name=PARAMETER,
                                               group_type_name=PARAMETER_GROUP,
                                               args=args, kwargs=kwargs)

Response: Adds a parameter to the trajectory.


Instruction:
How would you code a function in Python 3 to
add an empty result group under the current node.

Response:
def f_add_result_group(self, *args, **kwargs):
        """Adds an empty result group under the current node.

        Adds the full name of the current node as prefix to the name of the group.
        If current node is a single run (root) adds the prefix `'results.runs.run_08%d%'` to the
        full name where `'08%d'` is replaced by the index of the current run.

        The `name` can also contain subgroups separated via colons, for example:
        `name=subgroup1.subgroup2.subgroup3`. These other parent groups will be automatically
        be created.

        """

        return self._nn_interface._add_generic(self, type_name=RESULT_GROUP,
                                               group_type_name=RESULT_GROUP,
                                               args=args, kwargs=kwargs)


Instruction:
Can you implement a function in Python 3 that
adds a result to the current node.

Response:
def f_add_result(self, *args, **kwargs):
        """Adds a result under the current node.

        There are two ways to add a new result either by adding a result instance:

        >>> new_result = Result('group1.group2.myresult', 1666, x=3, y=4, comment='Example!')
        >>> traj.f_add_result(new_result)

        Or by passing the values directly to the function, with the name being the first
        (non-keyword!) argument:

        >>> traj.f_add_result('group1.group2.myresult', 1666, x=3, y=3,comment='Example!')

        If you want to create a different result than the standard result, you can
        give the constructor as the first (non-keyword!) argument followed by the name
        (non-keyword!):

        >>> traj.f_add_result(PickleResult,'group1.group2.myresult', 1666, x=3, y=3, comment='Example!')

        Additional arguments (here `1666`) or keyword arguments (here `x=3, y=3`) are passed
        onto the constructor of the result.

        Adds the full name of the current node as prefix to the name of the result.
        If current node is a single run (root) adds the prefix `'results.runs.run_08%d%'` to the
        full name where `'08%d'` is replaced by the index of the current run.

        """
        return self._nn_interface._add_generic(self, type_name=RESULT,
                                               group_type_name=RESULT_GROUP,
                                               args=args, kwargs=kwargs)


Instruction:
Can you tell what is the following Python 3 function doing
def f_add_derived_parameter_group(self, *args, **kwargs):

        return self._nn_interface._add_generic(self, type_name=DERIVED_PARAMETER_GROUP,
                                               group_type_name=DERIVED_PARAMETER_GROUP,
                                               args=args, kwargs=kwargs)

Response: Adds an empty derived parameter group under the current node.


Instruction:
Explain what the following Python 3 code does
def f_add_derived_parameter(self, *args, **kwargs):
        return self._nn_interface._add_generic(self, type_name=DERIVED_PARAMETER,
                                               group_type_name=DERIVED_PARAMETER_GROUP,
                                               args=args, kwargs=kwargs)

Response: Adds a derived parameter under the current group.


Instruction:
Here you have a function in Python 3, explain what it does
def f_add_config_group(self, *args, **kwargs):
        return self._nn_interface._add_generic(self, type_name=CONFIG_GROUP,
                                               group_type_name=CONFIG_GROUP,
                                               args=args, kwargs=kwargs)

Response: Adds an empty config group under the current node.


Instruction:
Can you generate the documentation for the following Python 3 function
def f_add_config(self, *args, **kwargs):
        return self._nn_interface._add_generic(self, type_name=CONFIG,
                                               group_type_name=CONFIG_GROUP,
                                               args=args, kwargs=kwargs)

Response: Adds a config parameter under the current group.


Instruction:
Can you implement a function in Python 3 that
takes a unit string like 1. * volt and returns the BRIAN2 unit.

Response:
def unit_from_expression(expr):
    """Takes a unit string like ``'1. * volt'`` and returns the BRIAN2 unit."""
    if expr == '1':
        return get_unit_fast(1)
    elif isinstance(expr, str):
        mod = ast.parse(expr, mode='eval')
        expr = mod.body
        return unit_from_expression(expr)
    elif expr.__class__ is ast.Name:
        return ALLUNITS[expr.id]
    elif expr.__class__ is ast.Num:
        return expr.n
    elif expr.__class__ is ast.UnaryOp:
        op = expr.op.__class__.__name__
        operand = unit_from_expression(expr.operand)
        if op=='USub':
            return -operand
        else:
            raise SyntaxError("Unsupported operation "+op)
    elif expr.__class__ is ast.BinOp:
        op = expr.op.__class__.__name__
        left = unit_from_expression(expr.left)
        right = unit_from_expression(expr.right)
        if op=='Add':
            u = left+right
        elif op=='Sub':
            u = left-right
        elif op=='Mult':
            u = left*right
        elif op=='Div':
            u = left/right
        elif op=='Pow':
            n = unit_from_expression(expr.right)
            u = left**n
        elif op=='Mod':
            u = left % right
        else:
            raise SyntaxError("Unsupported operation "+op)
        return u
    else:
        raise RuntimeError('You shall not pass')


Instruction:
Create a Python 3 function to
check if data is supported by this parameter.

Response:
def f_supports(self, data):
        """ Simply checks if data is supported """
        if isinstance(data, Quantity):
            return True
        elif super(Brian2Parameter, self).f_supports(data):
            return True
        return False


Instruction:
Can you tell what is the following Python 3 function doing
def _supports(self, data):
        if isinstance(data, Quantity):
            return True
        elif super(Brian2Result, self)._supports(data):
            return True
        return False

Response: Check if data is supported by this class.


Instruction:
Implement a function in Python 3 to
set single item in Brian2MonitorResult.

Response:
def f_set_single(self, name, item):
        """ To add a monitor use `f_set_single('monitor', brian_monitor)`.

        Otherwise `f_set_single` works similar to :func:`~pypet.parameter.Result.f_set_single`.
        """
        if type(item) in [SpikeMonitor, StateMonitor, PopulationRateMonitor]:
            if self.v_stored:
                self._logger.warning('You are changing an already stored result. If '
                                     'you not explicitly overwrite the data on disk, '
                                     'this change might be lost and not propagated to disk.')

            self._extract_monitor_data(item)
        else:
            super(Brian2MonitorResult, self).f_set_single(name, item)


Instruction:
Write a Python 3 script for
adding the commit information to the trajectory.

Response:
def add_commit_variables(traj, commit):
    """Adds commit information to the trajectory."""

    git_time_value = time.strftime('%Y_%m_%d_%Hh%Mm%Ss', time.localtime(commit.committed_date))

    git_short_name = str(commit.hexsha[0:7])
    git_commit_name = 'commit_%s_' % git_short_name
    git_commit_name = 'git.' + git_commit_name + git_time_value

    if not traj.f_contains('config.'+git_commit_name, shortcuts=False):

        git_commit_name += '.'
        # Add the hexsha
        traj.f_add_config(git_commit_name+'hexsha', commit.hexsha,
                          comment='SHA-1 hash of commit')

        # Add the description string
        traj.f_add_config(git_commit_name+'name_rev', commit.name_rev,
                          comment='String describing the commits hex sha based on '
                                  'the closest Reference')

        # Add unix epoch
        traj.f_add_config(git_commit_name+'committed_date',
                          commit.committed_date, comment='Date of commit as unix epoch seconds')

        # Add commit message
        traj.f_add_config(git_commit_name+'message', str(commit.message),
                          comment='The commit message')


Instruction:
Can you implement a function in Python 3 that
makes a commit and returns if a new commit was triggered and the SHA_1 code of the commit.

Response:
def make_git_commit(environment, git_repository, user_message, git_fail):
    """ Makes a commit and returns if a new commit was triggered and the SHA_1 code of the commit.

    If `git_fail` is `True` program fails instead of triggering a new commit given
    not committed changes. Then a `GitDiffError` is raised.

    """

    # Import GitPython, we do it here to allow also users not having GitPython installed
    # to use the normal environment

    # Open the repository
    repo = git.Repo(git_repository)
    index = repo.index

    traj = environment.v_trajectory

    # Create the commit message and append the trajectory name and comment
    if traj.v_comment:
        commentstr = ', Comment: `%s`' % traj.v_comment
    else:
        commentstr = ''

    if user_message:
        user_message += ' -- '

    message = '%sTrajectory: `%s`, Time: `%s`, %s' % \
              (user_message, traj.v_name, traj.v_time, commentstr)

    # Detect changes:
    diff = index.diff(None)

    if diff:
        if git_fail:
            # User requested fail instead of a new commit
            raise pex.GitDiffError('Found not committed changes!')
        # Make the commit
        repo.git.add('-u')
        commit = index.commit(message)
        new_commit = True

    else:
        # Take old commit
        commit = repo.commit(None)
        new_commit = False

    # Add the commit info to the trajectory
    add_commit_variables(traj, commit)

    return new_commit, commit.hexsha


Instruction:
Here you have a function in Python 3, explain what it does
def flatten_dictionary(nested_dict, separator):
    flat_dict = {}
    for key, val in nested_dict.items():
        if isinstance(val, dict):
            new_flat_dict = flatten_dictionary(val, separator)
            for flat_key, inval in new_flat_dict.items():
                new_key = key + separator + flat_key
                flat_dict[new_key] = inval
        else:
            flat_dict[key] = val

    return flat_dict

Response: Flattens a nested dictionary.


Instruction:
Can you generate the documentation for the following Python 3 function
def nest_dictionary(flat_dict, separator):
    nested_dict = {}
    for key, val in flat_dict.items():
        split_key = key.split(separator)
        act_dict = nested_dict
        final_key = split_key.pop()
        for new_key in split_key:
            if not new_key in act_dict:
                act_dict[new_key] = {}

            act_dict = act_dict[new_key]

        act_dict[final_key] = val
    return nested_dict

Response: Nests a given flat dictionary.


Instruction:
Make a summary of the following Python 3 code
def progressbar(index, total, percentage_step=10, logger='print', log_level=logging.INFO,
                 reprint=True, time=True, length=20, fmt_string=None, reset=False):
    """Plots a progress bar to the given `logger` for large for loops.

    To be used inside a for-loop at the end of the loop:

    .. code-block:: python

        for irun in range(42):
            my_costly_job() # Your expensive function
            progressbar(index=irun, total=42, reprint=True) # shows a growing progressbar

    There is no initialisation of the progressbar necessary before the for-loop.
    The progressbar will be reset automatically if used in another for-loop.

    :param index: Current index of for-loop
    :param total: Total size of for-loop
    :param percentage_step: Steps with which the bar should be plotted
    :param logger:

        Logger to write to - with level INFO. If string 'print' is given, the print statement is
        used. Use ``None`` if you don't want to print or log the progressbar statement.

    :param log_level: Log level with which to log.
    :param reprint:

        If no new line should be plotted but carriage return (works only for printing)

    :param time: If the remaining time should be estimated and displayed
    :param length: Length of the bar in `=` signs.
    :param fmt_string:

        A string which contains exactly one `%s` in order to incorporate the progressbar.
        If such a string is given, ``fmt_string % progressbar`` is printed/logged.

    :param reset:

        If the progressbar should be restarted. If progressbar is called with a lower
        index than the one before, the progressbar is automatically restarted.

    :return:

        The progressbar string or `None` if the string has not been updated.

    """
    return _progressbar(index=index, total=total, percentage_step=percentage_step,
                        logger=logger, log_level=log_level, reprint=reprint,
                        time=time, length=length, fmt_string=fmt_string, reset=reset)

Response: Plots a progress bar to the given logger.


Instruction:
How would you code a function in Python 3 to
take a function and keyword arguments and returns the ones that can be passed.

Response:
def get_matching_kwargs(func, kwargs):
    """Takes a function and keyword arguments and returns the ones that can be passed."""
    args, uses_startstar = _get_argspec(func)
    if uses_startstar:
        return kwargs.copy()
    else:
        matching_kwargs = dict((k, kwargs[k]) for k in args if k in kwargs)
        return matching_kwargs


Instruction:
How would you explain what the following Python 3 function does
def result_sort(result_list, start_index=0):
    if len(result_list) < 2:
        return result_list
    to_sort = result_list[start_index:]
    minmax = [x[0] for x in to_sort]
    minimum = min(minmax)
    maximum = max(minmax)
    #print minimum, maximum
    sorted_list = [None for _ in range(minimum, maximum + 1)]
    for elem in to_sort:
        key = elem[0] - minimum
        sorted_list[key] = elem
    idx_count = start_index
    for elem in sorted_list:
        if elem is not None:
            result_list[idx_count] = elem
            idx_count += 1
    return result_list

Response: Sorts a list of results in O ( n ) in place


Instruction:
Can you create a Python 3 function that
formats timestamp to human readable format

Response:
def format_time(timestamp):
    """Formats timestamp to human readable format"""
    format_string = '%Y_%m_%d_%Hh%Mm%Ss'
    formatted_time = datetime.datetime.fromtimestamp(timestamp).strftime(format_string)
    return formatted_time


Instruction:
Make a summary of the following Python 3 code
def port_to_tcp(port=None):
    #address = 'tcp://' + socket.gethostbyname(socket.getfqdn())
    domain_name = socket.getfqdn()
    try:
        addr_list = socket.getaddrinfo(domain_name, None)
    except Exception:
        addr_list = socket.getaddrinfo('127.0.0.1', None)
    family, socktype, proto, canonname, sockaddr = addr_list[0]
    host = convert_ipv6(sockaddr[0])
    address =  'tcp://' + host
    if port is None:
        port = ()
    if not isinstance(port, int):
        # determine port automatically
        context = zmq.Context()
        try:
            socket_ = context.socket(zmq.REP)
            socket_.ipv6 = is_ipv6(address)
            port = socket_.bind_to_random_port(address, *port)
        except Exception:
            print('Could not connect to {} using {}'.format(address, addr_list))
            pypet_root_logger = logging.getLogger('pypet')
            pypet_root_logger.exception('Could not connect to {}'.format(address))
            raise
        socket_.close()
        context.term()
    return address + ':' + str(port)

Response: Returns local tcp address for a given port if None


Instruction:
How would you code a function in Python 3 to
like os. makedirs but takes care about race conditions

Response:
def racedirs(path):
    """Like os.makedirs but takes care about race conditions"""
    if os.path.isfile(path):
        raise IOError('Path `%s` is already a file not a directory')
    while True:
        try:
            if os.path.isdir(path):
                # only break if full path has been created or exists
                break
            os.makedirs(path)
        except EnvironmentError as exc:
            # Part of the directory path already exist
            if exc.errno != 17:
                # This error won't be any good
                raise


Instruction:
Create a Python 3 function to
reset the progressbar to the start of a new one

Response:
def _reset(self, index, total, percentage_step, length):
        """Resets to the progressbar to start a new one"""
        self._start_time = datetime.datetime.now()
        self._start_index = index
        self._current_index = index
        self._percentage_step = percentage_step
        self._total = float(total)
        self._total_minus_one = total - 1
        self._length = length
        self._norm_factor = total * percentage_step / 100.0
        self._current_interval = int((index + 1.0) / self._norm_factor)


Instruction:
Explain what the following Python 3 code does
def _get_remaining(self, index):
        try:
            current_time = datetime.datetime.now()
            time_delta = current_time - self._start_time
            try:
                total_seconds = time_delta.total_seconds()
            except AttributeError:
                # for backwards-compatibility
                # Python 2.6 does not support `total_seconds`
                total_seconds = ((time_delta.microseconds +
                                    (time_delta.seconds +
                                     time_delta.days * 24 * 3600) * 10 ** 6) / 10.0 ** 6)
            remaining_seconds = int((self._total - self._start_index - 1.0) *
                                    total_seconds / float(index - self._start_index) -
                                    total_seconds)
            remaining_delta = datetime.timedelta(seconds=remaining_seconds)
            remaining_str = ', remaining: ' + str(remaining_delta)
        except ZeroDivisionError:
            remaining_str = ''
        return remaining_str

Response: Calculates the remaining time as a string


Instruction:
Can you generate the documentation for the following Python 3 function
def f_to_dict(self, copy=True):
        if copy:
            return self._dict.copy()
        else:
            return self._dict

Response: Returns annotations as dictionary.


Instruction:
Can you tell what is the following Python 3 function doing
def f_get(self, *args):

        if len(args) == 0:
            if len(self._dict) == 1:
                return self._dict[list(self._dict.keys())[0]]
            elif len(self._dict) > 1:
                raise ValueError('Your annotation contains more than one entry: '
                                 '`%s` Please use >>f_get<< with one of these.' %
                                 (str(list(self._dict.keys()))))
            else:
                raise AttributeError('Your annotation is empty, cannot access data.')

        result_list = []
        for name in args:
            name = self._translate_key(name)
            try:
                result_list.append(self._dict[name])
            except KeyError:
                raise AttributeError('Your annotation does not contain %s.' % name)

        if len(args) == 1:
            return result_list[0]
        else:
            return tuple(result_list)

Response: Returns the annotations with name annotation_X.


Instruction:
Create a Python 3 function to
set annotations and annotations_X for all the items in args and kwargs.

Response:
def f_set(self, *args, **kwargs):
        """Sets annotations

        Items in args are added as `annotation` and `annotation_X` where
        'X' is the position in args for following arguments.

        """
        for idx, arg in enumerate(args):
            valstr = self._translate_key(idx)
            self.f_set_single(valstr, arg)

        for key, arg in kwargs.items():
            self.f_set_single(key, arg)


Instruction:
Given the following Python 3 function, write the documentation
def f_remove(self, key):
        key = self._translate_key(key)
        try:
            del self._dict[key]
        except KeyError:
            raise AttributeError('Your annotations do not contain %s' % key)

Response: Removes the key from the annotations


Instruction:
How would you explain what the following Python 3 function does
def f_ann_to_str(self):
        resstr = ''
        for key in sorted(self._dict.keys()):
            resstr += '%s=%s; ' % (key, str(self._dict[key]))
        return resstr[:-2]

Response: Returns all annotations lexicographically sorted as a concatenated string.


Instruction:
Explain what the following Python 3 code does
def make_ordinary_result(result, key, trajectory=None, reload=True):
    shared_data = result.f_get(key)
    if trajectory is not None:
        shared_data.traj = trajectory
    shared_data._request_data('make_ordinary')
    result.f_remove(key)
    if reload:
        trajectory.f_load_item(result, load_data=pypetconstants.OVERWRITE_DATA)
    return result

Response: Turns a given shared data item into an ordinary one.


Instruction:
Create a Python 3 function for
turning an ordinary data item into a shared one.

Response:
def make_shared_result(result, key, trajectory, new_class=None):
    """Turns an ordinary data item into a shared one.

    Removes the old result from the trajectory and replaces it.
    Empties the given result.

    :param result: The result containing ordinary data
    :param key: Name of ordinary data item
    :param trajectory: Trajectory container
    :param new_class:

        Class of new shared data item.
        Leave `None` for automatic detection.

    :return: The `result`

    """
    data = result.f_get(key)
    if new_class is None:
        if isinstance(data, ObjectTable):
            new_class = SharedTable
        elif isinstance(data, pd.DataFrame):
            new_class = SharedPandasFrame
        elif isinstance(data, (tuple, list)):
            new_class = SharedArray
        elif isinstance(data, (np.ndarray, np.matrix)):
            new_class = SharedCArray
        else:
            raise RuntimeError('Your data `%s` is not understood.' % key)
    shared_data = new_class(result.f_translate_key(key), result, trajectory=trajectory)
    result[key] = shared_data
    shared_data._request_data('make_shared')
    return result


Instruction:
Explain what the following Python 3 code does
def create_shared_data(self, **kwargs):
        if 'flag' not in kwargs:
            kwargs['flag'] = self.FLAG
        if 'data' in kwargs:
            kwargs['obj'] = kwargs.pop('data')
        if 'trajectory' in kwargs:
            self.traj = kwargs.pop('trajectory')
        if 'traj' in kwargs:
            self.traj = kwargs.pop('traj')
        if 'name' in kwargs:
            self.name = kwargs.pop['name']
        if 'parent' in kwargs:
            self.parent = kwargs.pop('parent')
            if self.name is not None:
                self.parent[self.name] = self
        return self._request_data('create_shared_data', kwargs=kwargs)

Response: Creates shared data on disk with a StorageService on disk.


Instruction:
Can you generate the documentation for the following Python 3 function
def _request_data(self, request, args=None, kwargs=None):
        return self._storage_service.store(pypetconstants.ACCESS_DATA,
                                           self.parent.v_full_name,
                                           self.name,
                                           request, args, kwargs,
                                           trajectory_name=self.traj.v_name)

Response: This method is used to store the data for the current node.


Instruction:
Write a Python 3 script to
return the actula node of the underlying data.

Response:
def get_data_node(self):
        """Returns the actula node of the underlying data.

        In case one uses HDF5 this will be the HDF5 leaf node.

        """
        if not self._storage_service.is_open:
            warnings.warn('You requesting the data item but your store is not open, '
                          'the item itself will be closed, too!',
                          category=RuntimeWarning)
        return self._request_data('__thenode__')


Instruction:
How would you explain what the following Python 3 function does
def _supports(self, item):
        result = super(SharedResult, self)._supports(item)
        result = result or type(item) in SharedResult.SUPPORTED_DATA
        return result

Response: Checks if outer data structure is supported.


Instruction:
How would you code a function in Python 3 to
call the corresponding function of the shared data item

Response:
def create_shared_data(self, name=None, **kwargs):
        """Calls the corresponding function of the shared data item"""
        if name is None:
            item = self.f_get()
        else:
            item = self.f_get(name)
        return item.create_shared_data(**kwargs)


Instruction:
How would you code a function in Python 3 to
target function that manipulates the trajectory and stores the manipulated data in the trajectory and the multiprocessing safe storage service.

Response:
def manipulate_multiproc_safe(traj):
    """ Target function that manipulates the trajectory.

    Stores the current name of the process into the trajectory and
    **overwrites** previous settings.

    :param traj:

        Trajectory container with multiprocessing safe storage service

    """

    # Manipulate the data in the trajectory
    traj.last_process_name = mp.current_process().name
    # Store the manipulated data
    traj.results.f_store(store_data=3)


Instruction:
How would you explain what the following Python 3 function does
def _unlock(self, name, client_id, request_id):
        if name in self._locks:
            other_client_id, other_request_id = self._locks[name]
            if other_client_id != client_id:
                response = (self.RELEASE_ERROR + self.DELIMITER +
                            'Lock `%s` was acquired by `%s` (old request id `%s`) and not by '
                            '`%s` (request id `%s`)' % (name,
                                                        other_client_id,
                                                        other_request_id,
                                                        client_id,
                                                        request_id))
                self._logger.error(response)
                return response
            else:
                del self._locks[name]
                return self.RELEASED
        else:
            response = (self.RELEASE_ERROR + self.DELIMITER +
                        'Lock `%s` cannot be found in database (client id `%s`, '
                        'request id `%s`)' % (name, client_id, request_id))
            self._logger.error(response)
            return response

Response: Handles unlocking a non - existent lock.