Esempio n. 1
0
    def _collect_explicit_graded(cls, block_structure):
        """
        Collect the 'explicit_graded' field for every block.
        """
        def _set_field(block_key, field_value):
            """
            Sets the explicit graded field to the given value for the
            given block.
            """
            block_structure.set_transformer_block_field(
                block_key, cls, cls.EXPLICIT_GRADED_FIELD_NAME, field_value)

        def _get_field(block_key):
            """
            Gets the explicit graded field to the given value for the
            given block.
            """
            return block_structure.get_transformer_block_field(
                block_key, cls, cls.EXPLICIT_GRADED_FIELD_NAME)

        block_types_to_ignore = {'course', 'chapter', 'sequential'}

        for block_key in block_structure.topological_traversal():
            if block_key.block_type in block_types_to_ignore:
                _set_field(block_key, None)
            else:
                explicit_field_on_block = get_field_on_block(
                    block_structure.get_xblock(block_key), 'graded')
                if explicit_field_on_block is not None:
                    _set_field(block_key, explicit_field_on_block)
                else:
                    values_from_parents = [
                        _get_field(parent)
                        for parent in block_structure.get_parents(block_key)
                        if parent.block_type not in block_types_to_ignore
                    ]
                    non_null_values_from_parents = [
                        value for value in values_from_parents if not None
                    ]
                    explicit_from_parents = functools_reduce(
                        lambda x, y: x or y, non_null_values_from_parents,
                        None)
                    _set_field(block_key, explicit_from_parents)
Esempio n. 2
0
    def _collect_explicit_graded(cls, block_structure):
        """
        Collect the 'explicit_graded' field for every block.
        """

        def _set_field(block_key, field_value):
            """
            Sets the explicit graded field to the given value for the
            given block.
            """
            block_structure.set_transformer_block_field(block_key, cls, cls.EXPLICIT_GRADED_FIELD_NAME, field_value)

        def _get_field(block_key):
            """
            Gets the explicit graded field to the given value for the
            given block.
            """
            return block_structure.get_transformer_block_field(block_key, cls, cls.EXPLICIT_GRADED_FIELD_NAME)

        block_types_to_ignore = {"course", "chapter", "sequential"}

        for block_key in block_structure.topological_traversal():
            if block_key.block_type in block_types_to_ignore:
                _set_field(block_key, None)
            else:
                explicit_field_on_block = get_field_on_block(block_structure.get_xblock(block_key), "graded")
                if explicit_field_on_block is not None:
                    _set_field(block_key, explicit_field_on_block)
                else:
                    values_from_parents = [
                        _get_field(parent)
                        for parent in block_structure.get_parents(block_key)
                        if parent.block_type not in block_types_to_ignore
                    ]
                    non_null_values_from_parents = [value for value in values_from_parents if not None]
                    explicit_from_parents = functools_reduce(lambda x, y: x or y, non_null_values_from_parents, None)
                    _set_field(block_key, explicit_from_parents)