def METHOD_NAME(cls):
    super().METHOD_NAME()
    cls.loader = FakeModelLoader(cls.env, cls.__module__)
    cls.loader.backup_registry()
    from .fake_models import MisKpiDataTestItem
    cls.loader.update_registry((MisKpiDataTestItem,))
    report = cls.env["mis.report"].create(dict(name="test report"))
    cls.kpi1 = cls.env["mis.report.kpi"].create(
        dict(
            report_id=report.id,
            name="k1",
            description="kpi 1",
            expression="AccountingNone",
        )
    )
    cls.expr1 = cls.kpi1.expression_ids[0]
    cls.kpi2 = cls.env["mis.report.kpi"].create(
        dict(
            report_id=report.id,
            name="k2",
            description="kpi 2",
            expression="AccountingNone",
        )
    )
    cls.expr2 = cls.kpi2.expression_ids[0]
    cls.kd11 = cls.env["mis.kpi.data.test.item"].create(
        dict(
            kpi_expression_id=cls.expr1.id,
            date_from="2017-05-01",
            date_to="2017-05-10",
            amount=10,
        )
    )
    cls.kd12 = cls.env["mis.kpi.data.test.item"].create(
        dict(
            kpi_expression_id=cls.expr1.id,
            date_from="2017-05-11",
            date_to="2017-05-20",
            amount=20,
        )
    )
    cls.kd13 = cls.env["mis.kpi.data.test.item"].create(
        dict(
            kpi_expression_id=cls.expr1.id,
            date_from="2017-05-21",
            date_to="2017-05-25",
            amount=30,
        )
    )
    cls.kd21 = cls.env["mis.kpi.data.test.item"].create(
        dict(
            kpi_expression_id=cls.expr2.id,
            date_from="2017-06-01",
            date_to="2017-06-30",
            amount=3,
        )
    )