---
# System prepended metadata

title: Untitled

---

    
    @dataclass
    class VarStore:
        data: defaultdict(lambda: pd.DataFrame())
        prep_data: defaultdict(lambda: pd.DataFrame())
        prods: list
        years: list
        sale_dirs: list
        inequations: list

        def auto_mods(self):
            # global data, prep_data
            ineq_mods = ['coal_preservation']
            obj_mods = []
            for mod in ('sales_down_limits',
                        'sales_up_limits',
                        'prod_ub',
                        'prod_lb',
                        'log_limits'):
                if mod in self.prep_data.keys():
                    ineq_mods.append(mod)
            for mod in ('log_costs', 'capex'):
                if mod in self.prep_data.keys():
                    obj_mods.append(mod)
            if 'var_costs_prod' in self.prep_data.keys():
                obj_mods.append('prod')
            if 'prices' in self.prep_data.keys():
                obj_mods.append('sold_simple')

            print('ineq_mods:', ineq_mods)
            print('obj_mods:', obj_mods)
                return ineq_mods, obj_mods``