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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def scipy_constraints(self, constraints):
 """ Returns all constraints in a scipy compatible format. :param constraints: List of either MinimizeModel instances (this is what is provided by :class:`~symfit.core.fit.Fit`), :class:`~symfit.core.fit.BaseModel`, or :class:`sympy.core.relational.Relational`. :return: dict of scipy compatible statements. """

        cons = []
        types = {  # scipy only distinguishes two types of constraint.
            sympy.Eq: 'eq', sympy.Ge: 'ineq',
        }

        for constraint in constraints:
            if isinstance(constraint, MinimizeModel):
                # Typically the case when called by `Fit
                constraint_type = constraint.model.constraint_type
            elif hasattr(constraint, 'constraint_type'):
                # Model object, not provided by `Fit`. Do the best we can.
                if self.parameters != constraint.params:
                    raise AssertionError('The constraint should accept the same'
                                         ' parameters as used for the fit.')
                constraint_type = constraint.constraint_type
                constraint = MinimizeModel(constraint, data=self.objective.data)
            elif isinstance(constraint, sympy.Rel):
                constraint_type = constraint.__class__
                constraint = self.objective.model.__class__.as_constraint(
                    constraint, self.objective.model
                )
                constraint = MinimizeModel(constraint, data=self.objective.data)
            else:
                raise TypeError('Unknown type for a constraint.')
            con = {
                'type': types[constraint_type],
                'fun': constraint,
                }
            cons.append(con)
        cons = tuple(cons)
        return cons