code: def minimize_l1(self, weights={}):
          
  
          if self._z is None:
              self._add_minimization_vars()
  
          objective = self._z.expr(
              (reaction_id, -weights.get(reaction_id, 1))
              for reaction_id in self._model.reactions)
          self._prob.set_objective(objective)
  
          self._solve()
docs: Solve the model by minimizing the L1 norm of the fluxes.
  
          If the weights dictionary is given, the weighted L1 norm if minimized
          instead. The dictionary contains the weights of each reaction
          (default 1).