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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 moma(self, wt_fluxes):
 """Minimize the redistribution of fluxes using Euclidean distance. Minimizing the redistribution of fluxes using a quadratic objective function. The distance is minimized by minimizing the sum of (wild type - knockout)^2. Args: wt_fluxes: Dictionary of all the wild type fluxes that will be used to find a close MOMA solution. Fluxes can be expiremental or calculated using :meth: get_fba_flux(objective). """

        reactions = set(self._adjustment_reactions())
        v = self._v

        obj_expr = 0
        for f_reaction, f_value in iteritems(wt_fluxes):
            if f_reaction in reactions:
                # Minimize the Euclidean distance between the two vectors
                obj_expr += (f_value - v[f_reaction])**2

        self._prob.set_objective(obj_expr)
        self._solve(lp.ObjectiveSense.Minimize)