Good evening,
I have been trying to implement my first simple pipeline algorithm: I want to trade the first 30 minutes of trading based on the overnight returns.
Unfortunately I haven't been able to run my backtest because I keep receiving the error:

UnsupportedOrderParameters: Passing non-Asset argument to 'order()' is not supported. Use 'sid()' or 'symbol()' methods to look up an Asset.
There was a runtime error on line 76.

This is my code that is giving me troubles:

from quantopian.algorithm import attach_pipeline, pipeline_output  
from quantopian.pipeline import Pipeline  
from quantopian.pipeline import CustomFactor  
from quantopian.pipeline.data.builtin import USEquityPricing  
from quantopian.pipeline.data import morningstar  
import numpy as np  
import pandas as pd  
from datetime import date, timedelta  
from quantopian.pipeline.filters.morningstar import Q500US

class get_open_price(CustomFactor):  
    inputs = [USEquityPricing.open]  
    window_length = 1  
    def compute(self, today, assets, out, open):  
        out[:] = open[0]  
class get_close_price(CustomFactor):  
    inputs = [USEquityPricing.close]  
    window_length = 1  
    def compute(self, today, assets, out, close):  
        out[:] = close[0]  
class get_overnight_returns(CustomFactor):  
    inputs = [USEquityPricing.close, USEquityPricing.open]  
    window_length = 1  
    def compute(self, today, assets, out, close, open):  
        out[:] = (open[0]-close[0])/close[0]

def initialize(context):  
    #schedule function to change position  
    #when the market opens the next morning  
    schedule_function(rebalance, date_rules.every_day(), time_rules.market_open(minutes=1))  
    #schedule function to close all positions 30 minutes  
    #after the market opens everyday  
    schedule_function(rebalance2, date_rules.every_day(), time_rules.market_open(minutes=31))  
    #leverage for long positions  
    context.long_leverage = 1  
    #leverage for short positions  
    context.short_leverage = -1  
    # Base universe set to the Q500US.  
    base_universe=Q500US()  
    #Create pipeline and attach it to algorithm.  
    pipe = Pipeline()  
    attach_pipeline(pipe, 'my_pipeline')  
    today_open = get_open_price()  
    pipe.add(today_open, 'today_open')  
    yesterday_close = get_close_price()  
    pipe.add(yesterday_close, 'yesterday_close')  
    returns = get_overnight_returns()  
    pipe.add(returns,'overnight_returns')  
    returns_rank = returns.rank(mask=base_universe)  
    pipe.add(returns_rank,'returns_rank')  
    pipe.set_screen(base_universe)  

def before_trading_start(context, data):  
    # Call pipelive_output to get the output  
    context.output = pipeline_output('my_pipeline')  
    context.Mlongs_list = context.output['returns_rank'].iloc[-25:]  
    context.Mshorts_list = context.output['returns_rank'].iloc[:25]  
    context.universe = context.Mlongs_list.index.union(context.Mshorts_list.index)

#This function rebalances my portfolio when the market opens  
#I go long if the "overnight returns" are positive and  
#I go short otherwise.  
#This happens only for the best-performing 5% stocks and  
#for the worst-performing 5% stocks  
def rebalance(context, data):  
    #compute weights  
    long_weight = context.long_leverage / float(len(context.Mlongs_list))  
    short_weight = context.short_leverage / float(len(context.Mshorts_list))  
    #If overnight returns are negative go long based on my  
    #long list, otherwise I don't invest.  
    for Mlong in context.Mlongs_list.index:  
      if data.can_trade(Mlong):  
          order_target_percent(context.Mlongs_list, long_weight)  
    #If overnight returns are positive go short based on my  
    #short list, otherwise I don't invest.  
    for Mshort in context.Mshorts_list.index:  
      if data.can_trade(Mshort):  
          order_target_percent(context.Mshorts_list, short_weight)  
#This function rebalances my portfolio by closing all positions  
#30 minutes after the market opens in the next morning  
def rebalance2(context, data):  
    #I close every position 30 minutes after the market opens  
    for stock in context.universe:  
            order_target(stock, 0)  

Can anybody please give me a hand in fixing this issue?
Thanks a lot in advance,
Mattia