Hi, When I run this code in 'research' it works like a charm, when I run it in the IDE, the context.output is empty. Any help?

from quantopian.algorithm import attach_pipeline, pipeline_output  
from quantopian.pipeline import Pipeline  
from quantopian.pipeline.data import morningstar  
from quantopian.pipeline.classifiers.morningstar import Sector  
from quantopian.pipeline.filters.morningstar import Q500US  
from quantopian.pipeline.factors import SimpleMovingAverage  
from quantopian.pipeline.data.builtin import USEquityPricing  
import pandas

def initialize(context):  
    # Schedule our rebalance function to run at the start of each week.  
    schedule_function(my_rebalance, date_rules.week_start(), time_rules.market_open(hours=3))  
    schedule_function(my_other_rebalance, date_rules.week_end(), time_rules.market_open(hours=3))  
    # Create our pipeline and attach it to our algorithm.  
    my_pipe = make_pipeline()  
    attach_pipeline(my_pipe, name='my_pipeline')  


def make_pipeline():  
    base_universe = Q500US()  
    exchange = morningstar.share_class_reference.exchange_id.latest  
    morningstar_sector = Sector()  
    nyse_filter = exchange.eq('NYS')  
    mean_close_7 = SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=7, mask=base_universe)  
    latest_close = USEquityPricing.close.latest  
    percent_difference = (((mean_close_7 - latest_close) / (mean_close_7)) * 100)  
    myfilter = (percent_difference > 1.00)  
    return Pipeline(columns={"% Diff" : percent_difference,  
                            "Over" : myfilter,  
                            "Exchange" : exchange,  
                            "Sector Code" : morningstar_sector}, screen=(myfilter & nyse_filter))

def before_trading_start(context, data):  
    context.output = pipeline_output(name='my_pipeline')  
    context.movers = context.output[context.output["Over"]].index.tolist()  
    length = len(context.movers)  
    print length  
    print context.movers



def my_rebalance(context, data):  
    for security in context.movers:  
        print (security)  
        if data.can_trade(security):  
            order_target_percent(security, (1/length))  
            log.info("Buying %s" % (security.symbol))

def my_other_rebalance(context, data):  
    for security in context.movers:  
        print (security)  
        current_price = data.current(security, 'price')  
        hist_price = data.history(asset=security, fields='price', bar_count=1, frequency='1w')  
        if data.can_trade(security) and current_price > hist_price:  
                order_target_percent(security, 0)  
                log.info("Buying %s" % (security.symbol))  
        else:  
            continue