I am trying to build a factor that measures the change in earnings using the morning star data. So I am trying to compare the current day's earnings with the previous day's earnings. I keep getting the following error and it points to the line where I am trying to access earnings data.

"zipline.pipeline.term.getitem() expected a value of type zipline.assets._assets.Asset for argument 'key', but got int instead."

Here is the code:

"""
This is a template algorithm on Quantopian for you to adapt and fill in.  
"""
from quantopian.algorithm import attach_pipeline, pipeline_output  
from quantopian.pipeline import Pipeline  
from quantopian.pipeline.data.builtin import USEquityPricing  
from quantopian.pipeline.factors import AverageDollarVolume  
from quantopian.pipeline.data import morningstar  
def initialize(context):  
    """  
    Called once at the start of the algorithm.  
    """  
    context.leverage_long = 0.5  
    context.leverage_short = -0.5  
    # Rebalance every day, 1 hour after market open.  
    schedule_function(my_rebalance, date_rules.every_day(), time_rules.market_open(hours=0.25))  
    # Record tracking variables at the end of each day.  
    schedule_function(my_record_vars, date_rules.every_day(), time_rules.market_close())  
    # Create our dynamic stock selector.  
    pipe = Pipeline()  
    pipe = attach_pipeline(pipe, name='my_pipeline')  
    earnings_change = (morningstar.earnings_report.basic_eps[-1])*(morningstar.valuation.shares_outstanding[-1])-(morningstar.earnings_report.basic_eps[-2]*morningstar.valuation.shares_outstanding[-2])  
    earnings_factor = earnings_change<0  
    #pipe.add(dollar_volume,'vol')  
    pipe.add(earnings_change,'ear_chg')  
    pipe.set_screen(earnings_factor)  

def before_trading_start(context, data):  
    """  
    Called every day before market open.  
    """  
    context.output = pipeline_output('my_pipeline')  
    # These are the securities that we are interested in trading each day.  
    context.security_list = context.output.index  
    print context.output.head(2)  
def my_assign_weights(context, data):  
    """  
    Assign weights to securities that we want to order.  
    """  
    pass  
def my_rebalance(context,data):  
    """  
    Execute orders according to our schedule_function() timing.  
    """  
    pass  
def my_record_vars(context, data):  
    """  
    Plot variables at the end of each day.  
    """  
    pass  
def handle_data(context,data):  
    """  
    Called every minute.  
    ""