from quantopian.algorithm import attach_pipeline, pipeline_output  
from quantopian.pipeline import Pipeline  
from quantopian.pipeline.factors import AverageDollarVolume



def initialize(context):  
    pipe = Pipeline()  
    pipe = attach_pipeline(pipe, name='my_pipeline')  
    dollar_volume = AverageDollarVolume(window_length=5)  
    pipe.add(dollar_volume, 'dollar_volume')  
    high_dollar_volume = dollar_volume.top(5)  
    pipe.set_screen(high_dollar_volume)  
def before_trading_start(context, data):  
    results = pipeline_output('my_pipeline')  
    print results.head(5)  
    context.pipeline_results = results  

So I'm not really sure what I am missing. I am trying to create a list of the five highest volume stocks over the past five days so that my algorithm can trade those. For some reason I can't get the algorithm to print the results of my screen on the pipeline. Any suggestions? I came up with this piece of code by combining these two pieces of code from the help page:

from quantopian.algorithm import attach_pipeline, pipeline_output  
from quantopian.pipeline import Pipeline  
from quantopian.pipeline.factors import AverageDollarVolume  
...
def initialize(context):  
    pipe = Pipeline()  
    attach_pipeline(pipe, name='my_pipeline')

    # Construct an average dollar volume factor and add it to the pipeline.  
    dollar_volume = AverageDollarVolume(window_length=30)  
    pipe.add(dollar_volume, 'dollar_volume')

    # Define high dollar-volume filter to be the top 10% of securities by dollar volume.  
    high_dollar_volume = dollar_volume.percentile_between(90, 100)

    # Filter to only the top dollar volume securities.  
    pipe.set_screen(high_dollar_volume)  

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 SimpleMovingAverage

def initialize(context):

    # Create and attach an empty Pipeline.  
    pipe = Pipeline()  
    pipe = attach_pipeline(pipe, name='my_pipeline')

    # Construct Factors.  
    sma_10 = SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=10)  
    sma_30 = SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=30)

    # Construct a Filter.  
    prices_under_5 = (sma_10 < 5)

    # Register outputs.  
    pipe.add(sma_10, 'sma_10')  
    pipe.add(sma_30, 'sma_30')

    # Remove rows for which the Filter returns False.  
    pipe.set_screen(prices_under_5)

def before_trading_start(context, data):  
    # Access results using the name passed to `attach_pipeline`.  
    results = pipeline_output('my_pipeline')  
    print results.head(5)

    # Store pipeline results for use by the rest of the algorithm.  
    context.pipeline_results = results