import pandas  
import numpy as np  
import talib

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  
from quantopian.pipeline.factors import SimpleMovingAverage

class AvgDailyDollarVolume(CustomFactor):  
    inputs = [USEquityPricing.close, USEquityPricing.volume]  
    window_length = 30  
    def compute(self, today, assets, out, close_price, volume):  
        dollar_volume = close_price * volume  
        avg_dollar_volume = np.mean(dollar_volume, axis=0)  
        out[:] = avg_dollar_volume  
#class Income_statement(CustomFactor):  
    # Pre-declare inputs and window_length  
    #inputs = [morningstar.income_statement]  
    #window_length = 1  
    # Compute market cap value  
    #def compute(self, today, assets, out, income):  
        #out[:] = income  
class MarketCap(CustomFactor):  
    # Pre-declare inputs and window_length  
    inputs = [USEquityPricing.close, morningstar.valuation.shares_outstanding]  
    window_length = 1  
    # Compute market cap value  
    def compute(self, today, assets, out, close, shares):  
        out[:] = close[-1] * shares[-1]  
def initialize(context):  
    #context.size = float(context.portfolio.cash / 20)  & (sma_long ) & (sma_short)  
    context.shorting = True  
    context.shorts = []  
    context.max_positions = 26  
    pipe = Pipeline()  
    attach_pipeline(pipe, 'mypipe')  
    sma_200 = SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=200)  
    sma_100 = SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=100)  
    sma_50 = SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=50)  
    sma_long =  ( (sma_100 > sma_200) & (sma_50 > sma_100))  
    sma_short = ( (sma_100 < sma_200) & (sma_50 < sma_100))  
    #pipe.add(sma_200, 'sma_200')  
    #pipe.add(sma_115, 'sma_115')    # and sma_long and sma_short  & (sma_long) & (sma_short )  
    #pipe.add(sma_35, 'sma_35')       # (sma_35 > sma_115) &  &  (sma_35 < sma_115))  
    pipe.add(sma_short, 'sma_short')  
    pipe.add(sma_long, 'sma_long')  
    mkt_cap = MarketCap()  
    pipe.add(mkt_cap, 'mkt_cap')  
    #income = Income_statement()  
    #pipe.add(income, 'income')  
    dollar_volume = AvgDailyDollarVolume()  
    pipe.add(dollar_volume, 'dollar_volume')  
    dv_filter = (dollar_volume > 10*10**6) & (dollar_volume < 30 * 10**6)  
    mkt_cap_fltr= (mkt_cap > 10*10**8) & (mkt_cap < 20*10**8)  
    pipe.set_screen (sma_long & sma_short & dv_filter & mkt_cap_fltr)  

    schedule_function(logic,date_rules.every_day(),time_rules.market_close())  
    #schedule_function(logic,date_rules.every_day(),time_rules.market_close(minutes=380))

def before_trading_start(context, data):

    context.output = pipeline_output('mypipe')  
    #log.info(len(context.output))  
    context.sma_long = context.output.sort(['sma_long'], ascending=True).iloc[:100]  
    log.info(len(context.sma_long))  
    log.info("\n" + str(context.sma_long.head(10)))  
    context.sma_short = context.output.sort(['sma_short'], ascending=True).iloc[:100]  
    log.info(len(context.sma_short))  
    log.info("\n" + str(context.sma_short.head(10)))  

    update_universe(context.sma_long.index.union(context.sma_short.index))  

def logic(context, data):  
    pass  
def handle_data(context, data):  
    pass  

That error typically means that your pipeline is empty on the first day of trading - you've written a set of criteria that nothing made it through. I started visualizing your pipeline, but I ran out of time - hopefully it's useful to you.

Thank you Dan for your reply.

If I use only 1 filter in pipe.set_screen, "**sma_long**" or "**sma_short**" it works fine. The problem is when I use both of them.

I'm new to coding so just bear with me.

Thanks!

There is a problem in your logic. I'll put the problematic bits together:

sma_long =  ( (sma_100 > sma_200) & (sma_50 > sma_100))  
sma_short = ( (sma_100 < sma_200) & (sma_50 < sma_100))  
pipe.set_screen (sma_long & sma_short)  

If you substitute sma_long and sma_short in the screen,

pipe.set_screen((sma_100 > sma_200) & (sma_50 > sma_100) & (sma_100 < sma_200) & (sma_50 < sma_100))  

Nothing will ever satisfy this screen.

Sunil

Thank you Sunil.

I want to create a universe where I can buy stocks with simple moving average SMA50 >SMA100 >SMA200, and short stocks with

simple moving average SMA50<SMA100 <SMA200. Is there a way to do this using the Pipeline API ?

Thanks.