Any comment please? I don't know if it is feasible in current Pipeline framework to redirect the output of one custom factor to the input of another custom factor? Can anyone answer my question? Thanks!

Yes, have a look at here: https://www.quantopian.com/posts/new-pipeline-features-slicing-and-correlation-slash-regression-methods

Here is what David Michalowicz said about using factors as input of other factor:

"[...] is now allowed for a select few factors deemed safe for use as inputs. This includes Returns and any factors created from rank or zscore. The main reason that these factors can be used as inputs is that they are comparable across splits. Returns, rank and zscore produce normalized values, meaning that they can be meaningfully compared in any context."

Anyway, if you are sure your factor is safe to be used as input to another factor define window_safe = True in the factor class and pipeline won't complain.

And this is an example:

from quantopian.pipeline.factors import CustomFactor, Returns

class LogReturns(CustomFactor):  
    inputs = [Returns(window_length=2)]  
    window_length = 1  
    window_safe = True

    def compute(self, today, assets, out, returns):  
        out[:] = np.log( (returns+1) )


class MeanReturn(CustomFactor):  
    inputs = [Returns(window_length=2)]  
    def compute(self, today, assets, out, returns):  
        out[:] = np.nanmean(returns, axis=0)


returns = Returns(window_length=50)  
technical1  = MeanReturn(inputs=[returns], window_length=252, mask=my_universe)

log_returns = LogReturns(inputs=[returns], mask=my_universe)  
technical2  = MeanReturn(inputs=[log_returns], window_length=252, mask=my_universe)  

Thank you so much, Luca!

Hello, would you know how to use RSI output for EMA custom function as input.