I've been trying to port my python algorithms from Quantopian to QC. For reasons that are not clear to me, the same functionality that I used in python at QP does not work at QP. 

https://www.quantconnect.com/terminal/processCache?request=embedded_backtest_1e30c81c3121cbcabf705974ca173e2c.html

Try running this algo with resolution in "take_profit"  function set to "Minute".  It runs fine for a while then runs in to what I presume are nan's.  This is my error:

Runtime Error: Python.Runtime.PythonException: KeyNotFoundException : 'TMF' wasn't found in the Slice object, likely because there was no-data at this moment in time and it wasn't possible to fillforward historical data. Please check the data exists before accessing it with data.ContainsKey("TMF")

So I presume it cannot find a corresponding value in one of the columns of the history dataframe. My ported code had originally contained command ").bfill().ffill()"  to fill out any NAN's in the data, but this bombed.

My final recourse was to use try / except to trap for the error and skip over it if encountered but that is obviously not an acceptable solution. I've got to find out how to forwad and backfill missing values.

Runtime Error: Python.Runtime.PythonException: AttributeError : '1, Culture=neutral, PublicKeyToken=null]]' object has no attribute 'bfill'

Also, I have been developing in the online IDE which does not allow me to inspect objects and variables and do any serious debugging. I have installed LEAN on the Google Cloud Engine but not yet figured out how to run my tests from there. I've set up Jypyter to run from my browser off of Google Cloud install but not clear to me how to point this to QC server to run and debut programs there. Any tips/tutorials would be much appreciated.

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