I see what you are doing. Don't worry about the code for now. I will start with excel, learn python for the future and use the retail tools. I think just getting a few simple spreads down first is more important.
This is one of the better seasonal charts I found on Scarr. I understand that in terms of mean reversion or stationarity, this is probably not as good as a butterfly or double butterfly. In any case, I just wanted to compare this with the chart below. In a lot of the seasonal spreads, I've noticed that one contract will lead and then lag. This relationship changes over time so we need to establish which contract is leading and which is lagging. From a little research, I've found a couple of ways to do this: 1) Visually. Eyeball the chart. 2) Scatter plots. 3) Use the granger causality test. This assumes that data is stationary although there are some causality tests for non stationary data. However, since we are trading a spread, we hope to find a stationary time series anyway. Here is a link to a Wilmott thread on the subject: http://www.wilmott.com/messageview.cfm?catid=8&threadid=73473.