I am considering a python script for the pick 3 type games that can take variable parameter input to adjust the settings. 

Something like a scan of X number of draws to determine hot, neutral and cold, and then look out Y future draws to determine the composition from the hot/neutral/cold group.

Such that running the formula

displayComposition(30,10)

Would take the last X+Y draws (in this case 40), grab the frequency distribution of the X (30) draws, split them into hot/neutral/cold, then display the next Y draws (in this case 10) with a composition such as HNH or CCN, to help determine the composition of hot, neutral and cold numbers that were drawn.

The point of the variables is simple, I don't know the ideal number of draws to do a recent history on, so this allows for some experimentation.

Because it will be modular, it will be able to be called several times in one run with different parameters, such as 

displayComposition(30,10)

displayComposition(250,20)

displayComposition(1000,7)

Since the composition would change with each change in X, we would be searching for some general guideline in the Y output, such as a higher amount of HNN draws when using X history...

I can do a great number of tasks with Python, but I am still sure I am not asking the right questions... after over 20 years of ideas, mostly in excel, I am losing motivation. Therefore I need some different avenues to explore, and one which I have neglected is the analysis of shorter term trends. Everything up to now has been done with entire game histories.

So a grouping of the top 3 hot, the middle 4 neutral and the last 3 cold seems like a fair split.

Output looking like

H1 = 7

H2 = 4

H3 = 2

N1 = 6

...

C3 =1

Would be the result of the analysis, and the output of the Y draws would look like

761 - H1, N1, C3

...

442 - H2, H2, H3

The generalization, which group it comes from, such as H, can be further refined with the digit that represents WHICH H it was, such as H1 being the hottest of the hots and C3 being the coldest of the colds.

Being able to change the number of draws out with Y can help to determine just how long the trends can extend, and also open the door to a sliding back test by partitioning the history into chunks of size X+Y.

There are still plenty of unknowns such as optimal values for X and Y, but it seems like a fitting start to begin short term trend analysis.