Python: forecast unevenly spaced time-series?
I reccomend you to use Prophet: 


  Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.


In the documentation you can see that is really easy to implement in python. 

Also you could convert the problem to a supervised learning one. You can read this blog where they make an introduction of how to face the problem.