summarizing time series dataset: extract time window sliding, change points, pattern seasonality in time series

I need to detect list of change points in time series dataset (temperature), and I need to split dataset into set of classes (patterns) and detect seasonality of each class (pattern). for example suppose that we create 2-classes named called and hot, each class contains readings that represent each state, I need to know seasonality of these state over the whole time period so that I can summarize dataset as hot state occurs from the time X to Y over month Z and from time ... to ... over month ... - it is preferable if there is a solution written in python/C++/C#