We thought about implementing long short-term memory (LSTM) in HydPy, which currently seems to be the most promising artificial neural network type for some hydrological applications (e.g. flood forecasting). I open this issue as a notebook for the following deeper discussions. The key questions are:

• What is the best way to implement LSTM in HydPy?
• What would be the advantages and disadvantages of including LSTM in HydPy (compared to combining HydPy and an independent LSTM library in Python scripts)?
• Depending on the expected necessary work, do we really want to do it?