How do I perform multi-step forecasting on LSTM trained with multiple observations of a sequence?
ConvLSTM, keras has an implementation, therefore you can go with Python itself.

If you want multiple outputs from the LSTM, you can have look at return_sequences and return_state feature in LSTM layers. Default values for them are None, But if you give True you can get multiple outputs for each timestep, and for everyone.

This excellent blog post helped me understand them.