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Helper library from Curvenote for data science in Jupyter notebooks

Project description


The Curvenote helper library for working in Jupyter Notebooks with Python kernels

## Installation

    ~$ python -m pip install curvenote


  • stash save a dict or pandas dataframe in a cell output without diaplying the data

         from curvenote import stash
         stash('myvars', myvars)
  • AppState a traitlet based class to help manage state in ipywidgets ui's

      from curvenote import AppState, with_state
      state = AppState()
      # register a widget in state
      wave_1_amp = FloatSlider(1.0, min=0.1, max=5.0, step=0.1, description="1 - Amp")
      state.register_stateful_widget(wave_1_amp, "wave_1_amp", Float(1.0))
      # register any trailet as a propery
      state.register_stateful_property("my_dict", Dict(dict(A="hello", B="world", C=1)))
      # observe the entire state
      def my_update_fn(state):
        some_calc_function(state.wave_1_amp, state.my_dict)
      # observe a single registered widget
      def wave_1_observer(evt):
      state.register_widget_observer("wave_1_amp", wave_1_observer)
      # observe a single trait
      def trait_observer(evt):
      state.register_widget_observer("my_dict", trait_observer)
      # display state changes for debugging
      from IPython.display import display

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