Helper library from Curvenote for data science in Jupyter notebooks

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Project description

curvenote

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

## Installation

    ~$ python -m pip install curvenote

Summary

  • 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)
  state.observe(with_state(my_update_fn))

  # observe a single registered widget
  def wave_1_observer(evt):
    pass
  state.register_widget_observer("wave_1_amp", wave_1_observer)

  # observe a single trait
  def trait_observer(evt):
    pass
  state.register_widget_observer("my_dict", trait_observer)

  # display state changes for debugging
  from IPython.display import display
  display(state.outlet)

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