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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def splot(axes="gca", smoothing=5000, degree=5, presmoothing=0, plot=True, spline_class=spline_single, interactive=True, show_derivative=1):
 """ gets the data from the plot and feeds it into splint returns an instance of spline_single axes="gca" which axes to get the data from. smoothing=5000 spline_single smoothing parameter presmoothing=0 spline_single data presmoothing factor (nearest neighbor) plot=True should we plot the result? spline_class=spline_single which data class to use? interactive=False should we spline fit interactively or just make a spline_single? """


    if   axes=="gca": axes = _pylab.gca()

    xlabel = axes.xaxis.label.get_text()
    ylabel = axes.yaxis.label.get_text()
    
    xdata = axes.get_lines()[0].get_xdata()
    ydata = axes.get_lines()[0].get_ydata()

    if interactive:
        return splinteractive(xdata, ydata, smoothing, degree, presmoothing, spline_class, xlabel, ylabel)
    else:
        return spline_class(xdata, ydata, smoothing, degree, presmoothing, plot, xlabel, ylabel)