human
!pip3 install scipy

from scipy.integrate import odeint 
# https://perso.crans.org/besson/publis/notebooks/Runge-Kutta_methods_for_ODE_integration_in_Python.html

%matplotlib notebook    
import scipy.optimize as so
import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np

V = lambda r, α, β, γ, λ: r**β + γ*(γ+1)/r**2 + λ/r**α

# potential parameters
αβγλ = 4, 2, 5, 100

# Energy Eigenvalues
Estop = 34
Espectrum = [15.54392598171621432978,
             19.92653800987177727185,
             24.26619272363845153429,
             28.57312197406556227733,
             Estop]

# Draw a line for each eigenvalue
EigenLine = []
for Ei in Espectrum:
    Vr = lambda x: V(x, *αβγλ) - Ei
    rL, rR = so.newton(Vr, 1e-1), so.newton(Vr, 6)
    EigenLine += [[[rL, rR], [Ei, Ei]]]
    
# create colors for the lines
Eimin = .7 * Espectrum[0]/Espectrum[-1]
Eimax = .7
cm_subsection = np.linspace(Eimin, Eimax, len(Espectrum)) 
colors = [ cm.hot_r(x) for x in cm_subsection ]

Scale = 4.5
plt.figure(figsize=(Scale, Scale*1.618))
for i, Ei in enumerate(EigenLine[:-1]):
    plt.axhline(Espectrum[i], color=colors[i], linestyle=':')
    plt.plot(*Ei, color=colors[i])
    
    
for i, Ei in enumerate(Espectrum[0:-1]):
    def pend(y, t):
        return np.array([y[1], -(Ei - V(t, *αβγλ))*y[0]])
    
    y0L =  1e-1, 1e-1
    y0R =  (-1)**i * 1e-1, (-1)**i * 1e-1
    
    rL, rR = EigenLine[i][0]
    rM = (rL + rR)/2
    tL = np.linspace(1e-1, rM, 101)
    tR = np.linspace(9, rM, 101)
    
    solL = odeint(pend, y0L, tL)
    solR = odeint(pend, y0R, tR)
    
    WL = solL[:, 0]/abs(solL[:, 0][-1])
    WR = solR[:, 0]/abs(solR[:, 0][-1])
    Wmax = max(max(abs(WL)), max(abs(WR)))
    
    plt.plot(tL, Ei + 1.6*WL/Wmax, color=colors[i])
    plt.plot(tR, Ei + 1.6*WR/Wmax, color=colors[i])
    
rs = np.linspace(*EigenLine[-1][0], 500)    
plt.plot(rs, V(rs, *αβγλ), color='blue')
plt.xlabel('r [arbitrary]', fontsize=14)
plt.ylabel('$\psi(r)$, V(r), E  [all arbitrary]',...
Given the above code, generate some markdown instructions for it.
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#Here is the Python program you requested.

Eigenvalues and Eigenfucntions for $\alpha = 4, \gamma = 5, \lambda = 100$