import requests
import json
GWEI = 10 ** 9
API= "https://ultrasound.money/api/fees/validator-rewards"
response= requests.get(API)
mev_fees = json.loads(response.text)
mev_per_validator = mev_fees.get('mev').get('annualReward') / GWEI
fees_per_validator = mev_fees.get('tips').get('annualReward') / GWEI
print('Fees Per Validator-')
print(fees_per_validator)
print('MEV Per Validator-')
print(mev_per_validator)
Fees Per Validator-
0.841319629
MEV Per Validator-
0.3
eth = int(input('Amount Of ETH Deposited- '))
validators= eth//4
print('Number Of Validators-')
print(validators)
Number Of Validators-
8
rewards = (mev_per_validator + fees_per_validator)/ 2 * validators
apr= rewards/ eth * 100
print('Annual Yield- ')
print(str(rewards) + ' ETH')
print('Annual APR- ')
print(str(apr) + ' %')
Annual Yield-
4.565278516 ETH
Annual APR-
14.2664953625 %
from scipy.stats import binom
earnings = binom.ppf([0.01, 0.5, 0.99],2628000, 1/472656)
rewards_1 = rewards * earnings[2]/earnings[1]
apr_1 = rewards/ eth * 100
print('Annual Yield- ')
print(str(rewards_1) + ' ETH')
print('Annual APR- ')
print(str(apr_1) + ' %')
Annual Yield-
10.956668438400001 ETH
Annual APR-
14.2664953625 %
from scipy.stats import binom
import matplotlib.pyplot as plt
x = [el for el in range(13)]
y = binom.pmf(x, 2628000, 1/472656)
x= [i/ earnings[0] * rewards for i in x]
fig, ax = plt.subplots(figsize=(12, 8))
ax.bar(x, y)
ax.set_xlim(xmin=0)
ax.set_ylim(ymin=0)
ax.set_title('Probability mass function (472656 validators) — Earnings For Your Validators In LSD In a Year')
ax.set_xlabel('Earnings In A Year (ETH)')
ax.set_ylabel('Probability')