AAVE_LPOOL_CONTRACT = "0x7d2768dE32b0b80b7a3454c06BdAc94A69DDc7A9" #Aave v2 Lending Pool Contract AAVE_ORACLE_CONTRACT = "0xA50ba011c48153De246E5192C8f9258A2ba79Ca9" # Aave Chain ASTETH_CONTRACT = "0x1982b2F5814301d4e9a8b0201555376e62F82428" #aSTETH token CURVE_POOL_CONTRACT = "0xDC24316b9AE028F1497c275EB9192a3Ea0f67022" BALANCER_POOL_CONTRACT = "0xBA12222222228d8Ba445958a75a0704d566BF2C8" BALANCER_POOL_ID = "0x32296969ef14eb0c6d29669c550d4a0449130230000200000000000000000080" WETH_TOKEN_CONTRACT = "0xC02aaA39b223FE8D0A0e5C4F27eAD9083C756Cc2" OINCH_POOL_CONTRACT = "0xC1A900Ae76dB21dC5aa8E418Ac0F4E888A4C7431" SUSHI_POOL_CONTRACT = "0xc5578194D457dcce3f272538D1ad52c68d1CE849" DAI_TOKEN_CONTRACT = "0x6B175474E89094C44Da98b954EedeAC495271d0F" curve_abi = json.load(open("curvepoolabi.json")) balancer_abi = json.load(open("balancerpoolabi.json")) oneinch_abi = json.load(open("oneinchpoolabi.json")) sushi_abi = json.load(open("sushipoolabi.json")) risk_rating = ['A','B+','B','B-','C','D','liquidation'] def get_userlist(vlink): #collects information about users that interacted with aSTETH contract, vlink - Flipside API link r = requests.get(f"{vlink}").json() df = pd.DataFrame(r) return df def get_user_stats(vuser): #gets information about user from Aave Lending pool contract abi = json.load(open("AaveLP.json")) contract = web3.eth.contract(address=AAVE_LPOOL_CONTRACT, abi=abi) (collateral_eth, debt_eth, available_borrows_eth, current_liquidation_threshold, ltv, healthfactor) = contract.functions.getUserAccountData(Web3.to_checksum_address(vuser)).call() return (collateral_eth, debt_eth, available_borrows_eth, current_liquidation_threshold, ltv, healthfactor) def get_steth_eth_price(): #gets current ETH price from Aave Oracle abi = json.load(open("AaveOracle.json")) contract = web3.eth.contract(address=AAVE_ORACLE_CONTRACT, abi=abi) price = contract.functions.getAssetPrice(Web3.to_checksum_address('0xae7ab96520DE3A18E5e111B5EaAb095312D7fE84')).call() price = price / pow(10,18) return price def get_asteth_balance(vuser): #gets current aSTETH balance of user abi = json.load(open("aSTETH.json")) contract = web3.eth.contract(address=ASTETH_CONTRACT, abi=abi) balance = contract.functions.balanceOf(Web3.to_checksum_address(vuser)).call() return balance def eth_last_price(): #gets current ETH price from coingecko req = requests.get(f'https://api.coingecko.com/api/v3/simple/price?ids=ethereum&vs_currencies=usd&include_market_cap=false&include_24hr_vol=false&include_24hr_change=false&include_last_updated_at=false' ).json() price = req['ethereum']['usd'] return price def steth_last_price(): #gets current stETH price from coingecko req = requests.get(f'https://api.coingecko.com/api/v3/simple/price?ids=staked-ether&vs_currencies=usd&include_market_cap=false&include_24hr_vol=false&include_24hr_change=false&include_last_updated_at=false' ).json() price = req['staked-ether']['usd'] return price def get_risks(data, collateral_loan_ratio): #calculates the risk level for each position and returns the positions sorted by risk dfrisk = pd.DataFrame(data = data) risk_rating_list = get_scale_dic(collateral_loan_ratio) dfrisk['risk_rating'] = [(x > risk_rating_list[0] and 'A') or (risk_rating_list[1] < x <= risk_rating_list[0] and 'B+') or (risk_rating_list[2] < x <= risk_rating_list[1] and 'B') or (risk_rating_list[3] < x <= risk_rating_list[2] and 'B-') or (risk_rating_list[4] < x <= risk_rating_list[3] and 'C') or (risk_rating_list[5] < x <= risk_rating_list[4] and 'D') or (risk_rating_list[5] <=x and 'liquidation') for x in dfrisk['healthf']] return dfrisk.query('amount > 0').sort_values(by = 'healthf', ascending = False) def get_distr(data): #calculates and returns a pivot table by risk levels risk_distr = data.pivot_table(index = 'risk_rating', values = ['amount'], aggfunc = ['sum', 'count']) risk_distr.columns = ['stETH','cnt'] risk_distr['stETH'] = risk_distr['stETH'] risk_distr['percent'] = (risk_distr['stETH']/risk_distr['stETH'].sum())*100 risk_distr['average'] = risk_distr['stETH']/risk_distr['cnt'] median_a0 = data.query('risk_rating == "A"')['amount'].median() data.loc[data['risk_rating']=='A','median'] = median_a0 median_b0 = data.query('risk_rating == "B+"')['amount'].median() data.loc[data['risk_rating']=='B+','median'] = median_b0 median_b1 = data.query('risk_rating == "B"')['amount'].median() data.loc[data['risk_rating']=='B','median'] = median_b1 median_b2 = data.query('risk_rating == "B-"')['amount'].median() data.loc[data['risk_rating']=='B-','median'] = median_b2 median_c0 = data.query('risk_rating == "C"')['amount'].median() data.loc[data['risk_rating']=='C','median'] = median_c0 median_d0 = data.query('risk_rating == "D"')['amount'].median() data.loc[data['risk_rating']=='D','median'] = median_d0 median_il = data.query('risk_rating == "is liquidating"')['amount'].median() data.loc[data['risk_rating']=='liquidation','median'] = median_il median_distr = data.pivot_table(index = 'risk_rating', values = ['median'], aggfunc = 'min') risk_distr = risk_distr.merge(median_distr, on = 'risk_rating', how = 'outer') return risk_distr.reindex(['A','B+','B','B-','C','D','liquidation']).fillna(0) def get_scale(collateral_loan_ratio): #calculates and returns scale-table risk_ratio1 = [str(f'{100/i:.0f}%') for i in collateral_loan_ratio] risk_ratio2 = ['0']+risk_ratio1[:-1] risk_ratio = [f'{risk_ratio2[i]} - {risk_ratio1[i]}' for i in range(len(risk_ratio1))] risk_ratio.append('>=100%') collateral_loan_ratio_list1 = [str(f'{i:.2f}x') for i in collateral_loan_ratio] collateral_loan_ratio_list2 = ['>']+ collateral_loan_ratio_list1[:-1] collateral_loan_ratio_list = [f'{collateral_loan_ratio_list1[i]} - {collateral_loan_ratio_list2[i]}' for i in range(len(collateral_loan_ratio_list2))] collateral_loan_ratio_list.append('=< 1.00x') risk_rating = ['A','B+','B','B-','C','D','liquidation'] return pd.DataFrame(data={'health factor' : collateral_loan_ratio_list, 'risk ratio' : risk_ratio, 'risk rating' : risk_rating}) def get_scale_dic(collateral_loan_ratio): return [i for i in collateral_loan_ratio] @unsync def get_debt_balance(vuser,varcontract, stabcontract): #gets current debt token balance of user if (varcontract == '-'): var_balance = 0 else: abi = json.load(open("VariableDebtToken.json")) contract = web3.eth.contract(address=Web3.to_checksum_address(varcontract), abi=abi) var_balance = contract.functions.balanceOf(Web3.to_checksum_address(vuser.lower())).call() #gets current debt token balance of user if (stabcontract == '-'): stable_balance = 0 else: abi = json.load(open("StableDebtToken.json")) contract = web3.eth.contract(address=Web3.to_checksum_address(stabcontract), abi=abi) stable_balance = contract.functions.balanceOf(Web3.to_checksum_address(vuser.lower())).call() balance = var_balance + stable_balance return balance @unsync def parse_ethdebt_balance(df): buf = [] tasks = [(user, get_debt_balance(user,'0xF63B34710400CAd3e044cFfDcAb00a0f32E33eCf', '0x4e977830ba4bd783C0BB7F15d3e243f73FF57121')) for user in df["user"]] for user, task in tasks: balance: float = task.result() # type: ignore buf.append({"user": user, "ethdebt": balance}) return buf

.css-15w88e5{color:var(--chakra-colors-fg-neutral-primary);font-weight:inherit;letter-spacing:-0.09px;}Aave V2 stETH Collateral Risk Monitor

Bin 1: Aave users with >=80% collaterals - stETH and >=80% debt - ETH

Bin 2: Aave users with stETH collateral and >=80% debt - not ETH

Bin 3: All other Aave users with stETH collateral

Aave V2 stETH Collateral Risk Monitor