class EthPriceFetcher:
cg: CoinGeckoAPI
cache: dict
__instance: EthPriceFetcher = None
def __init__(self) -> None:
if EthPriceFetcher.__instance is not None:
raise Exception("EthPriceFetcher is a singleton")
self.cg = CoinGeckoAPI()
self.cache = {}
EthPriceFetcher.__instance = self
@staticmethod
def get_instance():
if EthPriceFetcher.__instance is None:
EthPriceFetcher()
return EthPriceFetcher.__instance
def get_eth_usd_price_on_day(self, date: str) -> float:
try:
if date in self.cache:
return self.cache[date]
res = self.cg.get_coin_history_by_id("ethereum", date)
price = res["market_data"]["current_price"]["usd"]
self.cache[date] = price
return price
except Exception as e:
logging.error(e)
return 0
def query_coingecko_asset_price(self,
asset: str,
timestamp: datetime,
fiat: str = "usd"):
asset = self.get_gecko_token_name(asset)
logger.debug("Requesting price of {} at {}".format(asset, timestamp))
if asset == "euro":
return self.query_coingecko_asset_price("tether",
timestamp,
fiat="eur")
else:
cg = CoinGeckoAPI()
data = cg.get_coin_history_by_id(
asset,
timestamp.strftime("%d-%m-%Y %H:%M:%S"),
localization='false')
price = data["market_data"]["current_price"][fiat]
logger.debug("{} is {} at {}".format(asset, price, timestamp))
return float(price)
return num
args = parse_arguments()
bitc_price = cg.get_price(
ids="bitcoin,litecoin,ethereum",
vs_currencies="cad",
include_market_cap="true",
include_24hr_vol="true",
include_24hr_change="true",
)
# pprint(bitc_price)
# date format is dd-mm-yyyy
history = cg.get_coin_history_by_id(id="bitcoin", date="24-09-2020")
name = history["name"]
symbol = history["symbol"]
market_data = history["market_data"]
# pprint(market_data)
price = market_data["current_price"]["cad"]
market_cap = market_data["market_cap"]["cad"]
volume = market_data["total_volume"]["cad"]
price = sanitize_number(price)
market_cap = sanitize_number(market_cap)
volume = sanitize_number(volume)
#Giving Choices
st.write('''# Choose Date and Amount''')
today = datetime.utcnow().date()
previous_day = today - timedelta(days=1)
HIST_DATE = st.date_input("Date: ",
value=previous_day,
min_value=datetime(2021, 3, 14),
max_value=previous_day)
ORG_USD = st.number_input("USD Amount: ", min_value=1, max_value=999999999)
#Reformat Historical Date for next function
HIST_DATE_REFORMAT = HIST_DATE.strftime("%d-%m-%Y")
HIST_DATE_datetime = datetime.strptime(HIST_DATE_REFORMAT, "%d-%m-%Y")
sm_historic = cg.get_coin_history_by_id(
id='safemoon', vs_currencies='usd',
date=HIST_DATE_REFORMAT)['market_data']['current_price']['usd']
sm_historic = round(sm_historic, 9)
st.write('''# Results''')
st.write('''## Historic Analysis''')
st.write("You would have originally bought: ***{:,.2f}*** $SAFEMOON".format(
round(ORG_USD / sm_historic), 2))
st.write("At a price of ***{:,.9f}*** per $SAFEMOON".format(sm_historic))
st.write(" ")
st.write('''## Present Effects''')
total_sm = ORG_USD / sm_historic
current_USD = total_sm * sm_current
perc_change = (current_USD - ORG_USD) / (ORG_USD) * 100
from pycoingecko import CoinGeckoAPI
cg = CoinGeckoAPI()
# This gives the historical data of a coin on a particular day
# i.e, we want to plot the data of this coin like market_cap or price with other available coins
print("Here you can get the coin historical data on a particular day.")
id = input("Enter the coin name - ")
date = input(
"Enter the day on which you want the historical data of this coin in the dd-mm-yyyy format: "
)
data = cg.get_coin_history_by_id(id, date)
# Example -
# if I want to compare bitcoin with all other coins I will enter id as bitcoin
# For plotting price this value will be in Y axis and other coins will be on X axis
# Their will be bar charts arising from each of these coins
# The data is stored in prices and market_cap list
prices = data['prices']
market_cap = data['market_cap']
# For each of this you can see first element is coin name and other is conversion price or market_data
token_count = 0
for token, entry_date in data.items():
#token = token.lower()
#print(token)
if token in token_name:
wallet_id.append(wallet)
ids = token_id[token_name.index(token)]
token_names.append(ids)
#ids = token_file.loc[token_file[1]==token,0].item()
#ids = token_file[token_file[1]==token][0].apply(lambda x: "'" + str(x) + "'")
#ids = "'",ids, "'"
print(ids)
cg = CoinGeckoAPI()
days_50 = 4881600 #56.5 days, just over 8 weeks
entry = datetime.utcfromtimestamp(int(entry_date)).strftime('%d-%m-%Y')
price_request = cg.get_coin_history_by_id(ids, str(entry))
entry_price = float(price_request.get('market_data')['current_price']['usd'])
request = cg.get_coin_market_chart_range_by_id(ids,'usd', int(entry_date) - days_50, int(entry_date) + days_50)
content = request.get('prices')
token_price_data[ids] = content
wk8b = content[0:7]
wk7b = content[7:14]
wk6b = content[14:21]
wk5b = content[21:28]
wk4b = content[28:35]
wk3b = content[35:42]
wk2b = content[42:49]
wk1b = content[49:56]
GeckoID = []
for item in Info:
GeckoID.append(item['id'])
for date in ListOfDays:
print('Date:' + date)
Name = []
Symbol = []
MarketCap = []
Price = []
Rank = []
for item in CMC_id:
if item in GeckoID:
Coin = DataMain.get_coin_history_by_id(item, date)
if 'market_data' in Coin:
MarketCap.append(
Coin['market_data']['market_cap'][BaseCurrency.lower()])
Price.append(
Coin['market_data']['current_price'][BaseCurrency.lower()])
Symbol.append(Coin['symbol'].upper())
Name.append(Coin['name'])
else:
MarketCap.append(0.0)
Price.append(0.0)
Symbol.append(Coin['symbol'].upper())
Name.append(Coin['name'])
else:
continue
from pycoingecko import CoinGeckoAPI
import datetime
cg = CoinGeckoAPI()
date = []
yesterday = datetime.datetime.now()
for i in range(1, 365):
nxtDate = yesterday - datetime.timedelta(i)
nxtDate = nxtDate.strftime('%d-%m-%Y')
date.insert(0, nxtDate)
res = cg.get_coin_history_by_id(id = 'tether', date= date[0], localization=False, vs_currencies='usd')
prev_buy_price = res['market_data']['current_price']['usd']
startPrice = 3000
amt = startPrice / prev_buy_price
money = 0
trades = 0
prev_trades = 0
count = 1
thresh = 0.001
for dt in date:
res = cg.get_coin_history_by_id(id = 'tether', date= dt, localization=False, vs_currencies='usd')
if 'market_data' not in res.keys():
continue
price = res['market_data']['current_price']['usd']
if (prev_buy_price < price - thresh and amt != 0): #sell
# Compute "token weights" for each token
# for a rough estimate of capital-weighted
# early usage of the Compound protocol
# A token's capital weight is taken as the
# simple average of its USD price at CompV1deployBlock
# and its USD price at COMPlaunchBlock,
# the start and end of the early user analysis window.
# The following simplifications are adopted to
# sidestep limitations in CoinGecko historical data:
# --> Stablecoin weights are directly set to 1
# --> Bitcoin data is used for the WBTC price
# --> Ethereum data is used for the WETH price
CompV1deployBlockDate = '26-09-2018'
COMPlaunchBlockDate = '15-06-2020'
token_weights = {'sai': 1.0, 'usdc': 1.0, 'dai': 1.0}
for token in ['0x', 'basic-attention-token', 'augur', 'ethereum', 'bitcoin']:
rawdata = cg.get_coin_history_by_id(token, CompV1deployBlockDate)
print(rawdata)
StartPrice = rawdata["market_data"]["current_price"]["usd"]
print(token + CompV1deployBlockDate + str(StartPrice))
rawdata = cg.get_coin_history_by_id(token, COMPlaunchBlockDate)
EndPrice = rawdata["market_data"]["current_price"]["usd"]
print(token + CompV1deployBlockDate + str(EndPrice))
token_weights[token] = (0.5 * (StartPrice + EndPrice))
print("token_weights:")
print(token_weights)
