42 lines
1.8 KiB
Python
42 lines
1.8 KiB
Python
import bn
|
|
import pandas as pd
|
|
import mplfinance as mpf
|
|
import datetime as dt
|
|
import strategy.large_trans as lt
|
|
|
|
# def binanceDataFrame(klines):
|
|
# df = pd.DataFrame(klines.reshape(-1,12),dtype=float, columns = ('Open Time',
|
|
# 'Open',
|
|
# 'High',
|
|
# 'Low',
|
|
# 'Close',
|
|
# 'Volume',
|
|
# 'Close time',
|
|
# 'Quote asset volume',
|
|
# 'Number of trades',
|
|
# 'Taker buy base asset volume',
|
|
# 'Taker buy quote asset volume',
|
|
# 'Ignore'))
|
|
|
|
# df['Open Time'] = pd.to_datetime(df['Open Time'], unit='ms')
|
|
|
|
|
|
# return df
|
|
|
|
|
|
# klines = bn.klines('BTCUSDT', '1h')
|
|
|
|
# df = pd.DataFrame(klines,dtype=float)
|
|
# df.columns = ['Open time', 'Open', 'High', 'Low', 'Close', 'Volume', 'ctime', 'Quote asset volume', 'Number of trades', 'Taker buy base asset volume', 'Taker buy quote asset volume', 'Can be ignored']
|
|
# df.index = [dt.datetime.fromtimestamp(x/1000.0) for x in df.ctime]
|
|
# mpf.plot(df, type='line')
|
|
|
|
|
|
# lt.strategy_run()
|
|
from datetime import datetime, timedelta
|
|
import time,settings
|
|
|
|
last_min = datetime.now() - timedelta(minutes=settings.whaleAlert_minutes)
|
|
print(last_min)
|
|
print(time.mktime(last_min.timetuple()))
|
|
print(last_min.timestamp()) |