如何通过使用Python的加密的binance API获取所有价格历史？
如何通过使用Python的加密的binance API获取所有价格历史？
提问于 2021-02-21 02:34:31
我一直在使用这个脚本通过Binance API和这个脚本从一些加密货币中获取价格：https://steemit.com/python/@marketstack/how-to-download-historical-price-data-from-binance-with-python
问题是，使用此脚本我无法控制日期范围:例如，我想要选择2015年12月和2020年12月之间的期间范围，或者我想要任何加密...etc的第一天交易的每日价格。
所以我与你分享我正在使用的代码(从steemit代码复制并稍微修改一下)，我该怎么做呢？
# https://steemit.com/python/@marketstack/how-to-download-historical-price-data-from-binance-with-python###
import requests
import json
import pandas as pd
import numpy as np
import datetime as dt
frequency = input("Please enter the frequency (1m/5m/30m/.../1h/6h/1d/ : ")
def get_bars(symbol, interval=frequency):
root_url = 'https://api.binance.com/api/v1/klines'
url = root_url + '?symbol=' + symbol + '&interval=' + interval
data = json.loads(requests.get(url).text)
df = pd.DataFrame(data)
df.columns = ['open_time',
'o', 'h', 'l', 'c', 'v',
'close_time', 'qav', 'num_trades',
'taker_base_vol', 'taker_quote_vol', 'ignore']
df.index = [dt.datetime.fromtimestamp(x / 1000.0) for x in df.close_time]
return df
btcusdt = get_bars('BTCUSDT')
ethusdt = get_bars('ETHUSDT')
df0=pd.DataFrame(btcusdt)
df0.to_csv('_btcusdt.csv')
df1=pd.DataFrame(ethusdt)
df1.to_csv('_ethusdt.csv')有没有人能帮我优化一下？
回答 3
Stack Overflow用户
发布于 2021-07-29 18:36:38
我在binance文档之外使用了这个：https://python-binance.readthedocs.io/en/latest/binance.html?highlight=get_historical_klines#binance.client.Client.get_historical_klines
import os
from binance.client import Client
import pandas as pd
import datetime, time
def GetHistoricalData(self, howLong):
self.howLong = howLong
# Calculate the timestamps for the binance api function
self.untilThisDate = datetime.datetime.now()
self.sinceThisDate = self.untilThisDate - datetime.timedelta(days = self.howLong)
# Execute the query from binance - timestamps must be converted to strings !
self.candle = self.client.get_historical_klines("BNBBTC", Client.KLINE_INTERVAL_1MINUTE, str(self.sinceThisDate), str(self.untilThisDate))
# Create a dataframe to label all the columns returned by binance so we work with them later.
self.df = pd.DataFrame(self.candle, columns=['dateTime', 'open', 'high', 'low', 'close', 'volume', 'closeTime', 'quoteAssetVolume', 'numberOfTrades', 'takerBuyBaseVol', 'takerBuyQuoteVol', 'ignore'])
# as timestamp is returned in ms, let us convert this back to proper timestamps.
self.df.dateTime = pd.to_datetime(self.df.dateTime, unit='ms').dt.strftime(Constants.DateTimeFormat)
self.df.set_index('dateTime', inplace=True)
# Get rid of columns we do not need
self.df = self.df.drop(['closeTime', 'quoteAssetVolume', 'numberOfTrades', 'takerBuyBaseVol','takerBuyQuoteVol', 'ignore'], axis=1)
print(self.df)我真的希望这能帮助到一些人。
(请注意，这个方法是从我的一个类中切出来的，所以你可以去掉所有的self-s)，并且你需要在之前设置你的客户端。
client = Client(api_key, api_secret)
当然，任何改进都是欢迎的！
Stack Overflow用户
发布于 2021-02-21 03:50:48
这是我用过的一个函数。开始和结束是Unix时间戳格式的日期。interval是图形间隔。
请记住，Binance在2015年12月并不存在:-)
def get_klines_iter(symbol, interval, start, end, limit=5000):
df = pd.DataFrame()
startDate = end
while startDate>start:
url = 'https://api.binance.com/api/v3/klines?symbol=' + \
symbol + '&interval=' + interval + '&limit=' + str(iteration)
if startDate is not None:
url += '&endTime=' + str(startDate)
df2 = pd.read_json(url)
df2.columns = ['Opentime', 'Open', 'High', 'Low', 'Close', 'Volume', 'Closetime', 'Quote asset volume', 'Number of trades','Taker by base', 'Taker buy quote', 'Ignore']
df = pd.concat([df2, df], axis=0, ignore_index=True, keys=None)
startDate = df.Opentime[0]
df.reset_index(drop=True, inplace=True)
return df Stack Overflow用户
发布于 2021-11-20 13:26:53
from binance.client import Client
from datetime import datetime
import pandas as pd
def GetHistoricalData(symbol, interval, fromDate, toDate):
klines = client.get_historical_klines(symbol, interval, fromDate, toDate)
df = pd.DataFrame(klines, columns=['dateTime', 'open', 'high', 'low', 'close', 'volume', 'closeTime', 'quoteAssetVolume', 'numberOfTrades', 'takerBuyBaseVol', 'takerBuyQuoteVol', 'ignore'])
df.dateTime = pd.to_datetime(df.dateTime, unit='ms')
df['date'] = df.dateTime.dt.strftime("%d/%m/%Y")
df['time'] = df.dateTime.dt.strftime("%H:%M:%S")
df = df.drop(['dateTime', 'closeTime', 'quoteAssetVolume', 'numberOfTrades', 'takerBuyBaseVol','takerBuyQuoteVol', 'ignore'], axis=1)
column_names = ["date", "time", "open", "high", "low", "close", "volume"]
df = df.reindex(columns=column_names)
return df
api_key = ""
api_secret = ""
client = Client(api_key, api_secret)
fromDate = str(datetime.strptime('19/11/2021', '%d/%m/%Y'))
toDate = str(datetime.strptime('20/11/2021', '%d/%m/%Y'))
symbol = "BTCUSDT"
interval = Client.KLINE_INTERVAL_1MINUTE
df = GetHistoricalData(symbol, interval, fromDate, toDate)
df页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/66295187
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