获取金融数据--OKEX

-----------------------------------By Patrick 黄瀚祺

1、RESTFul API

2、开源数据 JAQS，Tushare

3、￥￥￥

可导入品种类型：Oanda、A股、商品期货、OKEX、binance

Install

vnpy_fxdayu: https://github.com/xingetouzi/vnpy_fxdayu

Mongodb: https://www.mongodb.com/download-center#community

安装说明: https://github.com/xingetouzi/vnpy_fxdayu/wiki/Windows环境安装

建议安装robomongo作为可视化数据库管理

导入模块(request、datetime、pandas)

import pandas as pd
from datetime import datetime,timedelta
import requests

API说明 :https://www.okex.com/docs/zh/

# OKEX V1
def getCandles(symbol, type, contract_type=None, size=None, since=None):
    params = {'symbol':symbol,'type':type,'contract_type':contract_type,'size':size,'since':since}
    if contract_type:  # url for future
        url = 'https://www.okex.me/api/v1/future_kline.do?'
    else:              # url for spot
        url = 'https://www.okex.me/api/v1/kline.do?'
    r = requests.get(url, params = params,timeout=10)
    text = eval(r.text)
    if contract_type:  
        df = pd.DataFrame(text, columns=["datetime", "open", "high", "low", "close", "volume","%s_volume"%symbol])
    else:
        df = pd.DataFrame(text, columns=["datetime", "open", "high", "low", "close", "volume"])
    df["datetime"] = df["datetime"].map(lambda x: datetime.fromtimestamp(x / 1000))
    # delta = datetime.timedelta(hours=8)
    # df.rename(lambda s: datetime.datetime.strptime(s, "%Y-%m-%d %H:%M:%S") + delta)  # Alter TimeZone 
    return df#.to_csv('a.csv')
getCandles('eos_usd','1min','quarter',size = 10)
# type available: 1min/3min/5min/15min/30min/1day/3day/1week/1hour/2hour/4hour/6hour/12hour
# size value up to 2000
# since value using timestamp, eg. since = 1417536000000

导入数据到mongodb

symbol = 'eos-usdt'
data =getCandles(symbol,'1min','quarter',size = 10)
import pymongo
client = pymongo.MongoClient('localhost', 27017)
collection = client['FinData'][symbol]
collection.create_index([('datetime', pymongo.ASCENDING)], unique=True)
for index, row in data.iterrows():
    bar = {}
    bar['open'] = row.open
    bar['close'] = row.close
    bar['high'] = row.high
    bar['low'] = row.low
    bar['volume'] = row.volume
    bar['symbol'] = symbol
    bar['datetime'] = row.datetime
    bar['date'] = bar['datetime'].date().strftime('%Y%m%d')
    bar['time'] = bar['datetime'].time().strftime('%H:%M:%S')
    flt = {'datetime': bar['datetime']}
    collection.update_one(flt, {'$set':bar}, upsert=True)