42df562e60
1. 重新设计的策略引擎API 2. 重新设计的策略模板，策略方面的开发更直观 3. 设计了一个基于EMA双均线的演示策略 4. 基于新的策略模板重写了行情记录工具DataRecorder
357 lines
14 KiB
Python
357 lines
14 KiB
Python
# encoding: UTF-8
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"""
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本模块中主要包含：
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1. 从通联数据下载历史行情的引擎
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2. 用来把MultiCharts导出的历史数据载入到MongoDB中用的函数
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"""
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from datetime import datetime, timedelta
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import pymongo
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from time import time
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from multiprocessing.pool import ThreadPool
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from ctaBase import *
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from vtConstant import *
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from datayesClient import DatayesClient
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# 以下为vn.trader和通联数据规定的交易所代码映射
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VT_TO_DATAYES_EXCHANGE = {}
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VT_TO_DATAYES_EXCHANGE[EXCHANGE_CFFEX] = 'CCFX' # 中金所
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VT_TO_DATAYES_EXCHANGE[EXCHANGE_SHFE] = 'XSGE' # 上期所
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VT_TO_DATAYES_EXCHANGE[EXCHANGE_CZCE] = 'XZCE' # 郑商所
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VT_TO_DATAYES_EXCHANGE[EXCHANGE_DCE] = 'XDCE' # 大商所
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DATAYES_TO_VT_EXCHANGE = {v:k for k,v in VT_TO_DATAYES_EXCHANGE.items()}
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########################################################################
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class HistoryDataEngine(object):
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"""CTA模块用的历史数据引擎"""
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#----------------------------------------------------------------------
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def __init__(self):
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"""Constructor"""
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self.dbClient = pymongo.MongoClient()
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self.datayesClient = DatayesClient()
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#----------------------------------------------------------------------
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def lastTradeDate(self):
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"""获取最近交易日（只考虑工作日，无法检查国内假期）"""
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today = datetime.now()
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oneday = timedelta(1)
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if today.weekday() == 5:
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today = today - oneday
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elif today.weekday() == 6:
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today = today - oneday*2
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return today.strftime('%Y%m%d')
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#----------------------------------------------------------------------
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def readFuturesProductSymbol(self):
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"""查询所有期货产品代码"""
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cx = self.dbClient[SETTING_DB_NAME]['FuturesSymbol'].find()
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return set([d['productSymbol'] for d in cx]) # 这里返回的是集合（因为会重复）
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#----------------------------------------------------------------------
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def readFuturesSymbol(self):
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"""查询所有期货合约代码"""
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cx = self.dbClient[SETTING_DB_NAME]['FuturesSymbol'].find()
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return [d['symbol'] for d in cx] # 这里返回的是列表
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#----------------------------------------------------------------------
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def downloadFuturesSymbol(self, tradeDate=''):
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"""下载所有期货的代码"""
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if not tradeDate:
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tradeDate = self.lastTradeDate()
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self.dbClient[SETTING_DB_NAME]['FuturesSymbol'].ensure_index([('symbol', pymongo.ASCENDING)],
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unique=True)
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path = 'api/market/getMktMFutd.json'
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params = {}
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params['tradeDate'] = tradeDate
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data = self.datayesClient.downloadData(path, params)
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if data:
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for d in data:
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symbolDict = {}
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symbolDict['symbol'] = d['ticker']
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symbolDict['productSymbol'] = d['contractObject']
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flt = {'symbol': d['ticker']}
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self.dbClient[SETTING_DB_NAME]['FuturesSymbol'].update_one(flt, {'$set':symbolDict},
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upsert=True)
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print u'期货合约代码下载完成'
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else:
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print u'期货合约代码下载失败'
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#----------------------------------------------------------------------
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def downloadFuturesDailyBar(self, symbol):
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"""
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下载期货合约的日行情，symbol是合约代码，
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若最后四位为0000（如IF0000），代表下载连续合约。
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"""
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print u'开始下载%s日行情' %symbol
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# 查询数据库中已有数据的最后日期
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cl = self.dbClient[DAILY_DB_NAME][symbol]
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cx = cl.find(sort=[('datetime', pymongo.DESCENDING)])
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if cx.count():
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last = cx[0]
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else:
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last = ''
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# 主力合约
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if '0000' in symbol:
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path = 'api/market/getMktMFutd.json'
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params = {}
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params['contractObject'] = symbol.replace('0000', '')
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params['mainCon'] = 1
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if last:
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params['startDate'] = last['date']
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# 交易合约
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else:
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path = 'api/market/getMktFutd.json'
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params = {}
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params['ticker'] = symbol
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if last:
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params['startDate'] = last['date']
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# 开始下载数据
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data = self.datayesClient.downloadData(path, params)
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if data:
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# 创建datetime索引
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self.dbClient[DAILY_DB_NAME][symbol].ensure_index([('datetime', pymongo.ASCENDING)],
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unique=True)
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for d in data:
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bar = CtaBarData()
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bar.vtSymbol = symbol
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bar.symbol = symbol
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try:
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bar.exchange = DATAYES_TO_VT_EXCHANGE.get(d.get('exchangeCD', ''), '')
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bar.open = d.get('openPrice', 0)
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bar.high = d.get('highestPrice', 0)
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bar.low = d.get('lowestPrice', 0)
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bar.close = d.get('closePrice', 0)
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bar.date = d.get('tradeDate', '').replace('-', '')
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bar.time = ''
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bar.datetime = datetime.strptime(bar.date, '%Y%m%d')
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bar.volume = d.get('turnoverVol', 0)
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bar.openInterest = d.get('openInt', 0)
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except KeyError:
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print d
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flt = {'datetime': bar.datetime}
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self.dbClient[DAILY_DB_NAME][symbol].update_one(flt, {'$set':bar.__dict__}, upsert=True)
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print u'%s下载完成' %symbol
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else:
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print u'找不到合约%s' %symbol
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#----------------------------------------------------------------------
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def downloadAllFuturesDailyBar(self):
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"""下载所有期货的主力合约日行情"""
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start = time()
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print u'开始下载所有期货的主力合约日行情'
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productSymbolSet = self.readFuturesProductSymbol()
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print u'代码列表读取成功，产品代码：%s' %productSymbolSet
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# 这里也测试了线程池，但可能由于下载函数中涉及较多的数据格
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# 式转换，CPU开销较大，多线程效率并无显著改变。
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#p = ThreadPool(10)
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#p.map(self.downloadFuturesDailyBar, productSymbolSet)
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#p.close()
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#p.join()
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for productSymbol in productSymbolSet:
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self.downloadFuturesDailyBar(productSymbol+'0000')
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print u'所有期货的主力合约日行情已经全部下载完成, 耗时%s秒' %(time()-start)
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#----------------------------------------------------------------------
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def downloadFuturesIntradayBar(self, symbol):
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"""下载期货的日内分钟行情"""
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print u'开始下载%s日内分钟行情' %symbol
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# 日内分钟行情只有具体合约
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path = 'api/market/getFutureBarRTIntraDay.json'
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params = {}
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params['instrumentID'] = symbol
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params['unit'] = 1
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data = self.datayesClient.downloadData(path, params)
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if data:
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today = datetime.now().strftime('%Y%m%d')
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# 创建datetime索引
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self.dbClient[MINUTE_DB_NAME][symbol].ensure_index([('datetime', pymongo.ASCENDING)],
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unique=True)
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for d in data:
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bar = CtaBarData()
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bar.vtSymbol = symbol
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bar.symbol = symbol
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try:
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bar.exchange = DATAYES_TO_VT_EXCHANGE.get(d.get('exchangeCD', ''), '')
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bar.open = d.get('openPrice', 0)
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bar.high = d.get('highestPrice', 0)
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bar.low = d.get('lowestPrice', 0)
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bar.close = d.get('closePrice', 0)
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bar.date = today
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bar.time = d.get('barTime', '')
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bar.datetime = datetime.strptime(bar.date + ' ' + bar.time, '%Y%m%d %H:%M')
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bar.volume = d.get('totalVolume', 0)
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bar.openInterest = 0
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except KeyError:
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print d
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flt = {'datetime': bar.datetime}
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self.dbClient[MINUTE_DB_NAME][symbol].update_one(flt, {'$set':bar.__dict__}, upsert=True)
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print u'%s下载完成' %symbol
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else:
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print u'找不到合约%s' %symbol
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#----------------------------------------------------------------------
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def downloadEquitySymbol(self, tradeDate=''):
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"""下载所有股票的代码"""
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if not tradeDate:
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tradeDate = self.lastTradeDate()
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self.dbClient[SETTING_DB_NAME]['EquitySymbol'].ensure_index([('symbol', pymongo.ASCENDING)],
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unique=True)
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path = 'api/market/getMktEqud.json'
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params = {}
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params['tradeDate'] = tradeDate
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data = self.datayesClient.downloadData(path, params)
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if data:
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for d in data:
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symbolDict = {}
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symbolDict['symbol'] = d['ticker']
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flt = {'symbol': d['ticker']}
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self.dbClient[SETTING_DB_NAME]['EquitySymbol'].update_one(flt, {'$set':symbolDict},
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upsert=True)
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print u'股票代码下载完成'
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else:
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print u'股票代码下载失败'
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#----------------------------------------------------------------------
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def downloadEquityDailyBar(self, symbol):
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"""
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下载股票的日行情，symbol是股票代码
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"""
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print u'开始下载%s日行情' %symbol
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# 查询数据库中已有数据的最后日期
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cl = self.dbClient[DAILY_DB_NAME][symbol]
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cx = cl.find(sort=[('datetime', pymongo.DESCENDING)])
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if cx.count():
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last = cx[0]
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else:
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last = ''
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# 开始下载数据
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path = 'api/market/getMktEqud.json'
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params = {}
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params['ticker'] = symbol
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if last:
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params['startDate'] = last['date']
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data = self.datayesClient.downloadData(path, params)
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if data:
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# 创建datetime索引
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self.dbClient[DAILY_DB_NAME][symbol].ensure_index([('datetime', pymongo.ASCENDING)],
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unique=True)
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for d in data:
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bar = CtaBarData()
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bar.vtSymbol = symbol
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bar.symbol = symbol
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try:
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bar.exchange = DATAYES_TO_VT_EXCHANGE.get(d.get('exchangeCD', ''), '')
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bar.open = d.get('openPrice', 0)
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bar.high = d.get('highestPrice', 0)
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bar.low = d.get('lowestPrice', 0)
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bar.close = d.get('closePrice', 0)
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bar.date = d.get('tradeDate', '').replace('-', '')
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bar.time = ''
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bar.datetime = datetime.strptime(bar.date, '%Y%m%d')
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bar.volume = d.get('turnoverVol', 0)
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except KeyError:
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print d
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flt = {'datetime': bar.datetime}
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self.dbClient[DAILY_DB_NAME][symbol].update_one(flt, {'$set':bar.__dict__}, upsert=True)
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print u'%s下载完成' %symbol
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else:
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print u'找不到合约%s' %symbol
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#----------------------------------------------------------------------
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def loadMcCsv(fileName, dbName, symbol):
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"""将Multicharts导出的csv格式的历史数据插入到Mongo数据库中"""
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import csv
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start = time()
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print u'开始读取CSV文件%s中的数据插入到%s的%s中' %(fileName, dbName, symbol)
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# 锁定集合，并创建索引
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client = pymongo.MongoClient()
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collection = client[dbName][symbol]
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collection.ensure_index([('datetime', pymongo.ASCENDING)], unique=True)
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# 读取数据和插入到数据库
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reader = csv.DictReader(file(fileName, 'r'))
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for d in reader:
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bar = CtaBarData()
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bar.vtSymbol = symbol
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bar.symbol = symbol
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bar.open = float(d['Open'])
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bar.high = float(d['High'])
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bar.low = float(d['Low'])
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bar.close = float(d['Close'])
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bar.date = datetime.strptime(d['Date'], '%Y/%m/%d').strftime('%Y%m%d')
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bar.time = d['Time']
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bar.datetime = datetime.strptime(bar.date + ' ' + bar.time, '%Y%m%d %H:%M:%S')
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bar.volume = d['TotalVolume']
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flt = {'datetime': bar.datetime}
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collection.update_one(flt, {'$set':bar.__dict__}, upsert=True)
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print bar.date, bar.time
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print u'插入完毕，耗时：%s' % (time()-start)
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if __name__ == '__main__':
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## 简单的测试脚本可以写在这里
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#from time import sleep
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#e = HistoryDataEngine()
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#sleep(1)
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#e.downloadEquityDailyBar('000001')
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# 这里将项目中包含的股指日内分钟线csv导入MongoDB，作者电脑耗时大约3分钟
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loadMcCsv('IF0000_1min.csv', MINUTE_DB_NAME, 'IF0000')
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