CTP tick数据合成K线的代码

Tick转K线的代码

tick已经存到本地csv，代码如下

import csv,random
from datetime import datetime,timedelta
import pandas as pd
with open('./data/rb2310_tick.csv',newline='') as f:
    reader = csv.reader(f)
    next(reader)#跳过首行
    a=list(reader)
class Tick(object):
    pass
class BarData(object):
    def __init__(self):
        self.symbol: str
        self.exchange: str
        self.date: time
        self.open: float = 0
        self.high: float = 0
        self.low: float = 0
        self.close: float = 0    
        self.volume: int = 0    
        self.openInterest: int = 0     
def onBar(bar):
    kline_list.append([bar.symbol,bar.exchange,bar.date,bar.open,bar.high,bar.low,bar.close,bar.volume,bar.openInterest])
    return pd.DataFrame(kline_list,columns=['symbol','exchange','date','open','high','low','close','volume','open_interest'])

bar=None
lastVolume=0
kline_list=[]

for m in a:
    tick=Tick()
    tick.symbol=m[1]
    tick.exchange=0 #未读取
    tick.updateTime= datetime.strptime(m[25]+m[18], '%Y%m%d%H:%M:%S')
    tick.lastPrice=round(float(m[2]),2)
    tick.volume=int(m[9])#后面要与整型计算 字符串会报错
    tick.openInterest=m[11]

    if not bar:
        newMinitue = True
    elif tick.updateTime.minute != bar.date.minute:
        sf=tick.updateTime.strftime('%H%M')
        if sf=='1500':#最后1笔数据是有效数据 持仓量在变 收盘也可能不同
            bar.close = tick.lastPrice
            bar.openInterest = tick.openInterest
            bar.volume += max(tick.volume-lastVolume,0)
            bar.high = max(bar.high, tick.lastPrice)
            bar.low = min(bar.low, tick.lastPrice)
        #数据清理后 推送K线
        if sf<='1500':
            # 推送已经结束的上一分钟K线
            bar.date+=timedelta(minutes=1)#以结束时间为K线结束
            df=onBar(bar)  
        newMinitue = True
    else:
        newMinitue = False
        
    if newMinitue :
        bar= BarData()
        bar.date =tick.updateTime.replace(second=0, microsecond=0) 
        bar.symbol = tick.symbol
        bar.exchange = tick.exchange

        bar.open = tick.lastPrice
        bar.high = tick.lastPrice
        bar.low = tick.lastPrice
    else :
        bar.high = max(bar.high, tick.lastPrice)
        bar.low = min(bar.low, tick.lastPrice)
    
    # 通用更新部分
    bar.close = tick.lastPrice
    bar.openInterest = tick.openInterest
    #注意Volume字段是累计成交量，所以这个时间段内成交量为该值与上一时间段末成交量的差值
    bar.volume += max(tick.volume-lastVolume,0)
    lastVolume = tick.volume

df.set_index('date',inplace=True)
print(df)

Tick和K线都在内存中，就需要用字典根据不同合约各自保存

import random,csv
import pandas as pd
from datetime import datetime,timedelta

with open('./data/rb2310_tick.csv',newline='') as f:
    reader = csv.reader(f)
    next(reader)
    a=list(reader)
        
with open('./data/au2310_tick.csv',newline='') as f:
    reader = csv.reader(f)
    next(reader)
    b=list(reader)    
with open('./data/sc2309_tick.csv',newline='') as f:
    reader = csv.reader(f)
    next(reader)
    c=list(reader)    
res=a+b+c
res.sort(key=lambda x: x[18])#根据tick时间排序
# [row[1]+' '+row[18] for row in res]#现在可以看到 从CTP获取数据一样的顺序了

class BarData(object):
    def __init__(self):
        self.symbol: str
        self.exchange: str
        self.date: time
        self.open: float = 0
        self.high: float = 0
        self.low: float = 0
        self.close: float = 0    
        self.volume: int = 0    
        self.openInterest: int = 0
        self.lastVolume: int = 0
        
subID=('rb2310','au2310','sc2309')
gtick_map={}
gbar_map={}
bar={}
temp_d={}
for key in subID:
    gtick_map[key]=[]
    gbar_map[key]=[]
    bar[key]=None
    temp_d[key]={}   
    temp_d[key]['lastVolume']=0
def onBar(bar):
    gbar_map[bar.symbol].append([bar.date,bar.symbol,bar.open,bar.high,bar.low,bar.close,bar.volume,bar.openInterest])

def tick2bar(tick):
    symbol=tick['symbol']
    if not bar[symbol]:
        newMinitue = True
    elif tick['updateTime'].minute != bar[symbol].date.minute:
        sf=tick['updateTime'].strftime('%H%M')
        #数据清理
        if sf>'1500':
            return
        if sf=='1500':#最后1笔数据是有效数据 持仓量在变 收盘也可能不同
            bar[symbol].close =tick['lastPrice'] 
            bar[symbol].openInterest =tick['openInterest']
            bar[symbol].high = max(bar[symbol].high, tick['lastPrice'])
            bar[symbol].low = min(bar[symbol].low, tick['lastPrice'])    
            bar[symbol].volume += max(tick['volume']-temp_d[symbol]['lastVolume'],0)
        bar[symbol].date+=timedelta(minutes=1)#以结束时间为K线结束
        onBar(bar[symbol]) 
        newMinitue = True    
    else:
        newMinitue = False
    
    if newMinitue :    
        bar[symbol]= BarData()  
        bar[symbol].date =tick['updateTime'].replace(second=0, microsecond=0) 
        bar[symbol].symbol = tick['symbol']
        bar[symbol].exchange = tick['exchange']
        bar[symbol].open =tick['lastPrice']
        bar[symbol].high =tick['lastPrice']
        bar[symbol].low = tick['lastPrice'] 
    else :
        bar[symbol].high = max(bar[symbol].high, tick['lastPrice'])
        bar[symbol].low = min(bar[symbol].low, tick['lastPrice'])    
    
    #通用更新部分
    bar[symbol].close =tick['lastPrice'] 
    bar[symbol].openInterest =tick['openInterest']
    bar[symbol].volume += max(tick['volume']-temp_d[symbol]['lastVolume'],0)
    temp_d[symbol]['lastVolume']=tick['volume']
    
for i in res:
    d={}
    d['symbol']=i[1]
    d['exchange']=0 #未读取
    d['updateTime']=datetime.strptime(i[25]+i[18], '%Y%m%d%H:%M:%S')
    d['lastPrice']=round(float(i[2]),2)
    d['volume']=int(i[9])
    d['openInterest']=i[11]
    gtick_map[d['symbol']].append(d)
    tick2bar(d)

df_bar=pd.DataFrame(gbar_map['au2310'],columns=['date','symbol','open','high','low','close','volume','open_interest'])
df_tick=pd.DataFrame(gtick_map['au2310'])
df_bar