Question

以下是我目前的代码：

import pandas as pd
import math
import csv

fund = 10000
print("investment",fund)

pval = 0
oldportfolio = []

dts = ["06 Feb 2017", "07 Feb 2017", "08 Feb 2017", "09 Feb 2017", "10 Feb 2017", "13 Feb 2017", "14 Feb 2017", "15 Feb 2017", "16 Feb 2017", "17 Feb 2017",
        "20 Feb 2017", "21 Feb 2017", "22 Feb 2017", "23 Feb 2017", "27 Feb 2017"]
for dt in dts:
    files = ["stocklistcustom.csv"]
    for file in files:
        df = pd.read_csv(file, header=None)
        i = 0
        filecount = len(df)
        result = []
        while i < filecount:
        # while i < 10:
            name = df[0][i]
            link = df[1][i]
            mcsym = df[2][i]
            i = i + 1
            filepath = "data/nse/his/" + mcsym + ".csv"
            try:
                sp = pd.read_csv(filepath, header=None)
                endrow = sp[sp[0] == dt].index[0] + 1
                parray = []
                tarray = []
                starray = []
                intdate = []
                p1 = 0
                p2 = 0
                p3 = 0
                p4 = 0
                j = 0
                mavg15 = ''
                mavg60 = ''
                olddiff = 0
                days = 2
                strtrow = endrow - days - 60
                for k in range (strtrow, endrow):
                    date = sp[0][k]
                    price = float(sp[4][k])
                    k = k + 1
                    parray.append(price)
                    j = j + 1
                    strtavg = j - 15
                    mavg15 = sum(parray[strtavg:j]) / 15
                    strtavg = j - 60
                    mavg60 = sum(parray[strtavg:j]) / 60
                    # buy criteria
                    if j > 59:
                        diff = mavg60 - mavg15
                        if diff < 0 and olddiff > 0:
                            trigger = 1
                            intdate.append(date)
                        else:
                            trigger = 0
                        tarray.append(trigger)
                        olddiff = diff
                    # sell criteria
                    if j == (days + 60):
                        pricep = (price - p1) * 100 / p1
                        p1p = (p1 - p2) * 100 / p2
                        p2p = (p2 - p3) * 100 / p3
                        p3p = (p3 - p4) * 100 / p4
                        if pricep < -5 or pricep > 8:
                            sell = 1
                        if price < p1 and p1 < p2 and p2 < p3:
                            sell = 1
                        else:
                            sell = 0
                    p4 = p3
                    p3 = p2
                    p2 = p1
                    p1 = price
                if sum(tarray) > 0:
                    result.append([name,mcsym,"buy",price])
                if sell > 0:
                    result.append([name,mcsym,"sell",price])
            except:
                # print(name,"not found")
                pass

    # print(result)

    output = "output/triggers/"+dt+"trigger.csv"
    with open(output, "wb") as f:
        writer = csv.writer(f)
        writer.writerows(result)
        print(output,"exported")

上面的代码创建了一个名为result的数组，并使用调用...

导出各种csv文件

下面的代码现在处理结果数组中的数据以计算投资组合值

    # Code for calculating investment
    portfolio = []
    for row in result:
        if row[2] == "sell" and len(oldportfolio) > 0:
            pindex = 0
            for buys in oldportfolio:
                bindex = 0
                for stock in buys:
                    if row[0] == stock[0]:
                        sellqty = stock[2]
                        sellp = row[3]
                        sellval = sellqty * sellp
                        purchasep = stock[1]
                        sellcost = purchasep * sellqty
                        print(dt,"selling",row[0],row[1],sellp,sellqty,sellval)
                        # print(oldportfolio)
                        del oldportfolio[pindex][bindex]
                        # print(oldportfolio)
                        fund = fund + sellval
                        pval = pval - sellcost
                    bindex = bindex + 1
                pindex = pindex + 1
    # print("op", oldportfolio)
    # print(dt,"fund after selling",fund)
    buycount = sum(1 for row in result if row[2]==("buy"))
    if buycount > 0:
        maxinvest = fund / buycount
    for row in result:
        if row[2] == "buy":
            name = row[0]
            price = row[3]
            qty = math.floor(maxinvest / price)
            if qty > 0:
                val = qty * price
                print(dt,"buying",name,row[1],price,qty,val)
                portfolio.append([name,price,qty,val])
                fund = fund - val

    # print("portfolio",portfolio)
    pval = pval + sum(row[3] for row in portfolio)
    print(dt,"cash",fund,"portfolio value",pval,"total",fund+pval)
    oldportfolio.append(portfolio)

print(oldportfolio)

根据某些规则，它给出了交易后每天投资组合的价值。但它的执行时间太长了。如何缩短执行时间？

另外，我需要更改pval，因为它在当前代码中计算不正确。必须根据特定日期的价格计算。

Answer 1

你的代码有多个嵌套循环，这可能就是为什么它太慢了。

但你最大的问题不是速度，而是可读性。你的代码真的很难推理，考虑重构。

我相信你会发现一些瓶颈，并且能够在重构时改进你的代码。

如何改进我的python代码以加快速度？

1 个答案: