Python BasicData类代码示例

def analyze(stock_code, date, period):
    score = 0.0
    signal = ""
    RSI = getRSI(stock_code, date)
    if 90 > RSI > 80:
        score -= 1
        signal += "[-1]当六日指标上升到达80时，表示股市已有超买现象;"
    if RSI > 90:
        score -= -1
        signal += "[-1]超过90以上时，则表示已到严重超买的警戒区，股价已形成头部，极可能在短期内反转回转;"
    if 10 < RSI < 20:
        score += 1
        signal += "[1]六日强弱指标下降至20时，表示股市有超卖现象;"
    if RSI < 10:
        score += 1
        signal += "[1]一旦继续下降至10以下时则表示已到严重超卖区域，股价极可能有止跌回升的机会;"

    close_in_period = bd.getBasicDataInPeriod("CLOSE_TODAY", stock_code, date, period)
    RSI_in_period = bd.getTechDataInPeriod("CCI", stock_code, date, period)
    close_k = mu.getPoly(close_in_period, 1)[0]
    RSI_k = mu.getPoly(RSI_in_period, 1)[0]

    if close_k > 0 and RSI_k < 0:
        signal += "强弱指标下降而股价反趋上涨，产生的背离现象;"
    if close_k < 0 and RSI_k > 0:
        signal += "强弱指标上升而股价反而下跌, 产生的背离现象;"
    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("RSI", str(score) + ";" + signal, stock_code, date)
    return [score, signal]

def calcROC(stock_code, date, period):
    pday = bd.getStockDate(stock_code, date, period)
    BX = bd.getBasicData("CLOSE_TODAY", stock_code, pday)
    close_today = bd.getBasicData("CLOSE_TODAY", stock_code, date)
    AX = close_today - BX
    ROC = AX / BX * 100
    return round(ROC, 3)

def analyze(stock_code, date, period1, period2):
    signal = ""
    score = 0.0
    recent_high_price = bd.getHighPriceInPeriod("CLOSE_TODAY", stock_code, date, period1)
    recent_low_price = bd.getLowPriceInPeriod("CLOSE_TODAY", stock_code, date, period1)
    close_today = bd.getBasicData("CLOSE_TODAY", stock_code, date)
    BBI = getBBI(stock_code, date)

    if (abs(close_today - recent_high_price) / recent_high_price <= HIGH_OFFSET / 100) and (BBI > close_today):
        score = score - 1
        signal = signal + "[-1]股价在高价区以收市价跌破多空线为卖出信号;"

    if (abs(close_today - recent_low_price) / recent_low_price <= LOW_OFFSET / 100) and (BBI < close_today):
        score = score + 1
        signal = signal + "[1]股价在低价区以收市价突破多空线为买入信号;"

    BBIs = getBBIs(stock_code, date, period2)
    K = mu.getPoly(BBIs, 1)[0]

    if (K > 0) and (BBI > close_today):
        score += 1
        signal += "[1]多空指数由下向上递增，股价在多空线上方，表明多头势强，可以继续持股;"

    if (K < 0) and (BBI < close_today):
        score -= 1
        signal += "[-1]多空指数由上向下递减，股价在多空线下方，表明空头势强，一般不宜买入;"

    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("BBI", str(score) + ";" + signal, stock_code, date)
    return [score, signal]

def calcAverageGain(stock_code, date, period):
    global iterator_count
    price_changed = bd.getBasicData("PRICE_CHANGED", stock_code, date)
    current_gain = 0.0
    if price_changed > 0:
        current_gain = price_changed

    if iterator_count >= max_iterator:
        return calcFirstAverageGain(stock_code, date, period)
    else:
        iterator_count += 1
        average_gain = (calcAverageGain(stock_code, bd.getStockDate(stock_code, date, 1), period) * (
            period - 1) + abs(current_gain)) / period
        # print date + " Average Gain: " + str(average_gain) + " Current Gain: " + str(current_gain)
        return round(average_gain, 3)

def calcEMA(stock_code, date, period):
    if ITERATOR_COUNT >= MAX_ITERATOR:
        EXPMA = MA.calcMA(stock_code, date, period)
        # print "MIN Date： " +date+ " MA:"+ str(EXPMA)
        return EXPMA
    else:
        global ITERATOR_COUNT
        ITERATOR_COUNT = ITERATOR_COUNT + 1

        close_today = bd.getBasicData("CLOSE_TODAY", stock_code, date)
        pday = du.convertDateToString(bd.getStockDate(stock_code, date, 1), "%Y-%m-%d")
        EXPMA_pday = calcEMA(stock_code, pday, period)
        EXPMA = 2 * (close_today - EXPMA_pday) / (period + 1) + EXPMA_pday
        # print date + ": EXPMA: "+str(EXPMA_PDAY)+" CLOSE: " + str(CLOSE_TODAY) + " EXPMA = " +str(EXPMA)
        return round(EXPMA, 3)

def calcAverageLoss(stock_code, date, period):
    global iterator_count
    price_changed = bd.getBasicData("PRICE_CHANGED", stock_code, date)
    current_loss = 0.0
    if price_changed < 0:
        current_loss = price_changed

    if iterator_count >= max_iterator:
        return calcFirstAverageLoss(stock_code, date, period)
    else:
        iterator_count += 1
        average_loss = (calcAverageLoss(stock_code, bd.getStockDate(stock_code, date, 1), period) * (
            period - 1) + abs(current_loss)) / period
        # print date + " " + str(average_loss) + " Current Loss: " + str(current_loss)
        return round(average_loss, 3)

def calcPSY(stock_code, date, period):
    result_set = bd.getBasicDataInPeriod("CLOSE_TODAY, CLOSE_PERVIOUS_DAY", stock_code, date, period)
    count = 0.0
    for each in result_set:
        if each[0] > each[1]:
            count += 1
    PSY = count / period * 100
    return round(PSY, 3)

def calcOBV(stock_code, date, period):
    global ITERATOR_COUNT
    close_today = bd.getBasicData("CLOSE_TODAY", stock_code, date)
    close_pervious_day = bd.getBasicData("CLOSE_PERVIOUS_DAY", stock_code, date)
    volumn = bd.getBasicData("VOLUMN", stock_code, date)
    today_volumn = 0.0
    if close_today > close_pervious_day:
        today_volumn = volumn
    if close_today < close_pervious_day:
        today_volumn = today_volumn*-1

    if ITERATOR_COUNT >= MAX_ITERATOR:
        return today_volumn
    else:
        ITERATOR_COUNT = ITERATOR_COUNT + 1
        pday = bd.getStockDate(stock_code, date, 1)
        OBV = today_volumn + calcOBV(stock_code, pday, period)
        return round(OBV, 3)

def calcFirstAverageGain(stock_code, date, period):
    price_changes_in_period = bd.getBasicDataInPeriod("PRICE_CHANGED", stock_code, date, period)
    first_average_gain = 0.0
    for each in price_changes_in_period:
        if first_average_gain > 0:
            first_average_gain += each[0]
    first_average_gain = first_average_gain / period
    print "First Average Gain: " + str(first_average_gain)
    return round(first_average_gain, 3)

def calcFirstAverageLoss(stock_code, date, period):
    price_changes_in_period = bd.getBasicDataInPeriod("PRICE_CHANGED", stock_code, date, period)
    first_average_loss = 0.0
    for each in price_changes_in_period:
        if first_average_loss < 0:
            first_average_loss += each[0]
    first_average_loss = abs(first_average_loss) / period
    print "First Average Loss: " + str(first_average_loss)
    return round(first_average_loss, 3)

def calcCCI(stock_code, date, period):
    high_today = bd.getBasicData("HIGH_TODAY", stock_code, date)
    low_today = bd.getBasicData("LOW_TODAY", stock_code, date)
    close_today = bd.getBasicData("CLOSE_TODAY", stock_code, date)

    MAn = 0.0
    price_in_period = bd.getBasicDataInPeriod("CLOSE_TODAY, HIGH_TODAY, LOW_TODAY", stock_code, date, period)
    for each in price_in_period:
        MAn += (each[0] + each[1] + each[2])/3
    MAn = MAn / period

    MD = 0.0
    TP = (high_today + low_today + close_today) / 3
    for each in price_in_period:
        MD += abs(MAn - (each[0] + each[1] + each[2])/3)
    MD = MD / period

    CCI = (TP - MAn) / MD / 0.015
    return round(CCI, 3)

def analyze(stock_code, date, period):
    signal = ""
    score = 0.0
    BR = getBR(stock_code, date)
    AR = getAR(stock_code, date)

    if (BR < AR) and (BR < 100):
        score += 1
        signal += "[1]BR＜AR，且BR＜100，可考虑逢低买进;"

    if (BR < AR) and (AR < 50):
        score += 1
        signal += "[1]BR＜AR，而AR＜50时，是买进信号;"

    BRs = getBRs(stock_code, date, period)
    ARs = getARs(stock_code, date, period)
    BR_K = mu.getPoly(BRs, 1)[0]
    AR_K = mu.getPoly(ARs, 1)[0]

    if (BR_K >= UP_RATIO_THREHOLD) and (AR_K >= UP_RATIO_THREHOLD):
        score -= 1
        signal += "[-1]AR和BR同时急速上升，意味着股价已近顶部，持股者应逢高卖出;"

    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("BRAR", str(score) + ";" + signal, stock_code, date)
    return [score, signal]

def analyze(stock_code, date, period):
    score = 0
    signal = ""
    WR = getWR(stock_code, date)
    if WR >= 80:
        score += 1
        signal += "[1]当％R线达到80时，市场处于超卖状况，股价走势随时可能见底。因此，80的横线一般称为买进线，投资者在此可以伺机买入;"
    if WR <= 20:
        score -= 1
        signal += "[-1]当％R线达到20时，市场处于超买状况，走势可能即将见顶，20的横线被称为卖出线;"

    WRs = bd.getTechDataInPeriod("WR", stock_code, date, period)
    WR_K = mu.getPoly(WRs, 1)[0]

    if WR > 50 and WR_K > 0:
        score += 1
        signal += "[1]当%R向下跌破50中轴线时，市场由弱转强，是买进信号;"

    if WR < 50 and WR_K < 0:
        score -= 1
        signal += "[-1]当%R从超买区向上爬升，突破50中轴线后，可以确认强势转弱，是卖出信号;"

    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("WR", str(score) + ";" + signal, stock_code, date)
    return [score, signal]

def analyze(stock_code, date, period):
    score = 0
    signal = ""

    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("DMI", str(score) + ";" + signal, stock_code, date)
    return [score, signal]

def analyze(stock_code, date):
    score = 0
    signal = ""
    pday = bd.getStockDate(stock_code, date, 1)
    KDJ_K, KDJ_D, KDJ_J = getKDJ(stock_code, date)
    KDJ_K_pday, KDJ_D_pday, KDJ_J_pday = getKDJ(stock_code, pday)

    if KDJ_K >= 90:
        score -= 1
        signal += "[-1]K线是快速确认线——数值在90以上为超买;"
    if KDJ_K <= 10:
        score += 1
        signal += "[1]K线是快速确认线——数值在10以下为超卖;"

    if KDJ_D >= 80:
        score -= 1
        signal += "[-1]D线是慢速主干线——数值在80以上为超买;"
    if KDJ_D <= 20:
        score += 1
        signal += "[1]D线是慢速主干线——数值在20以下为超卖;"

    if KDJ_J >= 90:
        score -= 1
        signal += "[-1]J线为方向敏感线，当J值大于90，特别是连续5天以上，股价至少会形成短期头部;"
    if KDJ_J <= 10:
        score += 1
        signal += "[1]J线为方向敏感线，当J值小于10，特别是连续数天以上，股价至少会形成短期底部;"

    if KDJ_K_pday < KDJ_D_pday and KDJ_K > KDJ_D:
        score += 1
        signal += "[1]K线从下方上穿D线，所以在图形上K线向上突破D线时，俗称金叉，即为买进的讯号;"
        if KDJ_K < 20 and KDJ_D < 20:
            score += 1
            signal += "[1]当K，D线在20以下交叉向上，此时的短期买入的信号较为准确;"
        # TODO 如果K值在50以下，由下往上接连两次上穿D值，形成右底比左底高的“W底”形态时，后市股价可能会有相当的涨幅。

    if KDJ_K_pday > KDJ_D_pday and KDJ_K < KDJ_D:
        score -= 1
        signal += "[-1]K线从上方下穿D线，显示趋势是向下的，所以在图形上K线向下突破D线时，俗称死叉，即为卖出的讯号;"
        if KDJ_K > 20 and KDJ_D > 20:
            score -= 1
            signal += "[-1]当K，D线在80以上交叉向下，此时的短期卖出的信号较为准确;"
        # TODO 如果K值在50以上，由上往下接连两次下穿D值，形成右头比左头低的“M头”形态时，后市股价可能会有相当的跌幅。。

    # TODO 4. 通过KDJ与股价背离的走势，判断股价顶底也是颇为实用的方法：4.1股价创新高，而KD值没有创新高，为顶背离，应卖出;4.2股价创新低，而KD值没有创新低，为底背离，应买入
    '''
    print KDJ_K
    print KDJ_D
    print KDJ_J

    print KDJ_K_pday
    print KDJ_D_pday
    print KDJ_J_pday
    '''
    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("KDJ", str(score) + ";" + signal, stock_code, date)
    return [score, signal]