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5 天以前 48fb7a00951f91bdc707e5dd2d196e5bccb752c3

 utils/buy_strategy_util.py

@@ -3,10 +3,12 @@
"""
import time

from code_attribute import gpcode_manager
from code_attribute import gpcode_manager, code_volumn_manager
from l2 import l2_data_util, l2_data_source_util, transaction_progress
from l2.l2_data_util import L2DataUtil
from l2.l2_transaction_data_manager import HuaXinSellOrderStatisticManager
from log_module import async_log_util
from log_module.log import logger_l2_error
from settings.trade_setting import MarketSituationManager, TradeBlockBuyModeManager
from trade import trade_data_manager
from utils import tool, buy_condition_util, global_util
@@ -43,7 +45,7 @@
                        break
            continue
        # 与当前时间相差3s的结束
        if tool.trade_time_sub_with_ms(end_time_with_ms, l2_data_util.L2DataUtil.get_time_with_ms(val)) > 6000:
        if tool.trade_time_sub_with_ms(end_time_with_ms, l2_data_util.L2DataUtil.get_time_with_ms(val)) > 10000:
            break

        cancel_count += 1
@@ -91,10 +93,10 @@
        if buy_index and start_index <= buy_index:
            cancel_count += 1
    if buy_count == 0:
        return False
        return False, "买入数量为0"
    if round(cancel_count / buy_count, 2) > threshhold_rate:
        return True
    return False
        return True, f"买入数量-{buy_count} 撤单数量-{cancel_count}"
    return False, f"买入数量-{buy_count} 撤单数量-{cancel_count}"


def is_far_away_from_trade_index(code, trade_index, buy1_money):
@@ -141,33 +143,52 @@
    @param trade_index:
    @return:
    """
    total_data = l2_data_util.local_today_datas.get(code)
    total_count = 0
    total_big_count = 0
    for i in range(trade_index + 1, total_data[-1]["index"] + 1):
        data = total_data[i]
        val = data["val"]
        if not l2_data_util.L2DataUtil.is_limit_up_price_buy(val):
            continue
        money = val["num"] * float(val["price"])
        if money < 5000:
            continue
    # 获取今日成交量与参考量
    # today = get_today_volumn(code)
    # max60, yesterday = get_histry_volumn(code)
    try:
        today_volume = code_volumn_manager.CodeVolumeManager().get_today_volumn_cache(code)
        histry_volumn = code_volumn_manager.CodeVolumeManager().get_histry_volumn(code)
        if not today_volume or not histry_volumn:
            return False, "尚未获取到量"
        threshhold_volume = (histry_volumn[0][0] - today_volume) // 3
        limit_up_price = gpcode_manager.get_limit_up_price_as_num(code)
        threshhold_volumes = threshhold_volume // 100, int(50000 / limit_up_price), int(200000 / limit_up_price)

        left_count = l2_data_source_util.L2DataSourceUtils.get_limit_up_buy_no_canceled_count_v2(
            code,
            i,
            total_data,
            l2_data_util.local_today_canceled_buyno_map.get(
                code))
        if left_count > 0:
            total_count += 1
            if money > 29900:
                total_big_count += 1
            if total_count > 10:
                break
    if total_count > 10 or total_big_count < 1:
        return False, f"未成交数量-{total_count}，大单数量-{total_big_count}"
    return True, ""
        total_data = l2_data_util.local_today_datas.get(code)
        total_count = 0
        total_big_count = 0
        total_num = 0
        for i in range(trade_index + 1, total_data[-1]["index"] + 1):
            data = total_data[i]
            val = data["val"]
            if not l2_data_util.L2DataUtil.is_limit_up_price_buy(val):
                continue
            money = val["num"] * float(val["price"])
            if money < 5000:
                continue

            left_count = l2_data_source_util.L2DataSourceUtils.get_limit_up_buy_no_canceled_count_v2(
                code,
                i,
                total_data,
                l2_data_util.local_today_canceled_buyno_map.get(
                    code))
            if left_count > 0:
                total_num += val["num"]
                total_count += 1
                if money > 29900:
                    total_big_count += 1
                if threshhold_volumes[2] < total_num:
                    break
        if threshhold_volumes[1] <= total_num <= threshhold_volumes[2] and total_num < threshhold_volumes[
            0] and total_big_count > 0:
            # 剩余的值在500w-2000w之间才会参与计算
            return True, ""
        return False, f"未成交手数-{total_num}，阈值-{threshhold_volumes[0]}，大单数量-{total_big_count}"
    except Exception as e:
        async_log_util.error(logger_l2_error, f"计算是否距离成交进度位置近：{str(e)}")
        return False, "计算异常"


def is_quantization(code, start_index, end_index):
@@ -178,18 +199,33 @@
    @param end_index:
    @return:(是否是量化, 下次可以下单时间)
    """
    THRESHOLD_BUY_COUNT = 20
    if end_index - start_index + 1 < THRESHOLD_BUY_COUNT:
        # 总数小于阈值
        return False, None

    # 阈值的取值范围
    THRESHOLD_MONEY_RANGE = 1e5, 3e5
    today_volume = code_volumn_manager.CodeVolumeManager().get_today_volumn_cache(code)
    histry_volumn = code_volumn_manager.CodeVolumeManager().get_histry_volumn(code)
    if not today_volume or not histry_volumn:
        return False, "尚未获取到量"
    threshhold_volume = (histry_volumn[0][0] - today_volume) // 6 // 100
    limit_up_price = gpcode_manager.get_limit_up_price_as_num(code)
    threshhold_volumes_range = int(THRESHOLD_MONEY_RANGE[0] / limit_up_price), int(
        THRESHOLD_MONEY_RANGE[1] / limit_up_price)
    if threshhold_volume < threshhold_volumes_range[0]:
        threshhold_volume = threshhold_volumes_range[0]
    if threshhold_volume > threshhold_volumes_range[1]:
        threshhold_volume = threshhold_volumes_range[1]
    total_datas = l2_data_util.local_today_datas.get(code)

    time_as_ms = tool.trade_time_sub_with_ms(
        L2DataUtil.get_time_with_ms(total_datas[end_index]["val"]),
        L2DataUtil.get_time_with_ms(total_datas[start_index]["val"]))
    if time_as_ms > (10 if tool.is_sz_code(code) else 100):
        return False, "非量化"

    limit_up_price = gpcode_manager.get_limit_up_price_as_num(code)

    buy_count = 0
    total_buy_nums = 0
    min_num = int(5000 / limit_up_price)
    trade_index, is_default = transaction_progress.TradeBuyQueue().get_traded_index(code)
    if trade_index is None:
        trade_index = 0
    # 获取成交进度位
    for i in range(start_index, end_index + 1):
        val = total_datas[i]["val"]
@@ -197,25 +233,20 @@
            continue
        if val["num"] < min_num:
            continue
        buy_count += 1
        if buy_count > THRESHOLD_BUY_COUNT:
        total_buy_nums += val["num"]
        if total_buy_nums > threshhold_volume:
            break
    if buy_count > THRESHOLD_BUY_COUNT:
    if total_buy_nums > threshhold_volume:
        # 判断是否为量化
        time_as_ms = tool.trade_time_sub_with_ms(
            L2DataUtil.get_time_with_ms(total_datas[end_index]["val"]),
            L2DataUtil.get_time_with_ms(total_datas[start_index]["val"]))
        if time_as_ms <= 10 if tool.is_sz_code(code) else 100:
            # 深证10ms内，上证100ms内就判定为量化
            HuaXinSellOrderStatisticManager.clear_latest_deal_volume(code)
            next_buy_time = time.time() + buy_condition_util.get_cancel_and_buy_space_time(
                code) / 1000
            # 如果是首次下单，增加一次下单次数
            place_order_count = trade_data_manager.PlaceOrderCountManager().get_place_order_count(code)
            if place_order_count == 0:
                trade_data_manager.PlaceOrderCountManager().place_order(code)
            return True, next_buy_time, f"执行位批次数据量({buy_count})大于{THRESHOLD_BUY_COUNT}  {start_index}-{end_index}"
        return False, None
        # 深证10ms内，上证100ms内就判定为量化
        HuaXinSellOrderStatisticManager.clear_latest_deal_volume(code)
        next_buy_time = time.time() + buy_condition_util.get_cancel_and_buy_space_time(
            code) / 1000
        # 如果是首次下单，增加一次下单次数
        place_order_count = trade_data_manager.PlaceOrderCountManager().get_place_order_count(code)
        if place_order_count == 0:
            trade_data_manager.PlaceOrderCountManager().place_order(code)
        return True, next_buy_time, f"执行位批次数据量({total_buy_nums})大于{threshhold_volume}  {start_index}-{end_index}"
    else:
        return False, None