"""
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网络代理管理器
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"""
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# 本地看盘网络代理
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import decimal
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import json
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import time
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from urllib.parse import parse_qs, urlparse
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import setting
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import trade_gui
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from kpl import kpl_util, kpl_api
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from kpl.kpl_data_manager import KPLLimitUpDataManager
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from utils import tool, xgb_api
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class LocalKanPanNetworkDelegate:
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# 保存代码涨幅
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__code_limit_rate_dict = {}
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# HTTP代理请求
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@classmethod
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def http_delegate_request(cls, url):
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if url.startswith("/kpl/get_limit_up_list"):
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return cls.__get_limit_up_list(url)
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elif url.startswith("/kpl/get_market_data"):
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return cls.__get_market_data(url)
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elif url.startswith("/kpl/get_plate_codes"):
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return cls.__get_plate_codes(url)
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elif url.startswith("/get_xgb_limit_up_reasons"):
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return cls.__get_xgb_limit_up_reasons(url)
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elif url.startswith("/get_kpl_market_feelings"):
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return cls.__get_kpl_market_feelings()
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elif url.startswith("/buy_by_ths"):
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# 获取可转债的列表
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return cls.buy_by_ths(url)
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return None, False
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@classmethod
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def __get_limit_up_list(cls, url):
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ps_dict = dict([(k, v[0]) for k, v in parse_qs(urlparse(url).query).items()])
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day = ps_dict.get("day")
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if day is None:
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day = tool.get_now_date_str()
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# (代码, 名称, 首次涨停时间, 最近涨停时间, 几板, 涨停原因, 板块, 实际流通, 主力净额, 涨停原因代码, 涨停原因代码数量)
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records = KPLLimitUpDataManager().get_limit_up_history_datas(day)
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currents = KPLLimitUpDataManager().get_limit_up_current_datas(day)
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current_codes = [d[0] for d in currents]
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fresult = []
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# 计算涨停时间排序
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record_reason_dict = {}
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current_reason_dict = {}
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for r in records:
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if r[5] not in record_reason_dict:
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record_reason_dict[r[5]] = []
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record_reason_dict[r[5]].append(r)
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for r in currents:
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if r[5] not in current_reason_dict:
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current_reason_dict[r[5]] = []
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current_reason_dict[r[5]].append(r)
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for k in record_reason_dict:
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record_reason_dict[k].sort(key=lambda x: x[2])
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for r in records:
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if r[0] in current_codes:
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limit_up_state = 1
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else:
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limit_up_state = 2
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rank = 0
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for i in range(len(record_reason_dict[r[5]])):
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if record_reason_dict[r[5]][i][0] == r[0]:
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rank = i
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# (代码, 名称, 涨停状态(0 - 无状态 1-涨停 2-炸板), 龙几, 首板, 分值, 涨停时间, 原因, 相同原因代码数量, 自由流通, 涨停原因是否变化,涨停原因的流入净额,下单简介)
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fresult.append((r[0], r[1], limit_up_state, f"龙{rank + 1}", r[4], 0,
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tool.time_format(int(r[2])), r[5], r[10], tool.money_desc(r[7]),
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'', '', ''))
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# (板块名称，涨停代码数量，炸板数量,涨停时间)
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limit_up_reason_statistic_info = [(k, len(record_reason_dict[k]), len(record_reason_dict[k]) - len(
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current_reason_dict.get(k) if k in current_reason_dict else []),
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record_reason_dict[k][0][5]) for k in record_reason_dict]
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limit_up_reason_statistic_info.sort(key=lambda x: x[1] - x[2])
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limit_up_reason_statistic_info.reverse()
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result = json.dumps({"code": 0, "data": {"limit_up_count": len(currents),
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"open_limit_up_count": len(records) - len(currents),
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"limit_up_reason_statistic": limit_up_reason_statistic_info,
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"limit_up_codes": fresult}})
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return result, True
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@classmethod
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def __get_market_data(cls, url):
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ps_dict = dict([(k, v[0]) for k, v in parse_qs(urlparse(url).query).items()])
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type_ = int(ps_dict['type'])
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result = []
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if type_ == 0:
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# 行业，主力净额倒序
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result = kpl_api.getMarketIndustryRealRankingInfo(True)
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result = kpl_util.parseMarketIndustry(result)
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elif type_ == 1:
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# 行业，主力净额顺序
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result = kpl_api.getMarketIndustryRealRankingInfo(False)
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result = kpl_util.parseMarketIndustry(result)
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elif type_ == 2:
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# 精选，主力净额倒序
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result = []
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for p in range(2):
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result_ = kpl_api.getMarketJingXuanRealRankingInfo(p + 1, True)
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result_ = kpl_util.parseMarketJingXuan(result_)
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result.extend(result_)
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elif type_ == 3:
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# 精选，主力净额顺序
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result = []
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for p in range(2):
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result_ = kpl_api.getMarketJingXuanRealRankingInfo(p + 1, False)
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result_ = kpl_util.parseMarketJingXuan(result_)
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result.extend(result_)
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fresult = []
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forbidden_plates = []
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for d in result:
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d = list(d)
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d.append(1 if d[1] in forbidden_plates else 0)
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fresult.append(d)
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response_data = json.dumps({"code": 0, "data": fresult})
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return response_data, True
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@classmethod
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def __get_plate_codes(cls, url):
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ps_dict = dict([(k, v[0]) for k, v in parse_qs(urlparse(url).query).items()])
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day = ps_dict.get("day")
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plate = ps_dict.get("plate")
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if not day:
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return None, False
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records = KPLLimitUpDataManager().get_limit_up_history_datas(day)
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currents = KPLLimitUpDataManager().get_limit_up_current_datas(day)
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rs = []
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for r in records:
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if r[5] != plate and plate not in r[6].split('、'):
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continue
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rs.append(r)
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current_codes = set()
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for r in currents:
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current_codes.add(r[0])
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rs.sort(key=lambda x: x[2])
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# 代码,名称,涨停时间,是否炸板,是否想买,是否已经下过单
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results = [(
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x[0], x[1], time.strftime("%H:%M:%S", time.localtime(x[2])), 0 if x[0] in current_codes else 1, 0, 0,
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x[4], f" {round(x[7] / 100000000, 1)}亿", 1 if x[5] == plate else 0) for x in rs]
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response_data = json.dumps({"code": 0, "data": results})
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return response_data, True
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# 获取昨日收盘价
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__pre_close_cache = {}
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@classmethod
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def __get_xgb_limit_up_reasons(cls, url):
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# 获取 昨日涨停数据
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ps_dict = dict([(k, v[0]) for k, v in parse_qs(urlparse(url).query).items()])
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code = ps_dict["code"]
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reasons = xgb_api.get_code_limit_up_reasons(code)
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if reasons:
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response_data = json.dumps(
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{"code": 0, "data": {"reasons": reasons[0], "description": reasons[1], "blocks": reasons[2],
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"zylt": f"{reasons[3]}亿"}})
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else:
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response_data = json.dumps({"code": 1, "msg": "尚未获取到涨停原因"})
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return response_data, True
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@classmethod
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def __get_kpl_market_feelings(cls):
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market_feelings = kpl_api.getMarketFelling()
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market_strong = kpl_api.getMarketStrong()
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ps = [('涨停', market_feelings['ZT'], 'red')]
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ps.append(('>%7', int(market_feelings['8']) + int(market_feelings['9']) + int(
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market_feelings['10']), 'red'))
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ps.append(('7~5%', int(market_feelings['6']) + int(market_feelings['7']), 'red'))
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ps.append(('5~2%', int(market_feelings['3']) + int(market_feelings['4']) + int(market_feelings['5']), 'red'))
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ps.append(('2~0%', int(market_feelings['2']) + int(market_feelings['1']), 'red'))
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ps.append(('平', int(market_feelings['0']), 'gray'))
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ps.append(('0~2%', int(market_feelings['-1']) + int(market_feelings['-2']), 'green'))
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ps.append(
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('2~5%', int(market_feelings['-3']) + int(market_feelings['-4']) + int(market_feelings['-5']), 'green'))
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ps.append(('5~7%', int(market_feelings['-6']) + int(market_feelings['-7']), 'green'))
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ps.append(
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('7%<', int(market_feelings['-8']) + int(market_feelings['-9']) + int(market_feelings['-10']), 'green'))
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ps.append(('跌停', market_feelings['DT'], 'green'))
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fdata = {"strong": market_strong, "map": ps, "SJZT": market_feelings['SJZT'], "SJDT": market_feelings['SJDT'],
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"SZJS": market_feelings['SZJS'], "XDJS": market_feelings['XDJS'], "sign": market_feelings['sign'],
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"qscln": market_feelings['qscln'] // 10000, "q_zrcs": market_feelings['q_zrcs'] // 10000}
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# 获取市场情绪
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return json.dumps(
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{"code": 0, "data": fdata}), True
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__cb_codes_list = None # 所有可转债数据
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__pre_price_dict = {} # 昨日收盘价
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@classmethod
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def buy_by_ths(cls, url):
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can_buy = setting.is_can_ths_buy()
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if can_buy:
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try:
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ps_dict = dict([(k, v[0]) for k, v in parse_qs(urlparse(url).query).items()])
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code = ps_dict["code"]
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trade_gui.start_buy(code)
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return json.dumps(
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{"code": 0, "data": {}}), True
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except Exception as e:
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return json.dumps(
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{"code": 1, "msg": str(e)}), True
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else:
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return json.dumps(
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{"code": 1, "msg": '同花顺不能买入'}), True
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if __name__ == "__main__":
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pass
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