| | |
| | | # 设置历史K线 |
| | | def set_record_datas(code, limit_up_price, record_datas): |
| | | k_format = get_k_format(float(limit_up_price), record_datas) |
| | | CodeNatureRecordManager.save_k_format(code, k_format) |
| | | CodeNatureRecordManager().save_k_format(code, k_format) |
| | | natures = get_nature(record_datas) |
| | | CodeNatureRecordManager.save_nature(code, natures) |
| | | CodeNatureRecordManager().save_nature(code, natures) |
| | | |
| | | |
| | | # 获取K线形态 |
| | |
| | | |
| | | # 是否具有辨识度 |
| | | p9 = is_special(record_datas) |
| | | p10 = is_latest_10d_max_volume_at_latest_2d(record_datas) |
| | | |
| | | return p1, p2, p3, p4, p5, p6, p7, p8, p9 |
| | | return p1, p2, p3, p4, p5, p6, p7, p8, p9, p10 |
| | | |
| | | |
| | | # 是否具有K线形态 |
| | | def is_has_k_format(limit_up_price, record_datas): |
| | | is_too_high, is_new_top, is_lowest, is_near_new_top, is_n, is_v, has_format, volume_info, is_special = get_k_format( |
| | | is_too_high, is_new_top, is_lowest, is_near_new_top, is_n, is_v, has_format, volume_info, is_special, has_max_volume = get_k_format( |
| | | float(limit_up_price), record_datas) |
| | | if not has_format: |
| | | return False, "不满足K线形态" |
| | |
| | | |
| | | |
| | | # 是否涨得太高 |
| | | def is_up_too_high_in_10d(record_datas): |
| | | def is_up_too_high_in_10d_with_limit_up(record_datas): |
| | | datas = copy.deepcopy(record_datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas = datas[-10:] |
| | |
| | | return True |
| | | |
| | | return False |
| | | |
| | | |
| | | # 10天内的最高量是否集中在最近两天 |
| | | def is_latest_10d_max_volume_at_latest_2d(record_datas): |
| | | datas = copy.deepcopy(record_datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas = datas[-10:] |
| | | max_volume_info = None |
| | | for i in range(0, len(datas)): |
| | | if not max_volume_info: |
| | | max_volume_info = (i, datas[i]["volume"]) |
| | | else: |
| | | if max_volume_info[1] < datas[i]["volume"]: |
| | | max_volume_info = (i, datas[i]["volume"]) |
| | | return len(datas) - max_volume_info[0] <= 2 |
| | | |
| | | |
| | | # 120 天内是否长得太高 |
| | |
| | | return False |
| | | |
| | | |
| | | # 在最近几天内股价是否长得太高 |
| | | def is_price_too_high_in_days(record_datas, limit_up_price, day_count=6): |
| | | datas = copy.deepcopy(record_datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas = datas[0 - day_count:] |
| | | min_price = None |
| | | max_price = None |
| | | for d in datas: |
| | | if min_price is None: |
| | | min_price = d["low"] |
| | | if max_price is None: |
| | | max_price = d["high"] |
| | | if min_price > d["low"]: |
| | | min_price = d["low"] |
| | | if max_price < d["high"]: |
| | | max_price = d["high"] |
| | | if max_price > float(limit_up_price): |
| | | return False |
| | | rate = (float(limit_up_price) - min_price) / min_price |
| | | # print(rate) |
| | | if rate >= 0.25: |
| | | return True |
| | | return False |
| | | |
| | | |
| | | # 是否有涨停 |
| | | def get_first_limit_up_count(datas): |
| | | datas = copy.deepcopy(datas) |