Initial commit

.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

Bi/Bi.py

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+from typing import List, Optional
+
+from Common.cache import make_cache
+from Common.CEnum import BI_DIR, BI_TYPE, DATA_FIELD, FX_TYPE, MACD_ALGO
+from Common.ChanException import CChanException, ErrCode
+from KLine.KLine import CKLine
+from KLine.KLine_Unit import CKLine_Unit
+
+
+class CBi:
+    def __init__(self, begin_klc: CKLine, end_klc: CKLine, idx: int, is_sure: bool):
+        # self.__begin_klc = begin_klc
+        # self.__end_klc = end_klc
+        self.__dir = None
+        self.__idx = idx
+        self.__type = BI_TYPE.STRICT
+
+        self.set(begin_klc, end_klc)
+
+        self.__is_sure = is_sure
+        self.__sure_end: List[CKLine] = []
+
+        self.__seg_idx: Optional[int] = None
+
+        from Seg.Seg import CSeg
+        self.parent_seg: Optional[CSeg[CBi]] = None  # 在哪个线段里面
+
+        from BuySellPoint.BS_Point import CBS_Point
+        self.bsp: Optional[CBS_Point] = None  # 尾部是不是买卖点
+
+        self.next: Optional[CBi] = None
+        self.pre: Optional[CBi] = None
+
+    def clean_cache(self):
+        self._memoize_cache = {}
+
+    @property
+    def begin_klc(self): return self.__begin_klc
+
+    @property
+    def end_klc(self): return self.__end_klc
+
+    @property
+    def dir(self): return self.__dir
+
+    @property
+    def idx(self): return self.__idx
+
+    @property
+    def type(self): return self.__type
+
+    @property
+    def is_sure(self): return self.__is_sure
+
+    @property
+    def sure_end(self): return self.__sure_end
+
+    @property
+    def klc_lst(self):
+        klc = self.begin_klc
+        while True:
+            yield klc
+            klc = klc.next
+            if not klc or klc.idx > self.end_klc.idx:
+                break
+
+    @property
+    def klc_lst_re(self):
+        klc = self.end_klc
+        while True:
+            yield klc
+            klc = klc.pre
+            if not klc or klc.idx < self.begin_klc.idx:
+                break
+
+    @property
+    def seg_idx(self): return self.__seg_idx
+
+    def set_seg_idx(self, idx):
+        self.__seg_idx = idx
+
+    def __str__(self):
+        return f"{self.dir}|{self.begin_klc} ~ {self.end_klc}"
+
+    def check(self):
+        try:
+            if self.is_down():
+                assert self.begin_klc.high > self.end_klc.low
+            else:
+                assert self.begin_klc.low < self.end_klc.high
+        except Exception as e:
+            raise CChanException(f"{self.idx}:{self.begin_klc[0].time}~{self.end_klc[-1].time}笔的方向和收尾位置不一致!", ErrCode.BI_ERR) from e
+
+    def set(self, begin_klc: CKLine, end_klc: CKLine):
+        self.__begin_klc: CKLine = begin_klc
+        self.__end_klc: CKLine = end_klc
+        if begin_klc.fx == FX_TYPE.BOTTOM:
+            self.__dir = BI_DIR.UP
+        elif begin_klc.fx == FX_TYPE.TOP:
+            self.__dir = BI_DIR.DOWN
+        else:
+            raise CChanException("ERROR DIRECTION when creating bi", ErrCode.BI_ERR)
+        self.check()
+        self.clean_cache()
+
+    @make_cache
+    def get_begin_val(self):
+        return self.begin_klc.low if self.is_up() else self.begin_klc.high
+
+    @make_cache
+    def get_end_val(self):
+        return self.end_klc.high if self.is_up() else self.end_klc.low
+
+    @make_cache
+    def get_begin_klu(self) -> CKLine_Unit:
+        if self.is_up():
+            return self.begin_klc.get_peak_klu(is_high=False)
+        else:
+            return self.begin_klc.get_peak_klu(is_high=True)
+
+    @make_cache
+    def get_end_klu(self) -> CKLine_Unit:
+        if self.is_up():
+            return self.end_klc.get_peak_klu(is_high=True)
+        else:
+            return self.end_klc.get_peak_klu(is_high=False)
+
+    @make_cache
+    def amp(self):
+        return abs(self.get_end_val() - self.get_begin_val())
+
+    @make_cache
+    def get_klu_cnt(self):
+        return self.get_end_klu().idx - self.get_begin_klu().idx + 1
+
+    @make_cache
+    def get_klc_cnt(self):
+        assert self.end_klc.idx == self.get_end_klu().klc.idx
+        assert self.begin_klc.idx == self.get_begin_klu().klc.idx
+        return self.end_klc.idx - self.begin_klc.idx + 1
+
+    @make_cache
+    def _high(self):
+        return self.end_klc.high if self.is_up() else self.begin_klc.high
+
+    @make_cache
+    def _low(self):
+        return self.begin_klc.low if self.is_up() else self.end_klc.low
+
+    @make_cache
+    def _mid(self):
+        return (self._high() + self._low()) / 2  # 笔的中位价
+
+    @make_cache
+    def is_down(self):
+        return self.dir == BI_DIR.DOWN
+
+    @make_cache
+    def is_up(self):
+        return self.dir == BI_DIR.UP
+
+    def update_virtual_end(self, new_klc: CKLine):
+        self.append_sure_end(self.end_klc)
+        self.update_new_end(new_klc)
+        self.__is_sure = False
+
+    def restore_from_virtual_end(self, sure_end: CKLine):
+        self.__is_sure = True
+        self.update_new_end(new_klc=sure_end)
+        self.__sure_end = []
+
+    def append_sure_end(self, klc: CKLine):
+        self.__sure_end.append(klc)
+
+    def update_new_end(self, new_klc: CKLine):
+        self.__end_klc = new_klc
+        self.check()
+        self.clean_cache()
+
+    def cal_macd_metric(self, macd_algo, is_reverse):
+        if macd_algo == MACD_ALGO.AREA:
+            return self.Cal_MACD_half(is_reverse)
+        elif macd_algo == MACD_ALGO.PEAK:
+            return self.Cal_MACD_peak()
+        elif macd_algo == MACD_ALGO.FULL_AREA:
+            return self.Cal_MACD_area()
+        elif macd_algo == MACD_ALGO.DIFF:
+            return self.Cal_MACD_diff()
+        elif macd_algo == MACD_ALGO.SLOPE:
+            return self.Cal_MACD_slope()
+        elif macd_algo == MACD_ALGO.AMP:
+            return self.Cal_MACD_amp()
+        elif macd_algo == MACD_ALGO.AMOUNT:
+            return self.Cal_MACD_trade_metric(DATA_FIELD.FIELD_TURNOVER, cal_avg=False)
+        elif macd_algo == MACD_ALGO.VOLUMN:
+            return self.Cal_MACD_trade_metric(DATA_FIELD.FIELD_VOLUME, cal_avg=False)
+        elif macd_algo == MACD_ALGO.VOLUMN_AVG:
+            return self.Cal_MACD_trade_metric(DATA_FIELD.FIELD_VOLUME, cal_avg=True)
+        elif macd_algo == MACD_ALGO.AMOUNT_AVG:
+            return self.Cal_MACD_trade_metric(DATA_FIELD.FIELD_TURNOVER, cal_avg=True)
+        elif macd_algo == MACD_ALGO.TURNRATE_AVG:
+            return self.Cal_MACD_trade_metric(DATA_FIELD.FIELD_TURNRATE, cal_avg=True)
+        elif macd_algo == MACD_ALGO.RSI:
+            return self.Cal_Rsi()
+        else:
+            raise CChanException(f"unsupport macd_algo={macd_algo}, should be one of area/full_area/peak/diff/slope/amp", ErrCode.PARA_ERROR)
+
+    @make_cache
+    def Cal_Rsi(self):
+        rsi_lst: List[float] = []
+        for klc in self.klc_lst:
+            rsi_lst.extend(klu.rsi for klu in klc.lst)
+        return 10000.0/(min(rsi_lst)+1e-7) if self.is_down() else max(rsi_lst)
+
+    @make_cache
+    def Cal_MACD_area(self):
+        _s = 1e-7
+        begin_klu = self.get_begin_klu()
+        end_klu = self.get_end_klu()
+        for klc in self.klc_lst:
+            for klu in klc.lst:
+                if klu.idx < begin_klu.idx or klu.idx > end_klu.idx:
+                    continue
+                if (self.is_down() and klu.macd.macd < 0) or (self.is_up() and klu.macd.macd > 0):
+                    _s += abs(klu.macd.macd)
+        return _s
+
+    @make_cache
+    def Cal_MACD_peak(self):
+        peak = 1e-7
+        for klc in self.klc_lst:
+            for klu in klc.lst:
+                if abs(klu.macd.macd) > peak:
+                    if self.is_down() and klu.macd.macd < 0:
+                        peak = abs(klu.macd.macd)
+                    elif self.is_up() and klu.macd.macd > 0:
+                        peak = abs(klu.macd.macd)
+        return peak
+
+    def Cal_MACD_half(self, is_reverse):
+        if is_reverse:
+            return self.Cal_MACD_half_reverse()
+        else:
+            return self.Cal_MACD_half_obverse()
+
+    @make_cache
+    def Cal_MACD_half_obverse(self):
+        _s = 1e-7
+        begin_klu = self.get_begin_klu()
+        peak_macd = begin_klu.macd.macd
+        for klc in self.klc_lst:
+            for klu in klc.lst:
+                if klu.idx < begin_klu.idx:
+                    continue
+                if klu.macd.macd*peak_macd > 0:
+                    _s += abs(klu.macd.macd)
+                else:
+                    break
+            else:  # 没有被break，继续找写一个KLC
+                continue
+            break
+        return _s
+
+    @make_cache
+    def Cal_MACD_half_reverse(self):
+        _s = 1e-7
+        begin_klu = self.get_end_klu()
+        peak_macd = begin_klu.macd.macd
+        for klc in self.klc_lst_re:
+            for klu in klc[::-1]:
+                if klu.idx > begin_klu.idx:
+                    continue
+                if klu.macd.macd*peak_macd > 0:
+                    _s += abs(klu.macd.macd)
+                else:
+                    break
+            else:  # 没有被break，继续找写一个KLC
+                continue
+            break
+        return _s
+
+    @make_cache
+    def Cal_MACD_diff(self):
+        """
+        macd红绿柱最大值最小值之差
+        """
+        _max, _min = float("-inf"), float("inf")
+        for klc in self.klc_lst:
+            for klu in klc.lst:
+                macd = klu.macd.macd
+                if macd > _max:
+                    _max = macd
+                if macd < _min:
+                    _min = macd
+        return _max-_min
+
+    @make_cache
+    def Cal_MACD_slope(self):
+        begin_klu = self.get_begin_klu()
+        end_klu = self.get_end_klu()
+        if self.is_up():
+            return (end_klu.high - begin_klu.low)/end_klu.high/(end_klu.idx - begin_klu.idx + 1)
+        else:
+            return (begin_klu.high - end_klu.low)/begin_klu.high/(end_klu.idx - begin_klu.idx + 1)
+
+    @make_cache
+    def Cal_MACD_amp(self):
+        begin_klu = self.get_begin_klu()
+        end_klu = self.get_end_klu()
+        if self.is_down():
+            return (begin_klu.high-end_klu.low)/begin_klu.high
+        else:
+            return (end_klu.high-begin_klu.low)/begin_klu.low
+
+    def Cal_MACD_trade_metric(self, metric: str, cal_avg=False) -> float:
+        _s = 0
+        for klc in self.klc_lst:
+            for klu in klc.lst:
+                metric_res = klu.trade_info.metric[metric]
+                if metric_res is None:
+                    return 0.0
+                _s += metric_res
+        return _s / self.get_klu_cnt() if cal_avg else _s
+
+    # def set_klc_lst(self, lst):
+    #     self.__klc_lst = lst

Bi/BiConfig.py

@@ -0,0 +1,30 @@
+from Common.CEnum import FX_CHECK_METHOD
+from Common.ChanException import CChanException, ErrCode
+
+
+class CBiConfig:
+    def __init__(
+        self,
+        bi_algo="normal",
+        is_strict=True,
+        bi_fx_check="half",
+        gap_as_kl=True,
+        bi_end_is_peak=True,
+        bi_allow_sub_peak=True,
+    ):
+        self.bi_algo = bi_algo
+        self.is_strict = is_strict
+        if bi_fx_check == "strict":
+            self.bi_fx_check = FX_CHECK_METHOD.STRICT
+        elif bi_fx_check == "loss":
+            self.bi_fx_check = FX_CHECK_METHOD.LOSS
+        elif bi_fx_check == "half":
+            self.bi_fx_check = FX_CHECK_METHOD.HALF
+        elif bi_fx_check == 'totally':
+            self.bi_fx_check = FX_CHECK_METHOD.TOTALLY
+        else:
+            raise CChanException(f"unknown bi_fx_check={bi_fx_check}", ErrCode.PARA_ERROR)
+
+        self.gap_as_kl = gap_as_kl
+        self.bi_end_is_peak = bi_end_is_peak
+        self.bi_allow_sub_peak = bi_allow_sub_peak

Bi/BiList.py

@@ -0,0 +1,235 @@
+from typing import List, Optional, Union, overload
+
+from Common.CEnum import FX_TYPE, KLINE_DIR
+from KLine.KLine import CKLine
+
+from .Bi import CBi
+from .BiConfig import CBiConfig
+
+
+class CBiList:
+    def __init__(self, bi_conf=CBiConfig()):
+        self.bi_list: List[CBi] = []
+        self.last_end = None  # 最后一笔的尾部
+        self.config = bi_conf
+
+        self.free_klc_lst = []  # 仅仅用作第一笔未画出来之前的缓存，为了获得更精准的结果而已，不加这块逻辑其实对后续计算没太大影响
+
+    def __str__(self):
+        return "\n".join([str(bi) for bi in self.bi_list])
+
+    def __iter__(self):
+        yield from self.bi_list
+
+    @overload
+    def __getitem__(self, index: int) -> CBi: ...
+
+    @overload
+    def __getitem__(self, index: slice) -> List[CBi]: ...
+
+    def __getitem__(self, index: Union[slice, int]) -> Union[List[CBi], CBi]:
+        return self.bi_list[index]
+
+    def __len__(self):
+        return len(self.bi_list)
+
+    def try_create_first_bi(self, klc: CKLine) -> bool:
+        for exist_free_klc in self.free_klc_lst:
+            if exist_free_klc.fx == klc.fx:
+                continue
+            if self.can_make_bi(klc, exist_free_klc):
+                self.add_new_bi(exist_free_klc, klc)
+                self.last_end = klc
+                return True
+        self.free_klc_lst.append(klc)
+        self.last_end = klc
+        return False
+
+    def update_bi(self, klc: CKLine, last_klc: CKLine, cal_virtual: bool) -> bool:
+        # klc: 倒数第二根klc
+        # last_klc: 倒数第1根klc
+        flag1 = self.update_bi_sure(klc)
+        if cal_virtual:
+            flag2 = self.try_add_virtual_bi(last_klc)
+            return flag1 or flag2
+        else:
+            return flag1
+
+    def can_update_peak(self, klc: CKLine):
+        if self.config.bi_allow_sub_peak or len(self.bi_list) < 2:
+            return False
+        if self.bi_list[-1].is_down() and klc.high < self.bi_list[-1].get_begin_val():
+            return False
+        if self.bi_list[-1].is_up() and klc.low > self.bi_list[-1].get_begin_val():
+            return False
+        if not end_is_peak(self.bi_list[-2].begin_klc, klc):
+            return False
+        if self[-1].is_down() and self[-1].get_end_val() < self[-2].get_begin_val():
+            return False
+        if self[-1].is_up() and self[-1].get_end_val() > self[-2].get_begin_val():
+            return False
+        return True
+
+    def update_peak(self, klc: CKLine, for_virtual=False):
+        if not self.can_update_peak(klc):
+            return False
+        _tmp_last_bi = self.bi_list[-1]
+        self.bi_list.pop()
+        if not self.try_update_end(klc, for_virtual=for_virtual):
+            self.bi_list.append(_tmp_last_bi)
+            return False
+        else:
+            if for_virtual:
+                self.bi_list[-1].append_sure_end(_tmp_last_bi.end_klc)
+            return True
+
+    def update_bi_sure(self, klc: CKLine) -> bool:
+        # klc: 倒数第二根klc
+        _tmp_end = self.get_last_klu_of_last_bi()
+        self.delete_virtual_bi()
+        # 返回值：是否出现新笔
+        if klc.fx == FX_TYPE.UNKNOWN:
+            return _tmp_end != self.get_last_klu_of_last_bi()  # 虚笔是否有变
+        if self.last_end is None or len(self.bi_list) == 0:
+            return self.try_create_first_bi(klc)
+        if klc.fx == self.last_end.fx:
+            return self.try_update_end(klc)
+        elif self.can_make_bi(klc, self.last_end):
+            self.add_new_bi(self.last_end, klc)
+            self.last_end = klc
+            return True
+        elif self.update_peak(klc):
+            return True
+        return _tmp_end != self.get_last_klu_of_last_bi()
+
+    def delete_virtual_bi(self):
+        if len(self) > 0 and not self.bi_list[-1].is_sure:
+            sure_end_list = [klc for klc in self.bi_list[-1].sure_end]
+            if len(sure_end_list):
+                self.bi_list[-1].restore_from_virtual_end(sure_end_list[0])
+                self.last_end = self[-1].end_klc
+                for sure_end in sure_end_list[1:]:
+                    self.add_new_bi(self.last_end, sure_end, is_sure=True)
+                    self.last_end = self[-1].end_klc
+            else:
+                del self.bi_list[-1]
+        self.last_end = self[-1].end_klc if len(self) > 0 else None
+        if len(self) > 0:
+            self[-1].next = None
+
+    def try_add_virtual_bi(self, klc: CKLine, need_del_end=False):
+        if need_del_end:
+            self.delete_virtual_bi()
+        if len(self) == 0:
+            return False
+        if klc.idx == self[-1].end_klc.idx:
+            return False
+        if (self[-1].is_up() and klc.high >= self[-1].end_klc.high) or (self[-1].is_down() and klc.low <= self[-1].end_klc.low):
+            # 更新最后一笔
+            self.bi_list[-1].update_virtual_end(klc)
+            return True
+        _tmp_klc = klc
+        while _tmp_klc and _tmp_klc.idx > self[-1].end_klc.idx:
+            assert _tmp_klc is not None
+            if self.can_make_bi(_tmp_klc, self[-1].end_klc, for_virtual=True):
+                # 新增一笔
+                self.add_new_bi(self.last_end, _tmp_klc, is_sure=False)
+                return True
+            elif self.update_peak(_tmp_klc, for_virtual=True):
+                return True
+            _tmp_klc = _tmp_klc.pre
+        return False
+
+    def add_new_bi(self, pre_klc, cur_klc, is_sure=True):
+        self.bi_list.append(CBi(pre_klc, cur_klc, idx=len(self.bi_list), is_sure=is_sure))
+        if len(self.bi_list) >= 2:
+            self.bi_list[-2].next = self.bi_list[-1]
+            self.bi_list[-1].pre = self.bi_list[-2]
+
+    def satisfy_bi_span(self, klc: CKLine, last_end: CKLine):
+        bi_span = self.get_klc_span(klc, last_end)
+        if self.config.is_strict:
+            return bi_span >= 4
+        uint_kl_cnt = 0
+        tmp_klc = last_end.next
+        while tmp_klc:
+            uint_kl_cnt += len(tmp_klc.lst)
+            if not tmp_klc.next:  # 最后尾部虚笔的时候，可能klc.idx == last_end.idx+1
+                return False
+            if tmp_klc.next.idx < klc.idx:
+                tmp_klc = tmp_klc.next
+            else:
+                break
+        return bi_span >= 3 and uint_kl_cnt >= 3
+
+    def get_klc_span(self, klc: CKLine, last_end: CKLine) -> int:
+        span = klc.idx - last_end.idx
+        if not self.config.gap_as_kl:
+            return span
+        if span >= 4:  # 加速运算，如果span需要真正精确的值，需要去掉这一行
+            return span
+        tmp_klc = last_end
+        while tmp_klc and tmp_klc.idx < klc.idx:
+            if tmp_klc.has_gap_with_next():
+                span += 1
+            tmp_klc = tmp_klc.next
+        return span
+
+    def can_make_bi(self, klc: CKLine, last_end: CKLine, for_virtual: bool = False):
+        satisify_span = True if self.config.bi_algo == 'fx' else self.satisfy_bi_span(klc, last_end)
+        if not satisify_span:
+            return False
+        if not last_end.check_fx_valid(klc, self.config.bi_fx_check, for_virtual):
+            return False
+        if self.config.bi_end_is_peak and not end_is_peak(last_end, klc):
+            return False
+        return True
+
+    def try_update_end(self, klc: CKLine, for_virtual=False) -> bool:
+        def check_top(klc: CKLine, for_virtual):
+            if for_virtual:
+                return klc.dir == KLINE_DIR.UP
+            else:
+                return klc.fx == FX_TYPE.TOP
+
+        def check_bottom(klc: CKLine, for_virtual):
+            if for_virtual:
+                return klc.dir == KLINE_DIR.DOWN
+            else:
+                return klc.fx == FX_TYPE.BOTTOM
+
+        if len(self.bi_list) == 0:
+            return False
+        last_bi = self.bi_list[-1]
+        if (last_bi.is_up() and check_top(klc, for_virtual) and klc.high >= last_bi.get_end_val()) or \
+           (last_bi.is_down() and check_bottom(klc, for_virtual) and klc.low <= last_bi.get_end_val()):
+            last_bi.update_virtual_end(klc) if for_virtual else last_bi.update_new_end(klc)
+            self.last_end = klc
+            return True
+        else:
+            return False
+
+    def get_last_klu_of_last_bi(self) -> Optional[int]:
+        return self.bi_list[-1].get_end_klu().idx if len(self) > 0 else None
+
+
+def end_is_peak(last_end: CKLine, cur_end: CKLine) -> bool:
+    if last_end.fx == FX_TYPE.BOTTOM:
+        cmp_thred = cur_end.high  # 或者严格点选择get_klu_max_high()
+        klc = last_end.get_next()
+        while True:
+            if klc.idx >= cur_end.idx:
+                return True
+            if klc.high > cmp_thred:
+                return False
+            klc = klc.get_next()
+    elif last_end.fx == FX_TYPE.TOP:
+        cmp_thred = cur_end.low  # 或者严格点选择get_klu_min_low()
+        klc = last_end.get_next()
+        while True:
+            if klc.idx >= cur_end.idx:
+                return True
+            if klc.low < cmp_thred:
+                return False
+            klc = klc.get_next()
+    return True

BuySellPoint/BSPointConfig.py

@@ -0,0 +1,78 @@
+from typing import Dict, List, Optional
+
+from Common.CEnum import BSP_TYPE, MACD_ALGO
+from Common.func_util import _parse_inf
+
+
+class CBSPointConfig:
+    def __init__(self, **args):
+        self.b_conf = CPointConfig(**args)
+        self.s_conf = CPointConfig(**args)
+
+    def GetBSConfig(self, is_buy):
+        return self.b_conf if is_buy else self.s_conf
+
+
+class CPointConfig:
+    def __init__(self,
+                 divergence_rate,
+                 min_zs_cnt,
+                 bsp1_only_multibi_zs,
+                 max_bs2_rate,
+                 macd_algo,
+                 bs1_peak,
+                 bs_type,
+                 bsp2_follow_1,
+                 bsp3_follow_1,
+                 bsp3_peak,
+                 bsp2s_follow_2,
+                 max_bsp2s_lv,
+                 strict_bsp3,
+                 ):
+        self.divergence_rate = divergence_rate
+        self.min_zs_cnt = min_zs_cnt
+        self.bsp1_only_multibi_zs = bsp1_only_multibi_zs
+        self.max_bs2_rate = max_bs2_rate
+        assert self.max_bs2_rate <= 1
+        self.SetMacdAlgo(macd_algo)
+        self.bs1_peak = bs1_peak
+        self.tmp_target_types = bs_type
+        self.target_types: List[BSP_TYPE] = []
+        self.bsp2_follow_1 = bsp2_follow_1
+        self.bsp3_follow_1 = bsp3_follow_1
+        self.bsp3_peak = bsp3_peak
+        self.bsp2s_follow_2 = bsp2s_follow_2
+        self.max_bsp2s_lv: Optional[int] = max_bsp2s_lv
+        self.strict_bsp3 = strict_bsp3
+
+    def parse_target_type(self):
+        _d: Dict[str, BSP_TYPE] = {x.value: x for x in BSP_TYPE}
+        if isinstance(self.tmp_target_types, str):
+            self.tmp_target_types = [t.strip() for t in self.tmp_target_types.split(",")]
+        for target_t in self.tmp_target_types:
+            assert target_t in ['1', '2', '3a', '2s', '1p', '3b']
+        self.target_types = [_d[_type] for _type in self.tmp_target_types]
+
+    def SetMacdAlgo(self, macd_algo):
+        _d = {
+            "area": MACD_ALGO.AREA,
+            "peak": MACD_ALGO.PEAK,
+            "full_area": MACD_ALGO.FULL_AREA,
+            "diff": MACD_ALGO.DIFF,
+            "slope": MACD_ALGO.SLOPE,
+            "amp": MACD_ALGO.AMP,
+            "amount": MACD_ALGO.AMOUNT,
+            "volumn": MACD_ALGO.VOLUMN,
+            "amount_avg": MACD_ALGO.AMOUNT_AVG,
+            "volumn_avg": MACD_ALGO.VOLUMN_AVG,
+            "turnrate_avg": MACD_ALGO.AMOUNT_AVG,
+            "rsi": MACD_ALGO.RSI,
+        }
+        self.macd_algo = _d[macd_algo]
+
+    def set(self, k, v):
+        v = _parse_inf(v)
+        if k == "macd_algo":
+            self.SetMacdAlgo(v)
+        else:
+            exec(f"self.{k} = {v}")

BuySellPoint/BSPointList.py

@@ -0,0 +1,342 @@
+from typing import Dict, Generic, List, Optional, TypeVar, Union, overload
+
+from Bi.Bi import CBi
+from Bi.BiList import CBiList
+from Common.CEnum import BSP_TYPE
+from Common.func_util import has_overlap
+from Seg.Seg import CSeg
+from Seg.SegListComm import CSegListComm
+from ZS.ZS import CZS
+
+from .BS_Point import CBS_Point
+from .BSPointConfig import CBSPointConfig, CPointConfig
+
+LINE_TYPE = TypeVar('LINE_TYPE', CBi, CSeg[CBi])
+LINE_LIST_TYPE = TypeVar('LINE_LIST_TYPE', CBiList, CSegListComm[CBi])
+
+
+class CBSPointList(Generic[LINE_TYPE, LINE_LIST_TYPE]):
+    def __init__(self, bs_point_config: CBSPointConfig):
+        self.lst: List[CBS_Point[LINE_TYPE]] = []
+        self.bsp_dict: Dict[int, CBS_Point[LINE_TYPE]] = {}
+        self.bsp1_lst: List[CBS_Point[LINE_TYPE]] = []
+        self.config = bs_point_config
+        self.last_sure_pos = -1
+
+    def __iter__(self):
+        yield from self.lst
+
+    def __len__(self):
+        return len(self.lst)
+
+    @overload
+    def __getitem__(self, index: int) -> CBS_Point: ...
+
+    @overload
+    def __getitem__(self, index: slice) -> List[CBS_Point]: ...
+
+    def __getitem__(self, index: Union[slice, int]) -> Union[List[CBS_Point], CBS_Point]:
+        return self.lst[index]
+
+    def cal(self, bi_list: LINE_LIST_TYPE, seg_list: CSegListComm[LINE_TYPE]):
+        self.lst = [bsp for bsp in self.lst if bsp.klu.idx <= self.last_sure_pos]
+        self.bsp_dict = {bsp.bi.get_end_klu().idx: bsp for bsp in self.lst}
+        self.bsp1_lst = [bsp for bsp in self.bsp1_lst if bsp.klu.idx <= self.last_sure_pos]
+
+        self.cal_seg_bs1point(seg_list, bi_list)
+        self.cal_seg_bs2point(seg_list, bi_list)
+        self.cal_seg_bs3point(seg_list, bi_list)
+
+        self.update_last_pos(seg_list)
+
+    def update_last_pos(self, seg_list: CSegListComm):
+        self.last_sure_pos = -1
+        for seg in seg_list[::-1]:
+            if seg.is_sure:
+                self.last_sure_pos = seg.end_bi.get_begin_klu().idx
+                return
+
+    def seg_need_cal(self, seg: CSeg):
+        return seg.end_bi.get_end_klu().idx > self.last_sure_pos
+
+    def add_bs(
+        self,
+        bs_type: BSP_TYPE,
+        bi: LINE_TYPE,
+        relate_bsp1: Optional[CBS_Point],
+        is_target_bsp: bool = True,
+        feature_dict=None,
+    ):
+        is_buy = bi.is_down()
+        if exist_bsp := self.bsp_dict.get(bi.get_end_klu().idx):
+            assert exist_bsp.is_buy == is_buy
+            exist_bsp.add_another_bsp_prop(bs_type, relate_bsp1)
+            return
+        if bs_type not in self.config.GetBSConfig(is_buy).target_types:
+            is_target_bsp = False
+
+        if is_target_bsp or bs_type in [BSP_TYPE.T1, BSP_TYPE.T1P]:
+            bsp = CBS_Point[LINE_TYPE](
+                bi=bi,
+                is_buy=is_buy,
+                bs_type=bs_type,
+                relate_bsp1=relate_bsp1,
+                feature_dict=feature_dict,
+            )
+        else:
+            return
+        if is_target_bsp:
+            self.lst.append(bsp)
+            self.bsp_dict[bi.get_end_klu().idx] = bsp
+        if bs_type in [BSP_TYPE.T1, BSP_TYPE.T1P]:
+            self.bsp1_lst.append(bsp)
+
+    def cal_seg_bs1point(self, seg_list: CSegListComm[LINE_TYPE], bi_list: LINE_LIST_TYPE):
+        for seg in seg_list:
+            if not self.seg_need_cal(seg):
+                continue
+            self.cal_single_bs1point(seg, bi_list)
+
+    def cal_single_bs1point(self, seg: CSeg[LINE_TYPE], bi_list: LINE_LIST_TYPE):
+        BSP_CONF = self.config.GetBSConfig(seg.is_down())
+        zs_cnt = seg.get_multi_bi_zs_cnt() if BSP_CONF.bsp1_only_multibi_zs else len(seg.zs_lst)
+        is_target_bsp = (BSP_CONF.min_zs_cnt <= 0 or zs_cnt >= BSP_CONF.min_zs_cnt)
+        if len(seg.zs_lst) > 0 and \
+           not seg.zs_lst[-1].is_one_bi_zs() and \
+           ((seg.zs_lst[-1].bi_out and seg.zs_lst[-1].bi_out.idx >= seg.end_bi.idx) or seg.zs_lst[-1].bi_lst[-1].idx >= seg.end_bi.idx) \
+           and seg.end_bi.idx - seg.zs_lst[-1].get_bi_in().idx > 2:
+            self.treat_bsp1(seg, BSP_CONF, is_target_bsp)
+        else:
+            self.treat_pz_bsp1(seg, BSP_CONF, bi_list, is_target_bsp)
+
+    def treat_bsp1(self, seg: CSeg[LINE_TYPE], BSP_CONF: CPointConfig, is_target_bsp: bool):
+        last_zs = seg.zs_lst[-1]
+        break_peak, _ = last_zs.out_bi_is_peak(seg.end_bi.idx)
+        if BSP_CONF.bs1_peak and not break_peak:
+            is_target_bsp = False
+        is_diver, divergence_rate = last_zs.is_divergence(BSP_CONF, out_bi=seg.end_bi)
+        if not is_diver:
+            is_target_bsp = False
+        feature_dict = {'divergence_rate': divergence_rate}
+        self.add_bs(bs_type=BSP_TYPE.T1, bi=seg.end_bi, relate_bsp1=None, is_target_bsp=is_target_bsp, feature_dict=feature_dict)
+
+    def treat_pz_bsp1(self, seg: CSeg[LINE_TYPE], BSP_CONF: CPointConfig, bi_list: LINE_LIST_TYPE, is_target_bsp):
+        last_bi = seg.end_bi
+        pre_bi = bi_list[last_bi.idx-2]
+        if last_bi.seg_idx != pre_bi.seg_idx:
+            return
+        if last_bi.dir != seg.dir:
+            return
+        if last_bi.is_down() and last_bi._low() > pre_bi._low():  # 创新低
+            return
+        if last_bi.is_up() and last_bi._high() < pre_bi._high():  # 创新高
+            return
+        in_metric = pre_bi.cal_macd_metric(BSP_CONF.macd_algo, is_reverse=False)
+        out_metric = last_bi.cal_macd_metric(BSP_CONF.macd_algo, is_reverse=True)
+        is_diver, divergence_rate = out_metric <= BSP_CONF.divergence_rate*in_metric, out_metric/(in_metric+1e-7)
+        if not is_diver:
+            is_target_bsp = False
+        if isinstance(bi_list, CBiList):
+            assert isinstance(last_bi, CBi) and isinstance(pre_bi, CBi)
+        feature_dict = {'divergence_rate': divergence_rate}
+        self.add_bs(bs_type=BSP_TYPE.T1P, bi=last_bi, relate_bsp1=None, is_target_bsp=is_target_bsp, feature_dict=feature_dict)
+
+    def cal_seg_bs2point(self, seg_list: CSegListComm[LINE_TYPE], bi_list: LINE_LIST_TYPE):
+        bsp1_bi_idx_dict = {bsp.bi.idx: bsp for bsp in self.bsp1_lst}
+        for seg in seg_list:
+            config = self.config.GetBSConfig(seg.is_down())
+            if BSP_TYPE.T2 not in config.target_types and BSP_TYPE.T2S not in config.target_types:
+                continue
+            self.treat_bsp2(seg, bsp1_bi_idx_dict, seg_list, bi_list)
+
+    def treat_bsp2(self, seg: CSeg, bsp1_bi_idx_dict, seg_list: CSegListComm[LINE_TYPE], bi_list: LINE_LIST_TYPE):
+        if not self.seg_need_cal(seg):
+            return
+        if len(seg_list) > 1:
+            BSP_CONF = self.config.GetBSConfig(seg.is_down())
+            bsp1_bi = seg.end_bi
+            bsp1_bi_idx = bsp1_bi.idx
+            real_bsp1 = bsp1_bi_idx_dict.get(bsp1_bi.idx)
+            if bsp1_bi.idx + 2 >= len(bi_list):
+                return
+            break_bi = bi_list[bsp1_bi.idx + 1]
+            bsp2_bi = bi_list[bsp1_bi.idx + 2]
+        else:
+            BSP_CONF = self.config.GetBSConfig(seg.is_up())
+            bsp1_bi, real_bsp1 = None, None
+            bsp1_bi_idx = -1
+            if len(bi_list) == 1:
+                return
+            bsp2_bi = bi_list[1]
+            break_bi = bi_list[0]
+        if BSP_CONF.bsp2_follow_1 and bsp1_bi_idx not in [bsp.bi.idx for bsp in self.bsp_dict.values()]:  # check bsp2_follow_1
+            return
+        retrace_rate = bsp2_bi.amp()/break_bi.amp()
+        bsp2_flag = retrace_rate <= BSP_CONF.max_bs2_rate
+        if bsp2_flag:
+            self.add_bs(bs_type=BSP_TYPE.T2, bi=bsp2_bi, relate_bsp1=real_bsp1)  # type: ignore
+        elif BSP_CONF.bsp2s_follow_2:
+            return
+        if BSP_TYPE.T2S not in self.config.GetBSConfig(seg.is_down()).target_types:
+            return
+        self.treat_bsp2s(seg_list, bi_list, bsp2_bi, break_bi, real_bsp1, BSP_CONF)  # type: ignore
+
+    def treat_bsp2s(
+        self,
+        seg_list: CSegListComm,
+        bi_list: LINE_LIST_TYPE,
+        bsp2_bi: LINE_TYPE,
+        break_bi: LINE_TYPE,
+        real_bsp1: Optional[CBS_Point],
+        BSP_CONF: CPointConfig,
+    ):
+        bias = 2
+        _low, _high = None, None
+        while bsp2_bi.idx + bias < len(bi_list):  # 计算类二
+            bsp2s_bi = bi_list[bsp2_bi.idx + bias]
+            assert bsp2s_bi.seg_idx is not None and bsp2_bi.seg_idx is not None
+            if BSP_CONF.max_bsp2s_lv is not None and bias/2 > BSP_CONF.max_bsp2s_lv:
+                break
+            if bsp2s_bi.seg_idx != bsp2_bi.seg_idx and (bsp2s_bi.seg_idx < len(seg_list)-1 or bsp2s_bi.seg_idx - bsp2_bi.seg_idx >= 2 or seg_list[bsp2_bi.seg_idx].is_sure):
+                break
+            if bias == 2:
+                if not has_overlap(bsp2_bi._low(), bsp2_bi._high(), bsp2s_bi._low(), bsp2s_bi._high()):
+                    break
+                _low = max([bsp2_bi._low(), bsp2s_bi._low()])
+                _high = min([bsp2_bi._high(), bsp2s_bi._high()])
+            elif not has_overlap(_low, _high, bsp2s_bi._low(), bsp2s_bi._high()):
+                break
+
+            if bsp2s_break_bsp1(bsp2s_bi, break_bi):
+                break
+            retrace_rate = abs(bsp2s_bi.get_end_val()-break_bi.get_end_val())/break_bi.amp()
+            if retrace_rate > BSP_CONF.max_bs2_rate:
+                break
+
+            self.add_bs(bs_type=BSP_TYPE.T2S, bi=bsp2s_bi, relate_bsp1=real_bsp1)  # type: ignore
+            bias += 2
+
+    def cal_seg_bs3point(self, seg_list: CSegListComm[LINE_TYPE], bi_list: LINE_LIST_TYPE):
+        bsp1_bi_idx_dict = {bsp.bi.idx: bsp for bsp in self.bsp1_lst}
+        for seg in seg_list:
+            if not self.seg_need_cal(seg):
+                continue
+            config = self.config.GetBSConfig(seg.is_down())
+            if BSP_TYPE.T3A not in config.target_types and BSP_TYPE.T3B not in config.target_types:
+                continue
+            if len(seg_list) > 1:
+                bsp1_bi = seg.end_bi
+                bsp1_bi_idx = bsp1_bi.idx
+                BSP_CONF = self.config.GetBSConfig(seg.is_down())
+                real_bsp1 = bsp1_bi_idx_dict.get(bsp1_bi.idx)
+                next_seg_idx = seg.idx+1
+                next_seg = seg.next  # 可能为None, 所以并不一定可以保证next_seg_idx == next_seg.idx
+            else:
+                next_seg = seg
+                next_seg_idx = seg.idx
+                bsp1_bi, real_bsp1 = None, None
+                bsp1_bi_idx = -1
+                BSP_CONF = self.config.GetBSConfig(seg.is_up())
+            if BSP_CONF.bsp3_follow_1 and bsp1_bi_idx not in [bsp.bi.idx for bsp in self.bsp_dict.values()]:
+                continue
+            if next_seg:
+                self.treat_bsp3_after(seg_list, next_seg, BSP_CONF, bi_list, real_bsp1, bsp1_bi_idx, next_seg_idx)
+            self.treat_bsp3_before(seg_list, seg, next_seg, bsp1_bi, BSP_CONF, bi_list, real_bsp1, next_seg_idx)
+
+    def treat_bsp3_after(
+        self,
+        seg_list: CSegListComm[LINE_TYPE],
+        next_seg: CSeg[LINE_TYPE],
+        BSP_CONF: CPointConfig,
+        bi_list: LINE_LIST_TYPE,
+        real_bsp1,
+        bsp1_bi_idx,
+        next_seg_idx
+    ):
+        first_zs = next_seg.get_first_multi_bi_zs()
+        if first_zs is None:
+            return
+        if BSP_CONF.strict_bsp3 and first_zs.get_bi_in().idx != bsp1_bi_idx+1:
+            return
+        if first_zs.bi_out is None or first_zs.bi_out.idx+1 >= len(bi_list):
+            return
+        bsp3_bi = bi_list[first_zs.bi_out.idx+1]
+        if bsp3_bi.parent_seg is None:
+            if next_seg.idx != len(seg_list)-1:
+                return
+        elif bsp3_bi.parent_seg.idx != next_seg.idx:
+            if len(bsp3_bi.parent_seg.bi_list) >= 3:
+                return
+        if bsp3_bi.dir == next_seg.dir:
+            return
+        if bsp3_bi.seg_idx != next_seg_idx and next_seg_idx < len(seg_list)-2:
+            return
+        if bsp3_back2zs(bsp3_bi, first_zs):
+            return
+        bsp3_peak_zs = bsp3_break_zspeak(bsp3_bi, first_zs)
+        if BSP_CONF.bsp3_peak and not bsp3_peak_zs:
+            return
+        self.add_bs(bs_type=BSP_TYPE.T3A, bi=bsp3_bi, relate_bsp1=real_bsp1)  # type: ignore
+
+    def treat_bsp3_before(
+        self,
+        seg_list: CSegListComm[LINE_TYPE],
+        seg: CSeg[LINE_TYPE],
+        next_seg: Optional[CSeg[LINE_TYPE]],
+        bsp1_bi: Optional[LINE_TYPE],
+        BSP_CONF: CPointConfig,
+        bi_list: LINE_LIST_TYPE,
+        real_bsp1,
+        next_seg_idx
+    ):
+        cmp_zs = seg.get_final_multi_bi_zs()
+        if cmp_zs is None:
+            return
+        if not bsp1_bi:
+            return
+        if BSP_CONF.strict_bsp3 and (cmp_zs.bi_out is None or cmp_zs.bi_out.idx != bsp1_bi.idx):
+            return
+        end_bi_idx = cal_bsp3_bi_end_idx(next_seg)
+        for bsp3_bi in bi_list[bsp1_bi.idx+2::2]:
+            if bsp3_bi.idx > end_bi_idx:
+                break
+            assert bsp3_bi.seg_idx is not None
+            if bsp3_bi.seg_idx != next_seg_idx and bsp3_bi.seg_idx < len(seg_list)-1:
+                break
+            if bsp3_back2zs(bsp3_bi, cmp_zs):  # type: ignore
+                continue
+            self.add_bs(bs_type=BSP_TYPE.T3B, bi=bsp3_bi, relate_bsp1=real_bsp1)  # type: ignore
+            break
+
+    def getLastestBspList(self) -> List[CBS_Point[LINE_TYPE]]:
+        if len(self.lst) == 0:
+            return []
+        return sorted(self.lst, key=lambda bsp: bsp.bi.idx, reverse=True)
+
+
+def bsp2s_break_bsp1(bsp2s_bi: LINE_TYPE, bsp2_break_bi: LINE_TYPE) -> bool:
+    return (bsp2s_bi.is_down() and bsp2s_bi._low() < bsp2_break_bi._low()) or \
+           (bsp2s_bi.is_up() and bsp2s_bi._high() > bsp2_break_bi._high())
+
+
+def bsp3_back2zs(bsp3_bi: LINE_TYPE, zs: CZS) -> bool:
+    return (bsp3_bi.is_down() and bsp3_bi._low() < zs.high) or (bsp3_bi.is_up() and bsp3_bi._high() > zs.low)
+
+
+def bsp3_break_zspeak(bsp3_bi: LINE_TYPE, zs: CZS) -> bool:
+    return (bsp3_bi.is_down() and bsp3_bi._high() >= zs.peak_high) or (bsp3_bi.is_up() and bsp3_bi._low() <= zs.peak_low)
+
+
+def cal_bsp3_bi_end_idx(seg: Optional[CSeg[LINE_TYPE]]):
+    if not seg:
+        return float("inf")
+    if seg.get_multi_bi_zs_cnt() == 0 and seg.next is None:
+        return float("inf")
+    end_bi_idx = seg.end_bi.idx-1
+    for zs in seg.zs_lst:
+        if zs.is_one_bi_zs():
+            continue
+        if zs.bi_out is not None:
+            end_bi_idx = zs.bi_out.idx
+            break
+    return end_bi_idx

BuySellPoint/BS_Point.py

@@ -0,0 +1,38 @@
+from typing import Dict, Generic, List, Optional, TypeVar, Union
+
+from Bi.Bi import CBi
+from ChanModel.Features import CFeatures
+from Common.CEnum import BSP_TYPE
+from Seg.Seg import CSeg
+
+LINE_TYPE = TypeVar('LINE_TYPE', CBi, CSeg)
+
+
+class CBS_Point(Generic[LINE_TYPE]):
+    def __init__(self, bi: LINE_TYPE, is_buy, bs_type: BSP_TYPE, relate_bsp1: Optional['CBS_Point'], feature_dict=None):
+        self.bi: LINE_TYPE = bi
+        self.klu = bi.get_end_klu()
+        self.is_buy = is_buy
+        self.type: List[BSP_TYPE] = [bs_type]
+        self.relate_bsp1 = relate_bsp1
+
+        self.bi.bsp = self  # type: ignore
+        self.features = CFeatures(feature_dict)
+
+        self.is_segbsp = False
+
+    def add_type(self, bs_type: BSP_TYPE):
+        self.type.append(bs_type)
+
+    def type2str(self):
+        return ",".join([x.value for x in self.type])
+
+    def add_another_bsp_prop(self, bs_type: BSP_TYPE, relate_bsp1):
+        self.add_type(bs_type)
+        if self.relate_bsp1 is None:
+            self.relate_bsp1 = relate_bsp1
+        elif relate_bsp1 is not None:
+            assert self.relate_bsp1.klu.idx == relate_bsp1.klu.idx
+
+    def add_feat(self, inp1: Union[str, Dict[str, float], Dict[str, Optional[float]], 'CFeatures'], inp2: Optional[float] = None):
+        self.features.add_feat(inp1, inp2)

Chan.py

@@ -0,0 +1,299 @@
+import copy
+import datetime
+from collections import defaultdict
+from typing import Dict, Iterable, List, Optional, Union
+
+from BuySellPoint.BS_Point import CBS_Point
+from ChanConfig import CChanConfig
+from Common.CEnum import AUTYPE, DATA_SRC, KL_TYPE
+from Common.ChanException import CChanException, ErrCode
+from Common.CTime import CTime
+from Common.func_util import check_kltype_order, kltype_lte_day
+from DataAPI.CommonStockAPI import CCommonStockApi
+from KLine.KLine_List import CKLine_List
+from KLine.KLine_Unit import CKLine_Unit
+
+
+class CChan:
+    def __init__(
+        self,
+        code,
+        begin_time=None,
+        end_time=None,
+        data_src: Union[DATA_SRC, str] = DATA_SRC.CCXT,
+        lv_list=None,
+        config=None,
+        autype: AUTYPE = AUTYPE.QFQ,
+    ):
+        if lv_list is None:
+            lv_list = [KL_TYPE.K_DAY, KL_TYPE.K_60M]
+        check_kltype_order(lv_list)  # lv_list顺序从高到低
+        self.code = code
+        self.begin_time = str(begin_time) if isinstance(begin_time, datetime.date) else begin_time
+        self.end_time = str(end_time) if isinstance(end_time, datetime.date) else end_time
+        self.begin_time = str(begin_time)
+        self.end_time = str(end_time)
+        self.autype = autype
+        self.data_src = data_src
+        self.lv_list: List[KL_TYPE] = lv_list
+
+        if config is None:
+            config = CChanConfig()
+        self.conf = config
+
+        self.kl_misalign_cnt = 0
+        self.kl_inconsistent_detail = defaultdict(list)
+
+        self.g_kl_iter = defaultdict(list)
+
+        self.do_init()
+
+        if not config.trigger_step:
+            for _ in self.load():
+                ...
+
+    def __deepcopy__(self, memo):
+        cls = self.__class__
+        obj: CChan = cls.__new__(cls)
+        memo[id(self)] = obj
+        obj.code = self.code
+        obj.begin_time = self.begin_time
+        obj.end_time = self.end_time
+        obj.autype = self.autype
+        obj.data_src = self.data_src
+        obj.lv_list = copy.deepcopy(self.lv_list, memo)
+        obj.conf = copy.deepcopy(self.conf, memo)
+        obj.kl_misalign_cnt = self.kl_misalign_cnt
+        obj.kl_inconsistent_detail = copy.deepcopy(self.kl_inconsistent_detail, memo)
+        obj.g_kl_iter = copy.deepcopy(self.g_kl_iter, memo)
+        if hasattr(self, 'klu_cache'):
+            obj.klu_cache = copy.deepcopy(self.klu_cache, memo)
+        if hasattr(self, 'klu_last_t'):
+            obj.klu_last_t = copy.deepcopy(self.klu_last_t, memo)
+        obj.kl_datas = {}
+        for kl_type, ckline in self.kl_datas.items():
+            obj.kl_datas[kl_type] = copy.deepcopy(ckline, memo)
+        for kl_type, ckline in self.kl_datas.items():
+            for klc in ckline:
+                for klu in klc.lst:
+                    assert id(klu) in memo
+                    if klu.sup_kl:
+                        memo[id(klu)].sup_kl = memo[id(klu.sup_kl)]
+                    memo[id(klu)].sub_kl_list = [memo[id(sub_kl)] for sub_kl in klu.sub_kl_list]
+        return obj
+
+    def do_init(self):
+        self.kl_datas: Dict[KL_TYPE, CKLine_List] = {}
+        for idx in range(len(self.lv_list)):
+            self.kl_datas[self.lv_list[idx]] = CKLine_List(self.lv_list[idx], conf=self.conf)
+
+    def load_stock_data(self, stockapi_instance: CCommonStockApi, lv) -> Iterable[CKLine_Unit]:
+        for KLU_IDX, klu in enumerate(stockapi_instance.get_kl_data()):
+            klu.set_idx(KLU_IDX)
+            klu.kl_type = lv
+            yield klu
+
+    def get_load_stock_iter(self, stockapi_cls, lv):
+        stockapi_instance = stockapi_cls(code=self.code, k_type=lv, begin_date=self.begin_time, end_date=self.end_time, autype=self.autype)
+        return self.load_stock_data(stockapi_instance, lv)
+
+    def add_lv_iter(self, lv_idx, iter):
+        if isinstance(lv_idx, int):
+            self.g_kl_iter[self.lv_list[lv_idx]].append(iter)
+        else:
+            self.g_kl_iter[lv_idx].append(iter)
+
+    def get_next_lv_klu(self, lv_idx):
+        if isinstance(lv_idx, int):
+            lv_idx = self.lv_list[lv_idx]
+        if len(self.g_kl_iter[lv_idx]) == 0:
+            raise StopIteration
+        try:
+            return self.g_kl_iter[lv_idx][0].__next__()
+        except StopIteration:
+            self.g_kl_iter[lv_idx] = self.g_kl_iter[lv_idx][1:]
+            if len(self.g_kl_iter[lv_idx]) != 0:
+                return self.get_next_lv_klu(lv_idx)
+            else:
+                raise
+
+    def step_load(self):
+        assert self.conf.trigger_step
+        self.do_init()  # 清空数据，防止再次重跑没有数据
+        yielded = False  # 是否曾经返回过结果
+        for idx, snapshot in enumerate(self.load(self.conf.trigger_step)):
+            if idx < self.conf.skip_step:
+                continue
+            yield snapshot
+            yielded = True
+        if not yielded:
+            yield self
+
+    def trigger_load(self, inp):
+        # {type: [klu, ...]}
+        if not hasattr(self, 'klu_cache'):
+            self.klu_cache: List[Optional[CKLine_Unit]] = [None for _ in self.lv_list]
+        if not hasattr(self, 'klu_last_t'):
+            self.klu_last_t = [CTime(1980, 1, 1, 0, 0) for _ in self.lv_list]
+        for lv_idx, lv in enumerate(self.lv_list):
+            if lv not in inp:
+                if lv_idx == 0:
+                    raise CChanException(f"最高级别{lv}没有传入数据", ErrCode.NO_DATA)
+                continue
+            for klu in inp[lv]:
+                klu.kl_type = lv
+            assert isinstance(inp[lv], list)
+            self.add_lv_iter(lv, iter(inp[lv]))
+        for _ in self.load_iterator(lv_idx=0, parent_klu=None, step=False):
+            ...
+        if not self.conf.trigger_step:  # 非回放模式全部算完之后才算一次中枢和线段
+            for lv in self.lv_list:
+                self.kl_datas[lv].cal_seg_and_zs()
+
+    def init_lv_klu_iter(self, stockapi_cls):
+        # 为了跳过一些获取数据失败的级别
+        lv_klu_iter = []
+        valid_lv_list = []
+        for lv in self.lv_list:
+            try:
+                lv_klu_iter.append(self.get_load_stock_iter(stockapi_cls, lv))
+                valid_lv_list.append(lv)
+            except CChanException as e:
+                if e.errcode == ErrCode.SRC_DATA_NOT_FOUND and self.conf.auto_skip_illegal_sub_lv:
+                    if self.conf.print_warning:
+                        print(f"[WARNING-{self.code}]{lv}级别获取数据失败，跳过")
+                    del self.kl_datas[lv]
+                    continue
+                raise e
+        self.lv_list = valid_lv_list
+        return lv_klu_iter
+
+    def GetStockAPI(self):
+        _dict = {}
+        if self.data_src == DATA_SRC.BAO_STOCK:
+            from DataAPI.BaoStockAPI import CBaoStock
+            _dict[DATA_SRC.BAO_STOCK] = CBaoStock
+        elif self.data_src == DATA_SRC.CCXT:
+            from DataAPI.ccxt import CCXT
+            _dict[DATA_SRC.CCXT] = CCXT
+        elif self.data_src == DATA_SRC.CSV:
+            from DataAPI.csvAPI import CSV_API
+            _dict[DATA_SRC.CSV] = CSV_API
+        if self.data_src in _dict:
+            return _dict[self.data_src]
+        assert isinstance(self.data_src, str)
+        if self.data_src.find("custom:") < 0:
+            raise CChanException("load src type error", ErrCode.SRC_DATA_TYPE_ERR)
+        package_info = self.data_src.split(":")[1]
+        package_name, cls_name = package_info.split(".")
+        exec(f"from DataAPI.{package_name} import {cls_name}")
+        return eval(cls_name)
+
+    def load(self, step=False):
+        stockapi_cls = self.GetStockAPI()
+        try:
+            stockapi_cls.do_init()
+            for lv_idx, klu_iter in enumerate(self.init_lv_klu_iter(stockapi_cls)):
+                self.add_lv_iter(lv_idx, klu_iter)
+            self.klu_cache: List[Optional[CKLine_Unit]] = [None for _ in self.lv_list]
+            self.klu_last_t = [CTime(1980, 1, 1, 0, 0) for _ in self.lv_list]
+
+            yield from self.load_iterator(lv_idx=0, parent_klu=None, step=step)  # 计算入口
+            if not step:  # 非回放模式全部算完之后才算一次中枢和线段
+                for lv in self.lv_list:
+                    self.kl_datas[lv].cal_seg_and_zs()
+        except Exception:
+            raise
+        finally:
+            stockapi_cls.do_close()
+        if len(self[0]) == 0:
+            raise CChanException("最高级别没有获得任何数据", ErrCode.NO_DATA)
+
+    def set_klu_parent_relation(self, parent_klu, kline_unit, cur_lv, lv_idx):
+        if self.conf.kl_data_check and kltype_lte_day(cur_lv) and kltype_lte_day(self.lv_list[lv_idx-1]):
+            self.check_kl_consitent(parent_klu, kline_unit)
+        parent_klu.add_children(kline_unit)
+        kline_unit.set_parent(parent_klu)
+
+    def add_new_kl(self, cur_lv: KL_TYPE, kline_unit):
+        try:
+            self.kl_datas[cur_lv].add_single_klu(kline_unit)
+        except Exception:
+            if self.conf.print_err_time:
+                print(f"[ERROR-{self.code}]在计算{kline_unit.time}K线时发生错误!")
+            raise
+
+    def try_set_klu_idx(self, lv_idx: int, kline_unit: CKLine_Unit):
+        if kline_unit.idx >= 0:
+            return
+        if len(self[lv_idx]) == 0:
+            kline_unit.set_idx(0)
+        else:
+            kline_unit.set_idx(self[lv_idx][-1][-1].idx + 1)
+
+    def load_iterator(self, lv_idx, parent_klu, step):
+        # K线时间天级别以下描述的是结束时间，如60M线，每天第一根是10点30的
+        # 天以上是当天日期
+        cur_lv = self.lv_list[lv_idx]
+        pre_klu = self[lv_idx][-1][-1] if len(self[lv_idx]) > 0 and len(self[lv_idx][-1]) > 0 else None
+        while True:
+            if self.klu_cache[lv_idx]:
+                kline_unit = self.klu_cache[lv_idx]
+                assert kline_unit is not None
+                self.klu_cache[lv_idx] = None
+            else:
+                try:
+                    kline_unit = self.get_next_lv_klu(lv_idx)
+                    self.try_set_klu_idx(lv_idx, kline_unit)
+                    if not kline_unit.time > self.klu_last_t[lv_idx]:
+                        raise CChanException(f"kline time err, cur={kline_unit.time}, last={self.klu_last_t[lv_idx]}", ErrCode.KL_NOT_MONOTONOUS)
+                    self.klu_last_t[lv_idx] = kline_unit.time
+                except StopIteration:
+                    break
+
+            if parent_klu and kline_unit.time > parent_klu.time:
+                self.klu_cache[lv_idx] = kline_unit
+                break
+            kline_unit.set_pre_klu(pre_klu)
+            pre_klu = kline_unit
+            self.add_new_kl(cur_lv, kline_unit)
+            if parent_klu:
+                self.set_klu_parent_relation(parent_klu, kline_unit, cur_lv, lv_idx)
+            if lv_idx != len(self.lv_list)-1:
+                for _ in self.load_iterator(lv_idx+1, kline_unit, step):
+                    ...
+                self.check_kl_align(kline_unit, lv_idx)
+            if lv_idx == 0 and step:
+                yield self
+
+    def check_kl_consitent(self, parent_klu, sub_klu):
+        if parent_klu.time.year != sub_klu.time.year or \
+           parent_klu.time.month != sub_klu.time.month or \
+           parent_klu.time.day != sub_klu.time.day:
+            self.kl_inconsistent_detail[str(parent_klu.time)].append(sub_klu.time)
+            if self.conf.print_warning:
+                print(f"[WARNING-{self.code}]父级别时间是{parent_klu.time}，次级别时间却是{sub_klu.time}")
+            if len(self.kl_inconsistent_detail) >= self.conf.max_kl_inconsistent_cnt:
+                raise CChanException(f"父&子级别K线时间不一致条数超过{self.conf.max_kl_inconsistent_cnt}！！", ErrCode.KL_TIME_INCONSISTENT)
+
+    def check_kl_align(self, kline_unit, lv_idx):
+        if self.conf.kl_data_check and len(kline_unit.sub_kl_list) == 0:
+            self.kl_misalign_cnt += 1
+            if self.conf.print_warning:
+                print(f"[WARNING-{self.code}]当前{kline_unit.time}没在次级别{self.lv_list[lv_idx+1]}找到K线！！")
+            if self.kl_misalign_cnt >= self.conf.max_kl_misalgin_cnt:
+                raise CChanException(f"在次级别找不到K线条数超过{self.conf.max_kl_misalgin_cnt}！！", ErrCode.KL_DATA_NOT_ALIGN)
+
+    def __getitem__(self, n) -> CKLine_List:
+        if isinstance(n, KL_TYPE):
+            return self.kl_datas[n]
+        elif isinstance(n, int):
+            return self.kl_datas[self.lv_list[n]]
+        else:
+            raise CChanException("unspoourt query type", ErrCode.COMMON_ERROR)
+
+    def get_bsp(self, idx=None) -> List[CBS_Point]:
+        if idx is not None:
+            return sorted(self[idx].bs_point_lst.lst, key=lambda x: x.klu.time)
+        assert len(self.lv_list) == 1
+        return sorted(self[0].bs_point_lst.lst, key=lambda x: x.klu.time)

ChanConfig.py

@@ -0,0 +1,182 @@
+from typing import List
+
+from Bi.BiConfig import CBiConfig
+from BuySellPoint.BSPointConfig import CBSPointConfig
+from Common.CEnum import TREND_TYPE
+from Common.ChanException import CChanException, ErrCode
+from Common.func_util import _parse_inf
+from Math.BOLL import BollModel
+from Math.Demark import CDemarkEngine
+from Math.KDJ import KDJ
+from Math.MACD import CMACD
+from Math.RSI import RSI
+from Math.TrendModel import CTrendModel
+from Seg.SegConfig import CSegConfig
+from ZS.ZSConfig import CZSConfig
+
+
+class CChanConfig:
+    def __init__(self, conf=None):
+        if conf is None:
+            conf = {}
+        conf = ConfigWithCheck(conf)
+        self.bi_conf = CBiConfig(
+            bi_algo=conf.get("bi_algo", "normal"),
+            is_strict=conf.get("bi_strict", True),
+            bi_fx_check=conf.get("bi_fx_check", "strict"),
+            gap_as_kl=conf.get("gap_as_kl", False),
+            bi_end_is_peak=conf.get('bi_end_is_peak', True),
+            bi_allow_sub_peak=conf.get("bi_allow_sub_peak", True),
+        )
+        self.seg_conf = CSegConfig(
+            seg_algo=conf.get("seg_algo", "chan"),
+            left_method=conf.get("left_seg_method", "peak"),
+        )
+        self.zs_conf = CZSConfig(
+            need_combine=conf.get("zs_combine", True),
+            zs_combine_mode=conf.get("zs_combine_mode", "zs"),
+            one_bi_zs=conf.get("one_bi_zs", False),
+            zs_algo=conf.get("zs_algo", "normal"),
+        )
+
+        self.trigger_step = conf.get("trigger_step", False)
+        self.skip_step = conf.get("skip_step", 0)
+
+        self.kl_data_check = conf.get("kl_data_check", True)
+        self.max_kl_misalgin_cnt = conf.get("max_kl_misalgin_cnt", 2)
+        self.max_kl_inconsistent_cnt = conf.get("max_kl_inconsistent_cnt", 5)
+        self.auto_skip_illegal_sub_lv = conf.get("auto_skip_illegal_sub_lv", False)
+        self.print_warning = conf.get("print_warning", True)
+        self.print_err_time = conf.get("print_err_time", False)
+
+        self.mean_metrics: List[int] = conf.get("mean_metrics", [])
+        self.trend_metrics: List[int] = conf.get("trend_metrics", [])
+        self.macd_config = conf.get("macd", {"fast": 12, "slow": 26, "signal": 9})
+        self.cal_demark = conf.get("cal_demark", False)
+        self.cal_rsi = conf.get("cal_rsi", False)
+        self.cal_kdj = conf.get("cal_kdj", False)
+        self.rsi_cycle = conf.get("rsi_cycle", 14)
+        self.kdj_cycle = conf.get("kdj_cycle", 9)
+        self.demark_config = conf.get("demark", {
+            'demark_len': 9,
+            'setup_bias': 4,
+            'countdown_bias': 2,
+            'max_countdown': 13,
+            'tiaokong_st': True,
+            'setup_cmp2close': True,
+            'countdown_cmp2close': True,
+        })
+        self.boll_n = conf.get("boll_n", 20)
+
+        self.set_bsp_config(conf)
+
+        conf.check()
+
+    def GetMetricModel(self):
+        res: List[CMACD | CTrendModel | BollModel | CDemarkEngine | RSI | KDJ] = [
+            CMACD(
+                fastperiod=self.macd_config['fast'],
+                slowperiod=self.macd_config['slow'],
+                signalperiod=self.macd_config['signal'],
+            )
+        ]
+        res.extend(CTrendModel(TREND_TYPE.MEAN, mean_T) for mean_T in self.mean_metrics)
+
+        for trend_T in self.trend_metrics:
+            res.append(CTrendModel(TREND_TYPE.MAX, trend_T))
+            res.append(CTrendModel(TREND_TYPE.MIN, trend_T))
+        res.append(BollModel(self.boll_n))
+        if self.cal_demark:
+            res.append(CDemarkEngine(
+                demark_len=self.demark_config['demark_len'],
+                setup_bias=self.demark_config['setup_bias'],
+                countdown_bias=self.demark_config['countdown_bias'],
+                max_countdown=self.demark_config['max_countdown'],
+                tiaokong_st=self.demark_config['tiaokong_st'],
+                setup_cmp2close=self.demark_config['setup_cmp2close'],
+                countdown_cmp2close=self.demark_config['countdown_cmp2close'],
+            ))
+        if self.cal_rsi:
+            res.append(RSI(self.rsi_cycle))
+        if self.cal_kdj:
+            res.append(KDJ(self.kdj_cycle))
+        return res
+
+    def set_bsp_config(self, conf):
+        para_dict = {
+            "divergence_rate": float("inf"),
+            "min_zs_cnt": 1,
+            "bsp1_only_multibi_zs": True,
+            "max_bs2_rate": 0.9999,
+            "macd_algo": "peak",
+            "bs1_peak": True,
+            "bs_type": "1,1p,2,2s,3a,3b",
+            "bsp2_follow_1": True,
+            "bsp3_follow_1": True,
+            "bsp3_peak": False,
+            "bsp2s_follow_2": False,
+            "max_bsp2s_lv": None,
+            "strict_bsp3": False,
+        }
+        args = {para: conf.get(para, default_value) for para, default_value in para_dict.items()}
+        self.bs_point_conf = CBSPointConfig(**args)
+
+        self.seg_bs_point_conf = CBSPointConfig(**args)
+        self.seg_bs_point_conf.b_conf.set("macd_algo", "slope")
+        self.seg_bs_point_conf.s_conf.set("macd_algo", "slope")
+        self.seg_bs_point_conf.b_conf.set("bsp1_only_multibi_zs", False)
+        self.seg_bs_point_conf.s_conf.set("bsp1_only_multibi_zs", False)
+
+        for k, v in conf.items():
+            if isinstance(v, str):
+                v = f'"{v}"'
+            v = _parse_inf(v)
+            if k.endswith("-buy"):
+                prop = k.replace("-buy", "")
+                exec(f"self.bs_point_conf.b_conf.set('{prop}', {v})")
+            elif k.endswith("-sell"):
+                prop = k.replace("-sell", "")
+                exec(f"self.bs_point_conf.s_conf.set('{prop}', {v})")
+            elif k.endswith("-segbuy"):
+                prop = k.replace("-segbuy", "")
+                exec(f"self.seg_bs_point_conf.b_conf.set('{prop}', {v})")
+            elif k.endswith("-segsell"):
+                prop = k.replace("-segsell", "")
+                exec(f"self.seg_bs_point_conf.s_conf.set('{prop}', {v})")
+            elif k.endswith("-seg"):
+                prop = k.replace("-seg", "")
+                exec(f"self.seg_bs_point_conf.b_conf.set('{prop}', {v})")
+                exec(f"self.seg_bs_point_conf.s_conf.set('{prop}', {v})")
+            elif k in args:
+                exec(f"self.bs_point_conf.b_conf.set({k}, {v})")
+                exec(f"self.bs_point_conf.s_conf.set({k}, {v})")
+            else:
+                raise CChanException(f"unknown para = {k}", ErrCode.PARA_ERROR)
+        self.bs_point_conf.b_conf.parse_target_type()
+        self.bs_point_conf.s_conf.parse_target_type()
+        self.seg_bs_point_conf.b_conf.parse_target_type()
+        self.seg_bs_point_conf.s_conf.parse_target_type()
+
+
+class ConfigWithCheck:
+    def __init__(self, conf):
+        self.conf = conf
+
+    def get(self, k, default_value=None):
+        res = self.conf.get(k, default_value)
+        if k in self.conf:
+            del self.conf[k]
+        return res
+
+    def items(self):
+        visit_keys = set()
+        for k, v in self.conf.items():
+            yield k, v
+            visit_keys.add(k)
+        for k in visit_keys:
+            del self.conf[k]
+
+    def check(self):
+        if len(self.conf) > 0:
+            invalid_key_lst = ",".join(list(self.conf.keys()))
+            raise CChanException(f"invalid CChanConfig: {invalid_key_lst}", ErrCode.PARA_ERROR)

ChanModel/Features.py

@@ -0,0 +1,18 @@
+from typing import Optional
+
+
+class CFeatures:
+    def __init__(self, initFeat=None):
+        self.__features = {} if initFeat is None else dict(initFeat)
+
+    def items(self):
+        yield from self.__features.items()
+
+    def __getitem__(self, k):
+        return self.__features[k]
+
+    def add_feat(self, inp1, inp2: Optional[float] = None):
+        if inp2 is None:
+            self.__features.update(inp1)
+        else:
+            self.__features.update({inp1: inp2})

Combiner/Combine_Item.py

@@ -0,0 +1,25 @@
+from Common.ChanException import CChanException, ErrCode
+
+
+class CCombine_Item:
+    def __init__(self, item):
+        from Bi.Bi import CBi
+        from KLine.KLine_Unit import CKLine_Unit
+        from Seg.Seg import CSeg
+        if isinstance(item, CBi):
+            self.time_begin = item.begin_klc.idx
+            self.time_end = item.end_klc.idx
+            self.high = item._high()
+            self.low = item._low()
+        elif isinstance(item, CKLine_Unit):
+            self.time_begin = item.time
+            self.time_end = item.time
+            self.high = item.high
+            self.low = item.low
+        elif isinstance(item, CSeg):
+            self.time_begin = item.start_bi.begin_klc.idx
+            self.time_end = item.end_bi.end_klc.idx
+            self.high = item._high()
+            self.low = item._low()
+        else:
+            raise CChanException(f"{type(item)} is unsupport sub class of CCombine_Item", ErrCode.COMMON_ERROR)

Combiner/KLine_Combiner.py

@@ -0,0 +1,175 @@
+from typing import Generic, Iterable, List, Optional, Self, TypeVar, Union, overload
+
+from Common.cache import make_cache
+from Common.CEnum import FX_TYPE, KLINE_DIR
+from Common.ChanException import CChanException, ErrCode
+from KLine.KLine_Unit import CKLine_Unit
+
+from .Combine_Item import CCombine_Item
+
+T = TypeVar('T')
+
+
+class CKLine_Combiner(Generic[T]):
+    def __init__(self, kl_unit: T, _dir):
+        item = CCombine_Item(kl_unit)
+        self.__time_begin = item.time_begin
+        self.__time_end = item.time_end
+        self.__high = item.high
+        self.__low = item.low
+
+        self.__lst: List[T] = [kl_unit]  # 本级别每一根单位K线
+
+        self.__dir = _dir
+        self.__fx = FX_TYPE.UNKNOWN
+        self.__pre: Optional[Self] = None
+        self.__next: Optional[Self] = None
+
+    def clean_cache(self):
+        self._memoize_cache = {}
+
+    @property
+    def time_begin(self): return self.__time_begin
+
+    @property
+    def time_end(self): return self.__time_end
+
+    @property
+    def high(self): return self.__high
+
+    @property
+    def low(self): return self.__low
+
+    @property
+    def lst(self): return self.__lst
+
+    @property
+    def dir(self): return self.__dir
+
+    @property
+    def fx(self): return self.__fx
+
+    @property
+    def pre(self) -> Self:
+        assert self.__pre is not None
+        return self.__pre
+
+    @property
+    def next(self): return self.__next
+
+    def get_next(self) -> Self:
+        assert self.next is not None
+        return self.next
+
+    def test_combine(self, item: CCombine_Item, exclude_included=False, allow_top_equal=None):
+        if (self.high >= item.high and self.low <= item.low):
+            return KLINE_DIR.COMBINE
+        if (self.high <= item.high and self.low >= item.low):
+            if allow_top_equal == 1 and self.high == item.high and self.low > item.low:
+                return KLINE_DIR.DOWN
+            elif allow_top_equal == -1 and self.low == item.low and self.high < item.high:
+                return KLINE_DIR.UP
+            return KLINE_DIR.INCLUDED if exclude_included else KLINE_DIR.COMBINE
+        if (self.high > item.high and self.low > item.low):
+            return KLINE_DIR.DOWN
+        if (self.high < item.high and self.low < item.low):
+            return KLINE_DIR.UP
+        else:
+            raise CChanException("combine type unknown", ErrCode.COMBINER_ERR)
+
+    def add(self, unit_kl: T):
+        # only for deepcopy
+        self.__lst.append(unit_kl)
+
+    def set_fx(self, fx: FX_TYPE):
+        # only for deepcopy
+        self.__fx = fx
+
+    def try_add(self, unit_kl: T, exclude_included=False, allow_top_equal=None):
+        # allow_top_equal = None普通模式
+        # allow_top_equal = 1 被包含，顶部相等不合并
+        # allow_top_equal = -1 被包含，底部相等不合并
+        combine_item = CCombine_Item(unit_kl)
+        _dir = self.test_combine(combine_item, exclude_included, allow_top_equal)
+        if _dir == KLINE_DIR.COMBINE:
+            self.__lst.append(unit_kl)
+            if isinstance(unit_kl, CKLine_Unit):
+                unit_kl.set_klc(self)
+            if self.dir == KLINE_DIR.UP:
+                if combine_item.high != combine_item.low or combine_item.high != self.high:  # 处理一字K线
+                    self.__high = max([self.high, combine_item.high])
+                    self.__low = max([self.low, combine_item.low])
+            elif self.dir == KLINE_DIR.DOWN:
+                if combine_item.high != combine_item.low or combine_item.low != self.low:  # 处理一字K线
+                    self.__high = min([self.high, combine_item.high])
+                    self.__low = min([self.low, combine_item.low])
+            else:
+                raise CChanException(f"KLINE_DIR = {self.dir} err!!! must be {KLINE_DIR.UP}/{KLINE_DIR.DOWN}", ErrCode.COMBINER_ERR)
+            self.__time_end = combine_item.time_end
+            self.clean_cache()
+        # 返回UP/DOWN/COMBINE给KL_LIST，设置下一个的方向
+        return _dir
+
+    def get_peak_klu(self, is_high) -> T:
+        # 获取最大值 or 最小值所在klu/bi
+        return self.get_high_peak_klu() if is_high else self.get_low_peak_klu()
+
+    @make_cache
+    def get_high_peak_klu(self) -> T:
+        for kl in self.lst[::-1]:
+            if CCombine_Item(kl).high == self.high:
+                return kl
+        raise CChanException("can't find peak...", ErrCode.COMBINER_ERR)
+
+    @make_cache
+    def get_low_peak_klu(self) -> T:
+        for kl in self.lst[::-1]:
+            if CCombine_Item(kl).low == self.low:
+                return kl
+        raise CChanException("can't find peak...", ErrCode.COMBINER_ERR)
+
+    def update_fx(self, _pre: Self, _next: Self, exclude_included=False, allow_top_equal=None):
+        # allow_top_equal = None普通模式
+        # allow_top_equal = 1 被包含，顶部相等不合并
+        # allow_top_equal = -1 被包含，底部相等不合并
+        self.set_next(_next)
+        self.set_pre(_pre)
+        _next.set_pre(self)
+        if exclude_included:
+            if _pre.high < self.high and _next.high <= self.high and _next.low < self.low:
+                if allow_top_equal == 1 or _next.high < self.high:
+                    self.__fx = FX_TYPE.TOP
+            elif _next.high > self.high and _pre.low > self.low and _next.low >= self.low:
+                if allow_top_equal == -1 or _next.low > self.low:
+                    self.__fx = FX_TYPE.BOTTOM
+        elif _pre.high < self.high and _next.high < self.high and _pre.low < self.low and _next.low < self.low:
+            self.__fx = FX_TYPE.TOP
+        elif _pre.high > self.high and _next.high > self.high and _pre.low > self.low and _next.low > self.low:
+            self.__fx = FX_TYPE.BOTTOM
+        self.clean_cache()
+
+    def __str__(self):
+        return f"{self.time_begin}~{self.time_end} {self.low}->{self.high}"
+
+    @overload
+    def __getitem__(self, index: int) -> T: ...
+
+    @overload
+    def __getitem__(self, index: slice) -> List[T]: ...
+
+    def __getitem__(self, index: Union[slice, int]) -> Union[List[T], T]:
+        return self.lst[index]
+
+    def __len__(self):
+        return len(self.lst)
+
+    def __iter__(self) -> Iterable[T]:
+        yield from self.lst
+
+    def set_pre(self, _pre: Self):
+        self.__pre = _pre
+        self.clean_cache()
+
+    def set_next(self, _next: Self):
+        self.__next = _next
+        self.clean_cache()

Common/CEnum.py

@@ -0,0 +1,137 @@
+from enum import Enum, auto
+from typing import Literal
+
+
+class DATA_SRC(Enum):
+    BAO_STOCK = auto()
+    CCXT = auto()
+    CSV = auto()
+
+
+class KL_TYPE(Enum):
+    K_1M = auto()
+    K_DAY = auto()
+    K_WEEK = auto()
+    K_MON = auto()
+    K_YEAR = auto()
+    K_5M = auto()
+    K_15M = auto()
+    K_30M = auto()
+    K_60M = auto()
+    K_4H = auto()
+    K_6H = auto()
+    K_8H = auto()
+    K_12H = auto()
+    K_3DAY = auto()
+    K_3M = auto()
+    K_QUARTER = auto()
+
+
+class KLINE_DIR(Enum):
+    UP = auto()
+    DOWN = auto()
+    COMBINE = auto()
+    INCLUDED = auto()
+
+
+class FX_TYPE(Enum):
+    BOTTOM = auto()
+    TOP = auto()
+    UNKNOWN = auto()
+
+
+class BI_DIR(Enum):
+    UP = auto()
+    DOWN = auto()
+
+class SEG_DIR(Enum):
+    UP = auto()
+    DOWN = auto()
+
+class BI_TYPE(Enum):
+    UNKNOWN = auto()
+    STRICT = auto()
+    SUB_VALUE = auto()  # 次高低点成笔
+    TIAOKONG_THRED = auto()
+    DAHENG = auto()
+    TUIBI = auto()
+    UNSTRICT = auto()
+    TIAOKONG_VALUE = auto()
+
+
+BSP_MAIN_TYPE = Literal['1', '2', '3']
+
+
+class BSP_TYPE(Enum):
+    T1 = '1'
+    T1P = '1p'
+    T2 = '2'
+    T2S = '2s'
+    T3A = '3a'  # 中枢在1类后面
+    T3B = '3b'  # 中枢在1类前面
+
+    def main_type(self) -> BSP_MAIN_TYPE:
+        return self.value[0]  # type: ignore
+
+
+class AUTYPE(Enum):
+    QFQ = auto()
+    HFQ = auto()
+    NONE = auto()
+
+
+class TREND_TYPE(Enum):
+    MEAN = "mean"
+    MAX = "max"
+    MIN = "min"
+
+
+class TREND_LINE_SIDE(Enum):
+    INSIDE = auto()
+    OUTSIDE = auto()
+
+
+class LEFT_SEG_METHOD(Enum):
+    ALL = auto()
+    PEAK = auto()
+
+
+class FX_CHECK_METHOD(Enum):
+    STRICT = auto()
+    LOSS = auto()
+    HALF = auto()
+    TOTALLY = auto()
+
+
+class SEG_TYPE(Enum):
+    BI = auto()
+    SEG = auto()
+
+
+class MACD_ALGO(Enum):
+    AREA = auto()
+    PEAK = auto()
+    FULL_AREA = auto()
+    DIFF = auto()
+    SLOPE = auto()
+    AMP = auto()
+    VOLUMN = auto()
+    AMOUNT = auto()
+    VOLUMN_AVG = auto()
+    AMOUNT_AVG = auto()
+    TURNRATE_AVG = auto()
+    RSI = auto()
+
+
+class DATA_FIELD:
+    FIELD_TIME = "time_key"
+    FIELD_OPEN = "open"
+    FIELD_HIGH = "high"
+    FIELD_LOW = "low"
+    FIELD_CLOSE = "close"
+    FIELD_VOLUME = "volume"  # 成交量
+    FIELD_TURNOVER = "turnover"  # 成交额
+    FIELD_TURNRATE = "turnover_rate"  # 换手率
+
+
+TRADE_INFO_LST = [DATA_FIELD.FIELD_VOLUME, DATA_FIELD.FIELD_TURNOVER, DATA_FIELD.FIELD_TURNRATE]

Common/CTime.py

@@ -0,0 +1,44 @@
+from datetime import datetime
+
+
+class CTime:
+    def __init__(self, year, month, day, hour, minute, second=0, auto=True):
+        self.year = year
+        self.month = month
+        self.day = day
+        self.hour = hour
+        self.minute = minute
+        self.second = second
+        self.auto = auto  # 自适应对天的理解
+        self.set_timestamp()  # set self.ts
+
+    def __str__(self):
+        if self.hour == 0 and self.minute == 0:
+            return f"{self.year:04}/{self.month:02}/{self.day:02}"
+        else:
+            return f"{self.year:04}/{self.month:02}/{self.day:02} {self.hour:02}:{self.minute:02}"
+
+    def to_str(self):
+        if self.hour == 0 and self.minute == 0:
+            return f"{self.year:04}/{self.month:02}/{self.day:02}"
+        else:
+            return f"{self.year:04}/{self.month:02}/{self.day:02} {self.hour:02}:{self.minute:02}"
+
+    def toDateStr(self, splt=''):
+        return f"{self.year:04}{splt}{self.month:02}{splt}{self.day:02}"
+
+    def toDate(self):
+        return CTime(self.year, self.month, self.day, 0, 0, auto=False)
+
+    def set_timestamp(self):
+        if self.hour == 0 and self.minute == 0 and self.auto:
+            date = datetime(self.year, self.month, self.day, 23, 59, self.second)
+        else:
+            date = datetime(self.year, self.month, self.day, self.hour, self.minute, self.second)
+        self.ts = date.timestamp()
+
+    def __gt__(self, t2):
+        return self.ts > t2.ts
+
+    def __ge__(self, t2):
+        return self.ts >= t2.ts

Common/ChanException.py

@@ -0,0 +1,88 @@
+from enum import IntEnum
+
+
+class ErrCode(IntEnum):
+    # chan err
+    _CHAN_ERR_BEGIN = 0
+    COMMON_ERROR = 1
+    SRC_DATA_NOT_FOUND = 3
+    SRC_DATA_TYPE_ERR = 4
+    PARA_ERROR = 5
+    EXTRA_KLU_ERR = 6
+    SEG_END_VALUE_ERR = 7
+    SEG_EIGEN_ERR = 8
+    BI_ERR = 9
+    COMBINER_ERR = 10
+    PLOT_ERR = 11
+    MODEL_ERROR = 12
+    SEG_LEN_ERR = 13
+    ENV_CONF_ERR = 14
+    UNKNOWN_DB_TYPE = 15
+    FEATURE_ERROR = 16
+    CONFIG_ERROR = 17
+    SRC_DATA_FORMAT_ERROR = 18
+    _CHAN_ERR_END = 99
+
+    # Trade Error
+    _TRADE_ERR_BEGIN = 100
+    SIGNAL_EXISTED = 101
+    RECORD_NOT_EXIST = 102
+    RECORD_ALREADY_OPENED = 103
+    QUOTA_NOT_ENOUGH = 104
+    RECORD_NOT_OPENED = 105
+    TRADE_UNLOCK_FAIL = 106
+    PLACE_ORDER_FAIL = 107
+    LIST_ORDER_FAIL = 108
+    CANDEL_ORDER_FAIL = 109
+    GET_FUTU_PRICE_FAIL = 110
+    GET_FUTU_LOT_SIZE_FAIL = 111
+    OPEN_RECORD_NOT_WATCHING = 112
+    GET_HOLDING_QTY_FAIL = 113
+    RECORD_CLOSED = 114
+    REQUEST_TRADING_DAYS_FAIL = 115
+    COVER_ORDER_ID_NOT_UNIQUE = 116
+    SIGNAL_TRADED = 117
+    _TRADE_ERR_END = 199
+
+    # KL data Error
+    _KL_ERR_BEGIN = 200
+    PRICE_BELOW_ZERO = 201
+    KL_DATA_NOT_ALIGN = 202
+    KL_DATA_INVALID = 203
+    KL_TIME_INCONSISTENT = 204
+    TRADEINFO_TOO_MUCH_ZERO = 205
+    KL_NOT_MONOTONOUS = 206
+    SNAPSHOT_ERR = 207
+    SUSPENSION = 208  # 疑似停牌
+    STOCK_IPO_TOO_LATE = 209
+    NO_DATA = 210
+    STOCK_NOT_ACTIVE = 211
+    STOCK_PRICE_NOT_ACTIVE = 212
+    _KL_ERR_END = 299
+
+
+class CChanException(Exception):
+    def __init__(self, message, code=ErrCode.COMMON_ERROR):
+        self.errcode = code
+        self.msg = message
+        Exception.__init__(self, message)
+
+    def is_kldata_err(self):
+        return ErrCode._KL_ERR_BEGIN < self.errcode < ErrCode._KL_ERR_END
+
+    def is_chan_err(self):
+        return ErrCode._CHAN_ERR_BEGIN < self.errcode < ErrCode._CHAN_ERR_END
+
+
+if __name__ == "__main__":
+    def foo():
+        raise CChanException("XXX", ErrCode.CONFIG_ERROR)
+
+    try:
+        foo()
+    except CChanException as e:
+        print(str(e.errcode))
+        # python3.8 结果为： ErrCode.CONFIG_ERROR
+        # python3.11 结果为：17
+
+        print(e.errcode.name, type(e.errcode.name))

Common/cache.py

@@ -0,0 +1,34 @@
+import inspect
+import types
+
+
+class make_cache:
+    def __init__(self, func):
+        self.func = func
+
+        fargspec = inspect.getfullargspec(func)
+        if len(fargspec.args) != 1 or fargspec.args[0] != "self":
+            raise Exception("@memoize must be `(self)`")
+
+        # set key for this function
+        self.func_key = str(func)
+
+    def __get__(self, instance, cls):
+        if instance is None:
+            raise Exception("@memoize's must be bound")
+
+        if not hasattr(instance, "_memoize_cache"):
+            setattr(instance, "_memoize_cache", {})
+
+        return types.MethodType(self, instance)
+
+    def __call__(self, *args, **kwargs):
+        instance = args[0]
+        cache = instance._memoize_cache
+
+        if self.func_key in cache:
+            return cache[self.func_key]
+
+        result = self.func(*args, **kwargs)
+        cache[self.func_key] = result
+        return result

Common/func_util.py

@@ -0,0 +1,59 @@
+from .CEnum import BI_DIR, KL_TYPE
+
+
+def kltype_lt_day(_type):
+    return _type in [KL_TYPE.K_1M, KL_TYPE.K_5M, KL_TYPE.K_15M, KL_TYPE.K_30M, KL_TYPE.K_60M]
+
+
+def kltype_lte_day(_type):
+    return _type in [KL_TYPE.K_1M, KL_TYPE.K_5M, KL_TYPE.K_15M, KL_TYPE.K_30M, KL_TYPE.K_60M, KL_TYPE.K_DAY]
+
+
+def check_kltype_order(type_list: list):
+    _dict = {
+        KL_TYPE.K_1M: 1,
+        KL_TYPE.K_3M: 2,
+        KL_TYPE.K_5M: 3,
+        KL_TYPE.K_15M: 4,
+        KL_TYPE.K_30M: 5,
+        KL_TYPE.K_60M: 6,
+        KL_TYPE.K_4H: 7,      # 4小时
+        KL_TYPE.K_6H: 8,      # 6小时
+        KL_TYPE.K_8H: 9,      # 8小时
+        KL_TYPE.K_12H: 10,    # 12小时
+        KL_TYPE.K_DAY: 11,
+        KL_TYPE.K_3DAY: 12,   # 3日线
+        KL_TYPE.K_WEEK: 13,
+        KL_TYPE.K_MON: 14,
+        KL_TYPE.K_QUARTER: 15,
+        KL_TYPE.K_YEAR: 16,
+    }
+    last_lv = float("inf")
+    for kl_type in type_list:
+        cur_lv = _dict[kl_type]
+        assert cur_lv < last_lv, "lv_list的顺序必须从大级别到小级别"
+        last_lv = cur_lv
+
+
+def revert_bi_dir(dir):
+    return BI_DIR.DOWN if dir == BI_DIR.UP else BI_DIR.UP
+
+
+def has_overlap(l1, h1, l2, h2, equal=False):
+    return h2 >= l1 and h1 >= l2 if equal else h2 > l1 and h1 > l2
+
+
+def str2float(s):
+    try:
+        return float(s)
+    except ValueError:
+        return 0.0
+
+
+def _parse_inf(v):
+    if type(v) == float:
+        if v == float("inf"):
+            v = 'float("inf")'
+        if v == float("-inf"):
+            v = 'float("-inf")'
+    return v

DataAPI/BaoStockAPI.py

@@ -0,0 +1,114 @@
+import baostock as bs
+
+from Common.CEnum import AUTYPE, DATA_FIELD, KL_TYPE
+from Common.CTime import CTime
+from Common.func_util import kltype_lt_day, str2float
+from KLine.KLine_Unit import CKLine_Unit
+
+from .CommonStockAPI import CCommonStockApi
+
+
+def create_item_dict(data, column_name):
+    for i in range(len(data)):
+        data[i] = parse_time_column(data[i]) if i == 0 else str2float(data[i])
+    return dict(zip(column_name, data))
+
+
+def parse_time_column(inp):
+    # 20210902113000000
+    # 2021-09-13
+    if len(inp) == 10:
+        year = int(inp[:4])
+        month = int(inp[5:7])
+        day = int(inp[8:10])
+        hour = minute = 0
+    elif len(inp) == 17:
+        year = int(inp[:4])
+        month = int(inp[4:6])
+        day = int(inp[6:8])
+        hour = int(inp[8:10])
+        minute = int(inp[10:12])
+    elif len(inp) == 19:
+        year = int(inp[:4])
+        month = int(inp[5:7])
+        day = int(inp[8:10])
+        hour = int(inp[11:13])
+        minute = int(inp[14:16])
+    else:
+        raise Exception(f"unknown time column from baostock:{inp}")
+    return CTime(year, month, day, hour, minute)
+
+
+def GetColumnNameFromFieldList(fileds: str):
+    _dict = {
+        "time": DATA_FIELD.FIELD_TIME,
+        "date": DATA_FIELD.FIELD_TIME,
+        "open": DATA_FIELD.FIELD_OPEN,
+        "high": DATA_FIELD.FIELD_HIGH,
+        "low": DATA_FIELD.FIELD_LOW,
+        "close": DATA_FIELD.FIELD_CLOSE,
+        "volume": DATA_FIELD.FIELD_VOLUME,
+        "amount": DATA_FIELD.FIELD_TURNOVER,
+        "turn": DATA_FIELD.FIELD_TURNRATE,
+    }
+    return [_dict[x] for x in fileds.split(",")]
+
+
+class CBaoStock(CCommonStockApi):
+    is_connect = None
+
+    def __init__(self, code, k_type=KL_TYPE.K_DAY, begin_date=None, end_date=None, autype=AUTYPE.QFQ):
+        super(CBaoStock, self).__init__(code, k_type, begin_date, end_date, autype)
+
+    def get_kl_data(self):
+        # 天级别以上才有详细交易信息
+        if kltype_lt_day(self.k_type):
+            if not self.is_stock:
+                raise Exception("没有获取到数据，注意指数是没有分钟级别数据的！")
+            fields = "time,open,high,low,close"
+        else:
+            fields = "date,open,high,low,close,volume,amount,turn"
+        autype_dict = {AUTYPE.QFQ: "2", AUTYPE.HFQ: "1", AUTYPE.NONE: "3"}
+        rs = bs.query_history_k_data_plus(
+            code=self.code,
+            fields=fields,
+            start_date=self.begin_date,
+            end_date=self.end_date,
+            frequency=self.__convert_type(),
+            adjustflag=autype_dict[self.autype],
+        )
+        if rs.error_code != '0':
+            raise Exception(rs.error_msg)
+        while rs.error_code == '0' and rs.next():
+            yield CKLine_Unit(create_item_dict(rs.get_row_data(), GetColumnNameFromFieldList(fields)))
+
+    def SetBasciInfo(self):
+        rs = bs.query_stock_basic(code=self.code)
+        if rs.error_code != '0':
+            raise Exception(rs.error_msg)
+        code, code_name, ipoDate, outDate, stock_type, status = rs.get_row_data()
+        self.name = code_name
+        self.is_stock = (stock_type == '1')
+
+    @classmethod
+    def do_init(cls):
+        if not cls.is_connect:
+            cls.is_connect = bs.login()
+
+    @classmethod
+    def do_close(cls):
+        if cls.is_connect:
+            bs.logout()
+            cls.is_connect = None
+
+    def __convert_type(self):
+        _dict = {
+            KL_TYPE.K_DAY: 'd',
+            KL_TYPE.K_WEEK: 'w',
+            KL_TYPE.K_MON: 'm',
+            KL_TYPE.K_5M: '5',
+            KL_TYPE.K_15M: '15',
+            KL_TYPE.K_30M: '30',
+            KL_TYPE.K_60M: '60',
+        }
+        return _dict[self.k_type]

DataAPI/CommonStockAPI.py

@@ -0,0 +1,34 @@
+import abc
+from typing import Iterable
+
+from KLine.KLine_Unit import CKLine_Unit
+
+
+class CCommonStockApi:
+    def __init__(self, code, k_type, begin_date, end_date, autype):
+        self.code = code
+        self.name = None
+        self.is_stock = None
+        self.k_type = k_type
+        self.begin_date = begin_date
+        self.end_date = end_date
+        self.autype = autype
+        self.SetBasciInfo()
+
+    @abc.abstractmethod
+    def get_kl_data(self) -> Iterable[CKLine_Unit]:
+        pass
+
+    @abc.abstractmethod
+    def SetBasciInfo(self):
+        pass
+
+    @classmethod
+    @abc.abstractmethod
+    def do_init(cls):
+        pass
+
+    @classmethod
+    @abc.abstractmethod
+    def do_close(cls):
+        pass

DataAPI/WebDataAPI.py

@@ -0,0 +1,100 @@
+from datetime import datetime
+import pandas as pd
+from Common.CEnum import AUTYPE, DATA_FIELD, KL_TYPE
+from Common.CTime import CTime
+from Common.func_util import kltype_lt_day, str2float
+from KLine.KLine_Unit import CKLine_Unit
+from .CommonStockAPI import CCommonStockApi
+
+
+class WebDataAPI(CCommonStockApi):
+    """Web应用的数据API适配器，用于将web应用的数据转换为chan.py格式"""
+    
+    # 类变量用于存储数据
+    _data_cache = {}
+    
+    def __init__(self, code, k_type=KL_TYPE.K_DAY, begin_date=None, end_date=None, autype=AUTYPE.QFQ):
+        super().__init__(code, k_type, begin_date, end_date, autype)
+    
+    @classmethod
+    def set_data(cls, code, df_data):
+        """设置指定代码的数据"""
+        cls._data_cache[code] = df_data
+    
+    def get_kl_data(self):
+        """将DataFrame数据转换为CKLine_Unit迭代器"""
+        df_data = self._data_cache.get(self.code)
+        if df_data is None or len(df_data) == 0:
+            return
+        
+        # 确保数据按时间排序并重置索引
+        df_data = df_data.sort_values('date').reset_index(drop=True)
+        print(f"WebDataAPI: 处理 {len(df_data)} 条K线数据，K线级别: {self.k_type}")
+        
+        # 检查并处理重复时间
+        if 'timestamp' in df_data.columns:
+            df_data = df_data.drop_duplicates(subset=['timestamp'], keep='last')
+            df_data = df_data.sort_values('timestamp').reset_index(drop=True)
+        
+        prev_timestamp = None
+        for idx, row in df_data.iterrows():
+            # 转换时间格式
+            if isinstance(row['date'], str):
+                time_obj = datetime.fromisoformat(row['date'].replace('Z', '+00:00'))
+            else:
+                time_obj = row['date']
+            
+            # 检查时间戳确保单调递增
+            if 'timestamp' in row:
+                current_timestamp = row['timestamp']
+                if prev_timestamp is not None and current_timestamp <= prev_timestamp:
+                    print(f"跳过重复或倒序时间戳: {current_timestamp}, 上个时间戳: {prev_timestamp}")
+                    continue
+                prev_timestamp = current_timestamp
+            
+            # 创建CTime对象 - 根据K线级别智能决定auto参数
+            # 对于日线及以上级别，且时分秒为0的情况，使用auto=True
+            # 对于分钟级别或有具体时分的数据，使用auto=False确保精确时间
+            use_auto = False  # 默认不使用auto，确保时间精确
+            
+            # 只有在日线级别且时分秒都为0时才考虑使用auto
+            if self.k_type in [KL_TYPE.K_DAY, KL_TYPE.K_WEEK, KL_TYPE.K_MON]:
+                if time_obj.hour == 0 and time_obj.minute == 0 and time_obj.second == 0:
+                    use_auto = True
+            
+            ctime = CTime(
+                time_obj.year, 
+                time_obj.month, 
+                time_obj.day, 
+                time_obj.hour, 
+                time_obj.minute,
+                time_obj.second,
+                auto=use_auto
+            )
+            
+            # 输出详细调试信息（只输出前几条）
+            if idx < 3:
+                print(f"第{idx+1}条数据: 原始时间={time_obj}, CTime={ctime}, auto={use_auto}, timestamp={ctime.ts}")
+            
+            # 创建数据字典
+            data_dict = {
+                DATA_FIELD.FIELD_TIME: ctime,
+                DATA_FIELD.FIELD_OPEN: float(row['open']),
+                DATA_FIELD.FIELD_HIGH: float(row['high']),
+                DATA_FIELD.FIELD_LOW: float(row['low']),
+                DATA_FIELD.FIELD_CLOSE: float(row['close']),
+                DATA_FIELD.FIELD_VOLUME: float(row['volume']) if 'volume' in row and pd.notna(row['volume']) else 0.0
+            }
+            
+            yield CKLine_Unit(data_dict, autofix=True)
+    
+    def SetBasciInfo(self):
+        pass
+    
+    @classmethod
+    def do_init(cls):
+        pass
+    
+    @classmethod
+    def do_close(cls):
+        pass 

DataAPI/ccxt.py

@@ -0,0 +1,102 @@
+from datetime import datetime
+
+import ccxt
+import json
+from Common.CEnum import AUTYPE, DATA_FIELD, KL_TYPE
+from Common.CTime import CTime
+from Common.func_util import kltype_lt_day, str2float
+from KLine.KLine_Unit import CKLine_Unit
+
+from .CommonStockAPI import CCommonStockApi
+
+
+def GetColumnNameFromFieldList(fileds: str):
+    _dict = {
+        "time": DATA_FIELD.FIELD_TIME,
+        "open": DATA_FIELD.FIELD_OPEN,
+        "high": DATA_FIELD.FIELD_HIGH,
+        "low": DATA_FIELD.FIELD_LOW,
+        "close": DATA_FIELD.FIELD_CLOSE,
+    }
+    return [_dict[x] for x in fileds.split(",")]
+
+
+class CCXT(CCommonStockApi):
+    is_connect = None
+
+    def __init__(self, code, k_type=KL_TYPE.K_DAY, begin_date=None, end_date=None, autype=AUTYPE.QFQ):
+        super(CCXT, self).__init__(code, k_type, begin_date, end_date, autype)
+
+    def get_kl_data(self):
+        fields = "time,open,high,low,close"
+        exchange = ccxt.binance()
+        timeframe = self.__convert_type()
+        since_date = exchange.parse8601(f'{self.begin_date}T08:00:00')
+        
+        #file_path = "BTC_USDT-5m-futures.json"
+        #with open(file_path, 'r') as file:
+        #    data = json.load(file)
+        data = exchange.fetch_ohlcv(self.code, timeframe, since=since_date)
+        for item in data:
+            time_obj = datetime.fromtimestamp(item[0] / 1000)
+            time_str = time_obj.strftime('%Y-%m-%d %H:%M:%S')
+            item_data = [
+                time_str,
+                item[1],
+                item[2],
+                item[3],
+                item[4],
+                item[5]
+            ]
+            yield CKLine_Unit(self.create_item_dict(item_data, GetColumnNameFromFieldList(fields)), autofix=True)
+
+    def SetBasciInfo(self):
+        pass
+
+    @classmethod
+    def do_init(cls):
+        pass
+
+    @classmethod
+    def do_close(cls):
+        pass
+
+    def __convert_type(self):
+        _dict = {
+            KL_TYPE.K_DAY: '1d',
+            KL_TYPE.K_WEEK: '1w',
+            KL_TYPE.K_MON: '1M',
+            KL_TYPE.K_5M: '5m',
+            KL_TYPE.K_15M: '15m',
+            KL_TYPE.K_30M: '30m',
+            KL_TYPE.K_60M: '1h',
+            KL_TYPE.K_1M: '1m', # need to add this 1m
+        }
+        return _dict[self.k_type]
+
+    def parse_time_column(self, inp):
+        if len(inp) == 10:
+            year = int(inp[:4])
+            month = int(inp[5:7])
+            day = int(inp[8:10])
+            hour = minute = 0
+        elif len(inp) == 17:
+            year = int(inp[:4])
+            month = int(inp[4:6])
+            day = int(inp[6:8])
+            hour = int(inp[8:10])
+            minute = int(inp[10:12])
+        elif len(inp) == 19:
+            year = int(inp[:4])
+            month = int(inp[5:7])
+            day = int(inp[8:10])
+            hour = int(inp[11:13])
+            minute = int(inp[14:16])
+        else:
+            raise Exception(f"unknown time column from TradingView:{inp}")
+        return CTime(year, month, day, hour, minute, auto=not kltype_lt_day(self.k_type))
+
+    def create_item_dict(self, data, column_name):
+        for i in range(len(data)):
+            data[i] = self.parse_time_column(data[i]) if i == 0 else str2float(data[i])
+        return dict(zip(column_name, data))

DataAPI/csvAPI.py

@@ -0,0 +1,86 @@
+import os
+
+from Common.CEnum import DATA_FIELD, KL_TYPE
+from Common.ChanException import CChanException, ErrCode
+from Common.CTime import CTime
+from Common.func_util import str2float
+from KLine.KLine_Unit import CKLine_Unit
+
+from .CommonStockAPI import CCommonStockApi
+
+
+def create_item_dict(data, column_name):
+    for i in range(len(data)):
+        data[i] = parse_time_column(data[i]) if column_name[i] == DATA_FIELD.FIELD_TIME else str2float(data[i])
+    return dict(zip(column_name, data))
+
+
+def parse_time_column(inp):
+    # 20210902113000000
+    # 2021-09-13
+    if len(inp) == 10:
+        year = int(inp[:4])
+        month = int(inp[5:7])
+        day = int(inp[8:10])
+        hour = minute = 0
+    elif len(inp) == 17:
+        year = int(inp[:4])
+        month = int(inp[4:6])
+        day = int(inp[6:8])
+        hour = int(inp[8:10])
+        minute = int(inp[10:12])
+    elif len(inp) == 19:
+        year = int(inp[:4])
+        month = int(inp[5:7])
+        day = int(inp[8:10])
+        hour = int(inp[11:13])
+        minute = int(inp[14:16])
+    else:
+        raise Exception(f"unknown time column from csv:{inp}")
+    return CTime(year, month, day, hour, minute)
+
+
+class CSV_API(CCommonStockApi):
+    def __init__(self, code, k_type=KL_TYPE.K_DAY, begin_date=None, end_date=None, autype=None):
+        self.headers_exist = True  # 第一行是否是标题，如果是数据，设置为False
+        self.columns = [
+            DATA_FIELD.FIELD_TIME,
+            DATA_FIELD.FIELD_OPEN,
+            DATA_FIELD.FIELD_HIGH,
+            DATA_FIELD.FIELD_LOW,
+            DATA_FIELD.FIELD_CLOSE,
+            # DATA_FIELD.FIELD_VOLUME,
+            # DATA_FIELD.FIELD_TURNOVER,
+            # DATA_FIELD.FIELD_TURNRATE,
+        ]  # 每一列字段
+        self.time_column_idx = self.columns.index(DATA_FIELD.FIELD_TIME)
+        super(CSV_API, self).__init__(code, k_type, begin_date, end_date, autype)
+
+    def get_kl_data(self):
+        cur_path = os.path.dirname(os.path.realpath(__file__))
+        file_path = f"{cur_path}/../{self.code}.csv"
+        if not os.path.exists(file_path):
+            raise CChanException(f"file not exist: {file_path}", ErrCode.SRC_DATA_NOT_FOUND)
+
+        for line_number, line in enumerate(open(file_path, 'r')):
+            if self.headers_exist and line_number == 0:
+                continue
+            data = line.strip("\n").split(",")
+            if len(data) != len(self.columns):
+                raise CChanException(f"file format error: {file_path}", ErrCode.SRC_DATA_FORMAT_ERROR)
+            if self.begin_date is not None and data[self.time_column_idx] < self.begin_date:
+                continue
+            if self.end_date is not None and data[self.time_column_idx] > self.end_date:
+                continue
+            yield CKLine_Unit(create_item_dict(data, self.columns))
+
+    def SetBasciInfo(self):
+        pass
+
+    @classmethod
+    def do_init(cls):
+        pass
+
+    @classmethod
+    def do_close(cls):
+        pass

Debug/FeatureDict.py

@@ -0,0 +1,123 @@
+import json
+from typing import Dict, TypedDict
+import sys 
+import os
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py"))
+import xgboost as xgb
+from BuySellPoint.BS_Point import CBS_Point
+from Chan import CChan
+from ChanConfig import CChanConfig
+from ChanModel.Features import CFeatures
+from Common.CEnum import AUTYPE, DATA_SRC, KL_TYPE, BSP_TYPE,  MACD_ALGO
+from Common.CTime import CTime
+from Plot.PlotDriver import CPlotDriver
+from Bi.Bi import CBi
+
+class FeatureDict:
+    def klc_features(self, klc):
+        # klc features
+        klc_feature_dict = {
+            "klu_max_high": klc.get_klu_max_high(),
+            "klu_max_low": klc.get_klu_min_low(),
+
+        }
+        return klc_feature_dict
+    def bi_features(self, bi):
+        # bi features 
+        bi_feature_dict = {
+            "bi_macd_area": bi.cal_macd_metric(MACD_ALGO.AREA, False),
+            "bi_macd_peak": bi.cal_macd_metric(MACD_ALGO.PEAK, False),
+            "bi_macd_full_area": bi.cal_macd_metric(MACD_ALGO.FULL_AREA, False),
+            "bi_macd_diff": bi.cal_macd_metric(MACD_ALGO.DIFF, False),
+            "bi_macd_slop": bi.cal_macd_metric(MACD_ALGO.SLOPE, False),
+            "bi_macd_amp": bi.cal_macd_metric(MACD_ALGO.AMP, False),
+            "bi_macd_amount": bi.cal_macd_metric(MACD_ALGO.AMOUNT, False),
+            "bi_macd_rsi": bi.cal_macd_metric(MACD_ALGO.RSI, False),
+        }
+        #bi_feature_dict.update(self.klc_features(bi.begin_klc))
+        #bi_feature_dict.update(self.klc_features(bi.end_klc))
+        return bi_feature_dict
+
+    def seg_features(self, seg):
+        seg_feature_dict = {
+            # seg features
+            "seg_macd_slope": seg.Cal_MACD_slope(),
+            "seg_macd_amp": seg.Cal_MACD_amp(),
+            "seg_amp": seg.amp(),
+            "seg_cal_klu_slope": seg.cal_klu_slope(),
+            "seg_cal_amp": seg.amp(),
+        }
+        return seg_feature_dict
+
+    def zs_features(self, zs):
+        zs_feature_dict = {
+            f"zs_high": zs.high,
+            f"zs_low": zs.low,
+            f"zs_mid": zs.mid,
+            f"zs_peak_low": zs.peak_low,
+            f"zs_peak_high": zs.peak_high,
+        }
+        #zs_feature_dict.update(bi_features(zs.begin_bi))
+        #zs_feature_dict.update(bi_features(zs.end_bi))
+        #zs_feature_dict.update(bi_features(zs.bi_in))
+        #zs_feature_dict.update(bi_features(zs.bi_out))
+        return zs_feature_dict
+
+    def klu_features(self, klu):
+        klu_feature_dict = {
+            # klu features
+            "klu_rsi": klu.rsi,
+            "klu_macd_fast_ema": klu.macd.fast_ema,
+            "klu_macd_slow_ema": klu.macd.slow_ema,
+            "klu_macd_DIF": klu.macd.DIF,
+            "klu_macd_DEA": klu.macd.DEA,
+            "klu_macd_macd": klu.macd.macd,
+            "klu_kdj_k": klu.kdj.k,
+            "klu_kdj_d": klu.kdj.d,
+            "klu_kdj_j": klu.kdj.j,
+        }
+        return klu_feature_dict
+
+    def stragety_feature(self, last_bsp):
+        last_bi = last_bsp.bi
+        last_klu = last_bsp.klu
+        feature_dict = {
+            "open_klu_rate": (last_klu.close - last_klu.open)/last_klu.open,
+             
+        }
+        # add klu features
+        feature_dict.update(self.klu_features(last_klu))
+        # add bi features
+        #feature_dict.update(self.bi_features(last_bi))
+        # add seg features
+        seg = last_bi.parent_seg
+        #feature_dict.update(seg_features(seg))
+
+        # add zs features
+        zs_list = seg.zs_lst
+        zs_feature_dict = {}
+        if zs_list:
+            zs_feature_dict = {
+                f"zs_count": len(zs_list),
+            }
+            bi_in_zs = False
+            for zs in zs_list:
+                if last_bi in zs.bi_lst:
+                    bi_in_zs = True
+            if bi_in_zs:
+                zs_feature_dict.update({
+                    "bi_in_zs": 1
+                })
+            else:
+                zs_feature_dict.update({
+                    "bi_in_zs": 0
+                })
+            zs_feature_dict.update(self.zs_features(zs_list[-1]))
+        else:
+            zs_feature_dict ={
+                "zs_count": 0,
+            }
+        feature_dict.update(zs_feature_dict)
+        return feature_dict
+
+

Debug/buy_feature.libsvm

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Debug/buy_strategy.py

@@ -0,0 +1,158 @@
+import json
+from typing import Dict, TypedDict
+import sys 
+import os
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py"))
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py/Debug"))
+import xgboost as xgb
+
+from Chan import CChan
+from ChanConfig import CChanConfig
+from ChanModel.Features import CFeatures
+from Common.CEnum import AUTYPE, DATA_SRC, KL_TYPE, BSP_TYPE,  MACD_ALGO
+from Common.CTime import CTime
+from Plot.PlotDriver import CPlotDriver
+from Bi.Bi import CBi
+from FeatureDict import FeatureDict
+
+class T_SAMPLE_INFO(TypedDict):
+    feature: CFeatures
+    is_buy: bool
+    open_time: CTime
+
+
+def plot(chan, plot_marker):
+    plot_config = {
+        "plot_kline": True,
+        "plot_bi": True,
+        "plot_seg": True,
+        "plot_zs": True,
+        "plot_bsp": True,
+        "plot_marker": True,
+        "plot_macd": True,
+    }
+    plot_para = {
+        "figure": {
+            "x_range": 4000,
+        },
+        "marker": {
+            "markers": plot_marker
+        }
+    }
+    plot_driver = CPlotDriver(
+        chan,
+        plot_config=plot_config,
+        plot_para=plot_para,
+    )
+    plot_driver.save2img("buy.png")
+
+
+if __name__ == "__main__":
+    """
+    本demo主要演示如何记录策略产出的买卖点的特征
+    然后将这些特征作为样本，训练一个模型(以XGB为demo)
+    用于预测买卖点的准确性
+
+    请注意，demo训练预测都用的是同一份数据，这是不合理的，仅仅是为了演示
+    """
+    code = "BTC/USDT:USDT"
+    begin_time = "2024-12-1"
+    end_time = "2024-12-4"
+    data_src = DATA_SRC.CCXT
+    lv_list = [KL_TYPE.K_1M]
+
+    config = CChanConfig({
+        "trigger_step": True,  # 打开开关！
+        "bi_strict": True,
+        "skip_step": 0,
+        "divergence_rate": float("inf"),
+        "bsp2_follow_1": False,
+        "bsp3_follow_1": False,
+        "min_zs_cnt": 0,
+        "bs1_peak": False,
+        "macd_algo": "peak",
+        "bs_type": '1,2,3a,1p,2s,3b',
+        "print_warning": True,
+        "zs_algo": "normal",
+        "cal_rsi": True,
+        "cal_kdj": True,
+    })
+
+    chan = CChan(
+        code=code,
+        begin_time=begin_time,
+        end_time=end_time,
+        data_src=data_src,
+        lv_list=lv_list,
+        config=config,
+        autype=AUTYPE.QFQ,
+    )
+    bsp_dict: Dict[int, T_SAMPLE_INFO] = {}  # 存储策略产出的bsp的特征
+
+    # 跑策略，保存买卖点的特征
+    index = 0
+    for chan_snapshot in chan.step_load():
+        last_klu = chan_snapshot[0][-1][-1]
+        bsp_list = chan_snapshot.get_bsp()
+        if not bsp_list:
+            continue
+        last_bsp = bsp_list[-1]
+        cur_lv_chan = chan_snapshot[0]
+        if BSP_TYPE.T1 in last_bsp.type or BSP_TYPE.T1P in last_bsp.type:
+            if last_bsp.klu.idx not in bsp_dict and cur_lv_chan[-2].idx == last_bsp.klu.klc.idx and last_bsp.is_buy:
+                # 假如策略是：买卖点分形第三元素出现时交易
+                bsp_dict[last_bsp.klu.idx] = {
+                    "feature": last_bsp.features,
+                    "is_buy": last_bsp.is_buy,
+                    "open_time": last_klu.time,
+                }
+                bsp_dict[last_bsp.klu.idx]['feature'].add_feat(FeatureDict().stragety_feature(last_bsp))  # 开仓K线特征
+                print(index, last_bsp.klu.time, last_bsp.is_buy)
+                index += 1
+
+    # 生成libsvm样本特征
+    bsp_academy = [bsp.klu.idx for bsp in chan.get_bsp()]
+    feature_meta = {}  # 特征meta
+    cur_feature_idx = 0
+    plot_marker = {}
+    fid = open("buy_feature.libsvm", "w")
+    for bsp_klu_idx, feature_info in bsp_dict.items():
+        label = int(bsp_klu_idx in bsp_academy)  # 以买卖点识别是否准确为label
+        features = []  # List[(idx, value)]
+        for feature_name, value in feature_info['feature'].items():
+            if feature_name not in feature_meta:
+                feature_meta[feature_name] = cur_feature_idx
+                cur_feature_idx += 1
+            features.append((feature_meta[feature_name], value))
+        features.sort(key=lambda x: x[0])
+        feature_str = " ".join([f"{idx}:{value}" for idx, value in features])
+        fid.write(f"{label} {feature_str}\n")
+        plot_marker[feature_info["open_time"].to_str()] = ("√" if label else "×", "down" if feature_info["is_buy"] else "up")
+    fid.close()
+
+    with open("feature.meta", "w") as fid:
+        # meta保存下来，实盘预测时特征对齐用
+        fid.write(json.dumps(feature_meta))
+
+    # 画图检查label是否正确
+    plot(chan, plot_marker)
+
+    # load sample file & train model
+    dtrain = xgb.DMatrix("buy_feature.libsvm?format=libsvm")  # load sample
+    param = {'max_depth': 2, 'eta': 0.3, 'objective': 'binary:logistic', 'eval_metric': 'auc'}
+    evals_result = {}
+    bst = xgb.train(
+        param,
+        dtrain=dtrain,
+        num_boost_round=50,
+        evals=[(dtrain, "train")],
+        evals_result=evals_result,
+        verbose_eval=True,
+    )
+    bst.save_model("buy_model.json")
+
+    # load model
+    model = xgb.Booster()
+    model.load_model("buy_model.json")
+    # predict
+    print(model.predict(dtrain))

Debug/eval_feature.libsvm

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Debug/feature.meta

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+{"divergence_rate": 0, "open_klu_rate": 1, "klu_rsi": 2, "klu_macd_fast_ema": 3, "klu_macd_slow_ema": 4, "klu_macd_DIF": 5, "klu_macd_DEA": 6, "klu_macd_macd": 7, "klu_kdj_k": 8, "klu_kdj_d": 9, "klu_kdj_j": 10, "zs_count": 11, "bi_in_zs": 12, "zs_high": 13, "zs_low": 14, "zs_mid": 15, "zs_peak_low": 16, "zs_peak_high": 17}

Debug/models/buy_models/b1_models/20241211_1m/feature.meta

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+{"divergence_rate": 0, "open_klu_rate": 1, "klu_rsi": 2, "klu_macd_fast_ema": 3, "klu_macd_slow_ema": 4, "klu_macd_DIF": 5, "klu_macd_DEA": 6, "klu_macd_macd": 7, "klu_kdj_k": 8, "klu_kdj_d": 9, "klu_kdj_j": 10, "bi_macd_area": 11, "bi_macd_peak": 12, "bi_macd_full_area": 13, "bi_macd_diff": 14, "bi_macd_slop": 15, "bi_macd_amp": 16, "bi_macd_amount": 17, "bi_macd_rsi": 18, "klu_max_high": 19, "klu_max_low": 20, "seg_macd_slope": 21, "seg_macd_amp": 22, "seg_amp": 23, "seg_cal_klu_slope": 24, "seg_cal_amp": 25, "zs_count": 26, "bi_in_zs": 27, "zs_high": 28, "zs_low": 29, "zs_mid": 30, "zs_peak_low": 31, "zs_peak_high": 32}

Debug/models/buy_models/b1_models/20241211_1m/read_me.txt

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+Read me
+Training Data
+Timerange: 20240101-20241130
+Timeframe: 1m
+Evaluation Data
+Timerange: 20241205-20241207
+Timeframe: 1m
+Resulting Model Feature: 这个模型识别急跌情况下的b1，其它b1被忽略

Debug/models/buy_models/b1_models/20241211_5m/read_me.txt

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+Read me
+Training Data
+Timerange: 20220101-20241130
+Timeframe: 5m
+Evaluation Data
+Timerange: 20241205-20241207
+Timeframe: 5m
+Resulting Model Feature: 

Debug/sell_feature.libsvm

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Debug/sell_strategy.py

@@ -0,0 +1,157 @@
+import json
+from typing import Dict, TypedDict
+import sys 
+import os
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py"))
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py/Debug"))
+import xgboost as xgb
+
+from Chan import CChan
+from ChanConfig import CChanConfig
+from ChanModel.Features import CFeatures
+from Common.CEnum import AUTYPE, DATA_SRC, KL_TYPE, BSP_TYPE,  MACD_ALGO
+from Common.CTime import CTime
+from Plot.PlotDriver import CPlotDriver
+from Bi.Bi import CBi
+from FeatureDict import FeatureDict
+class T_SAMPLE_INFO(TypedDict):
+    feature: CFeatures
+    is_buy: bool
+    open_time: CTime
+
+
+def plot(chan, plot_marker):
+    plot_config = {
+        "plot_kline": True,
+        "plot_bi": True,
+        "plot_seg": True,
+        "plot_zs": True,
+        "plot_bsp": True,
+        "plot_marker": True,
+        "plot_macd": True,
+    }
+    plot_para = {
+        "figure": {
+            "x_range": 4000,
+        },
+        "marker": {
+            "markers": plot_marker
+        }
+    }
+    plot_driver = CPlotDriver(
+        chan,
+        plot_config=plot_config,
+        plot_para=plot_para,
+    )
+    plot_driver.save2img("sell.png")
+
+if __name__ == "__main__":
+    """
+    本demo主要演示如何记录策略产出的买卖点的特征
+    然后将这些特征作为样本，训练一个模型(以XGB为demo)
+    用于预测买卖点的准确性
+
+    请注意，demo训练预测都用的是同一份数据，这是不合理的，仅仅是为了演示
+    """
+    code = "BTC/USDT:USDT"
+    begin_time = "2024-12-1"
+    end_time = "2024-12-4"
+    data_src = DATA_SRC.CCXT
+    lv_list = [KL_TYPE.K_1M]
+
+    config = CChanConfig({
+        "trigger_step": True,  # 打开开关！
+        "bi_strict": True,
+        "skip_step": 0,
+        "divergence_rate": float("inf"),
+        "bsp2_follow_1": False,
+        "bsp3_follow_1": False,
+        "min_zs_cnt": 0,
+        "bs1_peak": False,
+        "macd_algo": "peak",
+        "bs_type": '1,2,3a,1p,2s,3b',
+        "print_warning": True,
+        "zs_algo": "normal",
+        "cal_rsi": True,
+        "cal_kdj": True,
+    })
+
+    chan = CChan(
+        code=code,
+        begin_time=begin_time,
+        end_time=end_time,
+        data_src=data_src,
+        lv_list=lv_list,
+        config=config,
+        autype=AUTYPE.QFQ,
+    )
+
+    bsp_dict: Dict[int, T_SAMPLE_INFO] = {}  # 存储策略产出的bsp的特征
+
+    # 跑策略，保存买卖点的特征
+    index = 0
+    for chan_snapshot in chan.step_load():
+        last_klu = chan_snapshot[0][-1][-1]
+        bsp_list = chan_snapshot.get_bsp()
+        if not bsp_list:
+            continue
+        last_bsp = bsp_list[-1]
+        cur_lv_chan = chan_snapshot[0]
+        if BSP_TYPE.T1 in last_bsp.type or BSP_TYPE.T1P in last_bsp.type:
+            if last_bsp.klu.idx not in bsp_dict and cur_lv_chan[-2].idx == last_bsp.klu.klc.idx and not last_bsp.is_buy:
+                # 假如策略是：买卖点分形第三元素出现时交易
+                bsp_dict[last_bsp.klu.idx] = {
+                    "feature": last_bsp.features,
+                    "is_buy": last_bsp.is_buy,
+                    "open_time": last_klu.time,
+                }
+                bsp_dict[last_bsp.klu.idx]['feature'].add_feat(FeatureDict().stragety_feature(last_bsp))  # 开仓K线特征
+                print(index, last_bsp.klu.time, last_bsp.is_buy)
+                index += 1
+
+    # 生成libsvm样本特征
+    bsp_academy = [bsp.klu.idx for bsp in chan.get_bsp()]
+    feature_meta = {}  # 特征meta
+    cur_feature_idx = 0
+    plot_marker = {}
+    fid = open("sell_feature.libsvm", "w")
+    for bsp_klu_idx, feature_info in bsp_dict.items():
+        label = int(bsp_klu_idx in bsp_academy)  # 以买卖点识别是否准确为label
+        features = []  # List[(idx, value)]
+        for feature_name, value in feature_info['feature'].items():
+            if feature_name not in feature_meta:
+                feature_meta[feature_name] = cur_feature_idx
+                cur_feature_idx += 1
+            features.append((feature_meta[feature_name], value))
+        features.sort(key=lambda x: x[0])
+        feature_str = " ".join([f"{idx}:{value}" for idx, value in features])
+        fid.write(f"{label} {feature_str}\n")
+        plot_marker[feature_info["open_time"].to_str()] = ("√" if label else "×", "down" if feature_info["is_buy"] else "up")
+    fid.close()
+
+    with open("feature.meta", "w") as fid:
+        # meta保存下来，实盘预测时特征对齐用
+        fid.write(json.dumps(feature_meta))
+
+    # 画图检查label是否正确
+    plot(chan, plot_marker)
+
+    # load sample file & train model
+    dtrain = xgb.DMatrix("sell_feature.libsvm?format=libsvm")  # load sample
+    param = {'max_depth': 2, 'eta': 0.3, 'objective': 'binary:logistic', 'eval_metric': 'auc'}
+    evals_result = {}
+    bst = xgb.train(
+        param,
+        dtrain=dtrain,
+        num_boost_round=50,
+        evals=[(dtrain, "train")],
+        evals_result=evals_result,
+        verbose_eval=True,
+    )
+    bst.save_model("sell_model.json")
+
+    # load model
+    model = xgb.Booster()
+    model.load_model("sell_model.json")
+    # predict
+    print(model.predict(dtrain))

Debug/strategy_demo.py

@@ -0,0 +1,51 @@
+from Chan import CChan
+from ChanConfig import CChanConfig
+from Common.CEnum import AUTYPE, BSP_TYPE, DATA_SRC, FX_TYPE, KL_TYPE
+
+if __name__ == "__main__":
+    """
+    一个极其弱智的策略，只交易一类买卖点，底分型形成后就开仓，直到一类卖点顶分型形成后平仓
+    只用做展示如何自己实现策略，做回测用~
+    """
+    code = "sz.000001"
+    begin_time = "2021-01-01"
+    end_time = None
+    data_src = DATA_SRC.BAO_STOCK
+    lv_list = [KL_TYPE.K_DAY]
+
+    config = CChanConfig({
+        "trigger_step": True,  # 打开开关！
+        "divergence_rate": 0.8,
+        "min_zs_cnt": 1,
+    })
+
+    chan = CChan(
+        code=code,
+        begin_time=begin_time,
+        end_time=end_time,
+        data_src=data_src,
+        lv_list=lv_list,
+        config=config,
+        autype=AUTYPE.QFQ,
+    )
+
+    is_hold = False
+    last_buy_price = None
+    for chan_snapshot in chan.step_load():  # 每增加一根K线，返回当前静态精算结果
+        bsp_list = chan_snapshot.get_bsp()  # 获取买卖点列表
+        if not bsp_list:  # 为空
+            continue
+        last_bsp = bsp_list[-1]  # 最后一个买卖点
+        if BSP_TYPE.T1 not in last_bsp.type and BSP_TYPE.T1P not in last_bsp.type:  # 假如只做1类买卖点
+            continue
+        cur_lv_chan = chan_snapshot[0]
+        if last_bsp.klu.klc.idx != cur_lv_chan[-2].idx:
+            continue
+        if cur_lv_chan[-2].fx == FX_TYPE.BOTTOM and last_bsp.is_buy and not is_hold:  # 底分型形成后开仓
+            last_buy_price = cur_lv_chan[-1][-1].close  # 开仓价格为最后一根K线close
+            print(f'{cur_lv_chan[-1][-1].time}:buy price = {last_buy_price}')
+            is_hold = True
+        elif cur_lv_chan[-2].fx == FX_TYPE.TOP and not last_bsp.is_buy and is_hold:  # 顶分型形成后平仓
+            sell_price = cur_lv_chan[-1][-1].close
+            print(f'{cur_lv_chan[-1][-1].time}:sell price = {sell_price}, profit rate = {(sell_price-last_buy_price)/last_buy_price*100:.2f}%')
+            is_hold = False

Debug/strategy_demo2.py

@@ -0,0 +1,62 @@
+import sys 
+import os
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py"))
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py/Debug"))
+from Chan import CChan
+from ChanConfig import CChanConfig
+from Common.CEnum import AUTYPE, BSP_TYPE, DATA_SRC, FX_TYPE, KL_TYPE
+from DataAPI.ccxt import CCXT
+
+if __name__ == "__main__":
+    """
+    一个极其弱智的策略，只交易一类买卖点，底分型形成后就开仓，直到一类卖点顶分型形成后平仓
+    只用做展示如何自己实现策略，做回测用~
+    相比于strategy_demo.py，本代码演示如何从CChan外部喂K线来触发内部缠论计算
+    """
+    code = "BTC/USDT"
+    begin_time = "2025-02-01"
+    end_time = None
+    data_src_type = DATA_SRC.CCXT
+    lv_list = [KL_TYPE.K_60M]
+
+    config = CChanConfig({
+        "trigger_step": True,
+        "divergence_rate": 0.8,
+        "min_zs_cnt": 0,
+    })
+
+    chan = CChan(
+        code=code,
+        begin_time=begin_time,  # 已经没啥用了这一行
+        end_time=end_time,  # 已经没啥用了这一行
+        data_src=data_src_type,  # 已经没啥用了这一行
+        lv_list=lv_list,
+        config=config,
+        autype=AUTYPE.QFQ,  # 已经没啥用了这一行
+    )
+    CCXT.do_init()
+    data_src = CCXT(code, k_type=KL_TYPE.K_60M, begin_date=begin_time, end_date=end_time, autype=AUTYPE.QFQ)  # 初始化数据源类
+
+    is_hold = False
+    last_buy_price = None
+    for klu in data_src.get_kl_data():  # 获取单根K线
+        chan.trigger_load({KL_TYPE.K_60M: [klu]})  # 喂给CChan新增k线
+        bsp_list = chan.get_bsp()
+        if not bsp_list:
+            continue
+        last_bsp = bsp_list[-1]
+        print(klu.time, last_bsp.is_buy)
+        if BSP_TYPE.T1 not in last_bsp.type and BSP_TYPE.T1P not in last_bsp.type:
+            continue
+        cur_lv_chan = chan[0]
+        if last_bsp.klu.klc.idx != cur_lv_chan[-2].idx:
+            continue
+        if cur_lv_chan[-2].fx == FX_TYPE.BOTTOM and last_bsp.is_buy and not is_hold:
+            last_buy_price = cur_lv_chan[-1][-1].close
+            print(f'{cur_lv_chan[-1][-1].time}:buy price = {last_buy_price}')
+            is_hold = True
+        elif cur_lv_chan[-2].fx == FX_TYPE.TOP and not last_bsp.is_buy and is_hold:
+            sell_price = cur_lv_chan[-1][-1].close
+            print(f'{cur_lv_chan[-1][-1].time}:sell price = {sell_price}, profit rate = {(sell_price-last_buy_price)/last_buy_price*100:.2f}%')
+            is_hold = False
+    CCXT.do_close()

Debug/strategy_demo3.py

@@ -0,0 +1,77 @@
+import copy
+from typing import List
+
+from Chan import CChan
+from ChanConfig import CChanConfig
+from Common.CEnum import AUTYPE, DATA_FIELD, DATA_SRC, KL_TYPE
+from DataAPI.BaoStockAPI import CBaoStock
+from KLine.KLine_Unit import CKLine_Unit
+
+
+def combine_60m_klu_form_15m(klu_15m_lst: List[CKLine_Unit]) -> CKLine_Unit:
+    return CKLine_Unit(
+        {
+            DATA_FIELD.FIELD_TIME: klu_15m_lst[-1].time,
+            DATA_FIELD.FIELD_OPEN: klu_15m_lst[0].open,
+            DATA_FIELD.FIELD_CLOSE: klu_15m_lst[-1].close,
+            DATA_FIELD.FIELD_HIGH: max(klu.high for klu in klu_15m_lst),
+            DATA_FIELD.FIELD_LOW: min(klu.low for klu in klu_15m_lst),
+        }
+    )
+
+
+if __name__ == "__main__":
+    """
+    代码不能直接跑，仅用于展示如何实现小级别K线更新直接刷新CChan结果
+    """
+    code = "sz.000001"
+    begin_time = "2023-09-10"
+    end_time = None
+    data_src_type = DATA_SRC.BAO_STOCK
+    lv_list = [KL_TYPE.K_60M, KL_TYPE.K_15M]
+
+    config = CChanConfig({
+        "trigger_step": True,
+    })
+
+    # 快照
+    chan_snapshot = CChan(
+        code=code,
+        data_src=data_src_type,
+        lv_list=lv_list,
+        config=config,
+    )
+    CBaoStock.do_init()
+    data_src = CBaoStock(code, k_type=KL_TYPE.K_15M, begin_date=begin_time, end_date=end_time, autype=AUTYPE.QFQ)  # 获取最小级别
+
+    klu_15m_lst_tmp: List[CKLine_Unit] = []  # 存储用于合成当前60M K线的15M k线
+
+    for klu_15m in data_src.get_kl_data():  # 获取单根15分钟K线
+        klu_15m_lst_tmp.append(klu_15m)
+        klu_60m = combine_60m_klu_form_15m(klu_15m_lst_tmp)  # 合成60分钟K线
+
+        """
+        拷贝一份chan_snapshot
+        如果是用序列化方式，这里可以采用pickle.load()
+        """
+        chan: CChan = copy.deepcopy(chan_snapshot)
+        chan.trigger_load({KL_TYPE.K_60M: [klu_60m], KL_TYPE.K_15M: klu_15m_lst_tmp})
+
+        """
+        策略开始：
+        这里基于chan实现你的策略
+        """
+        for kl_type, ele_manager in chan.kl_datas.items():
+            # 打印当前每一级别分别有多少K线
+            print(klu_15m.time, kl_type, sum(len(klc) for klc in ele_manager))
+        # 策略结束：
+
+        if len(klu_15m_lst_tmp) == 4:  # 已经完成4根15分钟K线了，说明这个最新的60分钟K线和里面的4根15分钟K线在将来不会再变化
+            """
+            把当前完整chan重新保存成chan_snapshot
+            如果是序列化方式，这里可以采用pickle.dump()
+            """
+            chan_snapshot = chan
+            klu_15m_lst_tmp = []  # 清空1分钟K线，用于下一个五分钟周期的合成
+
+    CBaoStock.do_close()

Debug/strategy_demo4.py

@@ -0,0 +1,53 @@
+from Chan import CChan
+from ChanConfig import CChanConfig
+from Common.CEnum import AUTYPE, DATA_SRC, KL_TYPE
+from DataAPI.BaoStockAPI import CBaoStock
+
+if __name__ == "__main__":
+    """
+    本demo演示当你要用多级别trigger load的时候，如何巧妙的解决时间对齐的问题：
+    解决方案就是喂第一根最大级别的时候，直接把所有的次级别全部喂进去
+    之后每次只需要喂一根最大级别即可，复用框架内置的K线时间对齐能力
+    从而避免了在trigger_load入参那里进行K线对齐，自己去找出最大级别那根K线下所有次级别的K线
+    """
+    code = "sz.000001"
+    begin_time = "2023-06-01"
+    end_time = None
+    data_src = DATA_SRC.BAO_STOCK
+    lv_list = [KL_TYPE.K_DAY, KL_TYPE.K_30M]
+
+    config = CChanConfig({
+        "trigger_step": True,
+        "divergence_rate": 0.8,
+        "min_zs_cnt": 1,
+    })
+
+    chan = CChan(
+        code=code,
+        begin_time=begin_time,  # 已经没啥用了这一行
+        end_time=end_time,  # 已经没啥用了这一行
+        data_src=data_src,  # 已经没啥用了这一行
+        lv_list=lv_list,
+        config=config,
+        autype=AUTYPE.QFQ,  # 已经没啥用了这一行
+    )
+    CBaoStock.do_init()
+    data_src_day = CBaoStock(code, k_type=KL_TYPE.K_DAY, begin_date=begin_time, end_date=end_time, autype=AUTYPE.QFQ)
+    data_src_30m = CBaoStock(code, k_type=KL_TYPE.K_30M, begin_date=begin_time, end_date=end_time, autype=AUTYPE.QFQ)
+    kl_30m_all = list(data_src_30m.get_kl_data())
+
+    for _idx, klu in enumerate(data_src_day.get_kl_data()):
+        # 本质是每喂一根日线的时候，这根日线之前的都要喂过，提前喂多点不要紧，框架会自动根据日线来截取需要的30M K线
+        # 30M一口气全部喂完，后续就不用关注时间对齐的问题了
+        if _idx == 0:
+            chan.trigger_load({KL_TYPE.K_DAY: [klu], KL_TYPE.K_30M: kl_30m_all})
+        else:
+            chan.trigger_load({KL_TYPE.K_DAY: [klu]})
+
+        if _idx == 4:  # demo只检查4根日线
+            break
+        # 检查时间对齐
+        print("当前所有日线:", [klu.time.to_str() for klu in chan[0].klu_iter()])
+        print("当前所有30M K线:", [klu.time.to_str() for klu in chan[1].klu_iter()], "\n")
+
+    CBaoStock.do_close()

Debug/strategy_demo5.py

@@ -0,0 +1,160 @@
+import json
+from typing import Dict, TypedDict
+import sys 
+import os
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py"))
+import xgboost as xgb
+
+from Chan import CChan
+from ChanConfig import CChanConfig
+from ChanModel.Features import CFeatures
+from Common.CEnum import AUTYPE, DATA_SRC, KL_TYPE, BSP_TYPE
+from Common.CTime import CTime
+from Plot.PlotDriver import CPlotDriver
+
+
+class T_SAMPLE_INFO(TypedDict):
+    feature: CFeatures
+    is_buy: bool
+    open_time: CTime
+
+
+def plot(chan, plot_marker):
+    plot_config = {
+        "plot_kline": True,
+        "plot_bi": True,
+        "plot_seg": True,
+        "plot_zs": True,
+        "plot_bsp": True,
+        "plot_marker": True,
+        "plot_macd": True,
+    }
+    plot_para = {
+        "figure": {
+            "x_range": 400,
+        },
+        "marker": {
+            "markers": plot_marker
+        }
+    }
+    plot_driver = CPlotDriver(
+        chan,
+        plot_config=plot_config,
+        plot_para=plot_para,
+    )
+    plot_driver.save2img("label.png")
+
+
+def stragety_feature(last_klu):
+    return {
+        "open_klu_rate": (last_klu.close - last_klu.open)/last_klu.open,
+    }
+
+
+if __name__ == "__main__":
+    """
+    本demo主要演示如何记录策略产出的买卖点的特征
+    然后将这些特征作为样本，训练一个模型(以XGB为demo)
+    用于预测买卖点的准确性
+
+    请注意，demo训练预测都用的是同一份数据，这是不合理的，仅仅是为了演示
+    """
+    code = "BTC/USDT"
+    begin_time = "2024-12-1"
+    end_time = None
+    data_src = DATA_SRC.CCXT
+    lv_list = [KL_TYPE.K_1M]
+
+    config = CChanConfig({
+        "trigger_step": True,  # 打开开关！
+        "bi_strict": True,
+        "skip_step": 0,
+        "divergence_rate": float("inf"),
+        "bsp2_follow_1": False,
+        "bsp3_follow_1": False,
+        "min_zs_cnt": 0,
+        "bs1_peak": False,
+        "macd_algo": "peak",
+        "bs_type": '1,2,3a,1p,2s,3b',
+        "print_warning": True,
+        "zs_algo": "normal",
+    })
+
+    chan = CChan(
+        code=code,
+        begin_time=begin_time,
+        end_time=end_time,
+        data_src=data_src,
+        lv_list=lv_list,
+        config=config,
+        autype=AUTYPE.QFQ,
+    )
+
+    bsp_dict: Dict[int, T_SAMPLE_INFO] = {}  # 存储策略产出的bsp的特征
+
+    # 跑策略，保存买卖点的特征
+    index = 0
+    for chan_snapshot in chan.step_load():
+        last_klu = chan_snapshot[0][-1][-1]
+        bsp_list = chan_snapshot.get_bsp()
+        if not bsp_list:
+            continue
+        last_bsp = bsp_list[-1]
+        cur_lv_chan = chan_snapshot[0]
+        if last_bsp.klu.idx not in bsp_dict and cur_lv_chan[-2].idx == last_bsp.klu.klc.idx and last_bsp.is_buy:
+            # 假如策略是：买卖点分形第三元素出现时交易
+            bsp_dict[last_bsp.klu.idx] = {
+                "feature": last_bsp.features,
+                "is_buy": last_bsp.is_buy,
+                "open_time": last_klu.time,
+            }
+            bsp_dict[last_bsp.klu.idx]['feature'].add_feat(stragety_feature(last_klu))  # 开仓K线特征
+            print(index, last_bsp.klu.time, last_bsp.is_buy)
+            index += 1
+
+    # 生成libsvm样本特征
+    bsp_academy = [bsp.klu.idx for bsp in chan.get_bsp()]
+    feature_meta = {}  # 特征meta
+    cur_feature_idx = 0
+    plot_marker = {}
+    fid = open("feature.libsvm", "w")
+    for bsp_klu_idx, feature_info in bsp_dict.items():
+        label = int(bsp_klu_idx in bsp_academy)  # 以买卖点识别是否准确为label
+        features = []  # List[(idx, value)]
+        for feature_name, value in feature_info['feature'].items():
+            if feature_name not in feature_meta:
+                feature_meta[feature_name] = cur_feature_idx
+                cur_feature_idx += 1
+            features.append((feature_meta[feature_name], value))
+        features.sort(key=lambda x: x[0])
+        feature_str = " ".join([f"{idx}:{value}" for idx, value in features])
+        fid.write(f"{label} {feature_str}\n")
+        plot_marker[feature_info["open_time"].to_str()] = ("√" if label else "×", "down" if feature_info["is_buy"] else "up")
+    fid.close()
+
+    with open("feature.meta", "w") as fid:
+        # meta保存下来，实盘预测时特征对齐用
+        fid.write(json.dumps(feature_meta))
+
+    # 画图检查label是否正确
+    plot(chan, plot_marker)
+
+    # load sample file & train model
+    dtrain = xgb.DMatrix("feature.libsvm?format=libsvm")  # load sample
+    param = {'max_depth': 2, 'eta': 0.3, 'objective': 'binary:logistic', 'eval_metric': 'auc'}
+    evals_result = {}
+    bst = xgb.train(
+        param,
+        dtrain=dtrain,
+        num_boost_round=50,
+        evals=[(dtrain, "train")],
+        evals_result=evals_result,
+        verbose_eval=True,
+    )
+    bst.save_model("buy_model.json")
+
+    # load model
+    model = xgb.Booster()
+    model.load_model("buy_model.json")
+    # predict
+    print(model.predict(dtrain))

Debug/strategy_demo6.py

@@ -0,0 +1,77 @@
+
+import json
+from typing import Dict, TypedDict
+
+import xgboost as xgb
+from strategy_demo5 import stragety_feature
+
+from BuySellPoint.BS_Point import CBS_Point
+from Chan import CChan
+from ChanConfig import CChanConfig
+from ChanModel.Features import CFeatures
+from Common.CEnum import AUTYPE, DATA_SRC, KL_TYPE
+from Common.CTime import CTime
+
+
+class T_SAMPLE_INFO(TypedDict):
+    feature: CFeatures
+    is_buy: bool
+    open_time: CTime
+
+
+def predict_bsp(model: xgb.Booster, last_bsp: CBS_Point, meta: Dict[str, int]):
+    missing = -9999999
+    feature_arr = [missing] * len(meta)
+    for feat_name, feat_value in last_bsp.features.items():
+        if feat_name in meta:
+            feature_arr[meta[feat_name]] = feat_value
+    feature_arr = [feature_arr]
+    dtest = xgb.DMatrix(feature_arr, missing=missing)
+    return model.predict(dtest)
+
+
+if __name__ == "__main__":
+    """
+    本demo主要演示如何在实盘中把策略产出的买卖点，对接到demo5中训练好的离线模型上
+    """
+    code = "BTC/USDT"
+    begin_time = "2023-11-30"
+    end_time = None
+    data_src = DATA_SRC.CCXT
+    lv_list = [KL_TYPE.K_DAY]
+
+    config = CChanConfig({
+        "trigger_step": True,  # 打开开关！
+    })
+
+    chan = CChan(
+        code=code,
+        begin_time=begin_time,
+        end_time=end_time,
+        data_src=data_src,
+        lv_list=lv_list,
+        config=config,
+        autype=AUTYPE.QFQ,
+    )
+
+    model = xgb.Booster()
+    model.load_model("model.json")
+    meta = json.load(open("feature.meta", "r"))
+
+    treated_bsp_idx = set()
+    for chan_snapshot in chan.step_load():
+        # 策略逻辑要对齐demo5
+        last_klu = chan_snapshot[0][-1][-1]
+        bsp_list = chan_snapshot.get_bsp()
+        if not bsp_list:
+            continue
+        last_bsp = bsp_list[-1]
+
+        cur_lv_chan = chan_snapshot[0]
+        if last_bsp.klu.idx in treated_bsp_idx or cur_lv_chan[-2].idx != last_bsp.klu.klc.idx:
+            continue
+
+        last_bsp.features.add_feat(stragety_feature(last_klu))  # 开仓K线特征
+        # 买卖点打分，应该和demo5最后的predict结果完全一致才对
+        print(last_bsp.klu.time, predict_bsp(model, last_bsp, meta))
+        treated_bsp_idx.add(last_bsp.klu.idx)

Debug/xgboost_eval.py

@@ -0,0 +1,166 @@
+import json
+from typing import Dict, TypedDict
+import sys 
+import os
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py"))
+sys.path.append(os.path.abspath("/Users/jack/Project/chan.py/Debug"))
+import xgboost as xgb
+from BuySellPoint.BS_Point import CBS_Point
+from Chan import CChan
+from ChanConfig import CChanConfig
+from ChanModel.Features import CFeatures
+from Common.CEnum import AUTYPE, DATA_SRC, KL_TYPE, BSP_TYPE,  MACD_ALGO
+from Common.CTime import CTime
+from Plot.PlotDriver import CPlotDriver
+from Bi.Bi import CBi
+from FeatureDict import FeatureDict
+class T_SAMPLE_INFO(TypedDict):
+    feature: CFeatures
+    is_buy: bool
+    open_time: CTime
+
+
+def plot(chan, plot_marker):
+    plot_config = {
+        "plot_kline": True,
+        "plot_bi": True,
+        "plot_seg": True,
+        "plot_zs": True,
+        "plot_bsp": True,
+        "plot_marker": True,
+        "plot_macd": True,
+    }
+    plot_para = {
+        "figure": {
+            "x_range": 4000,
+        },
+        "marker": {
+            "markers": plot_marker
+        }
+    }
+    plot_driver = CPlotDriver(
+        chan,
+        plot_config=plot_config,
+        plot_para=plot_para,
+    )
+    plot_driver.save2img("eval.png")
+
+def predict_bsp(last_bsp: CBS_Point):
+    model = xgb.Booster()
+    if last_bsp.is_buy:
+        model.load_model("buy_model.json")
+    else:
+        model.load_model("sell_model.json")
+    meta = json.load(open("feature.meta", "r"))
+    missing = -9999999
+    feature_arr = [missing] * len(meta)
+    for feat_name, feat_value in last_bsp.features.items():
+        if feat_name in meta:
+            feature_arr[meta[feat_name]] = feat_value
+    feature_arr = [feature_arr]
+    dtest = xgb.DMatrix(feature_arr, missing=missing)
+    return model.predict(dtest)
+
+
+if __name__ == "__main__":
+    """
+    本demo主要演示如何记录策略产出的买卖点的特征
+    然后将这些特征作为样本，训练一个模型(以XGB为demo)
+    用于预测买卖点的准确性
+
+    请注意，demo训练预测都用的是同一份数据，这是不合理的，仅仅是为了演示
+    """
+    code = "BTC/USDT:USDT"
+    begin_time = "2024-12-1"
+    end_time = "2024-12-20"
+    data_src = DATA_SRC.CCXT
+    lv_list = [KL_TYPE.K_1M]
+
+    config = CChanConfig({
+        "trigger_step": True,  # 打开开关！
+        "bi_strict": True,
+        "skip_step": 0,
+        "divergence_rate": float("inf"),
+        "bsp2_follow_1": False,
+        "bsp3_follow_1": False,
+        "min_zs_cnt": 0,
+        "bs1_peak": False,
+        "macd_algo": "peak",
+        "bs_type": '1,2,3a,1p,2s,3b',
+        "print_warning": True,
+        "zs_algo": "normal",
+        "cal_rsi": True,
+        "cal_kdj": True,
+    })
+
+    chan = CChan(
+        code=code,
+        begin_time=begin_time,
+        end_time=end_time,
+        data_src=data_src,
+        lv_list=lv_list,
+        config=config,
+        autype=AUTYPE.QFQ,
+    )
+
+    bsp_dict: Dict[int, T_SAMPLE_INFO] = {}  # 存储策略产出的bsp的特征
+
+    # 跑策略，保存买卖点的特征
+    index = 0
+    evals_count = 0
+    eval_klu_list = []
+    for chan_snapshot in chan.step_load():
+        last_klu = chan_snapshot[0][-1][-1]
+        bsp_list = chan_snapshot.get_bsp()
+        if not bsp_list:
+            continue
+        last_bsp = bsp_list[-1]
+        cur_lv_chan = chan_snapshot[0]
+        if BSP_TYPE.T1 in last_bsp.type or BSP_TYPE.T1P in last_bsp.type:
+            if last_bsp.klu.idx not in bsp_dict and cur_lv_chan[-2].idx == last_bsp.klu.klc.idx:
+                # 假如策略是：买卖点分形第三元素出现时交易
+                bsp_dict[last_bsp.klu.idx] = {
+                    "feature": last_bsp.features,
+                    "is_buy": last_bsp.is_buy,
+                    "open_time": last_klu.time,
+                }
+                bsp_dict[last_bsp.klu.idx]['feature'].add_feat(FeatureDict().stragety_feature(last_bsp))  # 开仓K线特征
+                score = predict_bsp(last_bsp)
+                ok = ""
+                if score > 0.5:
+                    ok = "OK"
+                    evals_count = evals_count + 1
+                    eval_klu_list.append(last_bsp.klu.idx)
+                print(index, last_bsp.klu.time, last_bsp.is_buy, score, ok)
+                index += 1
+
+    # 生成libsvm样本特征
+    bsp_academy = [bsp.klu.idx for bsp in chan.get_bsp()]
+    feature_meta = {}  # 特征meta
+    cur_feature_idx = 0
+    plot_marker = {}
+    fid = open("eval_feature.libsvm", "w")
+    label_count = 0
+    for bsp_klu_idx, feature_info in bsp_dict.items():
+        label = int(bsp_klu_idx in bsp_academy)  # 以买卖点识别是否准确为label
+        features = []  # List[(idx, value)]
+        for feature_name, value in feature_info['feature'].items():
+            if feature_name not in feature_meta:
+                feature_meta[feature_name] = cur_feature_idx
+                cur_feature_idx += 1
+            features.append((feature_meta[feature_name], value))
+        features.sort(key=lambda x: x[0])
+        feature_str = " ".join([f"{idx}:{value}" for idx, value in features])
+        fid.write(f"{label} {feature_str}\n")
+        plot_marker[feature_info["open_time"].to_str()] = ("√ "+ feature_info["open_time"].to_str() if label else "×", "down" if feature_info["is_buy"] else "up")
+        if label:
+            label_count = label_count + 1
+    fid.close()
+    print("Evals count: ", evals_count, "Lable count: ", label_count)
+    with open("feature.meta", "w") as fid:
+        # meta保存下来，实盘预测时特征对齐用
+        fid.write(json.dumps(feature_meta))
+
+    # 画图检查label是否正确
+    plot(chan, plot_marker)
+