93 lines
3.5 KiB
Python
93 lines
3.5 KiB
Python
from datetime import datetime
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import pandas as pd
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from Common.CEnum import AUTYPE, DATA_FIELD, KL_TYPE
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from Common.CTime import CTime
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from Common.func_util import kltype_lt_day, str2float
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from KLine.KLine_Unit import CKLine_Unit
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from .CommonStockAPI import CCommonStockApi
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class WebDataAPI(CCommonStockApi):
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"""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"""
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# 类变量用于存储数据
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_data_cache = {}
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def __init__(self, code, k_type=KL_TYPE.K_DAY, begin_date=None, end_date=None, autype=AUTYPE.QFQ):
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super().__init__(code, k_type, begin_date, end_date, autype)
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@classmethod
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def set_data(cls, code, df_data):
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"""设置指定代码的数据"""
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cls._data_cache[code] = df_data
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def get_kl_data(self):
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"""将DataFrame数据转换为CKLine_Unit迭代器"""
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df_data = self._data_cache.get(self.code)
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if df_data is None or len(df_data) == 0:
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return
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# 确保数据按时间排序并重置索引
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df_data = df_data.sort_values('date').reset_index(drop=True)
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# 检查并处理重复时间
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if 'timestamp' in df_data.columns:
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df_data = df_data.drop_duplicates(subset=['timestamp'], keep='last')
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df_data = df_data.sort_values('timestamp').reset_index(drop=True)
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prev_timestamp = None
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for idx, row in df_data.iterrows():
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# 转换时间格式
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if isinstance(row['date'], str):
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time_obj = datetime.fromisoformat(row['date'].replace('Z', '+00:00'))
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else:
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time_obj = row['date']
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# 检查时间戳确保单调递增
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if 'timestamp' in row:
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current_timestamp = row['timestamp']
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if prev_timestamp is not None and current_timestamp <= prev_timestamp:
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continue
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prev_timestamp = current_timestamp
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# 创建CTime对象 - 根据K线级别智能决定auto参数
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# 对于日线及以上级别，且时分秒为0的情况，使用auto=True
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# 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
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use_auto = False # 默认不使用auto，确保时间精确
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# 只有在日线级别且时分秒都为0时才考虑使用auto
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if self.k_type in [KL_TYPE.K_DAY, KL_TYPE.K_WEEK, KL_TYPE.K_MON]:
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if time_obj.hour == 0 and time_obj.minute == 0 and time_obj.second == 0:
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use_auto = True
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ctime = CTime(
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time_obj.year,
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time_obj.month,
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time_obj.day,
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time_obj.hour,
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time_obj.minute,
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time_obj.second,
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auto=use_auto
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)
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# 创建数据字典
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data_dict = {
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DATA_FIELD.FIELD_TIME: ctime,
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DATA_FIELD.FIELD_OPEN: float(row['open']),
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DATA_FIELD.FIELD_HIGH: float(row['high']),
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DATA_FIELD.FIELD_LOW: float(row['low']),
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DATA_FIELD.FIELD_CLOSE: float(row['close']),
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DATA_FIELD.FIELD_VOLUME: float(row['volume']) if 'volume' in row and pd.notna(row['volume']) else 0.0
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}
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yield CKLine_Unit(data_dict, autofix=True)
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def SetBasciInfo(self):
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pass
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@classmethod
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def do_init(cls):
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pass
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@classmethod
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def do_close(cls):
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pass |