547 lines
20 KiB
Python
547 lines
20 KiB
Python
import pandas as pd
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import logging
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from typing import Optional, List, Dict, Any, Union
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from core.db_manager import DBData
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from core.utils import check_date_time_format, datetime_to_timestamp
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logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s: %(message)s")
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class DBHugeVolumeData:
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def __init__(
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self,
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db_url: str
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):
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self.db_url = db_url
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self.table_name = "crypto_huge_volume"
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self.columns = [
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"symbol",
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"bar",
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"window_size",
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"timestamp",
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"date_time",
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"open",
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"high",
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"low",
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"close",
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"volume",
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"volCcy",
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"volCCyQuote",
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"volume_ma",
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"volume_std",
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"volume_threshold",
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"huge_volume",
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"volume_ratio",
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"spike_intensity",
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"close_80_percentile",
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"close_20_percentile",
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"price_80_high",
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"price_20_low",
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"volume_80_20_price_spike",
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"close_90_percentile",
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"close_10_percentile",
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"price_90_high",
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"price_10_low",
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"volume_90_10_price_spike",
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"create_time",
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]
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self.db_manager = DBData(db_url, self.table_name, self.columns)
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def _process_time_parameter(self, time_param: Optional[Union[str, int]]) -> Optional[int]:
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"""
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处理时间参数，统一转换为时间戳
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:param time_param: 时间参数（字符串或整数）
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:return: 时间戳或None
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"""
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if time_param is None:
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return None
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if isinstance(time_param, int):
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return time_param
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if isinstance(time_param, str):
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if time_param.isdigit():
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return int(time_param)
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else:
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parsed_time = check_date_time_format(time_param)
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if parsed_time is None:
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logging.warning(f"日期时间格式错误: {time_param}")
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return None
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return datetime_to_timestamp(parsed_time)
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return None
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def _build_query_conditions(
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self,
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symbol: Optional[str] = None,
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bar: Optional[str] = None,
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window_size: Optional[int] = None,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None,
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additional_conditions: Optional[List[str]] = None
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) -> tuple[List[str], Dict[str, Any]]:
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"""
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构建查询条件
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:param symbol: 交易对
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:param bar: K线周期
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:param window_size: 窗口大小
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:param start: 开始时间
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:param end: 结束时间
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:param additional_conditions: 额外的查询条件
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:return: (条件列表, 参数字典)
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"""
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conditions = additional_conditions or []
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condition_dict = {}
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if symbol:
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conditions.append("symbol = :symbol")
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condition_dict["symbol"] = symbol
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if bar:
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conditions.append("bar = :bar")
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condition_dict["bar"] = bar
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if window_size:
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conditions.append("window_size = :window_size")
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condition_dict["window_size"] = window_size
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# 处理时间参数
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start_timestamp = self._process_time_parameter(start)
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end_timestamp = self._process_time_parameter(end)
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if start_timestamp is not None:
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conditions.append("timestamp >= :start")
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condition_dict["start"] = start_timestamp
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if end_timestamp is not None:
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conditions.append("timestamp <= :end")
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condition_dict["end"] = end_timestamp
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return conditions, condition_dict
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def insert_data_to_mysql(self, df: pd.DataFrame) -> None:
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"""
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将巨量交易数据保存到MySQL的crypto_huge_volume表
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速度：⭐⭐⭐⭐⭐ 最快
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内存：⭐⭐⭐⭐ 中等
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适用场景：中小数据量（<10万条）
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:param df: 巨量交易数据DataFrame
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"""
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if df is None or df.empty:
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logging.warning("DataFrame为空，无需写入数据库。")
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return
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self.db_manager.insert_data_to_mysql(df)
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def insert_data_to_mysql_fast(self, df: pd.DataFrame) -> None:
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"""
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快速插入巨量交易数据（方案2：使用executemany批量插入）
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速度：⭐⭐⭐⭐ 很快
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内存：⭐⭐⭐⭐⭐ 低
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适用场景：中等数据量
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:param df: 巨量交易数据DataFrame
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"""
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if df is None or df.empty:
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logging.warning("DataFrame为空，无需写入数据库。")
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return
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self.db_manager.insert_data_to_mysql_fast(df)
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def insert_data_to_mysql_chunk(self, df: pd.DataFrame, chunk_size: int = 1000) -> None:
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"""
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分块插入巨量交易数据（方案3：适合大数据量）
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速度：⭐⭐⭐ 中等
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内存：⭐⭐⭐⭐⭐ 最低
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适用场景：大数据量（>10万条）
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:param df: 巨量交易数据DataFrame
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:param chunk_size: 分块大小
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"""
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if df is None or df.empty:
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logging.warning("DataFrame为空，无需写入数据库。")
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return
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self.db_manager.insert_data_to_mysql_chunk(df, chunk_size)
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def insert_data_to_mysql_simple(self, df: pd.DataFrame) -> None:
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"""
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简单插入巨量交易数据（方案4：直接使用to_sql，忽略重复）
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速度：⭐⭐⭐⭐⭐ 最快
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内存：⭐⭐⭐⭐ 中等
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注意：会抛出重复键错误，需要额外处理
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"""
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if df is None or df.empty:
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logging.warning("DataFrame为空，无需写入数据库。")
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return
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self.db_manager.insert_data_to_mysql_simple(df)
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def query_latest_data(self, symbol: str, bar: str, window_size: int) -> Optional[Dict[str, Any]]:
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"""
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查询最新巨量交易数据
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:param symbol: 交易对
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:param bar: K线周期
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:param window_size: 窗口大小
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:return: 最新数据记录或None
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"""
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sql = """
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SELECT * FROM crypto_huge_volume
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WHERE symbol = :symbol AND bar = :bar AND window_size = :window_size
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ORDER BY timestamp DESC
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LIMIT 1
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"""
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condition_dict = {"symbol": symbol, "bar": bar, "window_size": window_size}
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return self.db_manager.query_data(sql, condition_dict, return_multi=False)
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def query_data_by_symbol_bar_window_size_timestamp(self, symbol: str, bar: str, window_size: int, timestamp: int) -> Optional[Dict[str, Any]]:
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"""
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根据交易对、K线周期, 窗口大小和时间戳查询巨量交易数据
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:param symbol: 交易对
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:param bar: K线周期
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:param window_size: 窗口大小
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:param timestamp: 时间戳
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:return: 数据记录或None
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"""
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sql = """
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SELECT * FROM crypto_huge_volume
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WHERE symbol = :symbol AND bar = :bar AND window_size = :window_size AND timestamp = :timestamp
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"""
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condition_dict = {"symbol": symbol, "bar": bar, "window_size": window_size, "timestamp": timestamp}
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return self.db_manager.query_data(sql, condition_dict, return_multi=False)
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def query_huge_volume_data_by_symbol_bar_window_size(
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self,
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symbol: str,
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bar: str,
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window_size: int,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None
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) -> Optional[List[Dict[str, Any]]]:
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"""
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根据交易对、K线周期和窗口大小查询巨量交易数据
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:param symbol: 交易对
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:param bar: K线周期
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:param window_size: 窗口大小
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:param start: 开始时间
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:param end: 结束时间
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:return: 数据记录列表或None
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"""
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conditions, condition_dict = self._build_query_conditions(symbol, bar, window_size, start, end)
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where_clause = " AND ".join(conditions) if conditions else "1=1"
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sql = f"""
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SELECT * FROM crypto_huge_volume
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WHERE {where_clause}
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ORDER BY timestamp ASC
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"""
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def query_huge_volume_records(
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self,
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symbol: Optional[str] = None,
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bar: Optional[str] = None,
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window_size: Optional[int] = None,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None
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) -> Optional[List[Dict[str, Any]]]:
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"""
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查询巨量交易记录（只返回huge_volume=1的记录）
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:param symbol: 交易对
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:param bar: K线周期
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:param window_size: 窗口大小
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:param start: 开始时间
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:param end: 结束时间
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:return: 巨量交易记录列表或None
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"""
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conditions, condition_dict = self._build_query_conditions(
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symbol, bar, window_size, start, end, additional_conditions=["huge_volume = 1"]
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)
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where_clause = " AND ".join(conditions)
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sql = f"""
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SELECT * FROM crypto_huge_volume
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WHERE {where_clause}
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ORDER BY timestamp DESC
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"""
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def query_volume_80_20_price_spike_records(
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self,
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symbol: Optional[str] = None,
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bar: Optional[str] = None,
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window_size: Optional[int] = None,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None
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) -> Optional[List[Dict[str, Any]]]:
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"""
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查询80/20量价尖峰记录（只返回volume_80_20_price_spike=1的记录）
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:param symbol: 交易对
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:param bar: K线周期
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:param window_size: 窗口大小
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:param start: 开始时间
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:param end: 结束时间
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:return: 80/20量价尖峰记录列表或None
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"""
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conditions, condition_dict = self._build_query_conditions(
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symbol, bar, window_size, start, end, additional_conditions=["volume_80_20_price_spike = 1"]
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)
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where_clause = " AND ".join(conditions)
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sql = f"""
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SELECT * FROM crypto_huge_volume
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WHERE {where_clause}
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ORDER BY timestamp DESC
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"""
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def query_volume_90_10_price_spike_records(
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self,
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symbol: Optional[str] = None,
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bar: Optional[str] = None,
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window_size: Optional[int] = None,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None
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) -> Optional[List[Dict[str, Any]]]:
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"""
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查询90/10量价尖峰记录（只返回volume_90_10_price_spike=1的记录）
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:param symbol: 交易对
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:param bar: K线周期
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:param window_size: 窗口大小
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:param start: 开始时间
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:param end: 结束时间
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:return: 90/10量价尖峰记录列表或None
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"""
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conditions, condition_dict = self._build_query_conditions(
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symbol, bar, window_size, start, end, additional_conditions=["volume_90_10_price_spike = 1"]
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)
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where_clause = " AND ".join(conditions)
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sql = f"""
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SELECT * FROM crypto_huge_volume
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WHERE {where_clause}
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ORDER BY timestamp DESC
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"""
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def query_price_80_high_records(
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self,
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symbol: Optional[str] = None,
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bar: Optional[str] = None,
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window_size: Optional[int] = None,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None
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) -> Optional[List[Dict[str, Any]]]:
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"""
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查询价格达到80%分位数高点的记录（只返回price_80_high=1的记录）
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:param symbol: 交易对
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:param bar: K线周期
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:param window_size: 窗口大小
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:param start: 开始时间
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:param end: 结束时间
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:return: 价格80%分位数高点记录列表或None
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"""
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conditions, condition_dict = self._build_query_conditions(
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symbol, bar, window_size, start, end, additional_conditions=["price_80_high = 1"]
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)
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where_clause = " AND ".join(conditions)
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sql = f"""
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SELECT * FROM crypto_huge_volume
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WHERE {where_clause}
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ORDER BY timestamp DESC
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"""
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def query_price_20_low_records(
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self,
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symbol: Optional[str] = None,
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bar: Optional[str] = None,
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window_size: Optional[int] = None,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None
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) -> Optional[List[Dict[str, Any]]]:
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"""
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查询价格达到20%分位数低点的记录（只返回price_20_low=1的记录）
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:param symbol: 交易对
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:param bar: K线周期
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:param start: 开始时间
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:param end: 结束时间
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:return: 价格20%分位数低点记录列表或None
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"""
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conditions, condition_dict = self._build_query_conditions(
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symbol, bar, window_size, start, end, additional_conditions=["price_20_low = 1"]
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)
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where_clause = " AND ".join(conditions)
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sql = f"""
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SELECT * FROM crypto_huge_volume
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WHERE {where_clause}
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ORDER BY timestamp DESC
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"""
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def query_price_90_high_records(
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self,
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symbol: Optional[str] = None,
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bar: Optional[str] = None,
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window_size: Optional[int] = None,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None
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) -> Optional[List[Dict[str, Any]]]:
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"""
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查询价格达到90%分位数高点的记录（只返回price_90_high=1的记录）
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:param symbol: 交易对
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:param bar: K线周期
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:param start: 开始时间
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:param end: 结束时间
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:return: 价格90%分位数高点记录列表或None
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"""
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conditions, condition_dict = self._build_query_conditions(
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symbol, bar, window_size, start, end, additional_conditions=["price_90_high = 1"]
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)
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where_clause = " AND ".join(conditions)
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sql = f"""
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SELECT * FROM crypto_huge_volume
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WHERE {where_clause}
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ORDER BY timestamp DESC
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"""
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def query_price_10_low_records(
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self,
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symbol: Optional[str] = None,
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bar: Optional[str] = None,
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window_size: Optional[int] = None,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None
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) -> Optional[List[Dict[str, Any]]]:
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"""
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查询价格达到10%分位数低点的记录（只返回price_10_low=1的记录）
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:param symbol: 交易对
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:param bar: K线周期
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:param start: 开始时间
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:param end: 结束时间
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:return: 价格10%分位数低点记录列表或None
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"""
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conditions, condition_dict = self._build_query_conditions(
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symbol, bar, window_size, start, end, additional_conditions=["price_10_low = 1"]
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)
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where_clause = " AND ".join(conditions)
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sql = f"""
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SELECT * FROM crypto_huge_volume
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WHERE {where_clause}
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ORDER BY timestamp DESC
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"""
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def get_statistics_summary(
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self,
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symbol: Optional[str] = None,
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bar: Optional[str] = None,
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window_size: Optional[int] = None,
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start: Optional[Union[str, int]] = None,
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end: Optional[Union[str, int]] = None
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) -> Optional[Dict[str, Any]]:
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"""
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获取巨量交易统计摘要
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:param symbol: 交易对
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:param bar: K线周期
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:param window_size: 窗口大小
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:param start: 开始时间
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:param end: 结束时间
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:return: 统计摘要或None
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"""
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conditions, condition_dict = self._build_query_conditions(symbol, bar, window_size, start, end)
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where_clause = " AND ".join(conditions) if conditions else "1=1"
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sql = f"""
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SELECT
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COUNT(*) as total_records,
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SUM(huge_volume) as huge_volume_count,
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SUM(volume_80_20_price_spike) as volume_80_20_price_spike_count,
|
||
SUM(volume_90_10_price_spike) as volume_90_10_price_spike_count,
|
||
SUM(price_80_high) as price_80_high_count,
|
||
SUM(price_20_low) as price_20_low_count,
|
||
SUM(price_90_high) as price_90_high_count,
|
||
SUM(price_10_low) as price_10_low_count,
|
||
AVG(volume_ratio) as avg_volume_ratio,
|
||
MAX(volume_ratio) as max_volume_ratio,
|
||
AVG(spike_intensity) as avg_spike_intensity,
|
||
MAX(spike_intensity) as max_spike_intensity
|
||
FROM crypto_huge_volume
|
||
WHERE {where_clause}
|
||
"""
|
||
|
||
return self.db_manager.query_data(sql, condition_dict, return_multi=False)
|
||
|
||
def get_top_volume_spikes(
|
||
self,
|
||
symbol: Optional[str] = None,
|
||
bar: Optional[str] = None,
|
||
window_size: Optional[int] = None,
|
||
limit: int = 10
|
||
) -> Optional[List[Dict[str, Any]]]:
|
||
"""
|
||
获取成交量尖峰最高的记录
|
||
:param symbol: 交易对
|
||
:param bar: K线周期
|
||
:param window_size: 窗口大小
|
||
:param limit: 返回记录数量
|
||
:return: 成交量尖峰记录列表或None
|
||
"""
|
||
conditions, condition_dict = self._build_query_conditions(
|
||
symbol, bar, window_size, additional_conditions=["huge_volume = 1"]
|
||
)
|
||
|
||
where_clause = " AND ".join(conditions)
|
||
sql = f"""
|
||
SELECT * FROM crypto_huge_volume
|
||
WHERE {where_clause}
|
||
ORDER BY volume_ratio DESC
|
||
LIMIT :limit
|
||
"""
|
||
condition_dict["limit"] = limit
|
||
|
||
return self.db_manager.query_data(sql, condition_dict, return_multi=True)
|
||
|
||
def get_percentile_statistics(
|
||
self,
|
||
symbol: Optional[str] = None,
|
||
bar: Optional[str] = None,
|
||
window_size: Optional[int] = None,
|
||
start: Optional[Union[str, int]] = None,
|
||
end: Optional[Union[str, int]] = None
|
||
) -> Optional[Dict[str, Any]]:
|
||
"""
|
||
获取分位数统计信息
|
||
:param symbol: 交易对
|
||
:param bar: K线周期
|
||
:param window_size: 窗口大小
|
||
:param start: 开始时间
|
||
:param end: 结束时间
|
||
:return: 分位数统计信息或None
|
||
"""
|
||
conditions, condition_dict = self._build_query_conditions(symbol, bar, window_size, start, end)
|
||
|
||
where_clause = " AND ".join(conditions) if conditions else "1=1"
|
||
sql = f"""
|
||
SELECT
|
||
AVG(close_80_percentile) as avg_close_80_percentile,
|
||
AVG(close_20_percentile) as avg_close_20_percentile,
|
||
AVG(close_90_percentile) as avg_close_90_percentile,
|
||
AVG(close_10_percentile) as avg_close_10_percentile,
|
||
MAX(close_80_percentile) as max_close_80_percentile,
|
||
MIN(close_20_percentile) as min_close_20_percentile,
|
||
MAX(close_90_percentile) as max_close_90_percentile,
|
||
MIN(close_10_percentile) as min_close_10_percentile
|
||
FROM crypto_huge_volume
|
||
WHERE {where_clause}
|
||
"""
|
||
|
||
return self.db_manager.query_data(sql, condition_dict, return_multi=False)
|