complete market monitor functions.
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@ -8,7 +8,13 @@ import logging
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logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s: %(message)s")
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def create_metrics_report(row: pd.Series, only_output_rise: bool = False):
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def create_metrics_report(
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row: pd.Series,
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next_bar_row: pd.Series,
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btc_bar_row: pd.Series,
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only_output_huge_volume: bool = False,
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only_output_rise: bool = False
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):
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"""
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创建指标报告
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"""
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@ -18,15 +24,20 @@ def create_metrics_report(row: pd.Series, only_output_rise: bool = False):
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bar = row["bar"]
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window_size = row["window_size"]
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date_time = row["date_time"]
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if huge_volume == 1:
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logging.info(
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f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time} 巨量"
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)
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if only_output_huge_volume:
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if huge_volume == 1:
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logging.info(
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f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time} 巨量"
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)
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else:
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logging.info(
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f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time} 非巨量，此次不发送相关数据"
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)
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return
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else:
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logging.info(
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f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time} 非巨量，此次不发送相关数据"
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)
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return
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f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time}"
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)
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# fill -1 to nan
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row = row.fillna(1)
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@ -41,8 +52,10 @@ def create_metrics_report(row: pd.Series, only_output_rise: bool = False):
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f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time} 下跌，不发送相关数据"
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)
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return
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contents.append(f"# 交易巨量报告")
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if huge_volume == 1:
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contents.append(f"## 交易巨量报告")
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else:
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contents.append(f"## 交易量报告")
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contents.append(f"## {symbol} {bar} 滑动窗口: {window_size} 时间: {date_time}")
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contents.append(f"### 价格信息")
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contents.append(f"当前价格: {close}, 开盘价: {open}, 最高价: {high}, 最低价: {low}")
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@ -222,28 +235,83 @@ def create_metrics_report(row: pd.Series, only_output_rise: bool = False):
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if k_shape_value < 1:
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long_short_info["空"].append(f"K线形态: {k_shape}")
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if k_up_down == "阳线":
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if is_long and not is_over_buy:
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long_short_info["多"].append(f"量价关系: 非超买且放量上涨")
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if is_short and is_over_sell:
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long_short_info["多"].append(f"量价关系: 空头态势且超卖，但出现放量上涨，可能反转")
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long_short_info["多"].append(
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f"量价关系: 空头态势且超卖，但出现放量上涨，可能反转"
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)
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if k_up_down == "阴线":
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if is_long and is_over_buy:
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if close_80_high or close_90_high or high_80_high or high_90_high:
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long_short_info["空"].append(f"量价关系: 多头态势且超买, 目前是价位高点，但出现放量下跌，可能反转")
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long_short_info["空"].append(
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f"量价关系: 多头态势且超买, 目前是价位高点，但出现放量下跌，可能反转"
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)
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if is_short and not is_over_sell:
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long_short_info["空"].append(f"量价关系: 空头态势且非超卖，出现放量下跌")
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contents.append(f"### 技术指标信息")
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if ma_long_short_value == 1:
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contents.append(f"均线势头: 震荡")
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long_info_list = long_short_info["多"]
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short_info_list = long_short_info["空"]
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contents.append(f"#### 多头指标信号")
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if len(long_info_list) > 0:
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contents.append(f"#### 多头指标信号")
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contents.append(f"{"\n".join(long_info_list)}")
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else:
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contents.append(f"无多头指标信号")
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contents.append(f"#### 空头指标信号")
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if len(short_info_list) > 0:
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contents.append(f"#### 空头指标信号")
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contents.append(f"{"\n".join(short_info_list)}")
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else:
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contents.append(f"无空头指标信号")
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if next_bar_row is not None:
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contents.append(f"## {symbol} 与更长周期技术形态对比")
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contents.extend(get_long_short_over_buy_sell(next_bar_row))
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if btc_bar_row is not None:
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contents.append(f"## {symbol} 与BTC相同周期技术形态对比")
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contents.extend(get_long_short_over_buy_sell(btc_bar_row))
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mark_down_text = "\n\n".join(contents)
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return mark_down_text
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def get_long_short_over_buy_sell(
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row: pd.Series,
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):
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result = {}
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symbol = row["symbol"]
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bar = row["bar"]
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ma_long_short = str(row["ma_long_short"])
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macd_signal = str(row["macd_signal"])
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macd_divergence = str(row["macd_divergence"])
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kdj_signal = str(row["kdj_signal"])
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kdj_pattern = str(row["kdj_pattern"])
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rsi_signal = str(row["rsi_signal"])
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boll_signal = str(row["boll_signal"])
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boll_pattern = str(row["boll_pattern"])
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contents = []
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contents.append(f"### {symbol} {bar} 对比形态")
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if ma_long_short in ["多", "空"]:
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contents.append(f"均线形态: {ma_long_short}")
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else:
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contents.append(f"均线形态: 震荡")
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if macd_signal in ["金叉", "死叉"]:
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contents.append(f"MACD信号: {macd_signal}")
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if macd_divergence in ["顶背离", "底背离"]:
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contents.append(f"MACD背离: {macd_divergence}")
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if kdj_signal in ["金叉", "死叉"]:
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contents.append(f"KDJ信号: {kdj_signal}")
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if kdj_pattern in ["超超买", "超买", "超超卖", "超卖"]:
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contents.append(f"KDJ形态: {kdj_pattern}")
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if rsi_signal in ["超超买", "超买", "超超卖", "超卖"]:
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contents.append(f"RSI形态: {rsi_signal}")
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if boll_signal in ["突破下轨", "击穿上轨"]:
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contents.append(f"BOLL信号: {boll_signal}")
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if boll_pattern in ["超超买", "超买", "超超卖", "超卖"]:
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contents.append(f"BOLL形态: {boll_pattern}")
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return contents
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@ -27,7 +27,7 @@ class MarketMonitorMain:
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self.start_date = MONITOR_CONFIG.get("volume_monitor", {}).get(
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"initial_date", "2025-05-01 00:00:00"
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)
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self.latest_record_file_path = "./output/latest_record.json"
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self.latest_record_file_path = "./output/record/latest_record.json"
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self.latest_record = self.get_latest_record()
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self.output_folder = "./output/report/market_monitor/"
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os.makedirs(self.output_folder, exist_ok=True)
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@ -48,12 +48,17 @@ class MarketMonitorMain:
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"""
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获取最新记录
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"""
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if os.path.exists(self.latest_record_file_path):
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with open(self.latest_record_file_path, "r", encoding="utf-8") as f:
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return json.load(f)
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else:
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with open(self.latest_record_file_path, "w", encoding="utf-8") as f:
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json.dump({}, f, ensure_ascii=False, indent=4)
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os.makedirs(os.path.dirname(self.latest_record_file_path), exist_ok=True)
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try:
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if os.path.exists(self.latest_record_file_path):
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with open(self.latest_record_file_path, "r", encoding="utf-8") as f:
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return json.load(f)
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else:
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with open(self.latest_record_file_path, "w", encoding="utf-8") as f:
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json.dump({}, f, ensure_ascii=False, indent=4)
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return {}
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except Exception as e:
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logging.error(f"获取最后一次报表生成记录失败: {e}")
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return {}
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def monitor_realtime_market(
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@ -67,10 +72,14 @@ class MarketMonitorMain:
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监控最新市场数据
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考虑到速度，暂不与数据库交互，直接从api获取数据
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"""
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# 获得当前时间字符串
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now_datetime = datetime.now()
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now_datetime_str = now_datetime.strftime("%Y-%m-%d %H:%M:%S")
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end_time = transform_date_time_to_timestamp(now_datetime_str)
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real_time_data = self.market_data_main.market_data.get_realtime_kline_data(
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symbol=symbol,
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bar=bar,
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end_time=None,
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end_time=end_time,
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limit=50,
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)
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@ -79,28 +88,28 @@ class MarketMonitorMain:
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return
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latest_realtime_timestamp = real_time_data["timestamp"].iloc[-1]
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latest_realtime_timestamp = int(latest_realtime_timestamp)
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latest_record_timestamp = (
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self.latest_record.get(symbol, {}).get(bar, {}).get("timestamp", 0)
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self.latest_record.get(symbol, {}).get(bar, {}).get("timestamp", None)
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)
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latest_reatime_datetime = timestamp_to_datetime(latest_realtime_timestamp)
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latest_record_datetime = timestamp_to_datetime(latest_record_timestamp)
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if (
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latest_record_timestamp is not None
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and latest_realtime_timestamp <= latest_record_timestamp
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):
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if latest_record_timestamp is not None:
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latest_record_timestamp = int(latest_record_timestamp)
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latest_record_datetime = timestamp_to_datetime(latest_record_timestamp)
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if (
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latest_record_timestamp is not None
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and latest_realtime_timestamp <= latest_record_timestamp
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):
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logging.info(
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f"最新市场数据时间戳 {latest_reatime_datetime} 小于等于最新记录时间戳 {latest_record_datetime}， 不进行监控"
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)
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return
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logging.info(
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f"最新市场数据时间戳 {latest_reatime_datetime} 小于等于最新记录时间戳 {latest_record_datetime}， 不进行监控"
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)
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return
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f"最新市场数据时间 {latest_reatime_datetime}, 上一次记录时间 {latest_record_datetime}")
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else:
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self.latest_record[symbol] = {bar: {"timestamp": latest_realtime_timestamp}}
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with open(self.latest_record_file_path, "w", encoding="utf-8") as f:
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json.dump(self.latest_record, f, ensure_ascii=False, indent=4)
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logging.info(
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f"最新市场数据时间 {latest_reatime_datetime}, 上一次记录时间 {latest_record_datetime}"
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)
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logging.info(
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f"最新市场数据时间 {latest_reatime_datetime}, 上一次记录时间为空")
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real_time_data = self.market_data_main.add_new_columns(real_time_data)
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logging.info(f"开始计算技术指标: {symbol} {bar}")
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@ -111,7 +120,7 @@ class MarketMonitorMain:
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window_size=self.window_size,
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threshold=self.huge_volume_main.threshold,
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check_price=True,
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only_output_huge_volume=only_output_huge_volume,
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only_output_huge_volume=False,
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output_excel=False,
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)
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if real_time_data is None or len(real_time_data) == 0:
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@ -119,20 +128,42 @@ class MarketMonitorMain:
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f"计算大成交量失败: {symbol} {bar} 窗口大小: {self.window_size}"
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)
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return
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realtime_row = real_time_data.iloc[-1]
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report = create_metrics_report(real_time_data, only_output_rise)
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if only_output_huge_volume:
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if realtime_row["huge_volume"] == 1:
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logging.info(f"监控到巨量: {symbol} {bar} 窗口大小: {self.window_size}")
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else:
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logging.info(f"监控到非巨量: {symbol} {bar} 窗口大小: {self.window_size}，退出本次监控")
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return
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if only_output_rise:
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if realtime_row["pct_change"] > 0:
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logging.info(f"监控到上涨: {symbol} {bar} 窗口大小: {self.window_size}")
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else:
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logging.info(f"监控到下跌: {symbol} {bar} 窗口大小: {self.window_size}，退出本次监控")
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return
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next_bar_row = self.get_other_realtime_data(symbol, bar, end_time, next=True)
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if 'BTC-USDT' in symbol:
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btc_bar_row = None
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else:
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btc_bar_row = self.get_other_realtime_data('BTC-USDT', bar, end_time, next=False)
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report = create_metrics_report(realtime_row, next_bar_row, btc_bar_row, only_output_huge_volume, only_output_rise)
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text_length = len(report.encode("utf-8"))
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logging.info(f"发送报告到企业微信，字节数: {text_length}")
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self.wechat.send_markdown(report)
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self.latest_record[symbol][bar]["timestamp"] = latest_realtime_timestamp
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with open(self.latest_record_file_path, "w", encoding="utf-8") as f:
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json.dump(self.latest_record, f, ensure_ascii=False, indent=4)
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# remove punction in latest_reatime_datetime
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latest_reatime_datetime = re.sub(r"[\:\-\s]", "", latest_reatime_datetime)
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report_file_name = f"{symbol}_{bar}_{self.window_size}_{latest_reatime_datetime}.md"
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file_datetime = re.sub(r"[\:\-\s]", "", latest_reatime_datetime)
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report_file_name = (
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f"{symbol}_{bar}_{self.window_size}_{file_datetime}.md"
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)
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report_file_path = os.path.join(self.output_folder, report_file_name)
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with open(report_file_path, "w", encoding="utf-8") as f:
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f.write(report.replace(":", "_"))
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f.write(report)
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report_file_byte_size = os.path.getsize(report_file_path)
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report_data = {
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"symbol": symbol,
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@ -143,22 +174,68 @@ class MarketMonitorMain:
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"report": report,
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"report_file_path": report_file_path,
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"report_file_name": report_file_name,
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"report_file_byte_size": report_file_byte_size
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"report_file_byte_size": report_file_byte_size,
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}
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report_data = pd.DataFrame([report_data])
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logging.info(f"插入数据到数据库")
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self.db_market_monitor.insert_data_to_mysql(report_data)
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if self.latest_record.get(symbol, None) is None:
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self.latest_record[symbol] = {bar: {"timestamp": latest_realtime_timestamp}}
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else:
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self.latest_record[symbol][bar]["timestamp"] = latest_realtime_timestamp
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with open(self.latest_record_file_path, "w", encoding="utf-8") as f:
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json.dump(self.latest_record, f, ensure_ascii=False, indent=4)
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def get_other_realtime_data(self, symbol: str, bar: str, end_time: int, next: bool = True):
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"""
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获取下一个长周期实时数据
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"""
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if next:
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# 获得bar在self.market_data_main.bars中的索引
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bar_index = self.market_data_main.bars.index(bar)
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if bar_index == len(self.market_data_main.bars) - 1:
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logging.error(f"已经是最后一个bar: {bar}")
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return None
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# 获得下一个bar
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bar = self.market_data_main.bars[bar_index + 1]
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# 获得下一个bar的实时数据
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data = self.market_data_main.market_data.get_realtime_kline_data(
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symbol=symbol, bar=bar, end_time=end_time, limit=50
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)
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if data is None or len(data) == 0:
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logging.error(f"获取实时数据失败: {symbol}, {bar}")
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return None
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data = self.market_data_main.add_new_columns(data)
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logging.info(f"开始计算技术指标: {symbol} {bar}")
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data = self.market_data_main.calculate_metrics(data)
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row = data.iloc[-1]
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return row
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def batch_monitor_realtime_market(
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self,
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only_output_huge_volume: bool = True,
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only_output_rise: bool = False,
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only_output_rise: bool = True,
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):
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for symbol in self.market_data_main.symbols:
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for bar in self.market_data_main.bars:
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self.monitor_realtime_market(
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symbol,
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bar,
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only_output_huge_volume,
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only_output_rise,
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)
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logging.info(f"开始监控: {symbol} {bar} 窗口大小: {self.window_size} 行情数据")
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try:
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self.monitor_realtime_market(
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symbol,
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bar,
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only_output_huge_volume,
|
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only_output_rise,
|
||||
)
|
||||
except Exception as e:
|
||||
logging.error(f"监控失败: {symbol} {bar} 窗口大小: {self.window_size} 行情数据: {e}")
|
||||
continue
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
market_monitor_main = MarketMonitorMain()
|
||||
market_monitor_main.monitor_realtime_market(
|
||||
symbol="ETH-USDT",
|
||||
bar="5m",
|
||||
only_output_huge_volume=True,
|
||||
only_output_rise=False,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,20 @@
|
|||
from market_monitor_main import MarketMonitorMain
|
||||
import logging
|
||||
import time
|
||||
|
||||
logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s: %(message)s")
|
||||
|
||||
|
||||
def monitor_schedule():
|
||||
market_monitor_main = MarketMonitorMain()
|
||||
logging.info("开始监控")
|
||||
while True: # 每分钟监控一次
|
||||
market_monitor_main.batch_monitor_realtime_market(
|
||||
only_output_huge_volume=True,
|
||||
only_output_rise=False,
|
||||
)
|
||||
logging.info("本次循环监控结束，等待1分钟")
|
||||
time.sleep(60)
|
||||
|
||||
if __name__ == "__main__":
|
||||
monitor_schedule()
|
||||
|
|
@ -1,3 +1,5 @@
|
|||
select * from crypto_market_monitor;
|
||||
delete from crypto_market_monitor where timestamp=1754382900000;
|
||||
select date_time, open, high, low, close, k_shape from crypto_market_data
|
||||
WHERE symbol='XCH-USDT' and bar='5m' and date_time > '2025-08-04 15:00:00'
|
||||
order by timestamp ;
|
||||
|
|
@ -6,6 +8,10 @@ select * from crypto_market_data
|
|||
WHERE symbol='XCH-USDT' and bar='5m' and date_time > '2025-08-04 15:00:00'
|
||||
order by timestamp asc;
|
||||
|
||||
select * from crypto_huge_volume
|
||||
WHERE symbol='XCH-USDT' and bar='5m' #and date_time > '2025-08-04 15:00:00'
|
||||
order by timestamp asc;
|
||||
|
||||
|
||||
delete FROM crypto_market_data where symbol != 'XCH-USDT';
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue