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update for huge_volume_main.py

This commit is contained in:
blade 2025-08-04 22:36:25 +08:00
parent e0bf2bbbfb
commit cd0b64c5c9
5 changed files with 62 additions and 36 deletions
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3
core/db/db_huge_volume_data.py
View File

@ -24,9 +24,6 @@ class DBHugeVolumeData:
"high",
"low",
"close",
"pre_close",
"close_change",
"pct_chg",
"volume",
"volCcy",
"volCCyQuote",

74
huge_volume_main.py
View File

@ -138,7 +138,12 @@ class HugeVolumeMain:
symbol, bar, window_size
)
if latest_huge_volume_data is None or len(latest_huge_volume_data) == 0:
self.detect_volume_spike(symbol, bar, only_output_huge_volume=False)
self.detect_volume_spike(
symbol=symbol,
bar=bar,
window_size=window_size,
only_output_huge_volume=False,
)
return
else:
earliest_date_time = latest_huge_volume_data["date_time"]
@ -296,8 +301,7 @@ class HugeVolumeMain:
end_date_time = timestamp_to_datetime(end_timestamp)
logging.info(f"开始获取巨量交易数据: {start} 到 {end}")
huge_volume_data = self.db_huge_volume_data.query_huge_volume_records(
start=start_timestamp,
end=end_timestamp
start=start_timestamp, end=end_timestamp
)
if huge_volume_data is None or len(huge_volume_data) == 0:
logging.warning(f"获取巨量交易数据为空: {start} 到 {end}")
@ -311,13 +315,15 @@ class HugeVolumeMain:
huge_volume_data = huge_volume_data[huge_volume_data["huge_volume"] == 1]
# 过滤huge_volume_data，要求(price_80_high == 1 or price_90_high == 1 or price_20_low == 1 or price_10_low == 1)
huge_volume_data = huge_volume_data[
(huge_volume_data["price_90_high"] == 1) |
(huge_volume_data["price_10_low"] == 1)
(huge_volume_data["price_90_high"] == 1)
| (huge_volume_data["price_10_low"] == 1)
]
# 过滤huge_volume_data，要求volume_ratio > 10
huge_volume_data = huge_volume_data[huge_volume_data["volume_ratio"] > 10]
# 根据symbol, bar, window_size, timestamp排序
huge_volume_data = huge_volume_data.sort_values(by=["symbol", "bar", "window_size", "timestamp"], ascending=True)
huge_volume_data = huge_volume_data.sort_values(
by=["symbol", "bar", "window_size", "timestamp"], ascending=True
)
huge_volume_data = huge_volume_data.reset_index(drop=True)
logging.info(f"获取巨量交易数据: {len(huge_volume_data)}条")
contents = []
@ -330,39 +336,52 @@ class HugeVolumeMain:
contents.append(f"# 放量交易数据: {start_date_time} 到 {end_date_time}")
contents.append(f"## 币种: {symbol}")
symbol_data = huge_volume_data[huge_volume_data["symbol"] == symbol]
symbol_data = symbol_data.sort_values(by=["bar", "window_size", "timestamp"], ascending=True)
symbol_data = symbol_data.sort_values(
by=["bar", "window_size", "timestamp"], ascending=True
)
symbol_data = symbol_data.reset_index(drop=True)
for index, row in symbol_data.iterrows():
if row['huge_volume'] == 1 and (row['price_80_high'] == 1 or row['price_90_high'] == 1 or row['price_20_low'] == 1 or row['price_10_low'] == 1):
if row['price_90_high'] == 1:
if row["huge_volume"] == 1 and (
row["price_80_high"] == 1
or row["price_90_high"] == 1
or row["price_20_low"] == 1
or row["price_10_low"] == 1
):
if row["price_90_high"] == 1:
price_position_text = "90%分位数高点"
elif row['price_80_high'] == 1:
elif row["price_80_high"] == 1:
price_position_text = "80%分位数高点"
else:
price_position_text = ""
if price_position_text == "":
if row['price_10_low'] == 1:
if row["price_10_low"] == 1:
price_position_text = "10%分位数低点"
elif row['price_20_low'] == 1:
elif row["price_20_low"] == 1:
price_position_text = "20%分位数低点"
else:
price_position_text = ""
open_price = str(round(row['open'], 6))
high = str(round(row['high'], 6))
low = str(round(row['low'], 6))
close = str(round(row['close'], 6))
volume = str(round(row['volume'], 6))
volCCyQuote = str(round(row['volCCyQuote'], 6))
volume_ratio = str(round(row['volume_ratio'], 6))
contents.append(f"交易周期: {row['bar']}, 滑动窗口: {row['window_size']} , 发生时间: {row['date_time']}")
contents.append(f"开盘价: {open_price}, 最高价: {high}, 最低价: {low}, 收盘价: {close}")
contents.append(f"成交量: {volume}, 成交量USDT: {volCCyQuote}, 交易量比率: {volume_ratio}")
open_price = str(round(row["open"], 6))
high = str(round(row["high"], 6))
low = str(round(row["low"], 6))
close = str(round(row["close"], 6))
volume = str(round(row["volume"], 6))
volCCyQuote = str(round(row["volCCyQuote"], 6))
volume_ratio = str(round(row["volume_ratio"], 6))
contents.append(
f"交易周期: {row['bar']}, 滑动窗口: {row['window_size']} , 发生时间: {row['date_time']}"
)
contents.append(
f"开盘价: {open_price}, 最高价: {high}, 最低价: {low}, 收盘价: {close}"
)
contents.append(
f"成交量: {volume}, 成交量USDT: {volCCyQuote}, 交易量比率: {volume_ratio}"
)
contents.append(f"价格分位: {price_position_text}")
contents.append(f"--------------------------------")
text = "\n\n".join(contents)
# 获得text的字节数
text_length = len(text.encode('utf-8'))
text_length = len(text.encode("utf-8"))
logging.info(f"发送巨量交易数据到微信，字节数: {text_length}")
# with open(os.path.join(self.output_folder, "huge_volume_data.md"), "w", encoding="utf-8") as f:
@ -447,10 +466,13 @@ def batch_initial_detect_volume_spike(threshold: float = 2.0):
):
window_sizes = [50, 80, 100, 120]
huge_volume_main = HugeVolumeMain(threshold)
start_date = MONITOR_CONFIG.get("volume_monitor", {}).get(
"initial_date", "2025-05-01 00:00:00"
)
for window_size in window_sizes:
huge_volume_main.batch_initial_detect_volume_spike(
window_size=window_size,
start="2025-05-01 00:00:00",
start=start_date,
)
@ -479,8 +501,8 @@ def test_send_huge_volume_data_to_wechat():
if __name__ == "__main__":
test_send_huge_volume_data_to_wechat()
# batch_initial_detect_volume_spike(threshold=2.0)
# test_send_huge_volume_data_to_wechat()
batch_initial_detect_volume_spike(threshold=2.0)
# batch_update_volume_spike(threshold=2.0)
# huge_volume_main = HugeVolumeMain(threshold=2.0)
# huge_volume_main.batch_next_periods_rise_or_fall(output_excel=True)

7
market_data_main.py
View File

@ -224,14 +224,16 @@ class MarketDataMain:
before_data = self.db_market_data.query_data_before_timestamp(
symbol, bar, min_start_time_ts, 30
)
latest_before_timestamp = None
if before_data is not None and len(before_data) > 0:
earliest_timestamp = before_data[-1]["timestamp"]
latest_before_timestamp = before_data[0]["timestamp"]
else:
earliest_timestamp = min_start_time_ts
handle_data = self.db_market_data.query_market_data_by_symbol_bar(
symbol=symbol, bar=bar, start=earliest_timestamp, end=None
)
if handle_data is not None and len(handle_data) > 0:
if handle_data is not None and len(handle_data) > len(before_data):
if isinstance(handle_data, list):
handle_data = pd.DataFrame(handle_data)
elif isinstance(handle_data, dict):
@ -243,6 +245,9 @@ class MarketDataMain:
return None
handle_data = self.calculate_metrics(handle_data)
if latest_before_timestamp is not None:
handle_data = handle_data[handle_data["timestamp"] > latest_before_timestamp]
handle_data.reset_index(drop=True, inplace=True)
logging.info(f"开始保存技术指标数据: {symbol} {bar}")
self.db_market_data.insert_data_to_mysql(handle_data)
return data

5
sql/query/sql_playground.sql
View File

@ -2,6 +2,11 @@ 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 ;
select * from crypto_market_data
WHERE symbol='XCH-USDT' and bar='5m' and date_time > '2025-08-04 15:00:00'
order by timestamp desc;
delete FROM crypto_market_data where symbol != 'XCH-USDT';
select * from crypto_trade_data

3
sql/table/crypto_huge_volume.sql
View File

@ -9,9 +9,6 @@ CREATE TABLE IF NOT EXISTS crypto_huge_volume (
high DECIMAL(20,10) NOT NULL COMMENT '最高价',
low DECIMAL(20,10) NOT NULL COMMENT '最低价',
close DECIMAL(20,10) NOT NULL COMMENT '收盘价',
pre_close DECIMAL(20,10) NOT NULL COMMENT '前收盘价',
close_change DECIMAL(20,10) NOT NULL COMMENT '涨跌额',
pct_chg DECIMAL(20,10) NOT NULL COMMENT '涨跌幅',
volume DECIMAL(30,10) NOT NULL COMMENT '交易量',
volCcy DECIMAL(30,10) NOT NULL COMMENT '交易量(基础货币)',
volCCyQuote DECIMAL(30,10) NOT NULL COMMENT '交易量(计价货币)',