update

cryptoai/agents/crypto_agent.py

@@ -18,7 +18,7 @@ from models.data_processor import DataProcessor
 from utils.config_loader import ConfigLoader
 from utils.dingtalk_bot import DingTalkBot
 from utils.discord_bot import DiscordBot
-from models.analysis_result import AnalysisResultManager
+from cryptoai.models.analysis_result import AnalysisResultManager
 from utils.db_manager import SessionLocal
 
 class CryptoAgent:

cryptoai/tasks/token_selector.py

@@ -0,0 +1,172 @@
+from binance.client import Client
+import pandas as pd
+import numpy as np
+from datetime import datetime
+import requests
+from rich.console import Console
+from rich.table import Table
+from rich.panel import Panel
+from rich.text import Text
+from rich import box
+
+
+# 初始化 Binance API
+api_key = 'HCpeel8g6fsTK2630b7BvGBcS09Z3qfXkLVcAY2JkpaiMm1J6DWRvoQZBQlElDJg'
+api_secret = 'TySs6onlHOTrGzV8fMdDxLKTWWYnQ4rCHVAmjrcHby17acKflmo7xVTWVsbqtxe7'
+client = Client(api_key, api_secret)
+
+# 获取 24h 涨幅和成交量
+url = "https://api.binance.com/api/v3/ticker/24hr"
+response = requests.get(url)
+tickers = response.json()
+
+df = pd.DataFrame(tickers)
+df = df[df['symbol'].str.endswith('USDT') & (~df['symbol'].str.contains('UP|DOWN|BULL|BEAR'))]
+df['priceChangePercent'] = pd.to_numeric(df['priceChangePercent'], errors='coerce')
+df['quoteVolume'] = pd.to_numeric(df['quoteVolume'], errors='coerce')
+
+# 初筛条件，成交量大于3000万，24h涨幅小于20%
+filtered = df[(df['quoteVolume'] > 3e7) & (df['priceChangePercent'] < 20)]
+
+top_symbols = filtered.sort_values(by='priceChangePercent', ascending=False).head(50)['symbol'].tolist()
+
+# 技术指标分析函数
+def analyze_symbol(symbol, interval='1h', limit=1000):
+    try:
+        klines = client.get_klines(symbol=symbol, interval=interval, limit=limit)
+        df = pd.DataFrame(klines, columns=['time', 'open', 'high', 'low', 'close', 'volume',
+                                           'close_time', 'quote_volume', 'trades',
+                                           'taker_buy_base', 'taker_buy_quote', 'ignore'])
+        df['close'] = pd.to_numeric(df['close'])
+        df['volume'] = pd.to_numeric(df['volume'])
+
+        # 计算指标
+        df['ema20'] = df['close'].ewm(span=20).mean()
+        df['ema50'] = df['close'].ewm(span=50).mean()
+        df['ema200'] = df['close'].ewm(span=200).mean()
+        df['vol_ma20'] = df['volume'].rolling(20).mean()
+
+        # 当前状态
+        latest = df.iloc[-1]
+        
+        # 成交量突增
+        vol_spike = latest['volume'] > 1.5 * latest['vol_ma20']
+        
+        # 上涨趋势
+        bull_trend = latest['ema20'] > latest['ema50'] > latest['ema200']
+        
+        # 价格突破
+        price_break = latest['close'] > df['close'].rolling(20).max().shift(1).iloc[-1]
+
+        # 是否是箱体运动
+        # 计算200根K线内的最高价和最低价
+        high_200 = df['high'].rolling(200).max().iloc[-1]
+        low_200 = df['low'].rolling(200).min().iloc[-1]
+        # 计算当前价格与200根K线最高价和最低价的距离
+        price_distance_high = (latest['close'] - high_200) / high_200
+        price_distance_low = (latest['close'] - low_200) / low_200
+        
+        # 是否是箱体运动
+        box_movement = price_distance_high < 0.05 and price_distance_low < 0.05
+
+        score = int(vol_spike) + int(bull_trend) + int(price_break) + int(box_movement)
+
+        return {
+            '币种': symbol,
+            '上涨趋势': '是' if bull_trend else '否',
+            '价格突破': '是' if price_break else '否',
+            '箱体运动': '是' if box_movement else '否',
+            '得分': score
+        }
+
+    except Exception as e:
+        return {
+            '币种': symbol,
+            '上涨趋势': '错误',
+            '价格突破': '错误',
+            '箱体运动': '错误',
+            '得分': 0
+        }
+    
+if __name__ == "__main__":
+    # 执行分析
+    results = [analyze_symbol(sym) for sym in top_symbols]
+    df_result = pd.DataFrame(results)
+
+    # 只取上涨趋势为是
+    df_result = df_result[df_result['上涨趋势'] == '是']
+
+    # 按照得分排序
+    df_result = df_result.sort_values(by='得分', ascending=False)
+
+    # 取前10个
+    df_final = df_result.head(10)
+
+    # 创建 Rich 控制台
+    console = Console()
+
+    # 创建标题面板
+    title_panel = Panel(
+        Text("🔥 今日潜在强势币种分析 🔥", style="bold red", justify="center"),
+        style="bright_blue",
+        box=box.DOUBLE
+    )
+
+    # 创建时间信息
+    time_text = Text(f"📅 分析时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", style="dim")
+
+    # 创建漂亮的表格
+    table = Table(
+        title="💰 币种分析结果",
+        show_header=True,
+        header_style="bold magenta",
+        box=box.ROUNDED,
+        title_style="bold cyan"
+    )
+
+    # 添加列
+    table.add_column("币种", style="bold yellow", width=12)
+    table.add_column("上涨趋势", justify="center", width=10)
+    table.add_column("价格突破", justify="center", width=10)
+    table.add_column("箱体运动", justify="center", width=10)
+    table.add_column("得分", justify="center", style="bold green", width=8)
+
+    # 添加数据行
+    for _, row in df_final.iterrows():
+        # 根据得分设置颜色
+        if row['得分'] >= 3:
+            score_style = "bold green"
+        elif row['得分'] >= 2:
+            score_style = "bold yellow"
+        else:
+            score_style = "bold red"
+        
+        # 设置趋势指标的颜色
+        trend_color = "green" if row['上涨趋势'] == '是' else "red"
+        break_color = "green" if row['价格突破'] == '是' else "red"
+        box_color = "green" if row['箱体运动'] == '是' else "red"
+        
+        table.add_row(
+            f"[bold]{row['币种']}[/bold]",
+            f"[{trend_color}]{row['上涨趋势']}[/{trend_color}]",
+            f"[{break_color}]{row['价格突破']}[/{break_color}]",
+            f"[{box_color}]{row['箱体运动']}[/{box_color}]",
+            f"[{score_style}]{row['得分']}[/{score_style}]"
+        )
+
+    # 输出结果
+    console.print("\n")
+    console.print(title_panel)
+    console.print(time_text, justify="center")
+    console.print("\n")
+    console.print(table)
+
+    # 添加说明信息
+    info_panel = Panel(
+        Text("📊 分析说明\n• 上涨趋势：EMA20 > EMA50 > EMA200\n• 价格突破：突破20日最高价\n• 箱体运动：价格在200日高低点范围内波动\n• 得分越高代表技术面越强势", 
+            style="dim"), 
+        title="💡 指标说明", 
+        border_style="blue"
+    )
+    console.print("\n")
+    console.print(info_panel)

docker-compose.yml

@@ -4,7 +4,7 @@ services:
   cryptoai-task:
     build: .
     container_name: cryptoai-task
-    image: cryptoai:0.0.18
+    image: cryptoai:0.0.19
     restart: always
     volumes:
       - ./cryptoai/data:/app/cryptoai/data

requirements.txt

@@ -15,6 +15,7 @@ python-multipart==0.0.9
 email-validator==2.1.0
 tencentcloud-sdk-python==3.0.1030
 adata
+tabulate
 # # 日志相关
 # logging==0.4.9.6
 # # 数据处理相关

test.py

@@ -1,20 +1,5 @@
-from cryptoai.api.adata_api import AStockAPI
-from cryptoai.api.binance_api import get_binance_api
-import json
-from time import sleep
-from cryptoai.models.token import TokenManager
-from cryptoai.utils.db_manager import get_db_context
-from cryptoai.tasks.user import task_run
 from cryptoai.agents.crypto_agent import CryptoAgent
 
 if __name__ == "__main__":
-    CryptoAgent().start_agent()
-
-    # data = get_binance_api().get_historical_klines(
-    #     symbol="BTCUSDT",
-    #     interval="1h",
-    #     start_str="2024-01-01",
-    #     end_str="2024-01-02",
-    #     limit=100
-    # )   
-    # print(data) 
+    agent = CryptoAgent()
+    agent.start_agent()