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