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app/routes/stocks.py Normal file
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from flask import Blueprint, request, jsonify
from app import db
from clickhouse_driver import Client
import pandas as pd
from datetime import datetime, timedelta
import pytz
bp = Blueprint('stocks', __name__, url_prefix='/api/stock')
def get_clickhouse_client():
"""获取ClickHouse客户端"""
return Client('localhost', port=9000, user='default', password='', database='default')
@bp.route('/quotes', methods=['GET', 'POST'])
def get_stock_quotes():
"""获取股票实时报价"""
try:
if request.method == 'GET':
# GET 请求从 URL 参数获取数据
codes = request.args.get('codes', '').split(',')
event_time_str = request.args.get('event_time')
else:
# POST 请求从 JSON 获取数据
codes = request.json.get('codes', [])
event_time_str = request.json.get('event_time')
if not codes:
return jsonify({'success': False, 'error': '请提供股票代码'}), 400
# 过滤空字符串
codes = [code.strip() for code in codes if code.strip()]
if not codes:
return jsonify({'success': False, 'error': '请提供有效的股票代码'}), 400
# 解析事件时间
event_time = None
if event_time_str:
try:
event_time = datetime.fromisoformat(event_time_str.replace('Z', '+00:00'))
except ValueError:
return jsonify({'success': False, 'error': '事件时间格式错误'}), 400
# 获取当前时间
now = datetime.now(pytz.timezone('Asia/Shanghai'))
# 如果提供了事件时间,使用事件时间;否则使用当前时间
target_time = event_time if event_time else now
# 获取交易日和交易时间
def get_trading_day_and_times(event_datetime):
"""获取交易日和交易时间列表"""
# 这里简化处理,实际应该查询交易日历
trading_day = event_datetime.strftime('%Y-%m-%d')
# 生成交易时间列表 (9:30-11:30, 13:00-15:00)
morning_times = [f"{trading_day} {hour:02d}:{minute:02d}"
for hour in range(9, 12)
for minute in range(0, 60, 1)
if not (hour == 9 and minute < 30) and not (hour == 11 and minute > 30)]
afternoon_times = [f"{trading_day} {hour:02d}:{minute:02d}"
for hour in range(13, 16)
for minute in range(0, 60, 1)]
return trading_day, morning_times + afternoon_times
trading_day, trading_times = get_trading_day_and_times(target_time)
# 模拟股票数据
results = {}
for code in codes:
# 这里应该从ClickHouse或其他数据源获取真实数据
# 现在使用模拟数据
import random
base_price = 10.0 + random.random() * 20.0
change = (random.random() - 0.5) * 2.0
results[code] = {
'price': round(base_price, 2),
'change': round(change, 2),
'name': f'股票{code}'
}
return jsonify({
'success': True,
'data': results
})
except Exception as e:
print(f"Error getting stock quotes: {e}")
return jsonify({'success': False, 'error': str(e)}), 500
@bp.route('/<stock_code>/kline')
def get_stock_kline(stock_code):
"""获取股票K线数据"""
try:
chart_type = request.args.get('type', 'daily')
event_time_str = request.args.get('event_time')
if not event_time_str:
return jsonify({'success': False, 'error': '请提供事件时间'}), 400
try:
event_datetime = datetime.fromisoformat(event_time_str.replace('Z', '+00:00'))
except ValueError:
return jsonify({'success': False, 'error': '事件时间格式错误'}), 400
# 获取股票名称(这里简化处理)
stock_name = f'股票{stock_code}'
if chart_type == 'daily':
return get_daily_kline(stock_code, event_datetime, stock_name)
elif chart_type == 'minute':
return get_minute_kline(stock_code, event_datetime, stock_name)
elif chart_type == 'timeline':
return get_timeline_data(stock_code, event_datetime, stock_name)
else:
return jsonify({'error': f'Unsupported chart type: {chart_type}'}), 400
except Exception as e:
print(f"Error getting stock kline: {e}")
return jsonify({'success': False, 'error': str(e)}), 500
def get_daily_kline(stock_code, event_datetime, stock_name):
"""获取日K线数据"""
try:
# 模拟日K线数据
data = []
base_price = 10.0
for i in range(30):
date = (event_datetime - timedelta(days=30-i)).strftime('%Y-%m-%d')
open_price = base_price + (i * 0.1) + (i % 3 - 1) * 0.5
close_price = open_price + (i % 5 - 2) * 0.3
high_price = max(open_price, close_price) + 0.2
low_price = min(open_price, close_price) - 0.2
volume = 1000000 + i * 50000
data.append({
'date': date,
'open': round(open_price, 2),
'close': round(close_price, 2),
'high': round(high_price, 2),
'low': round(low_price, 2),
'volume': volume
})
return jsonify({
'code': stock_code,
'name': stock_name,
'trade_date': event_datetime.strftime('%Y-%m-%d'),
'data': data
})
except Exception as e:
print(f"Error getting daily kline: {e}")
return jsonify({'success': False, 'error': str(e)}), 500
def get_minute_kline(stock_code, event_datetime, stock_name):
"""获取分钟K线数据"""
try:
# 模拟分钟K线数据
data = []
base_price = 10.0
trading_times = []
# 生成交易时间
for hour in range(9, 16):
if hour == 12:
continue
for minute in range(0, 60):
if (hour == 9 and minute < 30) or (hour == 11 and minute > 30):
continue
trading_times.append(f"{hour:02d}:{minute:02d}")
for i, time in enumerate(trading_times):
open_price = base_price + (i * 0.01) + (i % 10 - 5) * 0.02
close_price = open_price + (i % 7 - 3) * 0.01
high_price = max(open_price, close_price) + 0.01
low_price = min(open_price, close_price) - 0.01
volume = 50000 + i * 1000
data.append({
'time': time,
'open': round(open_price, 2),
'close': round(close_price, 2),
'high': round(high_price, 2),
'low': round(low_price, 2),
'volume': volume
})
return jsonify({
'code': stock_code,
'name': stock_name,
'trade_date': event_datetime.strftime('%Y-%m-%d'),
'data': data
})
except Exception as e:
print(f"Error getting minute kline: {e}")
return jsonify({'success': False, 'error': str(e)}), 500
def get_timeline_data(stock_code, event_datetime, stock_name):
"""获取分时图数据"""
try:
# 模拟分时图数据
data = []
base_price = 10.0
trading_times = []
# 生成交易时间
for hour in range(9, 16):
if hour == 12:
continue
for minute in range(0, 60):
if (hour == 9 and minute < 30) or (hour == 11 and minute > 30):
continue
trading_times.append(f"{hour:02d}:{minute:02d}")
for i, time in enumerate(trading_times):
price = base_price + (i * 0.01) + (i % 10 - 5) * 0.02
avg_price = price + (i % 5 - 2) * 0.01
volume = 50000 + i * 1000
data.append({
'time': time,
'price': round(price, 2),
'avg_price': round(avg_price, 2),
'volume': volume
})
return jsonify({
'code': stock_code,
'name': stock_name,
'trade_date': event_datetime.strftime('%Y-%m-%d'),
'data': data
})
except Exception as e:
print(f"Error getting timeline data: {e}")
return jsonify({'success': False, 'error': str(e)}), 500