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Problemas asincrónicos, volviéndose loco

Created 2023-03-15 10:43:20

1523

import pandas as pd
from binance.client import AsyncClient
from datetime import datetime, timedelta
import aiohttp
import json
def utc_to_local(utc_dt): # convertido a la hora de Beijing
local_tz = datetime.timezone{datetime.timedelta{hours=8)) # Diferencia horaria de las ocho regiones del este
local_dt = utc_dt.replace(tzinfo=datetime.timezone.utc).astimezone(local_tz)
return local_dt

Inicialización asíncrona en el cliente Binance

async def init_client():
client = await AsyncClient.create(api_key=api_key, api_secret=api_secret)


            
            
            
return client

Obtención asíncrona de datos de línea K

async def get_klines(client, symbol, start_time, end_time, interval):
klines = await client.futures_klines(symbol=symbol, interval=interval, startTime=start_time.timestamp()*1000, endTime=end_time.timestamp()*1000)
df = pd.DataFrame(klines, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume', 'close_time', 'quote_asset_volume', 'number_of_trades', 'taker_buy_base_asset_volume', 'taker_buy_quote_asset_volume', 'ignore'])
df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
df['close_time'] = pd.to_datetime(df['close_time'], unit='ms')
df.set_index('timestamp', inplace=True)
df.drop(columns=['close_time', 'ignore'], inplace=True)
df = df.astype('float')
return df

El cliente de Binance está fuera de sincronía

async def close_client(client):
await client.close_connection()

Ejecución de la función principal asíncrona

async def main():
client = await init_client()

Obtener todos los pares de USDT de los contratos de perpetuidad

exchange_info = await client.futures_exchange_info()
symbols = [symbol_info['symbol'] for symbol_info in exchange_info['symbols'] if symbol_info['contractType'] == 'PERPETUAL' and symbol_info['quoteAsset'] == 'USDT']

Crear un marco de datos vacío

df = pd.DataFrame(columns=['Symbol', 'Open', 'High', 'Low', 'Close', 'Change', 'Volume'])
df.set_index('Symbol', inplace=True)


            
            
            
# 将所有交易对添加到 DataFrame 中
for symbol in symbols:
    df.loc[symbol] = [None] * len(df.columns)
# 遍历所有交易对
for symbol in symbols:
    # 设置起止时间
    start_time = datetime.utcnow() - timedelta(minutes=16)#开始时间为16分钟前
    end_time = datetime.utcnow()
    try:
   # 获取M15k线
        current_klines = await get_klines(client, symbol, end_time - timedelta(minutes=15), end_time, '15m')
    except Exception as e:
        Log(f"An error occurred: {e}")
        current_klines = []
    # 将数据存入 DataFrame
   # 更新对应的行
    df.loc[symbol, 'Open'] = current_klines['open'].iloc[-1]
    df.loc[symbol, 'High'] = current_klines['high'].iloc[-1]
    df.loc[symbol, 'Low'] = current_klines['low'].iloc[-1]
    df.loc[symbol, 'Close'] = current_klines['close'].iloc[-1]
    df.loc[symbol, 'Change'] = current_change
    df.loc[symbol, 'Volume'] = current_klines['volume'].iloc[-1]

# 关闭客户端
Log(df)
await close_client(client)