import pandas as pd from binance.client import AsyncClient from datetime import datetime, timedelta imported aiohttp import json def utc_to_local ((utc_dt):# Converted to Beijing time local_tz = datetime.timezone ((datetime.timedelta ((hours=8)) # East 8th district time difference Local_dt = utc_dt.replace ((tzinfo=datetime.timezone.utc).astimezone ((local_tz)) is a local_tz that is used to replace the local_tz. return local_dt

Asynchronous initialization of the Binance client

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

return client

Asynchronous acquisition of K-line data

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

Asynchronous shutdown of the Binance client

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

Asynchronous execution of the main function

Async def main (: client = await init_client (()) # Acquire all pairs of USDT perpetual contracts Exchange_info = await client.Futures_exchange_info is the name of the client. symbols = [symbol_info [symbol] for symbol_info in exchange_info [symbols] if symbol_info [contractType] == PERPETUAL and symbol_info [quoteAsset] == USDT] # Create an empty dataframe df = pd.DataFrame ((columns=[Symbol array, Open array, High array, Low array, Close array, Change array, Volume array]) df.set_index ((Symbol array, in place=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)

Running asynchronous

if name == ‘main’: import asyncio asyncio.run(main())

The aim is to obtain data on the fall of all contract currencies against the M15.

Log ((df) after one error; i.e. after one update of all symbols, data such as price, etc. error: Trackback (most recent call last): File , line 1246, ininit_ctxFile , line 147, in TypeError: Object of type coroutine is not JSON serializable sys:1: RuntimeWarning: coroutine ChatGpt also failed to fix it, so we asked for help.