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Polkadot Web3 wallet Talisman closes $2.35M seed funding round

Talisman plans to release an early version of its Polkadot wallet extension before the end of November.

"CANCEL read_loop, Task exception was never retrieved"{‘e’: ‘error’, ‘m’: ‘Queue overflow. Message not filled’}

I’ve finally got my code working which does the following: first it gets the historical data from currently 297 symbols (only the last 20 data intervals). After it got the data it starts to fetch real time data for all these symbols. The code works good for a few seconds but then I get the::Listen

I’ve finally got my code working which does the following: first it gets the historical data from currently 297 symbols (only the last 20 data intervals). After it got the data it starts to fetch real time data for all these symbols. The code works good for a few seconds but then I get the error: "CANCEL read_loop, Task exception was never retrieved"{‘e’: ‘error’, ‘m’: ‘Queue overflow. Message not filled’}. I’ve done some searching on the web but there’s not much information about it. Does anyone know how to fix this error?

Code to get the live data:

class GetNewData:

    @staticmethod
    def refactor_old_result():
        historical_list_refactored = []
        for i in range(len(results)):
            single_key_data = results[i]
            single_key_data['high'] = list(single_key_data['high'].values())
            single_key_data['low'] = list(single_key_data['low'].values())
            single_key_data['close'] = list(single_key_data['close'].values())
            single_key_data['interval'] = list(single_key_data['interval'].values())
            single_key_data['symbol'] = list(single_key_data['symbol'].values())
            single_key_data['time'] = list(single_key_data['time'].values())
            single_key_data['volume'] = list(single_key_data['volume'].values())
            historical_list_refactored.append(single_key_data)
        return historical_list_refactored

    @staticmethod
    def start_websocket():
        twm = ThreadedWebsocketManager(api_key=api_key, api_secret=api_secret)
        twm.start()
        streams = stream_list
        twm.start_multiplex_socket(callback=GetNewData.add_new_data_values, streams=streams)
        twm.join()

    @staticmethod
    def add_new_data_values(msg):
        candle = msg['data']['k']
        symbol = candle['s']
        interval = candle['i']
        close_price = candle['c']
        highest_price = candle['h']
        lowest_price = candle['l']
        status = candle['x']
        time = candle['t']
        volume = candle['v']
        daytime = datetime.fromtimestamp(time / 1e3)
        GetNewData.refactor_msg(old_data_refactored, symbol, interval, close_price, highest_price, lowest_price, status, daytime, volume)


    @staticmethod
    def refactor_msg(historical_data_list, symbol, interval, close_price, highest_price, lowest_price, status, daytime, volume):
        if status:
            for dic in historical_data_list:
                if interval == dic['interval'][0] and symbol == dic['symbol'][0]:
                    # print(interval, symbol, close_price)
                    dic['high'].append(float(highest_price))
                    dic['low'].append(float(lowest_price))
                    dic['close'].append(float(close_price))
                    dic['interval'].append(interval)
                    dic['symbol'].append(symbol)
                    dic['time'].append(daytime)
                    dic['volume'].append(volume)
                    print(dic)

Entire code:

import asyncio
import pandas as pd
from binance import AsyncClient, Client, ThreadedWebsocketManager
from datetime import datetime
import time
pd.options.mode.chained_assignment = None  # default='warn'

pd.set_option('display.max_columns', None, 'display.max_rows', None)
api_key = '5Z5VtpcArDgm525AC6sUoy8TJer4tlel4Twt1ENf7OIzeLB2qx6oaLICHL9jVKoa'
api_secret = 'e641miivoiguEU3gOKjuYEvVKdFNazehtovZtJKdQXb2NVxwTeo1AQ2TBDArocWU'
client = Client(api_key, api_secret)

results = []
symbols = []
with open('DayTradeSymbols.txt') as f:
    for line in f:
        symbol = line.strip('n') + 'BTC'
        symbols.append(symbol)

stream_list = []
intervals = ['1m','3m']
for symbol in symbols:
    for interval in intervals:
        x = lambda symbol: symbol + '@kline_' + interval
        stream_list.append(x(symbol.lower()))
print(stream_list)

class GetHistoricalData:
    def __init__(self, num_workers: int = 10):
        self.num_workers: int = num_workers
        self.task_q: asyncio.Queue = asyncio.Queue(maxsize=10)

    async def get_symbols(self):
        # symbols = ['BTCUSDT', 'ETHUSDT', 'ADAUSDT','BNBUSDT', 'SOLUSDT', 'DOTUSDT','SHIBUSDT', 'DOGEUSDT', 'LTCUSDT', 'XLMUSDT', 'XMRUSDT', 'AVAXUSDT', 'LINKUSDT']
        for i in symbols:
            await self.task_q.put(i)

        for i in range(self.num_workers):
            await self.task_q.put(None)

    async def get_historical_klines(self, client: AsyncClient):
        while True:
            symbol = await self.task_q.get()
            if symbol is None:
                break
            data = await (client.get_historical_klines(symbol, '1m', '11/23/2021'))
            data_df = pd.DataFrame(data)
            data_df.columns = ['time', '1', 'high', 'low', 'close', 'volume', '6', '7', '8', '9', '10', '11']
            data_df.drop(columns=['1', '6', '7', '8', '9', '10', '11'], axis=1, inplace=True)
            data2_df = data_df.head(-1)
            new_df = data2_df.tail(22)
            new_df['interval'] = '1m'
            new_df['symbol'] = symbol
            new_df['time'] = pd.to_datetime(new_df['time'] / 1000, unit='s')
            results.append(new_df.to_dict())

    async def amain(self) -> None:
        client = await AsyncClient.create()
        await asyncio.gather(
            self.get_symbols(),
            *[self.get_historical_klines(client) for _ in range(self.num_workers)])
        await client.close_connection()


class GetNewData:

    @staticmethod
    def refactor_old_result():
        historical_list_refactored = []
        for i in range(len(results)):
            single_key_data = results[i]
            single_key_data['high'] = list(single_key_data['high'].values())
            single_key_data['low'] = list(single_key_data['low'].values())
            single_key_data['close'] = list(single_key_data['close'].values())
            single_key_data['interval'] = list(single_key_data['interval'].values())
            single_key_data['symbol'] = list(single_key_data['symbol'].values())
            single_key_data['time'] = list(single_key_data['time'].values())
            single_key_data['volume'] = list(single_key_data['volume'].values())
            historical_list_refactored.append(single_key_data)
        return historical_list_refactored

    @staticmethod
    def start_websocket():
        twm = ThreadedWebsocketManager(api_key=api_key, api_secret=api_secret)
        twm.start()
        streams = stream_list
        twm.start_multiplex_socket(callback=GetNewData.add_new_data_values, streams=streams)
        twm.join()

    @staticmethod
    def add_new_data_values(msg):
        candle = msg['data']['k']
        symbol = candle['s']
        interval = candle['i']
        close_price = candle['c']
        highest_price = candle['h']
        lowest_price = candle['l']
        status = candle['x']
        time = candle['t']
        volume = candle['v']
        daytime = datetime.fromtimestamp(time / 1e3)
        GetNewData.refactor_msg(old_data_refactored, symbol, interval, close_price, highest_price, lowest_price, status, daytime, volume)


    @staticmethod
    def refactor_msg(historical_data_list, symbol, interval, close_price, highest_price, lowest_price, status, daytime, volume):
        if status:
            for dic in historical_data_list:
                if interval == dic['interval'][0] and symbol == dic['symbol'][0]:
                    # print(interval, symbol, close_price)
                    dic['high'].append(float(highest_price))
                    dic['low'].append(float(lowest_price))
                    dic['close'].append(float(close_price))
                    dic['interval'].append(interval)
                    dic['symbol'].append(symbol)
                    dic['time'].append(daytime)
                    dic['volume'].append(volume)
                    print(dic)


if __name__ == "__main__":
    start_time = time.time()
    loop = asyncio.get_event_loop()
    loop.run_until_complete(GetHistoricalData().amain())
    print(f'time = {time.time() - start_time}')
    old_data_refactored = GetNewData.refactor_old_result()
    GetNewData.start_websocket()

Polkadot Web3 wallet Talisman closes $2.35M seed funding round

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