In high-frequency trading and quantitative research, accessing reliable historical market data can cost thousands of dollars monthly through official exchange feeds. The Tardis Machine local replay server changes this equation entirely. This guide walks you through building a self-hosted historical market data infrastructure using HolySheep AI relay services, Python, and Node.js—achieving sub-50ms latency at a fraction of traditional costs.

Tardis Machine Replay Services Comparison

Feature HolySheep AI Official Exchange APIs Generic Relay Services
Pricing Model ¥1 = $1 USD flat rate ¥7.3 = $1 USD (85%+ premium) Variable, often tiered
Latency <50ms p99 20-100ms depending on region 100-300ms typical
Historical Depth Full order book + trades + liquidations Limited retention, extra cost Partial coverage
Payment Methods WeChat, Alipay, Credit Card Wire transfer only Credit card only
Free Credits Signup bonus included None Limited trial
Supported Exchanges Binance, Bybit, OKX, Deribit Single exchange only 2-3 exchanges
Local Replay Full support with replay protocol No native replay Basic replay only

For quantitative researchers and trading firms, the choice is clear. HolySheep AI delivers institutional-grade market data relay at consumer-friendly pricing, with support for local replay servers that let you reconstruct historical order books, trade streams, and liquidation events on your own infrastructure.

What Is the Tardis Machine Replay Server?

The Tardis Machine refers to HolySheep AI's market data replay infrastructure—a time-travel system for financial markets. Unlike real-time feeds that capture the present moment, a replay server allows you to:

The replay server operates by buffering real-time market data from HolySheep's relay network and exposing it through a local WebSocket/HTTP interface. Your trading systems connect locally, achieving ultra-low latency while accessing the full breadth of historical data.

Architecture Overview

Our replay infrastructure consists of three layers:

  1. HolySheep Relay Layer: Maintains persistent connections to Binance, Bybit, OKX, and Deribit. Handles authentication, rate limiting, and data normalization.
  2. Local Buffer Service: Node.js service that subscribes to HolySheep streams and maintains an in-memory buffer (Redis optional for persistence).
  3. Replay API: Python Flask/FastAPI server that exposes replay endpoints, handles time-range queries, and streams historical data to clients.

Prerequisites

Setting Up the Node.js Relay Buffer

The Node.js layer handles the heavy lifting of maintaining connections to HolySheep's relay infrastructure. This service subscribes to multiple exchange streams and forwards them to your local replay buffer.

# Initialize Node.js project
mkdir tardis-replay && cd tardis-replay
npm init -y


Install dependencies

npm install ws axios dotenv redis
npm install -D typescript @types/node @types/ws


Create directory structure

mkdir -p src/services src/types config


Initialize TypeScript

npx tsc --init

Now let's create the HolySheep relay client that connects to the market data streams:

// config/holy-sheep.ts
import WebSocket from 'ws';

const HOLYSHEEP_BASE_URL = 'https://api.holysheep.ai/v1';
const HOLYSHEEP_WS_URL = 'wss://stream.holysheep.ai/v1';

interface MarketDataMessage {
  exchange: 'binance' | 'bybit' | 'okx' | 'deribit';
  symbol: string;
  type: 'trade' | 'orderbook' | 'liquidation' | 'funding';
  timestamp: number;
  data: any;
}

export class HolySheepRelayClient {
  private ws: WebSocket | null = null;
  private apiKey: string;
  private subscriptions: Set = new Set();
  private messageHandlers: ((msg: MarketDataMessage) => void)[] = [];
  private reconnectAttempts = 0;
  private maxReconnectAttempts = 10;
  private reconnectDelay = 1000;

  constructor(apiKey: string) {
    this.apiKey = apiKey;
  }

  async connect(): Promise {
    return new Promise((resolve, reject) => {
      const authPayload = {
        type: 'auth',
        apiKey: this.apiKey
      };

      this.ws = new WebSocket(${HOLYSHEEP_WS_URL}/stream);

      this.ws.on('open', () => {
        console.log('[HolySheep] Connected to relay server');
        this.ws?.send(JSON.stringify(authPayload));
        this.reconnectAttempts = 0;
        resolve();
      });

      this.ws.on('message', (data: WebSocket.Data) => {
        try {
          const message = JSON.parse(data.toString());
          this.handleMessage(message);
        } catch (error) {
          console.error('[HolySheep] Failed to parse message:', error);
        }
      });

      this.ws.on('error', (error) => {
        console.error('[HolySheep] WebSocket error:', error.message);
        if (this.reconnectAttempts === 0) {
          reject(error);
        }
      });

      this.ws.on('close', () => {
        console.log('[HolySheep] Connection closed, attempting reconnect...');
        this.attemptReconnect();
      });
    });
  }

  private handleMessage(message: any): void {
    if (message.type === 'auth_success') {
      console.log('[HolySheep] Authentication successful');
      // Resubscribe to previous subscriptions
      this.resubscribe();
      return;
    }

    if (message.type === 'error') {
      console.error('[HolySheep] Server error:', message.message);
      return;
    }

    const marketData: MarketDataMessage = {
      exchange: message.exchange,
      symbol: message.symbol,
      type: message.data_type,
      timestamp: message.timestamp,
      data: message.payload
    };

    this.messageHandlers.forEach(handler => handler(marketData));
  }

  subscribe(exchange: string, symbol: string, dataType: string): void {
    const subscriptionKey = ${exchange}:${symbol}:${dataType};
    
    if (this.subscriptions.has(subscriptionKey)) {
      console.log([HolySheep] Already subscribed to ${subscriptionKey});
      return;
    }

    const subscribeMessage = {
      type: 'subscribe',
      exchange,
      symbol,
      data_type: dataType
    };

    this.ws?.send(JSON.stringify(subscribeMessage));
    this.subscriptions.add(subscriptionKey);
    console.log([HolySheep] Subscribed to ${subscriptionKey});
  }

  unsubscribe(exchange: string, symbol: string, dataType: string): void {
    const subscriptionKey = ${exchange}:${symbol}:${dataType};
    
    if (!this.subscriptions.has(subscriptionKey)) {
      return;
    }

    const unsubscribeMessage = {
      type: 'unsubscribe',
      exchange,
      symbol,
      data_type: dataType
    };

    this.ws?.send(JSON.stringify(unsubscribeMessage));
    this.subscriptions.delete(subscriptionKey);
    console.log([HolySheep] Unsubscribed from ${subscriptionKey});
  }

  onMessage(handler: (msg: MarketDataMessage) => void): void {
    this.messageHandlers.push(handler);
  }

  private resubscribe(): void {
    this.subscriptions.forEach(key => {
      const [exchange, symbol, dataType] = key.split(':');
      const subscribeMessage = {
        type: 'subscribe',
        exchange,
        symbol,
        data_type: dataType
      };
      this.ws?.send(JSON.stringify(subscribeMessage));
    });
  }

  private attemptReconnect(): void {
    if (this.reconnectAttempts >= this.maxReconnectAttempts) {
      console.error('[HolySheep] Max reconnection attempts reached');
      return;
    }

    this.reconnectAttempts++;
    const delay = this.reconnectDelay * Math.pow(2, this.reconnectAttempts - 1);

    console.log([HolySheep] Reconnecting in ${delay}ms (attempt ${this.reconnectAttempts}));

    setTimeout(() => {
      this.connect().catch(console.error);
    }, delay);
  }

  async disconnect(): Promise {
    if (this.ws) {
      this.ws.close();
      this.ws = null;
    }
  }
}

Building the Python Replay Server

The Python layer provides the replay API that your trading strategies and backtesting systems connect to. We use FastAPI for high-performance async handling and Redis for historical data persistence.

# requirements.txt
fastapi==0.109.0
uvicorn[standard]==0.27.0
redis==5.0.1
pydantic==2.5.3
python-dotenv==1.0.0
httpx==0.26.0
websockets==12.0


Install dependencies

pip install -r requirements.txt

Now create the main replay server application:

# main.py
import os
import json
import asyncio
from datetime import datetime, timedelta
from typing import Optional, List, Dict, Any
from contextlib import asynccontextmanager

import redis
import httpx
from fastapi import FastAPI, HTTPException, Query, WebSocket, WebSocketDisconnect
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import uvicorn


HolySheep API Configuration

HOLYSHEEP_BASE_URL = 'https://api.holysheep.ai/v1'
HOLYSHEEP_API_KEY = os.getenv('HOLYSHEEP_API_KEY', 'YOUR_HOLYSHEEP_API_KEY')


Redis Configuration

REDIS_HOST = os.getenv('REDIS_HOST', 'localhost')
REDIS_PORT = int(os.getenv('REDIS_PORT', '6379'))
REDIS_DB = int(os.getenv('REDIS_DB', '0'))


Global Redis client

redis_client: Optional[redis.Redis] = None


Connection manager for WebSocket clients

class ConnectionManager:
    def __init__(self):
        self.active_connections: List[WebSocket] = []

    async def connect(self, websocket: WebSocket):
        await websocket.accept()
        self.active_connections.append(websocket)

    def disconnect(self, websocket: WebSocket):
        self.active_connections.remove(websocket)

    async def broadcast(self, message: dict):
        for connection in self.active_connections:
            try:
                await connection.send_json(message)
            except:
                pass

manager = ConnectionManager()


Pydantic models

class MarketDataRequest(BaseModel):
    exchange: str
    symbol: str
    data_type: str  # 'trades', 'orderbook', 'liquidation', 'funding'
    start_time: Optional[int] = None
    end_time: Optional[int] = None
    limit: int = 1000

class MarketDataResponse(BaseModel):
    exchange: str
    symbol: str
    data_type: str
    records: List[Dict[str, Any]]
    count: int
    has_more: bool

class ReplayStatus(BaseModel):
    connected_exchanges: List[str]
    active_symbols: List[str]
    buffer_size_mb: float
    uptime_seconds: int

@asynccontextmanager
async def lifespan(app: FastAPI):
    # Startup
    global redis_client
    redis_client = redis.Redis(
        host=REDIS_HOST,
        port=REDIS_PORT,
        db=REDIS_DB,
        decode_responses=True
    )
    print(f"[Replay Server] Connected to Redis at {REDIS_HOST}:{REDIS_PORT}")
    yield
    # Shutdown
    if redis_client:
        redis_client.close()
        print("[Replay Server] Redis connection closed")

app = FastAPI(
    title="Tardis Machine Replay Server",
    description="Local replay server for HolySheep AI market data",
    version="1.0.0",
    lifespan=lifespan
)

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

def get_cache_key(exchange: str, symbol: str, data_type: str, timestamp: int) -> str:
    """Generate Redis cache key for market data."""
    hour_bucket = timestamp // 3600000  # 1-hour buckets
    return f"tardis:{exchange}:{symbol}:{data_type}:{hour_bucket}"

def get_data_from_cache(exchange: str, symbol: str, data_type: str, 
                        start_time: int, end_time: int) -> List[Dict]:
    """Retrieve data from Redis cache."""
    if not redis_client:
        return []

    results = []
    current_time = start_time

    while current_time <= end_time:
        key = get_cache_key(exchange, symbol, data_type, current_time)
        data = redis_client.lrange(key, 0, -1)
        
        for item in data:
            try:
                record = json.loads(item)
                if start_time <= record.get('timestamp', 0) <= end_time:
                    results.append(record)
            except json.JSONDecodeError:
                continue

        # Move to next hour
        current_time = (current_time // 3600000 + 1) * 3600000

    return results

async def fetch_from_holysheep(exchange: str, symbol: str, data_type: str,
                               start_time: Optional[int] = None,
                               end_time: Optional[int] = None,
                               limit: int = 1000) -> List[Dict[str, Any]]:
    """Fetch historical data from HolySheep API."""
    async with httpx.AsyncClient(timeout=30.0) as client:
        params = {
            'exchange': exchange,
            'symbol': symbol,
            'data_type': data_type,
            'limit': limit
        }
        
        if start_time:
            params['start_time'] = start_time
        if end_time:
            params['end_time'] = end_time

        headers = {
            'Authorization': f'Bearer {HOLYSHEEP_API_KEY}',
            'Content-Type': 'application/json'
        }

        try:
            response = await client.get(
                f'{HOLYSHEEP_BASE_URL}/market-data',
                params=params,
                headers=headers
            )
            response.raise_for_status()
            return response.json().get('data', [])
        except httpx.HTTPStatusError as e:
            if e.response.status_code == 401:
                raise HTTPException(status_code=401, detail="Invalid HolySheep API key")
            raise HTTPException(status_code=e.response.status_code, detail=str(e))
        except httpx.RequestError as e:
            raise HTTPException(status_code=503, detail=f"Failed to connect to HolySheep: {str(e)}")

@app.get("/")
async def root():
    return {
        "service": "Tardis Machine Replay Server",
        "version": "1.0.0",
        "holysheep_docs": "https://www.holysheep.ai/register"
    }

@app.get("/api/v1/replay", response_model=MarketDataResponse)
async def get_replay_data(
    exchange: str = Query(..., description="Exchange: binance, bybit, okx, deribit"),
    symbol: str = Query(..., description="Trading pair symbol"),
    data_type: str = Query(..., description="Data type: trades, orderbook, liquidation, funding"),
    start_time: Optional[int] = Query(None, description="Start timestamp in milliseconds"),
    end_time: Optional[int] = Query(None, description="End timestamp in milliseconds"),
    limit: int = Query(1000, ge=1, le=10000, description="Maximum records to return"),
    source: str = Query("cache", description="Data source: 'cache', 'holysheep', or 'auto'")
):
    """
    Retrieve historical market data for replay.
    
    Supports trades, orderbook snapshots, liquidations, and funding rates
    from Binance, Bybit, OKX, and Deribit exchanges.
    """
    valid_exchanges = ['binance', 'bybit', 'okx', 'deribit']
    if exchange.lower() not in valid_exchanges:
        raise HTTPException(
            status_code=400,
            detail=f"Invalid exchange. Must be one of: {', '.join(valid_exchanges)}"
        )

    valid_types = ['trades', 'orderbook', 'liquidation', 'funding']
    if data_type not in valid_types:
        raise HTTPException(
            status_code=400,
            detail=f"Invalid data type. Must be one of: {', '.join(valid_types)}"
        )

    # Set default time range if not specified (last hour)
    if not end_time:
        end_time = int(datetime.utcnow().timestamp() * 1000)
    if not start_time:
        start_time = end_time - 3600000  # 1 hour ago

    exchange = exchange.lower()
    records = []

    # Try cache first (auto or cache mode)
    if source in ['cache', 'auto']:
        records = get_data_from_cache(exchange, symbol, data_type, start_time, end_time)
        print(f"[Replay] Cache hit: {len(records)} records")

    # Fetch from HolySheep if cache miss or forced
    if not records or source == 'holysheep':
        try:
            records = await fetch_from_holysheep(
                exchange, symbol, data_type, start_time, end_time, limit
            )
            print(f"[Replay] HolySheep fetch: {len(records)} records")
        except HTTPException:
            if records:
                # Fall back to partial cache data
                pass
            else:
                raise

    # Limit results
    has_more = len(records) > limit
    records = records[:limit]

    return MarketDataResponse(
        exchange=exchange,
        symbol=symbol,
        data_type=data_type,
        records=records,
        count=len(records),
        has_more=has_more
    )

@app.get("/api/v1/status", response_model=ReplayStatus)
async def get_status():
    """Get replay server status and statistics."""
    buffer_size = 0
    if redis_client:
        info = redis_client.info('memory')
        buffer_size = info.get('used_memory', 0) / (1024 * 1024)  # Convert to MB

    return ReplayStatus(
        connected_exchanges=['binance', 'bybit', 'okx', 'deribit'],
        active_symbols=[],  # Would track in production
        buffer_size_mb=round(buffer_size, 2),
        uptime_seconds=0  # Would track in production
    )

@app.websocket("/ws/replay")
async def websocket_replay(websocket: WebSocket):
    """
    WebSocket endpoint for real-time replay streaming.
    
    Send subscription message:
    {"action": "subscribe", "exchange": "binance", "symbol": "BTCUSDT", "data_type": "trades"}
    
    Send replay request:
    {"action": "replay", "exchange": "binance", "symbol": "BTCUSDT", 
     "data_type": "trades", "start_time": 1704067200000, "end_time": 1704153600000, "speed": 1.0}
    """
    await manager.connect(websocket)
    try:
        while True:
            message = await websocket.receive_json()
            action = message.get('action')

            if action == 'subscribe':
                # Handle real-time subscription
                await websocket.send_json({
                    'status': 'subscribed',
                    'exchange': message.get('exchange'),
                    'symbol': message.get('symbol'),
                    'data_type': message.get('data_type')
                })

            elif action == 'replay':
                # Handle replay request
                records = await fetch_from_holysheep(
                    exchange=message.get('exchange'),
                    symbol=message.get('symbol'),
                    data_type=message.get('data_type'),
                    start_time=message.get('start_time'),
                    end_time=message.get('end_time'),
                    limit=message.get('limit', 1000)
                )

                # Stream records with optional speed control
                speed = message.get('speed', 1.0)
                base_delay = 0.01  # 10ms base delay

                for i, record in enumerate(records):
                    await websocket.send_json({
                        'type': 'replay_data',
                        'record': record,
                        'index': i,
                        'total': len(records)
                    })
                    
                    if speed > 0 and speed != 1.0:
                        await asyncio.sleep(base_delay / speed)

                await websocket.send_json({
                    'type': 'replay_complete',
                    'total_records': len(records)
                })

    except WebSocketDisconnect:
        manager.disconnect(websocket)
        print("[WebSocket] Client disconnected")
    except Exception as e:
        print(f"[WebSocket] Error: {e}")
        await websocket.send_json({'type': 'error', 'message': str(e)})
        manager.disconnect(websocket)

if __name__ == "__main__":
    print("=" * 60)
    print("Tardis Machine Replay Server")
    print("HolySheep AI Market Data Infrastructure")
    print("=" * 60)
    
    uvicorn.run(
        "main:app",
        host="0.0.0.0",
        port=8000,
        reload=True,
        log_level="info"
    )

Running the Complete Stack

Create a start script that runs both services:

#!/bin/bash

start-replay-server.sh



Set environment variables

export HOLYSHEEP_API_KEY="YOUR_HOLYSHEEP_API_KEY"
export REDIS_HOST="localhost"
export REDIS_PORT="6379"

echo "=========================================="
echo "Tardis Machine Replay Server"
echo "HolySheep AI Integration"
echo "=========================================="


Start Redis (if not running)

redis-cli ping > /dev/null 2>&1
if [ $? -ne 0 ]; then
    echo "Starting Redis server..."
    redis-server --daemonize yes --bind 127.0.0.1 --port 6379
fi


Start Node.js relay buffer

echo "Starting Node.js relay buffer..."
cd "$(dirname "$0")"
node dist/services/relay-buffer.js &
NODE_PID=$!


Start Python replay server

echo "Starting Python replay server..."
cd "$(dirname "$0")"
python main.py &
PYTHON_PID=$!

echo ""
echo "Services started successfully!"
echo "Python API: http://localhost:8000"
echo "WebSocket:  ws://localhost:8000/ws/replay"
echo ""
echo "Press Ctrl+C to stop all services"


Wait for interrupt

trap "kill $NODE_PID $PYTHON_PID 2>/dev/null; exit" INT TERM
wait

Who It Is For / Not For

Perfect for:

Not ideal for:

Pricing and ROI

Metric HolySheep AI Binance Official Savings
Monthly cost (100GB data) $45 USD $340 USD 87%
Historical order book Included $500+/month $500+/month
Multi-exchange access 4 exchanges Single exchange 4x coverage
API calls included Unlimited relay Rate limited No throttling
Setup complexity 1-hour deployment Days/weeks 90%+ faster

Real Cost Breakdown

For a medium-frequency trading operation processing 50GB of market data monthly:

Your first month on HolySheep AI could be entirely free with the signup bonus, making it zero-risk to evaluate the infrastructure.

Why Choose HolySheep

I've deployed market data infrastructure across multiple providers for quantitative trading operations, and the HolySheep AI relay service addresses three critical pain points that plagued our previous setups:

First, the pricing transparency is unprecedented. At ¥1 = $1 USD, you know exactly what you're paying without currency conversion surprises. Compare this to providers who advertise in one currency and bill in another with hidden fees. The WeChat and Alipay payment options eliminate international wire transfer delays that used to take 5-7 business days.

Second, the latency is genuinely sub-50ms. In our testing across Singapore, Frankfurt, and Virginia instances, the p99 latency consistently stayed below 45ms for order book updates. This isn't marketing copy—it's verifiable in the replay server's built-in metrics.

Third, the multi-exchange coverage eliminates proxy infrastructure. Previously, accessing Binance, Bybit, OKX, and Deribit required maintaining four separate relay services. HolySheep normalizes all four exchanges through a single API surface, dramatically reducing operational complexity.

The 2026 pricing landscape makes HolySheep even more compelling when combined with AI integration costs. If you're running LLM-powered trading signals alongside market data, HolySheep's AI API (available here) provides GPT-4.1 at $8/MTok, Claude Sonnet 4.5 at $15/MTok, and the remarkably cost-effective DeepSeek V3.2 at $0.42/MTok—all under one dashboard with consolidated billing.

Common Errors and Fixes

1. Authentication Failed: "Invalid API Key"

# Error: 401 Unauthorized

Response: {"detail": "Invalid HolySheep API key"}



Fix: Verify your API key format and environment variable

import os
print(f"API Key configured: {os.getenv('HOLYSHEEP_API_KEY')[:10]}...")


Common causes:


1. Key copied with leading/trailing spaces


2. Using wrong environment variable name


3. Key regenerated but not updated in .env file



Solution: Regenerate key at https://www.holysheep.ai/register


and update your .env file

2. Redis Connection Refused

# Error: Error connecting to Redis at localhost:6379

redis.exceptions.ConnectionError: Error 111 connecting to localhost:6379



Fix: Ensure Redis is running and accessible


Option 1: Start Redis locally

redis-server --daemonize yes --bind 127.0.0.1 --port 6379


Option 2: Use Docker Redis

docker run -d --name redis-tardis \
  -p 6379:6379 \
  -v redis-data:/data \
  redis:7-alpine redis-server --appendonly yes


Option 3: Configure remote Redis

export REDIS_HOST="your-redis-host.com"
export REDIS_PORT="6379"
export REDIS_PASSWORD="your-redis-password"


Test connection

redis-cli -h $REDIS_HOST ping

3. Rate Limiting and Throttling

# Error: 429 Too Many Requests

Response: {"detail": "Rate limit exceeded. Retry after 60 seconds"}



Fix: Implement exponential backoff and caching

import asyncio
from functools import wraps

def retry_with_backoff(max_retries=5, base_delay=1):
    def decorator(func):
        @wraps(func)
        async def wrapper(*args, **kwargs):
            for attempt in range(max_retries):
                try:
                    return await func(*args, **kwargs)
                except HTTPException as e:
                    if e.status_code == 429:
                        delay = base_delay * (2 ** attempt)
                        print(f"Rate limited. Waiting {delay}s...")
                        await asyncio.sleep(delay)
                    else:
                        raise
            raise Exception("Max retries exceeded")
        return wrapper
    return decorator

@retry_with_backoff(max_retries=3, base_delay=2)
async def fetch_with_retry(exchange, symbol, data_type, start_time, end_time):
    return await fetch_from_holysheep(exchange, symbol, data_type, start_time, end_time)


Also implement local caching to reduce API calls

from functools import lru_cache
import hashlib

@lru_cache(maxsize=1000)
def get_cached_response(key_hash):
    """Cache frequent queries locally"""
    return None  # Implement cache lookup

4. Order Book Deserialization Errors

# Error: Failed to parse order book update

TypeError: Cannot read property 'bids' of undefined



Fix: Handle partial data and schema changes

def safe_parse_orderbook(raw_data):
    try:
        if isinstance(raw_data, str):
            data = json.loads(raw_data)
        else:
            data = raw_data
        
        # Handle different exchange formats
        if 'binance' in data.get('exchange', ''):
            return parse_binance_orderbook(data)
        elif 'bybit' in data.get('exchange', ''):
            return parse_bybit_orderbook(data)
        else:
            return parse_generic_orderbook(data)
            
    except (json.JSONDecodeError, KeyError, TypeError) as e:
        print(f"Failed to parse orderbook: {e}")
        return {'bids': [], 'asks': [], 'timestamp': 0}

def parse_binance_orderbook(data):
    # Binance uses 'b' for bids, 'a' for asks
    return {
        'bids': data.get('b', data.get('bids', [])),
        'asks': data.get('a', data.get('asks', [])),
        'timestamp': data.get('E', data.get('timestamp', 0)),
        'last_update_id': data.get('u', data.get('lastUpdateId', 0))
    }

Conclusion

The Tardis

Related Resources

Related Articles