class CoinAPIDataAlgorithm(QCAlgorithm):

    def initialize(self) -> None:
        self.set_start_date(2020, 6, 1)
        self.set_end_date(2021, 6, 1)

        # Set Account Currency to Binance Stable Coin for USD
        self.set_account_currency("BUSD")
        self.set_cash(100000)

        self.set_brokerage_model(BrokerageName.BINANCE_FUTURES, AccountType.MARGIN)
        self.set_brokerage_model(BrokerageName.BINANCE_COIN_FUTURES, AccountType.MARGIN)
        
        crypto_future = self.add_crypto_future("BTCBUSD", Resolution.MINUTE)
        # perpetual futures does not have a filter function
        self.btcbusd = crypto_future.symbol

namespace QuantConnect
{
    public class CoinAPIDataAlgorithm : QCAlgorithm
    {
        private Symbol _symbol ;
        
        public override void Initialize()
        {
            SetStartDate(2020, 6, 1);
            SetEndDate(2021, 6, 1);

            // Set Account Currency to Binance Stable Coin for USD
            SetAccountCurrency("BUSD");
            SetCash(100000);

            SetBrokerageModel(BrokerageName.BinanceFutures, AccountType.Margin);
            SetBrokerageModel(BrokerageName.BinanceCoinFutures, AccountType.Margin);
            
            var cryptoFuture = AddCryptoFuture("BTCBUSD", Resolution.Minute);
            // perpetual futures does not have a filter function
            _symbol = cryptoFuture.Symbol;
        }
    }
}

def on_data(self, slice: Slice) -> None:
    if self.btcbusd in slice.bars:
        trade_bar = slice.bars[self.btcbusd]
        self.log(f"{self.btcbusd} close at {slice.time}: {trade_bar.close}")

    if self.btcbusd in slice.quote_bars:
        quote_bar = slice.quote_bars[self.btcbusd]
        self.log(f"{self.btcbusd} bid at {slice.time}: {quote_bar.bid.close}")

    if self.btcbusd in slice.ticks:
        ticks = slice.ticks[self.btcbusd]
        for tick in ticks:
            self.log(f"{self.btcbusd} price at {slice.time}: {tick.price}")

public override void OnData(Slice slice)
{
    if (slice.Bars.ContainsKey(_symbol))
    {
        var tradeBar = slice.Bars[_symbol];
        Log($"{_symbol} price at {slice.Time}: {tradeBar.Close}");
    }

    if (slice.QuoteBars.ContainsKey(_symbol))
    {
        var quoteBar = slice.QuoteBars[_symbol];
        Log($"{_symbol} bid at {slice.Time}: {quoteBar.Bid.Close}");
    }

    if (slice.Ticks.ContainsKey(_symbol))
    {
        var ticks = slice.Ticks[_symbol];
        foreach (var tick in ticks)
        {
            Log($"{_symbol} price at {slice.Time}: {tick.Price}");
        }
    }
}

def on_data(self, slice: Slice) -> None:
    for symbol, trade_bar in slice.bars.items():
        self.log(f"{symbol} close at {slice.time}: {trade_bar.close}")

    for symbol, quote_bar in slice.quote_bars.items():
        self.log(f"{symbol} bid at {slice.time}: {quote_bar.bid.close}")

    for symbol, ticks in slice.ticks.items():
        for tick in ticks:
            self.log(f"{symbol} price at {slice.time}: {tick.price}")

public override void OnData(Slice slice)
{
    foreach (var kvp in slice.Bars)
    {
        var symbol = kvp.Key;
        var tradeBar = kvp.Value;
        Log($"{symbol} price at {slice.Time}: {tradeBar.Close}");
    }

    foreach (var kvp in slice.QuoteBars)
    {
        var symbol = kvp.Key;
        var quoteBar = kvp.Value;
        Log($"{symbol} bid at {slice.Time}: {quoteBar.Bid.Close}");
    }

    foreach (var kvp in slice.Ticks)
    {
        var symbol = kvp.Key;
        var ticks = kvp.Value;
        foreach (var tick in ticks)
        {
            Log($"{symbol} price at {slice.Time}: {tick.Price}");
        }
    }
}

# DataFrame
history_df = self.history(self.btcbusd, 100, Resolution.DAILY)

# TradeBar objects
history_trade_bars = self.history[TradeBar](self.btcbusd, 100, Resolution.MINUTE)

# QuoteBar objects
history_quote_bars = self.history[QuoteBar](self.btcbusd, 100, Resolution.MINUTE)

# Tick objects
history_ticks = self.history[Tick](self.btcbusd, timedelta(seconds=10), Resolution.TICK)

// TradeBar objects 
var historyTradeBars = History(_symbol, 100, Resolution.Daily);

// QuoteBar objects 
var historyQuoteBars = History<QuoteBar>(_symbol, 100, Resolution.Minute);

// Tick objects 
var historyTicks = History<Tick>(_symbol, TimeSpan.FromSeconds(10), Resolution.Tick);

self.remove_security(self.btcbusd)

RemoveSecurity(_symbol);

from AlgorithmImports import *

class BinanceCryptoFutureDataAlgorithm(QCAlgorithm):

    def initialize(self) -> None:
        self.set_start_date(2022, 10, 1)
        self.set_end_date(2022, 10, 10)
        # Set Account Currency to Binance Stable Coin, since USD-BUSD will not auto-convert and USD cannot be used to trade
        self.set_cash("BUSD", 100000)
        # Binance Futures Exchange accepts both Cash and Margin account types, select the one you need for the best reality modeling.
        self.set_brokerage_model(BrokerageName.BINANCE_FUTURES, AccountType.MARGIN)

        # Requesting data, we only trade on BTCBUSD Future in Binance Future exchange
        crypto_future = self.add_crypto_future("BTCBUSD", Resolution.DAILY)
        # perpetual futures does not have a filter function
        self.btcbusd = crypto_future.symbol

        # Historical data
        history = self.history(self.btcbusd, 10, Resolution.DAILY)
        self.debug(f"We got {len(history)} from our history request for {self.btcbusd}")

    def on_data(self, slice: Slice) -> None:
        # Trade only based on updated price data
        if not slice.bars.contains_key(self.btcbusd) or not slice.quote_bars.contains_key(self.btcbusd):
            return
        
        quote = slice.quote_bars[self.btcbusd]
        price = slice.bars[self.btcbusd].price

        # Scalp-trade the bid-ask spread based on the supply-demand strength
        if price - quote.bid.close > quote.ask.close - price:
            self.set_holdings(self.btcbusd, -1)
        else:
            self.set_holdings(self.btcbusd, 1)

using System.Linq;
using QuantConnect.Data;
using QuantConnect.Brokerages;

namespace QuantConnect.Algorithm.CSharp
{
    public class BinanceCryptoFutureDataAlgorithm : QCAlgorithm
    {
        public Symbol _symbol;

        public override void Initialize()
        {
            SetStartDate(2022, 1, 1);
            SetEndDate(2023, 1, 1);
            // Set Account Currency to Binance Stable Coin, since USD-BUSD will not auto-convert and USD cannot be used to trade
            SetCash("BUSD", 100000);
            // Binance Futures Exchange accepts both Cash and Margin account types, select the one you need for the best reality modeling.
            SetBrokerageModel(BrokerageName.BinanceFutures, AccountType.Margin);

            // Requesting data, we only trade on BTCBUSD Future in Binance Future exchange
            var cryptoFuture = AddCryptoFuture("BTCBUSD", Resolution.Daily);
            // perpetual futures does not have a filter function
            _symbol = cryptoFuture.Symbol;

            // Historical data
            var history = History(_symbol, 10, Resolution.Daily);
            Debug($"We got {history.Count()} from our history request for {_symbol}");
        }

        public override void OnData(Slice slice)
        {
            // Trade only based on updated price data
            if (!slice.Bars.ContainsKey(_symbol) || !slice.QuoteBars.TryGet(_symbol, out var quote))
            {
                return;
            }
            var price = slice.Bars[_symbol].Price;
            
            // Scalp-trade the bid-ask spread based on the supply-demand strength
            if (price - quote.Bid.Close > quote.Ask.Close - price)
            {
                SetHoldings(_symbol, -1m);
            }
            else
            {
                SetHoldings(_symbol, 1m);
            }
        }
    }
}

from AlgorithmImports import *

class BinanceCryptoFutureDataAlgorithm(QCAlgorithm):

    def initialize(self) -> None:
        self.set_start_date(2022, 10, 1)
        self.set_end_date(2022, 10, 10)
        # Set Account Currency to Binance Stable Coin, since USD-BUSD will not auto-convert and USD cannot be used to trade
        self.set_cash("BUSD", 100000)
        # Binance Futures Exchange accepts both Cash and Margin account types, select the one you need for the best reality modeling.
        self.set_brokerage_model(BrokerageName.BINANCE_FUTURES, AccountType.MARGIN)

        self.universe_settings.resolution = Resolution.DAILY
        self.universe_settings.leverage = 2
        # We only trade on BTCBUSD Future in Binance Future exchange
        symbols = Symbol.create("BTCBUSD", SecurityType.CRYPTO_FUTURE, Market.BINANCE)
        self.add_universe_selection(ManualUniverseSelectionModel(symbols))
        # Custom alpha model to emit insights based on the Crypto Future price data
        self.add_alpha(CryptoFutureAlphaModel())
        # Equally invest to evenly dissipate the capital concentration risk of inidividual crypto pair
        self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel())
        self.set_execution(ImmediateExecutionModel())

class CryptoFutureAlphaModel(AlphaModel):

    def __init__(self) -> None:
        self.symbols = []

    def update(self, algorithm: QCAlgorithm, slice: Slice) -> List[Insight]:
        insights = []

        for symbol in self.symbols:
            # Trade only based on updated price data
            if not slice.bars.contains_key(symbol) or not slice.quote_bars.contains_key(symbol):
                continue

            quote = slice.quote_bars[symbol]
            price = slice.bars[symbol].price
            
            # Scalp-trade the bid-ask spread based on the supply-demand strength
            if price - quote.bid.close > quote.ask.close - price:
                insights.append(Insight.price(symbol, timedelta(1), InsightDirection.DOWN))
            else:
                insights.append(Insight.price(symbol, timedelta(1), InsightDirection.UP))
            
        return insights

    def on_securities_changed(self, algorithm: QCAlgorithm, changes: SecurityChanges) -> None:
        for security in changes.added_securities:
            symbol = security.symbol
            self.symbols.append(symbol)

            # Historical data
            history = algorithm.history(symbol, 10, Resolution.DAILY)
            algorithm.debug(f"We got {len(history)} from our history request for {symbol}")

        for security in changes.removed_securities:
            symbol = security.symbol
            if symbol in self.symbols:
                self.symbols.remove(symbol)

using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Brokerages;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Algorithm.Framework.Selection;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Algorithm.Framework.Execution;

namespace QuantConnect.Algorithm.CSharp
{
    public class BinanceCryptoFutureDataAlgorithm : QCAlgorithm
    {
        public Symbol _symbol;

        public override void Initialize()
        {
            SetStartDate(2022, 10, 1);
            SetEndDate(2022, 10, 10);
            // Set Account Currency to Binance Stable Coin, since USD-BUSD will not auto-convert and USD cannot be used to trade
            SetCash("BUSD", 100000);
            // Binance Futures Exchange accepts both Cash and Margin account types, select the one you need for the best reality modeling.
            SetBrokerageModel(BrokerageName.BinanceFutures, AccountType.Margin);

            UniverseSettings.Resolution = Resolution.Daily;
            UniverseSettings.Leverage = 2;
            // We only trade on BTCBUSD Future in Binance Future exchange
            var symbols = new List{
                QuantConnect.Symbol.Create("BTCBUSD", SecurityType.CryptoFuture, Market.Binance)
            };
            AddUniverseSelection(new ManualUniverseSelectionModel(symbols));
            // Custom alpha model to emit insights based on the Crypto Future price data
            AddAlpha(new CryptoFutureAlphaModel());
            // Equally invest to evenly dissipate the capital concentration risk of inidividual crypto pair
            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
            SetExecution(new ImmediateExecutionModel());
        }
    }

    public class CryptoFutureAlphaModel : AlphaModel
    {
        private List _symbols = new();

        public override List Update(QCAlgorithm algorithm, Slice slice)
        {
            var insights = new List();

            foreach (var symbol in _symbols)
            {
                // Trade only based on updated price data
                if (!slice.Bars.ContainsKey(symbol) || !slice.QuoteBars.TryGet(symbol, out var quote))
                {
                    continue;
                }
                var price = slice.Bars[symbol].Price;
                
                // Scalp-trade the bid-ask spread based on the supply-demand strength
                if (price - quote.Bid.Close > quote.Ask.Close - price)
                {
                    insights.Add(
                        Insight.Price(symbol, TimeSpan.FromDays(1), InsightDirection.Down)
                    );
                }
                else
                {
                    insights.Add(
                        Insight.Price(symbol, TimeSpan.FromDays(1), InsightDirection.Up)
                    );
                }
            }
            
            return insights;
        }

        public override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
        {
            foreach (var security in changes.AddedSecurities)
            {
                var symbol = security.Symbol;
                _symbols.Add(symbol);

                // Historical data
                var history = algorithm.History(symbol, 10, Resolution.Daily);
                algorithm.Debug($"We got {history.Count()} from our history request for {symbol}");
            }

            foreach (var security in changes.RemovedSecurities)
            {
                _symbols.Remove(security.Symbol);
            }
        }
    }
}