Futures

// Set the contract filter to select contracts that expire within 180 days.
future.SetFilter(0, 180);

# Set the contract filter to select contracts that expire within 180 days.
future.set_filter(0, 180)

// Set the contract filter to select contracts that expire within 180 days.
var history = qb.FutureHistory(
    future.Symbol, new DateTime(2025, 4, 1), new DateTime(2025, 4, 3), Resolution.Minute, 
    fillForward: false, extendedMarketHours: false
);

# Set the contract filter to select contracts that expire within 180 days.
history = qb.future_history(
    future.Symbol, datetime(2025, 4, 1), datetime(2025, 4, 3), Resolution.MINUTE, 
    fill_forward=False, extended_market_hours=False
)

foreach (var slice in history)
{
    foreach (var kvp in slice.FuturesChains)
    {
        var continuousContractSymbol = kvp.Key;
        var chain = kvp.Value;
        foreach (var contract in chain)
        {
            
        }
    }
}

for slice_ in history:
    for continuous_contract_symbol, chain in slice_.futures_chains.items(): 
        for contract in chain:
            pass

var expiries = history.GetExpiryDates();

expiries = history.get_expiry_dates()

// Get the daily TradeBar objects of the continuous contract. 
var history = qb.History<TradeBar>(future.Symbol, new DateTime(2025, 1, 1), new DateTime(2025, 4, 1), Resolution.Daily);

# Get the daily TradeBar objects of the continuous contract. 
history = qb.history(TradeBar, future.symbol, datetime(2025, 1, 1), datetime(2025, 4, 1), Resolution.DAILY)

// Get the rollovers of the continuous contract. 
var history = qb.History<SymbolChangedEvent>(future.Symbol, new DateTime(2024, 1, 1), new DateTime(2025, 1, 1));

# Get the rollovers of the continuous contract. 
history = qb.history(SymbolChangedEvent, future.symbol, datetime(2024, 1, 1), datetime(2025, 1, 1))

// Get the daily contract objects during Q1 2025.
var history = qb.History<FutureUniverse>(future.Symbol, new DateTime(2025, 1, 1), new DateTime(2025, 4, 1)); 
// Iterate through each day of the history.
foreach (var futureUniverse in history)
{
    var t = futureUniverse.EndTime;
    // Select the contract with the greatest open interest.
    var mostOi = futureUniverse.Select(c => c as FutureUniverse).OrderByDescending(c => c.OpenInterest).First();
}

# Get the daily contract objects during Q1 2025. 
history = qb.history(FutureUniverse, future.symbol, datetime(2025, 1, 1), datetime(2025, 4, 1), flatten=True)

// Load the required assembly files and data types in a separate cell.
#load "../Initialize.csx"

#load "../QuantConnect.csx"
using System;
using QuantConnect;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Data.Consolidators;
using QuantConnect.Indicators;
using QuantConnect.Algorithm;
using QuantConnect.Research;
using QuantConnect.Securities;

// Import Plotly for plotting.
#r "../Plotly.NET.dll"
using Plotly.NET;
using Plotly.NET.LayoutObjects;

// Create a QuantBook.
var qb = new QuantBook();

// Request the continuous future historical data.
var future = qb.AddFuture(Futures.Indices.SP500EMini);
var history = qb.History<TradeBar>(future.Symbol, 
    start: new DateTime(2024, 7, 1),
    end: new DateTime(2025, 1, 1),
    resolution: Resolution.Minute,
    fillForward: true,
    extendedMarketHours: true,
    dataMappingMode: DataMappingMode.OpenInterest,
    dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
    contractDepthOffset: 0);

// Set up a consolidator and a RollingWindow to save the data
var consolidator = new TradeBarConsolidator(TimeSpan.FromMinutes(5));
var window = new RollingWindow<TradeBar>(10000);

// Attach a consolidation handler method that saves the consolidated bars in the RollingWindow
consolidator.DataConsolidated += (sender, consolidated) =>
{
    window.Add(consolidated);
};

// Iterate the historical market data and feed each bar into the consolidator
foreach(var bar in history)
{
    consolidator.Update(bar);
}

// Crete the Candlestick chart using the 5-minute windows.
var chart = Chart2D.Chart.Candlestick<decimal, decimal, decimal, decimal, DateTime, string>(
    window.Select(x => x.Open),
    window.Select(x => x.High),
    window.Select(x => x.Low),
    window.Select(x => x.Close),
    window.Select(x => x.EndTime)
);
// Create a Layout as the plot settings.
LinearAxis xAxis = new LinearAxis();
xAxis.SetValue("title", "Time");
LinearAxis yAxis = new LinearAxis();
yAxis.SetValue("title", "Price ($)");
Title title = Title.init($"{future.Symbol} Price");

Layout layout = new Layout();
layout.SetValue("xaxis", xAxis);
layout.SetValue("yaxis", yAxis);
layout.SetValue("title", title);
// Assign the Layout to the chart.
chart.WithLayout(layout);
// Display the plot.
HTML(GenericChart.toChartHTML(chart))

# Import plotly library for plotting.
import plotly.graph_objects as go

# Create a QuantBook
qb = QuantBook()

# Request the continuous future historical data.
# Use raw normalization mode to fairly compare the actual bid and ask dollar volume.
future = qb.add_future(Futures.Indices.SP_500_E_MINI)
history = qb.history(
    future.symbol, 
    start=datetime(2024, 7, 1), 
    end=datetime(2025, 1, 1), 
    resolution=Resolution.MINUTE, 
    fill_forward=True, 
    extended_market_hours=True, 
    data_mapping_mode=DataMappingMode.OPEN_INTEREST, 
    data_normalization_mode=DataNormalizationMode.BACKWARDS_RATIO, 
    contract_depth_offset=0
)

# Drop level 0, 1 index (Symbol index) from the DataFrame
history = history.droplevel([0, 1])

# Select the required columns to obtain the 5-minute OHLC data.
history = history[["open", "high", "low", "close"]].resample("5T").agg({
    "open": "first",
    "high": "max",
    "low": "min",
    "close": "last"
})

# Crete the Candlestick chart using the 5-minute windows.
candlestick = go.Candlestick(
    x=history.index,
    open=history['open'],
    high=history['high'],
    low=history['low'],
    close=history['close']
)
# Create a Layout as the plot settings.
layout = go.Layout(
    title=go.layout.Title(text=f'{future.symbol} OHLC'),
    xaxis_title='Date',
    yaxis_title='Price',
    xaxis_rangeslider_visible=False
)
# Create the Figure.
fig = go.Figure(data=[candlestick], layout=layout)
# Display the plot.
fig.show()