chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"## Welcome to The QuantConnect Research Page\n",
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"#### Refer to this page for documentation https://www.quantconnect.com/docs/research/overview#\n",
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"#### Contribute to this template file https://github.com/QuantConnect/Lean/blob/master/Research/KitchenSinkCSharpQuantBookTemplate.ipynb"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## QuantBook Basics\n",
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"The following example is ready to be used in our Docker container, reference the readme for more details on setting this up.\n",
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"\n",
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"In order to use this notebook locally you will need to make a few small changes:\n",
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"\n",
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"1. Either create the notebook in your build folder (`bin/debug`) **or** set working directory of the notebook to it like so in the first cell:\n",
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"\n",
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" ```\n",
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" using System.IO\n",
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" Directory.SetCurrentDirectory(\"PathToLean/Lean/Launcher/bin/Debug/\");\n",
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" ```\n",
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"\n",
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"\n",
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"2. Load \"QuantConnect.csx\" instead of \"../QuantConnect.csx\", this is again because of the Notebook position relative to the build files. \n",
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"\n",
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"### Start QuantBook\n",
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"- Load \"Initialize.csx\" to load our assemblies into our C# Kernel\n",
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"- Load \"QuantConnect.csx\" with all the basic imports\n",
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"- Create a QuantBook instance"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// We need to load assemblies at the start in their own cell\n",
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"#load \"../Initialize.csx\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// Load in our startup script, this creates our Api Object\n",
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"#load \"../QuantConnect.csx\"\n",
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"\n",
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"// Load in the namespaces we are going to use\n",
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"using QuantConnect;\n",
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"using QuantConnect.Data;\n",
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"using QuantConnect.Data.Custom;\n",
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"using QuantConnect.Data.Market;\n",
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"using QuantConnect.Research;\n",
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"using QuantConnect.Algorithm;\n",
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"\n",
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"var qb = new QuantBook();"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Using the Web API\n",
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"Our script `QuantConnect.csx` automatically loads an instance of the web API for you to use.**\n",
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"\n",
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"Look at Lean's [Api](https://github.com/QuantConnect/Lean/tree/master/Api) class for more functions to interact with the cloud\n",
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"\n",
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"\n",
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"##### **Note: This will only connect if you have your User ID and Api token in `config.json` "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// Show that our api object is connected to the Web Api\n",
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"Console.WriteLine(api.Connected);"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// Get our list of projects from the cloud and print their names\n",
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"var projectResponse = api.ListProjects();\n",
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"foreach (var project in projectResponse.Projects) {\n",
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" Console.WriteLine(project.Name);\n",
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"}"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Selecting Asset Data\n",
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"Checkout the QuantConnect [docs](https://www.quantconnect.com/docs#Initializing-Algorithms-Selecting-Asset-Data) to learn how to select asset data."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"var spy = qb.AddEquity(\"SPY\");\n",
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"var eur = qb.AddForex(\"EURUSD\");\n",
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"var btc = qb.AddCrypto(\"BTCUSD\");\n",
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"var fxv = qb.AddData<FxcmVolume>(\"EURUSD_Vol\", Resolution.Hour);"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Historical Data Requests\n",
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"\n",
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"We can use the QuantConnect API to make Historical Data Requests. The data will be presented as multi-index pandas.DataFrame where the first index is the Symbol.\n",
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"\n",
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"For more information, please follow the [link](https://www.quantconnect.com/docs#Historical-Data-Historical-Data-Requests)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// Gets historical data from the subscribed assets, the last 360 datapoints with daily resolution\n",
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"var h1 = qb.History(qb.Securities.Keys, 360, Resolution.Daily);"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// Gets historical data from the subscribed assets, from the last 30 days with daily resolution\n",
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"var h2 = qb.History(qb.Securities.Keys, TimeSpan.FromDays(360), Resolution.Daily);"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// Gets historical data from the subscribed assets, between two dates with daily resolution\n",
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"var h3 = qb.History(btc.Symbol, new DateTime(2014,1,1), DateTime.Now, Resolution.Daily);"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// Only fetchs historical data from a desired symbol\n",
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"var h4 = qb.History(spy.Symbol, 360, Resolution.Daily);"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// Only fetchs historical data from a desired symbol\n",
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"var h5 = qb.History<QuoteBar>(eur.Symbol, TimeSpan.FromDays(360), Resolution.Daily);"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"// Fetchs custom data\n",
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"var h6 = qb.History<FxcmVolume>(fxv.Symbol, TimeSpan.FromDays(360));"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".NET (C#)",
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"language": "C#",
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"name": ".net-csharp"
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},
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"language_info": {
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"file_extension": ".cs",
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"mimetype": "text/x-csharp",
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"name": "C#",
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"pygments_lexer": "csharp",
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"version": "9.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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