Martin-Molinero
f3c386663b
* Update projects to use .NET 5.0, the successor to .NET Core
* Fix ambiguous errors. Add IBAutomator net5
* Remove FXCM
* Upgrade IBAutomater to v1.0.51
ignored, and an empty message aborts the commit.
* Fix rebase
- Fix ambiguous Index
- Remove StrategyCapacity.cs
- Update System.Threading.Tasks.Extensionsy
* Remove unrequired references
* Fixes
- Travis will use dotnet, not nunit nor mono
- Remove mono from foundation image
- Fix python setup in research
- Fix unit tests
* Don't call ReadKey when input is redirected
* Fix ConsoleLeanOptimizer
* Research fixes
* Update comment
* Add vsdbg to Dockerfile
* Fixes
- Revert dockerfile FROM custom changes
- Adjust and fix regression algorithms
- Option assignment will be deterministic in the order
- 'Rolling Averaged Population' is calculated using doubles, updating
expected values.
- Update readme, removing references to mono
- Add missing Py.Gil lock
* Replace ICSharp with .NET Interactive
* Fixes after rebase
* CSharp research fixes
- Adding new Initialize.csx that pre loads all assemblies
- Adjusting template research file
- Moving steps in dockerfilejupyter
- Fix unit tests and regression tests after rebase
Co-authored-by: Gerardo Salazar <gsalaz9800@gmail.com>
Co-authored-by: Stefano Raggi <stefano.raggi67@gmail.com>
Co-authored-by: Jasper van Merle <jaspervmerle@gmail.com>
95 lines
3.4 KiB
Plaintext
95 lines
3.4 KiB
Plaintext
{
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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#Introduction-to-Jupyter\n",
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"#### Contribute to this template file https://github.com/QuantConnect/Lean/blob/master/Research/BasicCSharpQuantBookTemplate.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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"\n",
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"### Start QuantBook\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 \"../QuantConnect.csx\"\n",
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"\n",
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"using QuantConnect;\n",
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"using QuantConnect.Data;\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();\n",
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"\n",
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"// Selecting asset data\n",
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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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]
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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);\n",
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"Console.WriteLine(string.Join(\",\", h1.SelectMany(slice => slice.Keys).Distinct()))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "C#",
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"language": "csharp",
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"name": "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": "c#",
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"version": "4.0.30319"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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