Add GH workflow. Improve readme

Author: Martin-Molinero

.github/workflows/build.yml

@@ -0,0 +1,22 @@
+name: Build & Test
+
+on:
+  push:
+    branches: ['*']
+    tags: ['*']
+  pull_request:
+    branches: [master]
+
+jobs:
+  build:
+    runs-on: ubuntu-20.04
+    container:
+        image: quantconnect/lean:foundation
+    steps:
+      - uses: actions/checkout@v2
+
+      - name: Build
+        run: dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 MyCustomDataType.sln
+
+      - name: Run Tests
+        run: dotnet test ./Tests/bin/Release/net5.0/Tests.dll

BashConverterScript.sh …taConverterScript/BashConverterScript.shBashConverterScript.sh renamed to DataConverterScript/BashConverterScript.sh BashConverterScript.sh renamed to DataConverterScript/BashConverterScript.sh

@@ -1,37 +1,73 @@
 # LeanDataSdk
 
+[![Build Status](https://github.com/QuantConnect/LeanDataSdk/workflows/Build%20%26%20Test/badge.svg)](https://github.com/QuantConnect/LeanDataSdk/actions?query=workflow%3A%22Build%20%26%20Test%22)
+
 ### Getting started
 
 #### Introduction
 
-The Lean Data SDK is a cross-platform template repository for developing custom data types for Lean. These data types will be consumed by trading algorithms and research environment.
+The Lean Data SDK is a cross-platform template repository for developing custom data types for Lean.
+These data types will be consumed by [QuantConnect](https://www.quantconnect.com/) trading algorithms and research environment, locally or in the cloud.
 
-It is composed by a .Net solution for the data type and example converter scripts.
+It is composed by example .Net solution for the data type and converter scripts.
 
 #### Prerequisites
 
-The solution targets dotnet 5, for installation instructions please follow (dotnet)[https://dotnet.microsoft.com/download].
+The solution targets dotnet 5, for installation instructions please follow [dotnet download](https://dotnet.microsoft.com/download).
 
 The data downloader and converter script can be developed in different ways: Python script, C# or Python jupyter notebook or even a bash script.
+- The python script should be compatible with python 3.6.8
+- C# notebook will run using [dotnet interactive](https://github.com/dotnet/interactive)
+- Bash script will run on Ubuntu Bionic
+
+Specifically, the enviroment where these scripts will be run is [quantconnect/research](https://hub.docker.com/repository/docker/quantconnect/research) based on [quantconnect/lean:foundation](https://hub.docker.com/repository/docker/quantconnect/lean).
 
 #### Installation
 
 This repository should be forked by each new data provider.
 
-Once it is cloned locally, should be able to successfully build the solution or execute the conveter scripts.
+Once it is cloned locally, should be able to successfully build the solution, run all tests and execute the conveter scripts.
+
+#### Usage
+
+- Once the repository is forked, the existing example implementation should be adjusted, in the fork, to create a new data type for a particular data set.
+- Converter and downloader scripts should be developed following the [examples in this repository](https://github.com/QuantConnect/LeanDataSdk/tree/master/DataConverterScript).
+
+The script should be provided to `QuantConnect` as well as the fork repository at a particual commit.
 
 ### User guide
 
-### Tutorial
+### Tutorials
 
 #### Create Data Type
 
 ##### Introduction
 
-Creating a custom data type will allow Lean algorithms or research environment to consume a particular data set.
+This tutorial we will create a new custom C# data type that will allow Lean algorithms or research environment to consume a particular data set.
+
+##### New Lean Data Type
+
+In [Lean](https://github.com/QuantConnect/Lean) each data type inherits from [BaseData](https://github.com/QuantConnect/Lean/blob/master/Common/Data/BaseData.cs), overrides a set of methods and incoporates any specific property this data set has.
+The `DataLibrary` project holds an example custom data type [MyCustomDataType](https://github.com/QuantConnect/LeanDataSdk/blob/master/DataLibrary/MyCustomDataType.cs).
+
+- `GetSource()` method returns an instance of `SubscriptionDataSource` which will tell Lean from where should it source data for a particular given date, ticker, and configuration.
+- `Reader()` method should return a new instance of this data type for a given line of data
+- `Clone()` Clones the data
+- `RequiresMapping()` Indicates whether the data source is tied to an underlying symbol and requires that corporate events be applied to it as well, such as renames and delistings
+- `IsSparseData()` Indicates whether the data is sparse. If true, we disable logging for missing files
+- `ToString()` converts the instance to string format
+- `DefaultResolution()` gets the default resolution for this data and security type if the user provided none
+- `SupportedResolutions()` gets the supported resolution for this data and security type
+- `DataTimeZone()` specifies the data time zone for this data type
+
+##### Tests
+
+It will be a requisite that each data type has a json and protobuf round trip serialization and deserialization, as well as a clone unit test. Examples provided at [MyCustomDataTypeTests](https://github.com/QuantConnect/LeanDataSdk/blob/master/Tests/MyCustomDataTypeTests.cs)
 
 #### Create Algorithm
 
+
+
 #### Create Data Converters
 
 ##### Python Notebook

CSharpConverterNotebook.ipynb …rterScript/CSharpConverterNotebook.ipynbCSharpConverterNotebook.ipynb renamed to DataConverterScript/CSharpConverterNotebook.ipynb CSharpConverterNotebook.ipynb renamed to DataConverterScript/CSharpConverterNotebook.ipynb

@@ -32,5 +32,11 @@ public void ProtobufRoundTrip()
         {
 
         }
+
+        [Test]
+        public void Clone()
+        {
+
+        }
     }
 }