Monthly Archives: December 2016

[HockeyApp + VSTS] Generate release notes from last git commit message

Continuous Integration and Continuous delivery for Xamarin apps with VSTS and HockeyApp is awesome!

I blogged about setting up CI/CD pipeline with VSTS+HockeyApp a few weeks ago.

If you want to add release notes to HockeyApp release you have two options:

  1. Add release notes manually, by setting ‘Release Notes’ property, and update them before every build (AKA – option that sucks)
  2. Add path to release notes file, by setting ‘Release Notes (file)’ property, and update it before every git push (AKA – option that sucks less)
  3. Add path to release notes file, by setting ‘Release Notes (file)’ property, and generate release notes from last git commit message on every build (AKA – option that rocks)

Applying options 1 and 2 is easy.

To make option 3 happen you need to add script that will get last git commit message, and output it to the file that you specified in ‘Release Notes (file)’ property. This script should be executed before ‘Deploy to HockeyApp’ step (of course).

For Xamarin.iOS you need to add ‘Shell Script’ task that can look like this:

echo "last commit: $BUILD_SOURCEVERSIONMESSAGE" > commit.txt

*it will output file to the same directory where shell script is located

For Xamarin.Droid and Windows builds, you can create PowerShell script.


Predicting future with F# and Azure Machine Learning

Earlier this year I blogged about StockEstimator – my side project for predicting future stock prices. Recently in addition to F# module, which estimates future prices, I added Web Service that takes advantage of Azure Machine Learning to do the same much faster.

Last month I talked about my project at .NET Developers Association Meetup in Redmond and in Seattle. I streamed both session with YouTube live, and recordings are already available:

Both videos cover the same topics. Not sure, which one is better. However, there was one gentleman who went to both my talks and he said that the second one was better 🙂

In both presentations I do a quick intro to F#, an overview of Machine Learning, and how I took advantage of both to predict future stock prices.

If you are interested in F# I recommend you to check my Getting started with F#.

Presentation slides are available here (you can find there a lot of references to materials about F#, Machine Learning and Azure Machine Learning).

StockEstimator project is open source and available on github.

I’m not going to stop here. As you can see on my slides, and at the end of my presentations I have future plans to evolve this overnight project 🙂