Bayesian.Ninja

AWS CloudFormation Pros and Cons So I'm building a PAAS product that does ML based optimisations and that means doing work in the cloud. The ML is a neat feature but without the basic product nothing will happen and to bootstrap this project on AWS I tried to make use of CloudFormation a service that automates creation and destruction of service stacks. Based on a week's worth of experimenting with CloudFormation I will try to answer the question: "Is learning CloudFormation worth the effort?" Despite the rant CloudFormation support creation, updating and deletion of entire stacks of services. SAM is built on top of CloudFormation and It has a visual editor. The way CloudFormation is described, is that you can copy paste snippets to create resources and build a library of reusable components. This is a simplistic point of view. In reality you need to bring properties, specify dependencies, and introduce signalling mechanisms to ensure your template works. T

While researching using the factory design pattern for  fragment creation I couldn't help but notice how that fragment creation is a long term source of bugs. Why is fragment creation error prone? Perhaps because the API for fragment has been changed so frequently that so much of the advice is dated. In the real world fragment is deprecated in favour of a decedent in the app support library but that has been deprecated as well in-favour of androidX support libraries.  Perhaps it is because many newcomers to Android are Java developers who follow the Java idiom of constructor overloading to pass parameters at creation for use in Activity.onCreate(). However, this is not a good idea it is an example of bug pattern. Using a constructor will usually appear to work fine until Android destroys the activity and looks for a default constructor. If there isn't one the app crashes with a runtime exception . This is because behind the scenes the default constructor is called ra