Validate Map Collections via Matchers

I was introduced to Hamcrest Matchers by the 3C team.  I am really liking it.  Today, I stumbled on a validation of a Map.  Here is how I usually solved the problem and then how I solved it using the syntax sugar of Matchers.

Lambdas and Java 8

Java 1.8 introduces the concept of streams, which are similar to iterators.

Why Lambdas are good for you:

• Form the basis of functional programming language
• Make parallel programming easier 
• Write more compact code 
• Richer data structure collections 
• Develop cleaner APIs 

 Lambdas Expression Lifecycle - think of them as having a two stage lifecycle:

1. Convert the lambda expression to a function.
2. Call the general function

Streams have two types of operations: intermediate and terminal.
Intermediate operation: specifies tasks to perform on the stream's elements and always results in a new stream.
filter: Result in a stream containing only the elements that satisfy a condition.
distinct: Result in a stream containing only the unique element.
limit: Result in a stream with the specified number of elements from the beginning of the original stream.
map: Result in a stream in which each element of the original stream is mapped to a new value (possibly of a different type).
sorted: Result in a stream in which the elements are in sorted order. The new stream has the same number of elements as the original stream.


Terminal operations initiates processing of a stream pipeline's intermediate operations and produces results.
forEach: Performs processing on every element in a stream.
average: Calculates the average of the elements in a numeric stream.
count: Returns the number of elements in the stream.
max: Locates the largest value in a numeric stream.
min: Locates the smallest value in a numeric stream.
reduce: Reduces the element of a collection to a single value using an associative accumulation function (e.g. a lambda that adds two elements -- in Scala this is the "map" operator).


Mutable reduction operations: creates a container (such as a collection or StringBuilder)
collect: Creates a new collection of elements containing the results of the streams's prior operations.
toArray: Creates an array containing the results of the stream's prior operations.


Search operations
findFirst: Find the first stream element based on the prior intermediate operations; immediately terminates the processing of the stream pipeline once such an element is found.
findAny: Finds any stream element based on the prior intermediate operations: immediately processing of the stream pipeline once such an element is found.
anyMatch: Determines whether any stream elements match a specified conditions; immediately terminates processing of the stream pipeline if an element matches.
allMatch: Determines whether all of the elements in the stream match a specified condition.

Examples:

Refactor: 

This has done so many different changes to some of my code. Here are some example of before and after: Before: I wanted to printout some of the results and so I leveraged Spring's CommandLineRunner.

 Here's the after code: Another example fetching a collection of records from a database: I can refactored it doing this: