The Collection Pipeline design pattern is intended to process collections of data by chaining together operations in a sequence where the output of one operation is the input for the next. It promotes a declarative approach to handling collections, focusing on what should be done rather than how.
The Fan-Out/Fan-In pattern aims to improve concurrency and optimize processing time by dividing a task into multiple sub-tasks that can be processed in parallel (fan-out) and then combining the results of these sub-tasks into a single outcome (fan-in).
The Filterer pattern aims to apply a series of filters to data objects, where each filter processes the data based on specific rules and criteria, and passes the data to the next filter in the sequence.
