Category: Misc Languages

Gulshan Singh visits from the future:

You have units of work that you want to run asynchronously, so you don’t block while they’re running. A future gives you a simple way to run an algorithm concurrently. A future starts running concurrently when you create it and returns a result at some point, well, in the future. In Scala, we call that a future returns eventually.

The Future instance is a handle to an eventually available result. You can continue doing other work until the future completes, either successfully or unsuccessfully.

You may also know of Futures as Promises. It’s quite similar to async calls in .NET as well.

Gulshan Singh describes three tricky terms for newcomers to functional programming:

Monoid is based on an associative function. Formally, a functor is a type F[A] with an operation
map with type (A => B) => F[B]. In functional programming one typically only deals with one category, the category of types. A functor is an interface with one method i.e a mapping of the category to category. Monads basically is a mechanism for sequencing computations. A monad is a way to wrap stuff, then operate on the wrapped stuff without unwrapping it.

If that wasn’t too clear, check out the post for more detail. And if you want a whole lot more detail, Bartosz Milewski’s YouTube series (and book) on category theory are great resources for dozens of hours of learning.

Pallav Gupta shows several methods for handling errors using Scala:

Error handling is the process of handling the possibility of failure. For example, failing to read a file and then continuing to use that bad input would clearly be problematic. Noticing and explicitly managing these errors saves the rest of the program from various pitfalls.

When an exception occurs, say an Arithmetic Exception then the current operation is aborted. Then the runtime system looks for an exception handler that can accept an Arithmetic Exception. Control resumes with the innermost handler. If no such handler exists, the program terminates.

Pallav starts with the most expensive option and ends with the best option with the Either monad.

Prakhar explains the difference between currying and partial application:

Currying simply means converting a function taking more than one parameter can be into a series of functions with each taking one parameter. Example:

Click through for an example, as well as the difference between currying and partial application. As for why currying is important, this is how we tie together the concept of mathematical functions, which require exactly one parameter (a function being defined as, for every value of the domain, there is one and only one value of the range), with computer science functions, which may have multiple parameters. Currying allows us to bridge that gap without needing to write loads of intermediary functions.