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So we have now seen that the concepts of asynchrony are deeply baked into the Swift language. If you want to perform asynchronous work you need to be in an asynchronous context, which is something that the compiler explicitly knows about. You either need to implement your function with the
async keyword applied to it, which means the caller is responsible for providing the asynchronous context, or you need to spin up a new task using the
Task initializer. The choice between these two styles of providing an asynchronous context are very different, but we will dive into that topic in a moment.
Before that, there was another topic we delved into for both threads and dispatch queues, and that is data synchronization and data races. We saw that if we accessed mutable state from multiple threads or queues, then we leave ourselves open to data races, where two threads simultaneously read and write to the same value. When this happens we get unexpected results, such as incrementing a counter 1,000 times from 1,000 different threads causes the count to be slightly less than 1,000. This happens when one thread writes the count in between the moment when another thread reads the count and then writes to it. In that case the second write will mutate with an out-of-date value.
Let’s see what new tools Swift gives us to solve this problem.
In life, there’s always work to be done. Every day brings with it a steady stream of tasks and chores to fill the working hours of our existence. Productivity is, as in life as it is in programming, a matter of scheduling and prioritizing and multi-tasking work in order to keep up appearances.
The libdispatch is one of the most misused API due to the way it was presented to us when it was introduced and for many years after that, and due to the confusing documentation and API. This page is a compilation of important things to know if you’re going to use this library. Many references are available at the end of this document pointing to comments from Apple’s very own libdispatch maintainer (Pierre Habouzit).
macOS 10.13 and iOS 11 have reinvented how Grand Central Dispatch and the Darwin kernel collaborate, enabling your applications to run concurrent workloads more efficiently. Learn how to modernize your code to take advantage of these improvements and make optimal use of hardware resources.
I’m delighted to announce Swift Atomics, a new open source package that enables direct use of low-level atomic operations in Swift code. The goal of this library is to enable intrepid systems programmers to start building synchronization constructs (such as concurrent data structures) directly in Swift.