What is the difference between Go's data races and deadlocks in concurrent programming?

Data races and deadlocks are two common issues that can occur in concurrent programming in Go.

A data race occurs when two or more goroutines access the same shared variable simultaneously, and at least one of those accesses is a write. In the absence of proper synchronization, the order of these accesses is undefined, and the result is unpredictable. Data races can lead to subtle bugs that are hard to reproduce and diagnose.

On the other hand, a deadlock occurs when two or more goroutines are waiting for each other to release a resource that they are holding. This can happen, for example, when two goroutines each hold a mutex and are waiting for the other to release it. Deadlocks can cause the program to hang or crash, and they are usually easier to diagnose than data races.

To prevent data races, Go provides several synchronization mechanisms, such as mutexes, channels, and atomic operations, that ensure that only one goroutine can access a shared variable at a time. To prevent deadlocks, it is important to avoid circular dependencies between goroutines and to use timeouts and cancellation signals to avoid waiting indefinitely for a resource that may never become available.

In summary, data races and deadlocks are both important issues to be aware of in concurrent programming, and Go provides mechanisms to address them, but they require careful consideration and design to avoid.