logo
  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
//! Synchronization primitives.
//!
//! This module is an async version of [`std::sync`].
//!
//! [`std::sync`]: https://doc.rust-lang.org/std/sync/index.html
//!
//! ## The need for synchronization
//!
//! async-std's sync primitives are scheduler-aware, making it possible to
//! `.await` their operations - for example the locking of a [`Mutex`].
//!
//! Conceptually, a Rust program is a series of operations which will
//! be executed on a computer. The timeline of events happening in the
//! program is consistent with the order of the operations in the code.
//!
//! Consider the following code, operating on some global static variables:
//!
//! ```
//! static mut A: u32 = 0;
//! static mut B: u32 = 0;
//! static mut C: u32 = 0;
//!
//! fn main() {
//!     unsafe {
//!         A = 3;
//!         B = 4;
//!         A = A + B;
//!         C = B;
//!         println!("{} {} {}", A, B, C);
//!         C = A;
//!     }
//! }
//! ```
//!
//! It appears as if some variables stored in memory are changed, an addition
//! is performed, result is stored in `A` and the variable `C` is
//! modified twice.
//!
//! When only a single thread is involved, the results are as expected:
//! the line `7 4 4` gets printed.
//!
//! As for what happens behind the scenes, when optimizations are enabled the
//! final generated machine code might look very different from the code:
//!
//! - The first store to `C` might be moved before the store to `A` or `B`,
//!   _as if_ we had written `C = 4; A = 3; B = 4`.
//!
//! - Assignment of `A + B` to `A` might be removed, since the sum can be stored
//!   in a temporary location until it gets printed, with the global variable
//!   never getting updated.
//!
//! - The final result could be determined just by looking at the code
//!   at compile time, so [constant folding] might turn the whole
//!   block into a simple `println!("7 4 4")`.
//!
//! The compiler is allowed to perform any combination of these
//! optimizations, as long as the final optimized code, when executed,
//! produces the same results as the one without optimizations.
//!
//! Due to the [concurrency] involved in modern computers, assumptions
//! about the program's execution order are often wrong. Access to
//! global variables can lead to nondeterministic results, **even if**
//! compiler optimizations are disabled, and it is **still possible**
//! to introduce synchronization bugs.
//!
//! Note that thanks to Rust's safety guarantees, accessing global (static)
//! variables requires `unsafe` code, assuming we don't use any of the
//! synchronization primitives in this module.
//!
//! [constant folding]: https://en.wikipedia.org/wiki/Constant_folding
//! [concurrency]: https://en.wikipedia.org/wiki/Concurrency_(computer_science)
//!
//! ## Out-of-order execution
//!
//! Instructions can execute in a different order from the one we define, due to
//! various reasons:
//!
//! - The **compiler** reordering instructions: If the compiler can issue an
//!   instruction at an earlier point, it will try to do so. For example, it
//!   might hoist memory loads at the top of a code block, so that the CPU can
//!   start [prefetching] the values from memory.
//!
//!   In single-threaded scenarios, this can cause issues when writing
//!   signal handlers or certain kinds of low-level code.
//!   Use [compiler fences] to prevent this reordering.
//!
//! - A **single processor** executing instructions [out-of-order]:
//!   Modern CPUs are capable of [superscalar] execution,
//!   i.e., multiple instructions might be executing at the same time,
//!   even though the machine code describes a sequential process.
//!
//!   This kind of reordering is handled transparently by the CPU.
//!
//! - A **multiprocessor** system executing multiple hardware threads
//!   at the same time: In multi-threaded scenarios, you can use two
//!   kinds of primitives to deal with synchronization:
//!   - [memory fences] to ensure memory accesses are made visible to
//!   other CPUs in the right order.
//!   - [atomic operations] to ensure simultaneous access to the same
//!   memory location doesn't lead to undefined behavior.
//!
//! [prefetching]: https://en.wikipedia.org/wiki/Cache_prefetching
//! [compiler fences]: https://doc.rust-lang.org/std/sync/atomic/fn.compiler_fence.html
//! [out-of-order]: https://en.wikipedia.org/wiki/Out-of-order_execution
//! [superscalar]: https://en.wikipedia.org/wiki/Superscalar_processor
//! [memory fences]: https://doc.rust-lang.org/std/sync/atomic/fn.fence.html
//! [atomic operations]: https://doc.rust-lang.org/std/sync/atomic/index.html
//!
//! ## Higher-level synchronization objects
//!
//! Most of the low-level synchronization primitives are quite error-prone and
//! inconvenient to use, which is why async-std also exposes some
//! higher-level synchronization objects.
//!
//! These abstractions can be built out of lower-level primitives.
//! For efficiency, the sync objects in async-std are usually
//! implemented with help from the scheduler, which is
//! able to reschedule the tasks while they are blocked on acquiring
//! a lock.
//!
//! The following is an overview of the available synchronization
//! objects:
//!
//! - [`Arc`]: Atomically Reference-Counted pointer, which can be used
//!   in multithreaded environments to prolong the lifetime of some
//!   data until all the threads have finished using it.
//!
//! - [`Barrier`]: Ensures multiple threads will wait for each other
//!   to reach a point in the program, before continuing execution all
//!   together.
//!
//! - [`channel`]: Multi-producer, multi-consumer queues, used for
//!   message-based communication. Can provide a lightweight
//!   inter-task synchronisation mechanism, at the cost of some
//!   extra memory.
//!
//! - [`Mutex`]: Mutual exclusion mechanism, which ensures that at
//!   most one task at a time is able to access some data.
//!
//! - [`RwLock`]: Provides a mutual exclusion mechanism which allows
//!   multiple readers at the same time, while allowing only one
//!   writer at a time. In some cases, this can be more efficient than
//!   a mutex.
//!
//! [`Arc`]: struct.Arc.html
//! [`Barrier`]: struct.Barrier.html
//! [`channel`]: fn.channel.html
//! [`Mutex`]: struct.Mutex.html
//! [`RwLock`]: struct.RwLock.html
//!
//! # Examples
//!
//! Spawn a task that updates an integer protected by a mutex:
//!
//! ```
//! # async_std::task::block_on(async {
//! #
//! use async_std::sync::{Arc, Mutex};
//! use async_std::task;
//!
//! let m1 = Arc::new(Mutex::new(0));
//! let m2 = m1.clone();
//!
//! task::spawn(async move {
//!     *m2.lock().await = 1;
//! })
//! .await;
//!
//! assert_eq!(*m1.lock().await, 1);
//! #
//! # })
//! ```

#![allow(clippy::needless_doctest_main)]

#[doc(inline)]
pub use std::sync::{Arc, Weak};

#[doc(inline)]
pub use async_lock::{Mutex, MutexGuard, MutexGuardArc};

#[doc(inline)]
pub use async_lock::{RwLock, RwLockReadGuard, RwLockUpgradableReadGuard, RwLockWriteGuard};

cfg_unstable! {
    pub use async_lock::{Barrier, BarrierWaitResult};
    pub use condvar::Condvar;
    pub(crate) use waker_set::WakerSet;

    mod condvar;

    pub(crate) mod waker_set;
}