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concurrencpp, the C++ concurrency library

Latest Release License: MIT

concurrencpp allows applications to write asynchronous code easily and safely by using executors and coroutines. By using concurrencpp applications can break down big procedures that need to be processed asynchronously into smaller tasks that run concurrently and work in a co-operative manner to achieve the wanted result. concurrencpp also allows applications to write parallel algorithms more easily by using parallel coroutines.

concurrencpp main advantages are:

  • Being able to write non-blocking, asynchronous code easily by using the C++20 coroutines and the co_await keyword.
  • Being able to write modern concurrent code without having to rely on low-level concurrency primitives like locks and condition variables.
  • The concurrency runtime manages all low-level resources such as threads automatically.
  • Reducing the possibility of race conditions, data races and deadlocks by using high-level objects with built-in synchronization.
  • concurrencpp provides various types of commonly used executors with a complete coroutine integration.
  • Applications can extend the library by using their own provided executors.
  • Applications automatically scale-up to use all hardware processors (cores).

concurrencpp is task-centric. A task is an asynchronous operation. Tasks provide higher level of abstraction for concurrent code than traditional thread-centric approaches. Tasks can be chained together, meaning that tasks pass their asynchronous result from one to another, where the result of one task is used as if it were a parameter or an intermediate value of another ongoing task. In concurrencpp, the concept of tasks is represented by coroutines. This allows tasks to be suspended, waiting for other tasks to finish, and chained using co_await, and thus solving the consumer-producer problem elegantly by giving the concurrent code a synchronous look.

concurrencpp is built around the RAII concept. In order to use tasks and executors, applications create a runtime instance in the beginning of the main function. The runtime is then used to acquire existing executors and register new user-defined executors. Executors are used to schedule new tasks to run, and they might return a result object that can be used to marshal the asynchronous result to another task that acts as its consumer. Results can be awaited and resolved in a non-blocking manner, and even switch the underlying executor in the process. When the runtime is destroyed, it iterates over every stored executor and calls its shutdown method. Every executor then exits gracefully. Unscheduled tasks are destroyed, and attempts to create new tasks will throw an exception.

"Hello world" program using concurrencpp:

#include "concurrencpp/concurrencpp.h"
#include <iostream>

int main() {
	concurrencpp::runtime runtime;
	auto result = runtime.thread_executor()->submit([] {
		std::cout << "hello world" << std::endl;
	});

	result.get();
	return 0;
}

In this basic example, we created a runtime object, then we acquired the thread executor from the runtime. We used submit to pass a lambda as our given callable. This lambda returns void, hence, the executor returns a result<void> object that marshals the asynchronous result back to the caller. main calls get which blocks the main thread until the result becomes ready. If no exception was thrown, get returns void. If an exception was thrown, get re-throws it. Asynchronously, thread_executor launches a new thread of execution and runs the given lambda. It implicitly co_return void and the task is finished. main is then unblocked.

Concurrent even-number counting:

#include "concurrencpp/concurrencpp.h"

#include <iostream>
#include <vector>
#include <algorithm>

#include <ctime>

using namespace concurrencpp;

std::vector<int> make_random_vector() {
    std::vector<int> vec(64 * 1'024);

    std::srand(std::time(nullptr));
    for (auto& i : vec) {
        i = ::rand();
    }

    return vec;
}

result<size_t> count_even(std::shared_ptr<thread_pool_executor> tpe, const std::vector<int>& vector) {
    const auto vecor_size = vector.size();
    const auto concurrency_level = tpe->max_concurrency_level();
    const auto chunk_size = vecor_size / concurrency_level;

    std::vector<result<size_t>> chunk_count;

    for (auto i = 0; i < concurrency_level; i++) {
        const auto chunk_begin = i * chunk_size;
        const auto chunk_end = chunk_begin + chunk_size;
        auto result = tpe->submit([&vector, chunk_begin, chunk_end]() -> size_t {
            return std::count_if(vector.begin() + chunk_begin, vector.begin() + chunk_end, [](auto i) {
                return i % 2 == 0;
            });
        });

        chunk_count.emplace_back(std::move(result));
    }

    size_t total_count = 0;

    for (auto& result : chunk_count) {
        total_count += co_await result;
    }

    co_return total_count;
}

int main() {
    concurrencpp::runtime runtime;
    const auto vector = make_random_vector();
    auto result = count_even(runtime.thread_pool_executor(), vector);
    const auto total_count = result.get();
    std::cout << "there are " << total_count << " even numbers in the vector" << std::endl;
    return 0;
}

In this example, we start the program by creating a runtime object. We create a vector filled with random numbers, then we acquire the thread_pool_executor from the runtime and call count_even. count_even is a coroutine that spawns more coroutines and co_awaits for them to finish inside. max_concurrency_level returns the maximum amount of workers that the executor supports, In the threadpool executor case, the number of workers is calculated from the number of cores. We then partition the array to match the number of workers and send every chunk to be processed in its own task. Asynchronously, the workers count how many even numbers each chunk contains, and co_return the result. count_even sums every result by pulling the count using co_await, the final result is then co_returned. The main thread, which was blocked by calling get is unblocked and the total count is returned. main prints the number of even numbers and the program terminates gracefully.


Table of contents


concurrencpp coroutines

concurrencpp coroutines are eager. they start to run the moment they are invoked (as opposed to lazy coroutines, which start to run only when co_awaited). concurrencpp coroutines can return any of concurrencpp::result or concurrencpp::null_result.

concurrencpp::result tells the coroutine to marshal the returned value or the thrown exception while concurrencpp::null_result tells the coroutine to drop and ignore any of them.

Coroutines can be created and scheduled using concurrencpp in many ways. The easiest way to create a coroutine is to submit a callable to one of the concurrencpp executors. Executors then wrap the callable in a thin coroutine layer and schedule it to run. Coroutines can also be created from scratch - when a function returns any of concurrencpp::result or concurrencpp::null_resultand contains at least one co_await or co_return in it's body, the function is a concurrencpp coroutine. In our count-even example above, count_even is such coroutine. We first spawned count_even, then inside it the threadpool executor spawned more child coroutines, that were eventually joined using co_await.

Coroutines can start to run synchronously, in the caller thread. This kind of coroutines is called "regular coroutines". Concurrencpp coroutines can also start to run in parallel, inside a given executor, this kind of coroutines is called "parallel coroutines".

Executors

A concurrencpp executor is an object that is able to schedule and run coroutines. Executors simplify the work of managing resources such as threads, thread pools and task queues by decoupling them away from application code. Executors provide a unified way of scheduling and executing coroutines, since they all extend concurrencpp::executor.

executor API

class executor {
	/*
		Initializes a new executor and gives it a name.
	*/
	executor(std::string_view name);

	/*
		Destroys this executor.
	*/
	virtual ~executor() noexcept = default;

	/*
		The name of the executor, used for logging and debugging.
	*/
	const std::string name;

	/*
		Schedules a suspended coroutine to run in this executor. 
		Throws concurrencpp::errors::executor_shutdown exception if shutdown was called before.
	*/
	virtual void enqueue(std::experimental::coroutine_handle<> task) = 0;

	/*
		Schedules a range of suspended coroutines to run in this executor. 
		Throws concurrencpp::errors::executor_shutdown exception if shutdown was called before.
	*/	
	virtual void enqueue(std::span<std::experimental::coroutine_handle<>> tasks) = 0;

	/*
		Returns the maximum count of real OS threads this executor supports. 
		The actual count of threads this executor is running might be smaller than this number. 
		returns numeric_limits<int>::max if the executor does not have a limit for OS threads. 
	*/
	virtual int max_concurrency_level() const noexcept = 0;

	/* 
		Returns true if shutdown was called before, false otherwise. 
	*/ 
	virtual bool shutdown_requested() const noexcept = 0;

	/* 
		Shuts down the executor:
		- Tells underlying threads to exit their work loop and joins them.
		- Destroyes unexecuted coroutines.
		- Makes subsequent calls to enqueue, post, submit, bulk_post and 
			bulk_submit to throw concurrencpp::errors::executor_shutdown exception.
		- Makes shutdown_requested return true.
	*/
	virtual void shutdown() noexcept = 0;

	/*
		Turns a callable and its argument into a suspended coroutine and schedules it to run in this executor using enqueue.
		Arguments are passed into the coroutine by decaying them first.
 		Throws errors::executor_shutdown exception if shutdown has been called before.
	*/
	template<class callable_type, class ... argument_types>
	void post(callable_type&& callable, argument_types&& ... arguments);
	
	/*
		Like post, but returns a result object that marshals the asynchronous result.
		Throws errors::executor_shutdown exception if shutdown has been called before.
	*/
	template<class callable_type, class ... argument_types>
	result<type> submit(callable_type&& callable, argument_types&& ... arguments);

	/*
		Turns an array of callables into an array of suspended coroutines and schedules them to run in this executor using enqueue.
		Throws errors::executor_shutdown exception if shutdown has been called before.
	*/
	template<class callable_type>
	void bulk_post(std::span<callable_type> callable_list);

	/*
		Like bulk_post, but returns an array of result objects that marshal the asynchronous results.
		Throws errors::executor_shutdown exception if shutdown has been called before. 
	*/	
	template<class callable_type>
	std::vector<concurrencpp::result<type>> bulk_submit(std::span<callable_type> callable_list);
};

Executor types

As mentioned above, concurrencpp provides commonly used executors. These executor types are:

  • thread pool executor - a general purpose executor that maintains a pool of threads. The thread pool executor is suitable for short cpu-bound tasks that don't block. Applications are encouraged to use this executor as the default executor for non-blocking tasks. The concurrencpp thread pool provides dynamic thread injection and dynamic work balancing.

  • blocking executor - a threadpool executor with a larger pool of threads. Suitable for launching short blocking tasks like file io and db queries.

  • thread executor - an executor that launches each enqueued task to run on a new thread of execution. Threads are not reused. This executor is good for long running tasks, like objects that run a work loop, or long blocking operations.

  • worker thread executor - a single thread executor that maintains a single task queue. Suitable when applications want a dedicated thread that executes many related tasks.

  • manual executor - an executor that does not execute coroutines by itself. Application code can execute previously enqueued tasks by manually invoking its execution methods.

  • derivable executor - a base class for user defined executors. Although inheriting directly from concurrencpp::executor is possible, derivable_executor uses the CRTP pattern that provides some optimization opportunities for the compiler.

  • inline executor - mainly used to override the behavior of other executors. Enqueuing a task is equivalent to invoking it inline.

Using executors

The bare mechanism of an executor is encapsulated in its enqueue method. This method enqueues a suspended coroutine for execution and has two overloads: One overload receives a single coroutine_handle<> as an argument, and another that receives a span<coroutine_handle<>>. The second overload is used to enqueue a batch of suspended coroutines. This allows better scheduling heuristics and decreased contention.

Applications don't have to rely on enqueue alone, concurrencpp::executor provides an API for scheduling non-coroutines by converting them to a suspended coroutine first. Applications can request executors to return a result object that marshals the asynchronous result of the provided callable. This is done by calling executor::submit and execuor::bulk_submit. submit gets a callable, and returns a result object. executor::bulk_submit gets a span of callables and returns a vectorof result objects in a similar way submit works. In many cases, applications are not interested in the asynchronous value or exception. In this case, applications can use executor:::post and executor::bulk_post to schedule a callable or a span of callables to execute, but also tells the task to drop any returned value or thrown exception. Not marshaling the asynchronous result is faster than marshaling, but then we have no way of knowing the status or the result of the ongoing task.

post, bulk_post, submit and bulk_submit use enqueue behind the scenes for the underlying scheduling mechanism.

Result objects

Asynchronous values and exceptions can be consumed using the concurrencpp result objects. A result object is a conduit for the asynchronous result, like std::future. When a coroutine finishes execution, it either returns a valid value or throws an exception. In either case, this asynchronous result is marshaled to the consumer of the result object. The result status therefore, vary from idle (the asynchronous result or exception aren't ready yet) to value (the coroutine terminated by returning a valid value) to exception (the coroutine terminated by throwing an exception).

Result objects are a move-only type, and as such, they cannot be used after their content was moved to another result object. In this case, the result object is considered to be empty and attempts to call any method other than operator bool and operator = will throw. After the asynchronous result has been pulled out of the result object (by calling get, await or await_via), the result object becomes empty. Emptiness can be tested with operator bool.

Results can be polled, waited, awaited or resolved.

Result objects can be polled for their status by calling result::status.

Results can be waited by calling any of result::wait, result::wait_for, result::wait_until or result::get. Waiting a result is a blocking operation (in the case the asynchronous result is not ready), and will suspend the entire thread of execution waiting for the asynchronous result to become available. Waiting operations are generally discouraged and only allowed in root-level tasks and in contexts which allow it, like blocking the main thread waiting for the rest of the application to finish gracefully, or using concurrencpp::blocking_executor or concurrencpp::thread_executor.

Awaiting a result means to suspend the current coroutine until the asynchronous result is ready. If a valid value was returned from the coroutine, it is returend from the result object. If the coroutine threw an exception, it is re-thrown. At the moment of awaiting, if the result is already ready, the coroutine resumes immediately. Otherwise, it is resumed by the thread that sets the asynchronous result or exception.

The behaviour of awaiting a result object can be further fine tuned by using await_via. This method accepts an executor and a boolean flag (force_rescheduling). If, at the moment of awaiting, the result is already ready, the behavior depends on the value of force_rescheduling. If force_rescheduling is true, the coroutine is forcefully suspended and resumed inside the given executor. If force_rescheduling is false, the coroutine is resumed immediately in the calling thread. If the asynchronous result is not ready at the moment of awaiting, the coroutine resumed after the result is set, by scheduling it to run in the given exector.

Resolving a result is similar to awaiting it. The different is that the co_await expression will return the result object itself, in a non empty form, in a ready state. The asynchronous result can then be pulled by using get or co_await. Just like await_via, resolve_via fine tunes the control flow of the coroutine by passing an executor and a flag suggesting how to behave when the result is already ready.

Awaiting a result object by using co_await (and by doing so, turning the current function into a coroutine as well) is the preferred way of consuming result objects.

result API

class result{
	/*
		Creates an empty result that isn't associated with any task.
	*/
	result() noexcept = default;

	/*
		Destroyes the result. Associated tasks are not cancelled.
		The destructor does not block waiting for the asynchronous result to become ready.
	*/	
	~result() noexcept = default;

	/*
		Moves the content of rhs to *this. After this call, rhs is empty. 
	*/
	result(result&& rhs) noexcept = default;

	/*
		Moves the content of rhs to *this. After this call, rhs is empty. Returns *this.		
	*/
	result& operator = (result&& rhs) noexcept = default;

	/*
		Returns true if this is a non-empty result.
		Applications must not use this object if this->operator bool() is false. 
	*/
	operator bool() const noexcept;

	/*
		Queries the status of *this.
		The return value is any of result_status::idle, result_status::value or result_status::exception.
		Throws concurrencpp::errors::empty_result if *this is empty.		
	*/
	result_status status() const;

	/*
		Blocks the current thread of execution until this result is ready, when status() != result_status::idle.
		Throws concurrencpp::errors::empty_result if *this is empty.					
	*/
	void wait();

	/*
		Blocks until this result is ready or duration has passed. Returns the status of this result after unblocking.
		Throws concurrencpp::errors::empty_result if *this is empty.					
	*/
	template<class duration_unit, class ratio>
	result_status wait_for(std::chrono::duration<duration_unit, ratio> duration);

	/*
		Blocks until this result is ready or timeout_time has reached. Returns the status of this result after unblocking.
		Throws concurrencpp::errors::empty_result if *this is empty.					
	*/
	template< class clock, class duration >
	result_status wait_until(std::chrono::time_point<clock, duration> timeout_time);

	/*
		Blocks the current thread of execution until this result is ready, when status() != result_status::idle.
		If the result is a valid value, it is returned, otherwise, get rethrows the asynchronous exception.		
		Throws concurrencpp::errors::empty_result if *this is empty.					
	*/
	type get();

	/*
		Returns an awaitable used to await this result.
		If the result is already ready - the current coroutine resumes immediately in the calling thread of execution.
		If the result is not ready yet, the current coroutine is suspended and resumed when the asynchronous result is ready,
		by the thread which had set the asynchronous value or exception.
		In either way, after resuming, if the result is a valid value, it is returned. 
		Otherwise, operator co_await rethrows the asynchronous exception.
		Throws concurrencpp::errors::empty_result if *this is empty.							
	*/
	auto operator co_await();

	/*
		Returns an awaitable used to await this result.
		If the result is not ready yet, the current coroutine is suspended and resumed when the asynchronous result is ready,
		by scheduling the current coroutine via executor.
		If the result is already ready - the behaviour depends on the value of force_rescheduling:
			If force_rescheduling = true, then the current coroutine is forcefully suspended and resumed via executor.
			If force_rescheduling = false, then the current coroutine resumes immediately in the calling thread of execution.
		In either way, after resuming, if the result is a valid value, it is returned. 
		Otherwise, operator co_await rethrows the asynchronous exception.
		Throws concurrencpp::errors::empty_result if *this is empty.		
		Throws std::invalid_argument if executor is null.
		If this result is ready and force_rescheduling=true, throws any exception that executor::enqueue may throw.	
	*/
	auto await_via(
		std::shared_ptr<concurrencpp::executor> executor,
		bool force_rescheduling = true);

	/*
		Returns an awaitable used to resolve this result.
		After co_await expression finishes, *this is returned in a non-empty form, in a ready state.
		Throws concurrencpp::errors::empty_result if *this is empty.
	*/	
	auto resolve();

	/*
		Returns an awaitable used to resolve this result.
		If the result is not ready yet, the current coroutine is suspended and resumed when the asynchronous result is ready,
		by scheduling the current coroutine via executor.
		If the result is already ready - the behaviour depends on the value of force_rescheduling:
			If force_rescheduling = true, then the current coroutine is forcefully suspended and resumed via executor.
			If force_rescheduling = false, then the current coroutine resumes immediately in the calling thread of execution.
		In either way, after resuming, *this is returned in a non-empty form and guaranteed that its status is not result_status::idle.
		Throws concurrencpp::errors::empty_result if *this is empty.		
		Throws std::invalid_argument if executor is null.
		If this result is ready and force_rescheduling=true, throws any exception that executor::enqueue may throw.					
	*/
	auto resolve_via(
		std::shared_ptr<concurrencpp::executor> executor,
		bool force_rescheduling = true);
};

Parallel coroutines

Regular coroutines start to run synchronously in the calling thread of execution. Execution might shift to another thread of execution if the coroutine undergoes a rescheduling, for example by awaiting an unready result object inside it. concurrencpp also provide parallel coroutines, which start to run inside a given executor, not in the invoking thread of execution. This style of scheduling coroutines is especially helpful when writing parallel algorithms, recursive algorithms and concurrent algorithms that use the fork-join model.

Every parallel coroutine must meet the following preconditions:

  1. Returns any of result / null_result .
  2. Gets executor_tag as its first argument .
  3. Gets any of type* / type& / std::shared_ptr<type>, where type is a concrete class of executor as its second argument.
  4. Contains any of co_await or co_return in its body.

If all the above applies, the function is a parallel coroutine: concurrencpp will start the function suspended and immediately re-schedule it to run in the provided executor. concurrencpp::executor_tag is a dummy placeholder to tell the concurrencpp runtime that this function is not a regular function, it needs to start running inside the given executor. Applications can then consume the result of the parallel coroutine by using the returned result object.

Parallel Fibonacci example:

#include "concurrencpp/concurrencpp.h"
#include <iostream>

using namespace concurrencpp;

int fibonacci_sync(int i) {
	if (i == 0) {
		return 0;
	}

	if (i == 1) {
		return 1;
	}

	return fibonacci_sync(i - 1) + fibonacci_sync(i - 2);
}

result<int> fibonacci(executor_tag, std::shared_ptr<thread_pool_executor> tpe, const int curr) {
	if (curr <= 10) {
		co_return fibonacci_sync(curr);
	}

	auto fib_1 = fibonacci({}, tpe, curr - 1);
	auto fib_2 = fibonacci({}, tpe, curr - 2);

	co_return co_await fib_1 + co_await fib_2;
}

int main() {
	concurrencpp::runtime runtime;
	auto fibb_30 = fibonacci({}, runtime.thread_pool_executor(), 30).get();
	std::cout << "fibonacci(30) = " << fibb_30 << std::endl;
	return 0;
}

In this example, we calculate the 30-th member of the Fibonacci sequence in a parallel manner. We start launching each Fibonacci step in its own parallel coroutine. The first argument is a dummy executor_tag and the second argument is the threadpool executor. Every recursive step invokes a new parallel coroutine that runs in parallel. Each result is co_returned to its parent task and acquired by using co_await.
When we deem the input to be small enough to be calculated synchronously (when curr <= 10), we stop executing each recursive step in its own task and just solve the algorithm synchronously.

To compare, this is how the same code is written without using parallel coroutines, and relying on exector::submit alone. Since fibonacci returns a result<int>, submitting it recursively via executor::submit will result a result<result<int>>.

#include "concurrencpp/concurrencpp.h"
#include <iostream>

using namespace concurrencpp;

int fibonacci_sync(int i) {
    if (i == 0) {
        return 0;
    }

    if (i == 1) {
        return 1;
    }

    return fibonacci_sync(i - 1) + fibonacci_sync(i - 2);
}

result<int> fibonacci(std::shared_ptr<thread_pool_executor> tpe, const int curr) {
    if (curr <= 10) {
        co_return fibonacci_sync(curr);
    }

    auto fib_1 = tpe->submit(fibonacci, tpe, curr - 1);
    auto fib_2 = tpe->submit(fibonacci, tpe, curr - 2);

    co_return
	co_await co_await fib_1 +
        co_await co_await fib_2;
}

int main() {
    concurrencpp::runtime runtime;
    auto fibb_30 = fibonacci(runtime.thread_pool_executor(), 30).get();
    std::cout << "fibonacci(30) = " << fibb_30 << std::endl;
    return 0;
}

Result-promises

Result objects are the main way to pass data between threads in concurrencpp and we've seen how executors and coroutines produce such objects. Sometimes we want to use the capabilities of a result object with non-coroutines, for example when using a third-party library. In this case, we can complete a result object by using a result_promise. result_promise resembles a std::promise object - applications can manually set the asynchronous result or exception and make the associated result object become ready.

Just like result objects, result-promises are a move only type that becomes empty after move. Similarly, after setting a result or an exception, the result promise becomes empty as well. If a result-promise gets out of scope and no result/exception has been set, the result-promise destructor sets a concurrencpp::errors::broken_task exception using the set_exception method. Suspended and blocked tasks waiting for the associated result object are resumed/unblocked.

Result promises can convert callback style of code into async/await style of code: whenever a component requires a callback to marshal the asynchronous result, we can pass a callback that calls set_result or set_exception (depending on the asynchronous result itself) on the passed result promise, and return the associated result.

result_promise API

template <class type>
class result_promise {	
	/*
		Constructs a valid result_promise.
	*/
	result_promise();

	/*
		Moves the content of rhs to *this. After this call, rhs is empty.
	*/		
	result_promise(result_promise&& rhs) noexcept;

	/*
		Destroys *this, possibly setting a concurrencpp::errors::broken_task exception
		by calling set_exception if *this is not empty at the time of destruction.
	*/		
	~result_promise() noexcept;

	/*
		Moves the content of rhs to *this. After this call, rhs is empty. 
	*/		
	result_promise& operator = (result_promise&& rhs) noexcept;

	/*
		Returns true if this is a non-empty result-promise.
		Applications must not use this object if this->operator bool() is false. 
	*/
	explicit operator bool() const noexcept;

	/*
		Sets a value by constructing <<type>> from arguments... in-place. 
		Makes the associated result object become ready - tasks waiting for it to become ready are unblocked. 
		Suspended tasks are resumed either inline or via the executor that was provided by calling result::await_via or result::resolve_via.
		After this call, *this becomes empty.
		If *this is empty, a concurrencpp::errors::empty_result_promise exception is thrown.
	*/
	template<class ... argument_types>
	void set_result(argument_types&& ... arguments);
	
	/*
		Sets an exception.
		Makes the associated result object become ready - tasks waiting for it to become ready are unblocked.
		Suspended tasks are resumed either inline or via the executor that was provided by calling result::await_via or result::resolve_via.
		After this call, *this becomes empty.
		If *this is empty, a concurrencpp::errors::empty_result_promise exception is thrown.
		If exception_ptr is null, an std::invalid_argument exception is thrown.
	*/
	void set_exception(std::exception_ptr exception_ptr);

	/*
		A convenience method that invokes callable with arguments... and calls set_result with the result of the invocation. 
		If an exception is thrown, the thrown exception is caught and set instead by calling set_exception.
		After this call, *this becomes empty.
		If *this is empty, a concurrencpp::errors::empty_result_promise exception is thrown.			
	*/
	template<class callable_type, class ... argument_types>
	void set_from_function(callable_type&& callable, argument_types&& ... arguments);
	
	/*
		Gets the associated result object. 
		If *this is empty, a concurrencpp::errors::empty_result_promise exception is thrown.
		If this method had been called before, a concurrencpp::errors::result_already_retrieved exception is thrown.
	*/
	result<type> get_result();
};

Example: Marshaling asynchronous result using result_promise:

#include "concurrencpp/concurrencpp.h"

#include <iostream>

int main() {
	concurrencpp::result_promise<std::string> promise;
	auto result = promise.get_result();

	std::thread my_3_party_executor([promise = std::move(promise)] () mutable {
		std::this_thread::sleep_for(std::chrono::seconds(1)); //Imitate real work 
		promise.set_result("hello world");
	});

	auto asynchronous_string = result.get();
	std::cout << "result promise returned string: " << asynchronous_string << std::endl;

	my_3_party_executor.join();
}

In this example, We use std::thread as a third-party executor. This represents a scenario when a non-concurrencpp executor is used as part of the application life-cycle. We extract the result object before we pass the promise and block the main thread until the result becomes ready. In my_3_party_executor, we set a result as if we co_returned it.

Summery: using coroutines

A concurrencpp coroutine is a C++ suspendable function. It is eager, meaning it starts to run the moment it is invoked. It returns one of concurrencpp::result / concurrencpp::null_result and contains any of co_await or co_return in its body. Parallel coroutines are a special kind of coroutines, that start run in another thread, by passing a concurrencpp::executor_tag and an instance of a valid concurrencpp executor as the first arguments. Coroutines might return a result object that marshals the asynchronous result or exception. This way we can chain coroutines together, creating a bigger, asynchronous flow graph that doesn't block. Result objects might also be created by converting callables into coroutines using executor methods, or by using the result_promise type.

Result auxiliary functions

concurrencpp provides helper functions that help manipulate result objects directly:

/*
	Creates a ready result object by building <<type>> from arguments&&... in-place.
*/
template<class type, class ... argument_types>
result<type> make_ready_result(argument_types&& ... arguments);

/*
	An overload for void type. 
*/
result<void> make_ready_result();

/*
	Creates a ready result object from an exception pointer.
	The returned result object will re-throw exception_ptr when calling get, await or await_via.
	Throws std::invalid_argument if exception_ptr is null.
*/
template<class type>
result<type> make_exceptional_result(std::exception_ptr exception_ptr);

/*
	Overload. Similar to make_exceptional_result(std::exception_ptr),
	but gets an exception object directly.
*/
template<class type, class exception_type>
result<type> make_exceptional_result(exception_type exception);
 
/*
	Creates a result object that becomes ready when all the input results become ready. 
	Passed result objects are emptied and returned as a tuple.
	Throws std::invalid_argument if any of the passed result objects is empty.
*/
template<class ... result_types>
result<std::tuple<typename std::decay<result_types>::type...>> when_all(result_types&& ... results);

/*
	Overload. Similar to when_all(result_types&& ...) but receives a pair of iterators referencing a range. 
	Passed result objects are emptied and returned as a vector.
	If begin == end, the function returns immediately with an empty vector.
	Throws std::invalid_argument if any of the passed result objects is empty.
*/
template<class iterator_type>
result<std::vector<typename std::iterator_traits<iterator_type>::value_type>> 
when_all(iterator_type begin, iterator_type end);

/*
	Overload. Returns a ready result object that doesn't monitor any asynchronous result.
*/
result<std::tuple<>> when_all();

/*
	Helper struct returned from when_any.
	index is the position of the ready result in results sequence.
	results is either an std::tuple or an std::vector of the results that were passed to when_any.
*/
template <class sequence_type>
struct when_any_result {
	std::size_t index;
	sequence_type results;
};

/*
	Creates a result object that becomes ready when at least one of the input results is ready.
	Passed result objects are emptied and returned as a tuple.
	Throws std::invalid_argument if any of the passed result objects is empty.
*/
template<class ... result_types>
result<when_any_result<std::tuple<result_types...>>> when_any(result_types&& ... results);

/*
	Overload. Similar to when_any(result_types&& ...) but receives a pair of iterators referencing a range.
	Passed result objects are emptied and returned as a vector.
	Throws std::invalid_argument if begin == end.
	Throws std::invalid_argument if any of the passed result objects is empty.
*/
template<class iterator_type>
result<when_any_result<std::vector<typename std::iterator_traits<iterator_type>::value_type>>>
when_any(iterator_type begin, iterator_type end);

Timers and Timer queues

concurrencpp also provides timers and timer queues. Timers are objects that define actions running on an executor within a well-defined interval of time. There are three types of timers - regular timers, onshot-timers and delay objects.

Regular timers have four properties that define them:

  1. Callable - a callable that will be scheduled to run periodically.
  2. Executor - an executor that schedules the callable to run periodically.
  3. Due time - from the time of creation, the interval in milliseconds the timer will be scheduled to run for the first time.
  4. Frequency - from the time the timer was scheduled to run for the first time, the interval in milliseconds the callable will be schedule to run periodically, until the timer is destructed or cancelled.

A timer queue is a concurrencpp worker that manages a collection of timers and processes them in just one thread of execution. It is also the agent used to create new timers. When a timer deadline (whether it is due-time or frequency) has reached, the timer queue "fires" the timer by scheduling its callable to run on the associated executor. Just like executors, timer queues also adhere to the RAII concpet. When the runtime object gets out of scope, It shuts down the timer queue, cancelling all pending timers. After a timer queue has been shut down, any subsequent call to make_timer, make_onshot_timer and make_delay_object will throw an errors::timer_queue_shutdown exception. Applications must not try to shut down timer queues by themselves.

timer_queue API:

class timer_queue {
	/*
		Destroyes this timer_queue.
	*/
	~timer_queue() noexcept;
	
	/*
		Shuts down this timer_queue:
		Tells the underlying thread of execution to quit and joins it.
		Cancells all pending timers.
		After this call, invocation of any method besides shutdown and shutdown_requested will throw an errors::timer_queue_shutdown.
		If shutdown had been called before, this method has no effect.
	*/
	void shutdown() noexcept;

	/*
		Returns true if shutdown had been called before, false otherwise.
	*/
	bool shutdown_requested() const noexcept;

	/*
		Creates a new running timer where *this is associated timer_queue.
		Throws std::invalid_argument if executor is null.
		Throws errors::timer_queue_shutdown if shutdown had been called before.
	*/
	template<class callable_type, class ... argumet_types>
	timer make_timer(
		std::chrono::milliseconds due_time,
		std::chrono::milliseconds frequency,
		std::shared_ptr<concurrencpp::executor> executor,
		callable_type&& callable,
		argumet_types&& ... arguments);

	/*
		Creates a new one-shot timer where *this is associated timer_queue.
		Throws std::invalid_argument if executor is null.
		Throws errors::timer_queue_shutdown if shutdown had been called before.
	*/
	template<class callable_type, class ... argumet_types>
	timer make_one_shot_timer(
		std::chrono::milliseconds due_time,
		std::shared_ptr<concurrencpp::executor> executor,
		callable_type&& callable,
		argumet_types&& ... arguments);

	/*
		Creates a new delay object where *this is associated timer_queue.
		Throws std::invalid_argument if executor is null.
		Throws errors::timer_queue_shutdown if shutdown had been called before.
	*/
	result<void> make_delay_object(
		std::chrono::milliseconds due_time,
		std::shared_ptr<concurrencpp::executor> executor);
};

timer API:

class timer {
	/*
		Creates an empty timer.
	*/
	timer() noexcept = default;

	/*
		Cancels the timer, if not empty.
	*/
	~timer() noexcept;

	/*
		Moves the content of rhs to *this.
		rhs is empty after this call.
	*/
	timer(timer&& rhs) noexcept = default;

	/*
		Moves the content of rhs to *this.
		rhs is empty after this call.
		Returns *this.
	*/
	timer& operator = (timer&& rhs) noexcept;

	/*
		Cancels this timer.
		After this call, the associated timer_queue will not schedule *this to run again and *this becomes empty.
		This method has no effect if *this is empty or the associated timer_queue has already expired. 
	*/
	void cancel();

	/*
		Returns the associated executor of this timer.	
		Throws concurrencpp::errors::empty_timer is *this is empty.
	*/
	std::shared_ptr<executor> get_executor() const;

	/*
		Returns the associated timer_queue of this timer.
		Throws concurrencpp::errors::empty_timer is *this is empty.
	*/
	std::weak_ptr<timer_queue> get_timer_queue() const;

	/*
		Returns the due time of this timer.
		Throws concurrencpp::errors::empty_timer is *this is empty.
	*/
	std::chrono::milliseconds get_due_time() const;

	/*
		Returns the frequency of this timer.	
		Throws concurrencpp::errors::empty_timer is *this is empty.
	*/
	std::chrono::milliseconds get_frequency() const;

	/*
		Sets new frequency for this timer.
		Callables already scheduled to run at the time of invocation are not affected.	
		Throws concurrencpp::errors::empty_timer is *this is empty.
	*/
	void set_frequency(std::chrono::milliseconds new_frequency);

	/*
		Returns true is *this is not an empty timer, false otherwise.
		The timer should not be used if this->operator bool() is false.
	*/
	operator bool() const noexcept;
};

Regular timer example:

#include "concurrencpp/concurrencpp.h"

#include <iostream>

using namespace std::chrono_literals;

int main() {
	concurrencpp::runtime runtime;
	std::atomic_size_t counter = 1;
	concurrencpp::timer timer = runtime.timer_queue()->make_timer(
		1500ms,
		2000ms,
		runtime.thread_pool_executor(),
		[&] {
			const auto c = counter.fetch_add(1);
			std::cout << "timer was invoked for the " << c << "th time" << std::endl;
		});

	std::this_thread::sleep_for(12s);
	return 0;
}

In this example we create a regular timer by using the timer queue. The timer schedules its callable after 1.5 seconds, then fires its callable every 2 seconds. The given callable runs in the threadpool executor.

Oneshot timers

A oneshot timer is a one-time timer with only a due time - after it schedules its callable to run once it never reschedules it to run again.

Oneshot timer example:

#include "concurrencpp/concurrencpp.h"

#include <iostream>

using namespace std::chrono_literals;

int main() {
	concurrencpp::runtime runtime;
	concurrencpp::timer timer = runtime.timer_queue()->make_one_shot_timer(
		3000ms,
		runtime.thread_executor(),
		[&] {
			std::cout << "hello and goodbye" << std::endl;
		});

	std::this_thread::sleep_for(4s);
	return 0;
}

In this example, we create a timer that runs only once - after 3 seconds from its creation, the timer will schedule to run its callable on a new thread of execution (using concurrencpp::thread_executor).

Delay objects

A delay object is a result object that becomes ready when its due time is reached. Applications can co_await this result object to delay the current task in a non-blocking way. The current coroutine is resumed by the executor that was passed to make_delay_object.

Delay object example:

#include "concurrencpp/concurrencpp.h"

#include <iostream>

using namespace std::chrono_literals;

concurrencpp::null_result delayed_task(
	std::shared_ptr<concurrencpp::timer_queue> tq,
	std::shared_ptr<concurrencpp::thread_pool_executor> ex) {
	size_t counter = 1;

	while(true) {
		std::cout << "task was invoked " << counter << " times." << std::endl;
		counter++;

		co_await tq->make_delay_object(1500ms, ex);
	}
}

int main() {
	concurrencpp::runtime runtime;
	delayed_task(runtime.timer_queue(), runtime.thread_pool_executor());

	std::this_thread::sleep_for(10s);
	return 0;
}

In this example, we created a coroutine (that does not marshal any result or thrown exception), which delays itself in a loop by calling co_await on a delay object.

The runtime object

The concurrencpp runtime object is the agent used to acquire, store and create new executors.
The runtime must be created as a value type as soon as the main function starts to run. When the concurrencpp runtime gets out of scope, it iterates over its stored executors and shuts them down one by one by calling executor::shutdown. Executors then exit their inner work loop and any subsequent attempt to schedule a new task will throw a concurrencpp::executor_shutdown exception. The runtime also contains the global timer queue used to create timers and delay objects. Upon destruction, stored executors will destroy unexecuted tasks, and wait for ongoing tasks to finish. If an ongoing task tries to use an executor to spawn new tasks or schedule its own task continuation - an exception will be thrown. In this case, ongoing tasks need to quit as soon as possible, allowing their underlying executors to quit. The timer queue will also be shut down, cancelling all running timers. With this RAII style of code, no tasks can be processed before the creation of the runtime object, and while/after the runtime gets out of scope. This frees concurrent applications from needing to communicate termination messages explicitly. Tasks are free use executors as long as the runtime object is alive.

runtime API

class runtime {
	/*
		Creates a runtime object with default options.	
	*/
	runtime();

	/*
		Creates a runtime object with user defined options.
	*/
	runtime(const concurrencpp::runtime_options& options);

	/*
		Destroys this runtime object. 
		Calls executor::shutdown on each monitored executor.
		Calls timer_queue::shutdown on the global timer queue.
	*/
	~runtime() noexcept;

	/*
		Returns this runtime timer queue used to create new times.
	*/
	std::shared_ptr<concurrencpp::timer_queue> timer_queue() const noexcept;

	/*
		Returns this runtime concurrencpp::inline_executor
	*/
	std::shared_ptr<concurrencpp::inline_executor> inline_executor() const noexcept;

	/*
		Returns this runtime concurrencpp::thread_pool_executor
	*/
	std::shared_ptr<concurrencpp::thread_pool_executor> thread_pool_executor() const noexcept;

	/*
		Returns this runtime concurrencpp::background_executor
	*/
	std::shared_ptr<concurrencpp::thread_pool_executor> background_executor() const noexcept;

	/*
		Returns this runtime concurrencpp::thread_executor
	*/
	std::shared_ptr<concurrencpp::thread_executor> thread_executor() const noexcept;

	/*
		Creates a new concurrencpp::worker_thread_executor and registers it in this runtime.
		Might throw std::bad_alloc or std::system_error if any underlying memory or system resource could not have been acquired.
	*/
	std::shared_ptr<concurrencpp::worker_thread_executor> make_worker_thread_executor();

	/*
		Creates a new concurrencpp::manual_executor and registers it in this runtime.
		Might throw std::bad_alloc or std::system_error if any underlying memory or system resource could not have been acquired.
	*/
	std::shared_ptr<concurrencpp::manual_executor> make_manual_executor();

	/*
		Creates a new user defined executor and registers it in this runtime.
		executor_type must be a valid concrete class of concurrencpp::executor.
		Might throw std::bad_alloc if no memory is available.
		Might throw any exception that the constructor of <<executor_type>> might throw. 
	*/
	template<class executor_type, class ... argument_types>
	std::shared_ptr<executor_type> make_executor(argument_types&& ... arguments);

	/*
		returns the version of concurrencpp that the library was built with.
	*/
	static std::tuple<unsigned int, unsigned int, unsigned int> version() noexcept;
};

Creating user-defined executors

As mentioned before, Applications can create their own custom executor type by inheriting the derivable_executor class. There are a few points to consider when implementing user defined executors: The most important thing is to remember that executors are used from multiple threads, so implemented methods must be thread-safe. Another important point is to handle shutdown correctly: shutdown, shutdown_requested and enqueue should all monitor the executor state and behave accordingly when invoked:

  • shutdown should tell underlying threads to quit and then join them. shutdown must also destroy each unexecuted coroutine_handle by calling coroutine_handle::destroy. shutdown might be called multiple times, and the method must handle this scenario by ignoring any subsequent call to shutdown after the first invocation.
  • enqueue must throw a concurrencpp::errors::executor_shutdown exception if shutdown had been called before. Coroutine handles that are passed to enqueue are expected to be non-finally-suspending coroutines, meaning that when a coroutine ends, it cleans after itself. Executors must not call coroutine_handle::destroy on coroutines that finished execution gracefully. Explicit destruction of coroutines happens only to unexecuted suspended-coroutines, when shutting down the executor.

In any case, new executors can be created using runtime::make_executor. Applications must not create new executors with plain instantiation (such as std::make_shared or plain new), only by using runtime::make_executor. Also, applications must not try to re-instantiate the built-in concurrencpp executors, like the threadpool or the thread executors, those executors must only be accessed through their instance in the runtime object.

Example: using a user-defined executor:

#include "concurrencpp/concurrencpp.h"

#include <iostream>
#include <queue>
#include <thread>
#include <mutex>
#include <condition_variable>

class logging_executor : public concurrencpp::derivable_executor<logging_executor> {

private:
	mutable std::mutex _lock;
	std::queue<std::experimental::coroutine_handle<>> _queue;
	std::condition_variable _condition;
	bool _shutdown_requested;
	std::thread _thread;
	const std::string _prefix;

	void work_loop() {
		while (true) {
			std::unique_lock<std::mutex> lock(_lock);
			if (_shutdown_requested) {
				return;
			}

			if (!_queue.empty()) {
				auto task = _queue.front();
				_queue.pop();
				lock.unlock();
				std::cout << _prefix << " A task is being executed" << std::endl;
				task();
				continue;
			}

			_condition.wait(lock, [this] {
				return !_queue.empty() || _shutdown_requested;
			});
		}
	}

public:
	logging_executor(std::string_view prefix) :
		derivable_executor<logging_executor>("logging_executor"),
		_shutdown_requested(false),
		_prefix(prefix) {
		_thread = std::thread([this] {
			work_loop();
		});
	}

	void enqueue(std::experimental::coroutine_handle<> task) override {
		std::cout << _prefix << " A task is being enqueued!" << std::endl;

		std::unique_lock<std::mutex> lock(_lock);
		if (_shutdown_requested) {
			throw concurrencpp::errors::executor_shutdown("logging executor - executor was shutdown.");
		}

		_queue.emplace(task);
		_condition.notify_one();
	}

	void enqueue(std::span<std::experimental::coroutine_handle<>> tasks) override {
		std::cout << _prefix << tasks.size() << " tasks are being enqueued!" << std::endl;

		std::unique_lock<std::mutex> lock(_lock);
		if (_shutdown_requested) {
			throw concurrencpp::errors::executor_shutdown("logging executor - executor was shutdown.");
		}

		for (auto task : tasks) {
			_queue.emplace(task);
		}

		_condition.notify_one();
	}

	int max_concurrency_level() const noexcept override {
		return 1;
	}

	bool shutdown_requested() const noexcept override {
		std::unique_lock<std::mutex> lock(_lock);
		return _shutdown_requested;
	}

	void shutdown() noexcept override {
		std::cout << _prefix << " shutdown requested" << std::endl;

		std::unique_lock<std::mutex> lock(_lock);
		if (_shutdown_requested) return; //nothing to do.
		_shutdown_requested = true;

		while(!_queue.empty()) {
			auto task = _queue.front();
			_queue.pop();

			task.destroy();
		}

		lock.unlock();

		_condition.notify_one();
		_thread.join();
	}
};

int main() {
	concurrencpp::runtime runtime;
	auto logging_ex = runtime.make_executor<logging_executor>("Session #1234");

	for (size_t i = 0; i < 10; i++) {
		logging_ex->post([] {
			std::cout << "hello world" << std::endl;
		});
	}

	std::getchar();
	return 0;
}

In this example, we created an executor which logs actions like enqueuing a task or executing it. We implement the executor interface, and we request the runtime to create, store and monitor an instance of it by calling runtime::make_executor. The rest of the application behaves exactly the same as if we were to use non user-defined executors.

Supported platforms and tools

  • Operating systems: Linux, macOS, Windows (Windows 10 and above)
  • Compilers: MSVC (Visual Studio 2019 and above), Clang (clang-9 and above, recommended version: clang-11 and above)

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