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[container] New container proposal: boost::container::hub, request for endorsement
by Joaquin M López Muñoz 03 Feb '26

03 Feb '26

Hi, I've been writing and benchmarking (candidate) boost::container::hub, a nearly drop-in replacement of C++26 std::hive that has excellent performance: https://github.com/joaquintides/hub/blob/develop/README.md#performance (The reason I didn't name it "hive" is because hub is not 100% conformant to std::hive spec, details at the repo linked above.) Is there interest in having this in Boost? If so, please endorse the submission! As the codebase is fairly small (single 1800-LOC header), and due to the subject matter, my inclination is to propose it as part of Boost.Container rather than as a separate library. Happy to discuss this proposal and its technical details. Looking forward to your feedback. Best, Joaquín M López Muñoz

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How to Understand C++ Coroutines from the Ground Up
by Vinnie Falco 02 Feb '26

02 Feb '26

I've been working on a family of libraries which are based on C++ 20 coroutines. I realize, that a lot of folks may not be familiar with this language feature as it is relatively new and the standard library also did not ship with the components needed to make use of the feature without additional third party libraries. I have worked up a tutorial to teach how to use coroutines. I hope someone finds this valuable. How To Understand C++20 Coroutines from the Ground Up <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#how-to…> Introduction <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#introd…> For over two decades, C++ programmers have wrestled with a fundamental challenge: how to write code that waits for things to happen without blocking everything else. Network requests need to complete. Files need to be read. User input must arrive. The traditional solutions—threads, callbacks, and state machines—each carry their own burden of complexity. Threads consume system resources and require careful synchronization. Callbacks scatter your logic across multiple functions. State machines bury simple ideas beneath layers of bookkeeping. C++20 introduces *coroutines*, a language feature that addresses this challenge directly. A coroutine is a function that can suspend its execution midway through, preserve its state, and resume later from exactly where it left off. This capability transforms the way you write asynchronous code, allowing you to express complex sequences of operations as straightforward, linear logic. In this tutorial, you will explore C++20 coroutines from the most basic concepts to practical implementations. You will begin by understanding the problem coroutines solve, then build your first coroutine step by step. By the end, you will have constructed a working generator type and understand the machinery that makes coroutines possible. Prerequisites <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#prereq…> Before beginning this tutorial, you should have the following: - A C++ compiler with C++20 support (GCC 10+, Clang 14+, or MSVC 2019 16.8+) - Familiarity with basic C++ concepts: functions, classes, templates, and lambdas - Understanding of how function calls work: the call stack, local variables, and return values - A text editor or IDE configured for C++ development The examples in this tutorial use standard C++20 features. If using GCC, compile with: g++ -std=c++20 -fcoroutines your_file.cpp If using Clang, compile with: clang++ -std=c++20 your_file.cpp If using MSVC, enable C++20 in your project settings or compile with: cl /std:c++20 your_file.cpp Step 1 — Understanding the Problem Coroutines Solve <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-1…> Before diving into coroutines, you must understand why they exist. Consider a server application that needs to handle an incoming network request. The server must read the request from the network, parse it, possibly read from a database, compute a response, and send that response back. Each of these steps might take time to complete. In traditional synchronous code, you might write something like this: void handle_request(connection& conn) { std::string request = conn.read(); // blocks until data arrives auto parsed = parse_request(request); auto data = database.query(parsed.id); // blocks until database responds auto response = compute_response(data); conn.write(response); // blocks until write completes } This code reads naturally from top to bottom. The logic flows in a straight line. But there is a problem: while waiting for the network or database, this function blocks the entire thread. If you have thousands of concurrent connections, you would need thousands of threads, each consuming memory and requiring the operating system to schedule them. The traditional alternative uses callbacks: void handle_request(connection& conn) { conn.async_read([&conn](std::string request) { auto parsed = parse_request(request); database.async_query(parsed.id, [&conn](auto data) { auto response = compute_response(data); conn.async_write(response, [&conn]() { // request complete }); }); }); } This code does not block. Each operation starts, registers a callback, and returns immediately. When the operation completes, the callback runs. But look what has happened to the code: three levels of nesting, logic scattered across multiple lambda functions, and local variables that cannot be shared between callbacks without careful lifetime management. David Mazières, in his exploration of C++ coroutines, described the pain of this approach vividly. In his SMTP server code, a single logical operation named cmd_rcpt had to be split across seven separate functions: cmd_rcpt, cmd_rcpt_0, cmd_rcpt_2, cmd_rcpt_3, cmd_rcpt_4, cmd_rcpt_5, and cmd_rcpt_6. Each function represented a different return point from an asynchronous operation. The logic of a single command was scattered across the codebase. Coroutines solve this problem by allowing you to write code that looks synchronous but behaves asynchronously: task<void> handle_request(connection& conn) { std::string request = co_await conn.async_read(); auto parsed = parse_request(request); auto data = co_await database.async_query(parsed.id); auto response = compute_response(data); co_await conn.async_write(response); } This code reads just like the original blocking version. The logic flows from top to bottom. Local variables like request, parsed, and data exist naturally in their scope. Yet the function suspends at each co_await point, allowing other work to proceed while waiting. The variable request maintains its value even though the function may suspend and resume multiple times. This is the fundamental capability that coroutines provide: the preservation of local state across suspension points. You have now seen the problem that coroutines solve. The callback approach fragments your logic. Coroutines restore the natural flow of code while maintaining asynchronous behavior. Step 2 — Recognizing Coroutines by Their Keywords <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-2…> A coroutine in C++20 looks almost like a regular function. The difference lies in what appears inside the function body. A function becomes a coroutine when it contains any of three special keywords: co_await, co_yield, or co_return. The keyword co_await suspends the coroutine and waits for some operation to complete. When you write co_await expr, the coroutine saves its state, pauses execution, and potentially allows other code to run. When the awaited operation completes, the coroutine resumes from exactly where it left off. The keyword co_yield produces a value and suspends the coroutine. This is useful for generators—functions that produce a sequence of values one at a time. After yielding a value, the coroutine pauses until someone asks for the next value. The keyword co_return completes the coroutine and optionally provides a final result. Unlike a regular return statement, co_return interacts with the coroutine machinery to properly finalize the coroutine's state. Here is the simplest possible coroutine: #include <coroutine> struct SimpleCoroutine { struct promise_type { SimpleCoroutine get_return_object() { return {}; } std::suspend_never initial_suspend() { return {}; } std::suspend_never final_suspend() noexcept { return {}; } void return_void() {} void unhandled_exception() {} }; }; SimpleCoroutine my_first_coroutine() { co_return; // This makes it a coroutine } Do not worry about the promise_type structure yet. You will explore it in detail later. For now, observe that the presence of co_return transforms what looks like a regular function into a coroutine. If you try to compile a function with these keywords but without proper infrastructure, the compiler will produce errors. The C++ coroutine mechanism requires certain types and functions to exist. This is why the example includes the promise_type nested structure—it provides the minimum scaffolding the compiler needs. The distinction between regular functions and coroutines matters because they behave fundamentally differently at runtime: - A regular function allocates its local variables on the stack. When it returns, those variables are gone. - A coroutine allocates its local variables in a heap-allocated *coroutine frame*. When it suspends, those variables persist. When it resumes, they are still there. This persistence of state is what allows coroutines to pause and resume while maintaining their local variables. You have now learned to recognize coroutines by their keywords. The presence of co_await, co_yield, or co_return signals that a function is a coroutine with special runtime behavior. Step 3 — Understanding Suspension and Resumption <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-3…> The heart of coroutines is the ability to suspend execution and resume it later. To understand how this works, you must examine what happens when a coroutine suspends. When you call a regular function, the system allocates space on the call stack for the function's local variables and parameters. When the function returns, this stack space is reclaimed. The function's state exists only during the call. When you call a coroutine, something different happens. The system allocates a *coroutine frame* on the heap. This frame holds the coroutine's local variables, parameters, and information about where execution should resume. Because the frame lives on the heap rather than the stack, it persists even when the coroutine is not actively running. Consider this example: #include <coroutine> #include <iostream> struct ReturnObject { struct promise_type { ReturnObject get_return_object() { return {}; } std::suspend_never initial_suspend() { return {}; } std::suspend_never final_suspend() noexcept { return {}; } void return_void() {} void unhandled_exception() {} }; }; struct Awaiter { std::coroutine_handle<>* handle_out; bool await_ready() { return false; } void await_suspend(std::coroutine_handle<> h) { *handle_out = h; } void await_resume() {} }; ReturnObject counter(std::coroutine_handle<>* handle) { Awaiter awaiter{handle}; for (unsigned i = 0; ; ++i) { std::cout << "counter: " << i << std::endl; co_await awaiter; } } int main() { std::coroutine_handle<> h; counter(&h); for (int i = 0; i < 3; ++i) { std::cout << "main: resuming" << std::endl; h(); } h.destroy(); } Output: counter: 0 main: resuming counter: 1 main: resuming counter: 2 main: resuming counter: 3 Study what happens in this example: 1. The main function calls counter, passing the address of a coroutine handle. 2. The counter coroutine begins executing. It prints "counter: 0" and then reaches co_await awaiter. 3. The co_await expression checks if the awaiter is ready by calling await_ready(). It returns false, so suspension proceeds. 4. The coroutine saves its state—including the value of i—to the coroutine frame. 5. The await_suspend method receives a handle to the suspended coroutine and stores it in main's variable h. 6. Control returns to main, which now holds a handle to the suspended coroutine. 7. The main function calls h(), which resumes the coroutine. 8. The coroutine continues from where it left off, increments i, prints its new value, and suspends again. 9. This cycle repeats until main destroys the coroutine. The variable i inside counter maintains its value across all these suspension and resumption cycles. It starts at 0, increments to 1, then 2, then 3. Each time the coroutine resumes, i is exactly where it was when the coroutine suspended. A std::coroutine_handle<> is a lightweight object, similar to a pointer. It references the coroutine frame on the heap. Calling the handle (using h() or h.resume()) resumes the coroutine. The handle does not own the coroutine frame—you must eventually call h.destroy() to free the memory. The Awaiter type in this example demonstrates the three methods that co_await uses: - await_ready(): Returns true if the result is immediately available and no suspension is needed. Returns false to proceed with suspension. - await_suspend(handle): Called when the coroutine suspends. Receives the coroutine handle, allowing external code to later resume the coroutine. - await_resume(): Called when the coroutine resumes. Its return value becomes the value of the co_await expression. The C++ standard library provides two predefined awaiters: std::suspend_always and std::suspend_never. As their names suggest, suspend_always::await_ready() always returns false (always suspend), while suspend_never::await_ready() always returns true (never suspend). You have now seen how suspension and resumption work. The coroutine frame preserves state on the heap, and the coroutine handle provides a way to resume execution. Step 4 — Understanding the Promise Type <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-4…> Every coroutine has an associated *promise type*. This type acts as a controller for the coroutine, defining how it behaves at key points in its lifecycle. The promise type is not something you pass to the coroutine—it is a nested type inside the coroutine's return type that the compiler uses automatically. The compiler expects to find a type named promise_type nested inside your coroutine's return type. If your coroutine returns Generator<int>, the compiler looks for Generator<int>::promise_type. This promise type must provide certain methods that the compiler calls at specific points during the coroutine's execution. Here are the required methods: get_return_object(): Called to create the object that will be returned to the caller of the coroutine. This happens before the coroutine body begins executing. initial_suspend(): Called immediately after get_return_object(). Returns an awaiter that determines whether the coroutine should suspend before running any of its body. Return std::suspend_never{} to start executing immediately, or std::suspend_always{} to suspend before the first statement. final_suspend(): Called when the coroutine completes (either normally or via exception). Returns an awaiter that determines whether to suspend one last time or destroy the coroutine state immediately. This method must be noexcept. return_void() or return_value(v): Called when the coroutine executes co_return or falls off the end of its body. Use return_void() if the coroutine does not return a value; use return_value(v) if it does. You must provide exactly one of these, matching how your coroutine returns. unhandled_exception(): Called if an exception escapes the coroutine body. Typically you either rethrow the exception, store it for later, or terminate the program. The compiler transforms your coroutine body into something resembling this pseudocode: { promise_type promise; auto return_object = promise.get_return_object(); co_await promise.initial_suspend(); try { // your coroutine body goes here } catch (...) { promise.unhandled_exception(); } co_await promise.final_suspend(); }// coroutine frame is destroyed when control flows off the end This transformation reveals important details. The return object is created before initial_suspend() runs, so it is available even if the coroutine suspends immediately. The final_suspend() determines whether the coroutine frame persists after completion—if it returns suspend_always, you must manually destroy the coroutine; if it returns suspend_never, the frame is destroyed automatically. Consider this example that demonstrates promise type behavior: #include <coroutine> #include <iostream> struct TracePromise { struct promise_type { promise_type() { std::cout << "promise constructed" << std::endl; } ~promise_type() { std::cout << "promise destroyed" << std::endl; } TracePromise get_return_object() { std::cout << "get_return_object called" << std::endl; return {}; } std::suspend_never initial_suspend() { std::cout << "initial_suspend called" << std::endl; return {}; } std::suspend_always final_suspend() noexcept { std::cout << "final_suspend called" << std::endl; return {}; } void return_void() { std::cout << "return_void called" << std::endl; } void unhandled_exception() { std::cout << "unhandled_exception called" << std::endl; } }; std::coroutine_handle<promise_type> handle; }; TracePromise trace_coroutine() { std::cout << "coroutine body begins" << std::endl; co_return; } int main() { std::cout << "calling coroutine" << std::endl; auto result = trace_coroutine(); std::cout << "coroutine returned" << std::endl; } Output: calling coroutine promise constructed get_return_object called initial_suspend called coroutine body begins return_void called final_suspend called coroutine returned Notice that the promise is constructed first, then get_return_object() creates the return value, then initial_suspend() runs. Since initial_suspend() returns suspend_never, the coroutine body executes immediately. After co_return, return_void() is called, followed by final_suspend(). Since final_suspend() returns suspend_always, the coroutine suspends one last time, and the promise is not destroyed until the coroutine handle is explicitly destroyed. One important warning: if your coroutine can fall off the end of its body without executing co_return, and your promise type lacks a return_void() method, the behavior is undefined. This is a dangerous pitfall. Always ensure your promise type has return_void() if there is any code path that might reach the end of the coroutine body without an explicit co_return. You have now learned how the promise type controls coroutine behavior. The methods on the promise type let you customize initialization, suspension, value delivery, and cleanup. Step 5 — Building a Generator with co_yield <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-5…> One of the most common uses for coroutines is building *generators*—functions that produce a sequence of values on demand. Instead of computing all values upfront and storing them in a container, a generator computes each value when requested. The co_yield keyword makes this pattern elegant. When a coroutine executes co_yield value, it delivers the value to its caller and suspends. The next time the coroutine resumes, it continues from just after the co_yield. Here is how co_yield works internally. The expression co_yield value is transformed by the compiler into: co_await promise.yield_value(value) The yield_value method is a new method you must add to your promise type. It receives the yielded value, typically stores it somewhere accessible, and returns an awaiter (usually std::suspend_always) to suspend the coroutine. Here is a complete generator example: #include <coroutine> #include <iostream> struct Generator { struct promise_type { int current_value; Generator get_return_object() { return Generator{ std::coroutine_handle<promise_type>::from_promise(*this) }; } std::suspend_always initial_suspend() { return {}; } std::suspend_always final_suspend() noexcept { return {}; } std::suspend_always yield_value(int value) { current_value = value; return {}; } void return_void() {} void unhandled_exception() { std::terminate(); } }; std::coroutine_handle<promise_type> handle; Generator(std::coroutine_handle<promise_type> h) : handle(h) {} ~Generator() { if (handle) handle.destroy(); } // Disable copying Generator(const Generator&) = delete; Generator& operator=(const Generator&) = delete; // Enable moving Generator(Generator&& other) noexcept : handle(other.handle) { other.handle = nullptr; } Generator& operator=(Generator&& other) noexcept { if (this != &other) { if (handle) handle.destroy(); handle = other.handle; other.handle = nullptr; } return *this; } bool next() { if (!handle || handle.done()) return false; handle.resume(); return !handle.done(); } int value() const { return handle.promise().current_value; } }; Generator count_to(int n) { for (int i = 1; i <= n; ++i) { co_yield i; } } int main() { auto gen = count_to(5); while (gen.next()) { std::cout << gen.value() << std::endl; } } Output: 1 2 3 4 5 Study the key parts of this example: The yield_value method stores the yielded value in current_value and returns suspend_always to pause the coroutine after each yield. The initial_suspend returns suspend_always, which means the coroutine suspends before executing any of its body. This is important—it means the first call to next() is what starts the coroutine running. The get_return_object method creates the Generator object and stores a handle to the coroutine. Notice the expression std::coroutine_handle<promise_type>::from_promise(*this). This static method creates a coroutine handle from a reference to the promise object. Since the promise object lives inside the coroutine frame at a known offset, this conversion is possible. The Generator class manages the coroutine handle's lifetime. The destructor calls handle.destroy() to free the coroutine frame. The class disables copying (copying handles would be problematic) but enables moving. The next() method resumes the coroutine and returns true if the coroutine produced a value, or false if the coroutine has completed. The value() method retrieves the most recently yielded value from the promise. Here is a more interesting generator that produces the Fibonacci sequence: Generator fibonacci() { int a = 0, b = 1; while (true) { co_yield a; int next = a + b; a = b; b = next; } } int main() { auto fib = fibonacci(); for (int i = 0; i < 10 && fib.next(); ++i) { std::cout << fib.value() << " "; } std::cout << std::endl; } Output: 0 1 1 2 3 5 8 13 21 34 The Fibonacci generator runs an infinite loop internally. It will produce values forever. But because it yields and suspends after each value, the caller controls when (and whether) to ask for more values. The generator only computes values on demand. This is the power of generators. The variables a and b persist across yields because they live in the coroutine frame on the heap. Each call to next() resumes the coroutine, which computes the next Fibonacci number, yields it, and suspends again. You have now built a working generator using co_yield. The promise type's yield_value method receives yielded values, and the Generator class provides an interface for retrieving them. Step 6 — Understanding Return Objects and Coroutine Handles <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-6…> You have seen coroutine handles and return objects in previous examples. Now you will examine them more closely to understand their relationship and how information flows between them. A *coroutine handle* (std::coroutine_handle<>) is a lightweight object that refers to a suspended coroutine. It is similar to a pointer: it does not own the memory it references, and copying it does not copy the coroutine. You can resume the coroutine by calling the handle (using handle() or handle.resume()), query whether the coroutine has completed with handle.done(), and destroy the coroutine frame with handle.destroy(). The coroutine handle is a template. std::coroutine_handle<> (equivalent to std::coroutine_handle<void>) is the most basic form—it can reference any coroutine but provides no access to the promise object. std::coroutine_handle<PromiseType> is a more specific form that knows about a particular promise type. This typed handle can be converted to the void handle, and it provides a promise() method that returns a reference to the promise object. The *return object* is what the caller receives when calling a coroutine. It is the type that appears in the coroutine's declaration. When you write: Generator my_coroutine() { co_yield 42; } The return type is Generator, and when you call my_coroutine(), you receive a Generator object. The return object is created by calling promise.get_return_object() before the coroutine body begins. This happens early in the coroutine's lifecycle, giving the return object a chance to capture the coroutine handle. Here is the sequence: 1. The coroutine frame is allocated on the heap. 2. The promise object is constructed inside the frame. 3. promise.get_return_object() is called, creating the return object. 4. co_await promise.initial_suspend() executes. 5. The coroutine body begins (if initial_suspend did not suspend). 6. The return object is given to the caller. The key insight is that get_return_object() runs before initial_suspend(). This means: - If initial_suspend() returns suspend_always, the coroutine suspends before any user code runs, but the return object already exists and contains the coroutine handle. - If initial_suspend() returns suspend_never, the coroutine runs immediately, and the return object is still created first. Inside get_return_object(), you can obtain the coroutine handle using the static method coroutine_handle::from_promise(*this). Since get_return_object() is called on the promise object (as this), this method returns a handle to the coroutine containing that promise. Here is an example that demonstrates the relationship: #include <coroutine> #include <iostream> struct Task { struct promise_type { Task get_return_object() { std::cout << "Creating return object" << std::endl; return Task{ std::coroutine_handle<promise_type>::from_promise(*this) }; } std::suspend_always initial_suspend() { std::cout << "Initial suspend" << std::endl; return {}; } std::suspend_always final_suspend() noexcept { std::cout << "Final suspend" << std::endl; return {}; } void return_void() {} void unhandled_exception() {} }; std::coroutine_handle<promise_type> handle; Task(std::coroutine_handle<promise_type> h) : handle(h) {} ~Task() { if (handle) handle.destroy(); } Task(Task&& other) noexcept : handle(other.handle) { other.handle = nullptr; } void resume() { handle.resume(); } bool done() const { return handle.done(); } }; Task example_task() { std::cout << "Task body: part 1" << std::endl; co_await std::suspend_always{}; std::cout << "Task body: part 2" << std::endl; } int main() { std::cout << "Before calling coroutine" << std::endl; Task task = example_task(); std::cout << "After calling coroutine, before first resume" << std::endl; task.resume(); std::cout << "After first resume, before second resume" << std::endl; task.resume(); std::cout << "After second resume" << std::endl; } Output: Before calling coroutine Creating return object Initial suspend After calling coroutine, before first resume Task body: part 1 After first resume, before second resume Task body: part 2 Final suspend After second resume Follow the execution flow: 1. Before example_task() is called, nothing has happened. 2. Calling example_task() creates the coroutine frame, constructs the promise, and calls get_return_object(). 3. The return object (Task) is created with a handle to the coroutine. 4. initial_suspend() runs and returns suspend_always, so the coroutine suspends immediately. 5. Control returns to main, which now holds the Task object. 6. The first resume() runs "Task body: part 1", then hits co_await suspend_always{} and suspends. 7. The second resume() runs "Task body: part 2", then falls off the end, triggering final_suspend(). 8. Since final_suspend() returns suspend_always, the coroutine suspends one final time. 9. When Task's destructor runs (at the end of main), it destroys the coroutine handle. The return object provides an interface to the caller. It hides the details of coroutine handles and promises behind whatever API makes sense for your use case. For a generator, the return object provides methods like next() and value(). For a task, it might provide resume() and done(). The return object owns the coroutine handle and is responsible for destroying it. You have now seen how return objects and coroutine handles work together. The return object is the caller's view of the coroutine, while the handle is the mechanism for resuming and managing the coroutine's lifetime. Step 7 — Completing Coroutines with co_return <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-7…> You have seen coroutines that yield sequences of values and suspend indefinitely. Now you will learn how coroutines complete their execution using co_return. A coroutine completes in one of three ways: 1. It executes co_return; (returning void) 2. It executes co_return expression; (returning a value) 3. Execution falls off the end of the coroutine body For case 1 and 3, the compiler calls promise.return_void(). For case 2, the compiler calls promise.return_value(expression). You must provide exactly one of these methods in your promise type, matching how your coroutine returns. When a coroutine completes (by any of these means), it then executes co_await promise.final_suspend(). The awaiter returned by final_suspend() determines what happens next: - If it suspends (like suspend_always), the coroutine frame remains valid. The caller can still access the promise object and must eventually call handle.destroy() to free the memory. - If it does not suspend (like suspend_never), the coroutine frame is destroyed automatically. Any handles to the coroutine become dangling pointers. The choice between these behaviors matters. If your caller needs to access the result stored in the promise after the coroutine completes, use suspend_always. If the coroutine's completion signals some external mechanism (like releasing a semaphore) and the result is not needed, you might use suspend_never to avoid manual cleanup. Here is an example of a coroutine that returns a value: #include <coroutine> #include <iostream> #include <optional> struct ComputeResult { struct promise_type { std::optional<int> result; ComputeResult get_return_object() { return ComputeResult{ std::coroutine_handle<promise_type>::from_promise(*this) }; } std::suspend_always initial_suspend() { return {}; } std::suspend_always final_suspend() noexcept { return {}; } void return_value(int value) { result = value; } void unhandled_exception() { result = std::nullopt; } }; std::coroutine_handle<promise_type> handle; ComputeResult(std::coroutine_handle<promise_type> h) : handle(h) {} ~ComputeResult() { if (handle) handle.destroy(); } ComputeResult(ComputeResult&& other) noexcept : handle(other.handle) { other.handle = nullptr; } void run() { while (!handle.done()) { handle.resume(); } } std::optional<int> get_result() const { return handle.promise().result; } }; ComputeResult compute_sum(int n) { int sum = 0; for (int i = 1; i <= n; ++i) { sum += i; co_await std::suspend_always{}; // yield control periodically } co_return sum; } int main() { auto computation = compute_sum(5); computation.run(); if (auto result = computation.get_result()) { std::cout << "Result: " << *result << std::endl; } } Output: Result: 15 The compute_sum coroutine adds numbers from 1 to n, periodically yielding control with co_await suspend_always{}. When the loop completes, it executes co_return sum, which calls promise.return_value(sum), storing the result in the promise. Because final_suspend() returns suspend_always, the coroutine frame remains valid after completion. The get_result() method can access handle.promise().result to retrieve the computed value. You can query whether a coroutine has completed using handle.done(). This method returns true after the coroutine has executed co_return (or fallen off the end) and completed the final_suspend awaiter. Do not confuse handle.done() with handle.operator bool(). The boolean conversion only checks if the handle is non-null; it does not indicate completion. A critical warning about undefined behavior: if your coroutine can fall off the end of its body and your promise type does not have a return_void() method, the behavior is undefined. This is dangerous because the compiler may not warn you. Always ensure your promise type has return_void() if any code path might reach the end of the coroutine without an explicit co_return. Here is the same computation rewritten to fall off the end instead of using explicit co_return: struct ComputeResult2 { struct promise_type { int result = 0; ComputeResult2 get_return_object() { return ComputeResult2{ std::coroutine_handle<promise_type>::from_promise(*this) }; } std::suspend_always initial_suspend() { return {}; } std::suspend_always final_suspend() noexcept { return {}; } void return_void() {} // Required because we fall off the end void unhandled_exception() {} }; std::coroutine_handle<promise_type> handle; // ... rest of the class }; ComputeResult2 compute_sum2(int n) { auto& result = co_await GetPromiseAwaiter{}; // hypothetical int sum = 0; for (int i = 1; i <= n; ++i) { sum += i; co_await std::suspend_always{}; } result = sum; // Falls off the end - calls promise.return_void() } In this version, we store the result in the promise before falling off the end. The return_void() method must exist even though it does nothing, because the coroutine reaches the end of its body. You have now learned how coroutines complete execution. The co_return statement (or falling off the end) triggers the promise's return methods, and final_suspend determines whether the coroutine frame persists. Step 8 — Building a Generic Generator <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-8…> You have learned all the pieces needed to build a reusable generator type. In this step, you will assemble them into a template class that works with any value type. A production-quality generator needs to handle several concerns: 1. Store and retrieve yielded values of any type 2. Manage the coroutine handle's lifetime correctly 3. Propagate exceptions from the coroutine to the caller 4. Provide a clean iteration interface Here is a complete generic generator: #include <coroutine> #include <exception> #include <utility> template<typename T>class Generator {public: struct promise_type { T value; std::exception_ptr exception; Generator get_return_object() { return Generator{Handle::from_promise(*this)}; } std::suspend_always initial_suspend() noexcept { return {}; } std::suspend_always final_suspend() noexcept { return {}; } std::suspend_always yield_value(T v) { value = std::move(v); return {}; } void return_void() noexcept {} void unhandled_exception() { exception = std::current_exception(); } template<typename U> std::suspend_never await_transform(U&&) = delete; }; using Handle = std::coroutine_handle<promise_type>; private: Handle handle_; public: explicit Generator(Handle h) : handle_(h) {} ~Generator() { if (handle_) { handle_.destroy(); } } Generator(const Generator&) = delete; Generator& operator=(const Generator&) = delete; Generator(Generator&& other) noexcept : handle_(std::exchange(other.handle_, nullptr)) {} Generator& operator=(Generator&& other) noexcept { if (this != &other) { if (handle_) { handle_.destroy(); } handle_ = std::exchange(other.handle_, nullptr); } return *this; } class iterator { Handle handle_; public: using iterator_category = std::input_iterator_tag; using value_type = T; using difference_type = std::ptrdiff_t; using pointer = T*; using reference = T&; iterator() : handle_(nullptr) {} explicit iterator(Handle h) : handle_(h) {} iterator& operator++() { handle_.resume(); if (handle_.done()) { auto& promise = handle_.promise(); handle_ = nullptr; if (promise.exception) { std::rethrow_exception(promise.exception); } } return *this; } iterator operator++(int) { iterator temp = *this; ++(*this); return temp; } T& operator*() const { return handle_.promise().value; } T* operator->() const { return &handle_.promise().value; } bool operator==(const iterator& other) const { return handle_ == other.handle_; } bool operator!=(const iterator& other) const { return !(*this == other); } }; iterator begin() { if (handle_) { handle_.resume(); if (handle_.done()) { auto& promise = handle_.promise(); if (promise.exception) { std::rethrow_exception(promise.exception); } return iterator{}; } } return iterator{handle_}; } iterator end() { return iterator{}; } }; This generator provides a standard iterator interface, allowing use in range-based for loops: Generator<int> range(int start, int end) { for (int i = start; i < end; ++i) { co_yield i; } } Generator<int> squares(int n) { for (int i = 0; i < n; ++i) { co_yield i * i; } } int main() { std::cout << "Range 1 to 5:" << std::endl; for (int x : range(1, 6)) { std::cout << x << " "; } std::cout << std::endl; std::cout << "First 5 squares:" << std::endl; for (int x : squares(5)) { std::cout << x << " "; } std::cout << std::endl; } Output: Range 1 to 5: 1 2 3 4 5 First 5 squares: 0 1 4 9 16 Several design choices in this generator deserve explanation: initial_suspend() returns suspend_always: The coroutine suspends before running any user code. This means begin() must resume the coroutine to get the first value. This design prevents work from being done if the generator is never iterated. final_suspend() returns suspend_always: The coroutine frame persists after completion. This is necessary because the iterator needs to check handle_.done() and potentially access the exception stored in the promise. If final_suspend() returned suspend_never, the handle would become invalid before these checks could occur. Exception handling: The unhandled_exception() method stores the current exception in the promise using std::current_exception(). The iterator's operator++ and begin() check for this exception and rethrow it using std::rethrow_exception(). This propagates exceptions from the coroutine to the calling code. await_transform is deleted: This prevents using co_await inside the generator. A generator should only yield values, not await other operations. Deleting await_transform makes any use of co_await inside a Generator<T> coroutine a compile error. Move semantics: The generator is movable but not copyable. Copying a coroutine handle would create aliasing problems—both copies would refer to the same coroutine frame, and destroying one would invalidate the other. Moving transfers ownership cleanly. Here is an example demonstrating exception propagation: Generator<int> may_throw(bool should_throw) { co_yield 1; co_yield 2; if (should_throw) { throw std::runtime_error("Generator error"); } co_yield 3; } int main() { try { for (int x : may_throw(true)) { std::cout << x << std::endl; } } catch (const std::exception& e) { std::cout << "Caught: " << e.what() << std::endl; } } Output: 1 2 Caught: Generator error The exception thrown inside the generator propagates to the calling code and can be caught normally. You have now built a production-quality generic generator. It handles value types, manages coroutine lifetime, propagates exceptions, and provides a standard iterator interface. Step 9 — Handling Exceptions in Coroutines <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-9…> Exceptions in coroutines require special attention. Because a coroutine can suspend and resume across different call stacks, the normal exception propagation mechanism does not work directly. The promise type's unhandled_exception() method provides the hook for handling exceptions that escape the coroutine body. When an exception is thrown inside a coroutine and not caught within the coroutine, the following happens: 1. The exception is caught by the implicit try-catch block surrounding the coroutine body. 2. promise.unhandled_exception() is called while the exception is still active. 3. After unhandled_exception() returns, co_await promise.final_suspend() executes. 4. The coroutine completes (either suspended or destroyed, depending on final_suspend). Inside unhandled_exception(), you have several options: Terminate the program: Call std::terminate(). This is the safest option if you cannot handle exceptions. void unhandled_exception() { std::terminate(); } Store the exception for later: Use std::current_exception() to capture the exception and store it in the promise. The caller can later check for the exception and rethrow it. void unhandled_exception() { exception_ = std::current_exception(); } Rethrow the exception: Call throw; to rethrow the exception. This propagates the exception to whoever is currently running the coroutine, but be careful—this may not be the original caller if the coroutine has been resumed from a different context. void unhandled_exception() { throw; } Swallow the exception: Do nothing. This silences the exception, which is almost always a mistake but might be appropriate in specific circumstances. void unhandled_exception() { // Exception is silently ignored } The stored exception pattern is most useful for generators and tasks where the caller expects to receive results: #include <coroutine> #include <exception> #include <iostream> #include <stdexcept> struct Task { struct promise_type { std::exception_ptr exception; Task get_return_object() { return Task{std::coroutine_handle<promise_type>::from_promise(*this)}; } std::suspend_always initial_suspend() { return {}; } std::suspend_always final_suspend() noexcept { return {}; } void return_void() {} void unhandled_exception() { exception = std::current_exception(); } }; std::coroutine_handle<promise_type> handle; Task(std::coroutine_handle<promise_type> h) : handle(h) {} ~Task() { if (handle) handle.destroy(); } void run() { handle.resume(); } void check_exception() { if (handle.promise().exception) { std::rethrow_exception(handle.promise().exception); } } }; Task risky_operation() { std::cout << "Starting risky operation" << std::endl; throw std::runtime_error("Something went wrong"); co_return; // Never reached } int main() { Task task = risky_operation(); try { task.run(); task.check_exception(); std::cout << "Operation completed successfully" << std::endl; } catch (const std::exception& e) { std::cout << "Operation failed: " << e.what() << std::endl; } } Output: Starting risky operation Operation failed: Something went wrong The timing of when to check for exceptions matters. In this example, check_exception() is called after run() completes. If the coroutine suspended multiple times, you might want to check for exceptions after each resumption. For generators with iterators, exceptions are typically checked during iteration: iterator& operator++() { handle_.resume(); if (handle_.done()) { auto& promise = handle_.promise(); if (promise.exception) { std::rethrow_exception(promise.exception); } } return *this; } This ensures that exceptions are propagated to the code iterating over the generator. Be aware of exception safety during coroutine initialization. If an exception is thrown before the first suspension point (and before initial_suspend completes), the exception propagates directly to the caller without going through unhandled_exception(). If initial_suspend() returns suspend_always, the coroutine suspends before any user code runs, avoiding this issue. You have now learned how to handle exceptions in coroutines. The unhandled_exception() method provides a hook for capturing or propagating exceptions, and the stored exception pattern allows callers to receive exceptions even when the coroutine has suspended and resumed. Step 10 — Practical Patterns and Applications <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#step-1…> You have learned the mechanics of C++20 coroutines. Now you will explore practical patterns that demonstrate their power. Lazy Sequences <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#lazy-s…> Generators excel at producing lazy sequences—sequences where values are computed only when needed. This pattern is useful when working with infinite sequences or when computing values is expensive. Generator<int> infinite_counter() { int i = 0; while (true) { co_yield i++; } } Generator<int> primes() { auto is_prime = [](int n) { if (n < 2) return false; if (n == 2) return true; if (n % 2 == 0) return false; for (int i = 3; i * i <= n; i += 2) { if (n % i == 0) return false; } return true; }; int n = 2; while (true) { if (is_prime(n)) { co_yield n; } ++n; } } int main() { int count = 0; for (int p : primes()) { std::cout << p << " "; if (++count >= 10) break; } std::cout << std::endl; } Output: 2 3 5 7 11 13 17 19 23 29 The prime generator tests each number for primality but only computes values as they are requested. An infinite number of primes exist, but the program only computes the first ten. Transforming Sequences <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#transf…> Generators can transform sequences from other generators, creating a pipeline of operations: Generator<int> take(Generator<int> source, int n) { int count = 0; for (int value : source) { if (count++ >= n) break; co_yield value; } } Generator<int> filter(Generator<int> source, bool (*predicate)(int)) { for (int value : source) { if (predicate(value)) { co_yield value; } } } Generator<int> transform(Generator<int> source, int (*func)(int)) { for (int value : source) { co_yield func(value); } } bool is_even(int n) { return n % 2 == 0; }int square(int n) { return n * n; } int main() { // Take first 5 even numbers from range, then square them auto pipeline = transform( filter( take(range(1, 100), 10), is_even ), square ); for (int x : pipeline) { std::cout << x << " "; } std::cout << std::endl; } Output: 4 16 36 64 100 Each generator in the pipeline produces values on demand. The filter generator only requests the next value from its source when it needs to produce an output. The transform generator only transforms values as they pass through. Tree Traversal <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#tree-t…> Ana Lúcia de Moura and Roberto Ierusalimschy, in their influential paper on coroutines, demonstrated tree traversal as a classic use case. With generators, you can traverse a tree structure while maintaining the simple recursive algorithm: struct TreeNode { int value; TreeNode* left; TreeNode* right; TreeNode(int v, TreeNode* l = nullptr, TreeNode* r = nullptr) : value(v), left(l), right(r) {} }; Generator<int> inorder(TreeNode* node) { if (node == nullptr) { co_return; } for (int v : inorder(node->left)) { co_yield v; } co_yield node->value; for (int v : inorder(node->right)) { co_yield v; } } int main() { // 4 // / \ // 2 6 // / \ / \ // 1 3 5 7 TreeNode n1(1), n3(3), n5(5), n7(7); TreeNode n2(2, &n1, &n3), n6(6, &n5, &n7); TreeNode root(4, &n2, &n6); for (int v : inorder(&root)) { std::cout << v << " "; } std::cout << std::endl; } Output: 1 2 3 4 5 6 7 The recursive structure of the tree traversal matches the recursive structure of the code. Each call to inorder creates a new generator that yields values from its subtree. The co_yield in the loop forwards those values upward. Cooperative Multitasking <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#cooper…> Coroutines enable cooperative multitasking without threads. Multiple tasks can make progress by voluntarily yielding control: #include <vector> #include <string> struct Task { struct promise_type { Task get_return_object() { return Task{std::coroutine_handle<promise_type>::from_promise(*this)}; } std::suspend_always initial_suspend() { return {}; } std::suspend_always final_suspend() noexcept { return {}; } void return_void() {} void unhandled_exception() { std::terminate(); } }; std::coroutine_handle<promise_type> handle; Task(std::coroutine_handle<promise_type> h) : handle(h) {} ~Task() { if (handle) handle.destroy(); } Task(Task&& other) noexcept : handle(other.handle) { other.handle = nullptr; } bool done() const { return handle.done(); } void resume() { handle.resume(); } }; struct Scheduler { std::vector<Task> tasks; void add(Task task) { tasks.push_back(std::move(task)); } void run() { while (!tasks.empty()) { for (size_t i = 0; i < tasks.size(); ) { tasks[i].resume(); if (tasks[i].done()) { tasks.erase(tasks.begin() + i); } else { ++i; } } } } }; Task worker(std::string name, int iterations) { for (int i = 0; i < iterations; ++i) { std::cout << name << " iteration " << i << std::endl; co_await std::suspend_always{}; } } int main() { Scheduler scheduler; scheduler.add(worker("Alice", 3)); scheduler.add(worker("Bob", 2)); scheduler.run(); } Output: Alice iteration 0 Bob iteration 0 Alice iteration 1 Bob iteration 1 Alice iteration 2 The scheduler interleaves the execution of Alice and Bob. Each task runs until it hits co_await suspend_always{}, then yields control. The scheduler resumes the next task, achieving cooperative multitasking. This pattern can be extended with I/O operations. Instead of suspend_always, tasks would await I/O completions. A real scheduler would integrate with an event loop, resuming tasks when their I/O operations complete. You have now seen practical applications of C++20 coroutines. Lazy sequences, sequence transformations, tree traversal, and cooperative multitasking all benefit from coroutines' ability to suspend and resume execution while preserving local state. Conclusion <https://gist.github.com/vinniefalco/bbf1d9d3a720e8ad2ef8fe2e837cdfc9#conclu…> In this tutorial, you explored C++20 coroutines from fundamental concepts to practical implementations. You began by understanding the problem coroutines solve: the fragmentation of logic that occurs when writing asynchronous code with callbacks. Coroutines restore the natural flow of sequential code while maintaining asynchronous behavior. You learned to recognize coroutines by their keywords: co_await for suspension, co_yield for producing values, and co_return for completion. You discovered that the presence of any of these keywords transforms a function into a coroutine with special runtime behavior. You examined the mechanics of suspension and resumption, understanding how the coroutine frame preserves local variables on the heap while the coroutine is suspended. The std::coroutine_handle provides the mechanism for resuming a suspended coroutine. You studied the promise type, the controller class that customizes coroutine behavior. Its methods—get_return_object, initial_suspend, final_suspend, yield_value, return_void, return_value, and unhandled_exception—define how the coroutine initializes, suspends, produces values, completes, and handles errors. You built a complete generator type that produces sequences of values on demand. The generator manages coroutine lifetime, provides an iterator interface, and propagates exceptions from the coroutine to calling code. You explored practical patterns: lazy sequences that compute values only when needed, pipelines that transform sequences, tree traversals that maintain recursive structure, and cooperative multitasking that interleaves multiple tasks. C++20 coroutines provide a foundation for building sophisticated asynchronous systems. The standard library in C++23 and beyond will provide higher-level abstractions built on this foundation. Understanding the mechanisms described in this tutorial will help you use those abstractions effectively and build your own when needed. For further exploration, consider studying: - The std::generator type introduced in C++23 - Asynchronous I/O frameworks that use coroutines - The senders and receivers model being developed for C++26 - Real-world applications of coroutines in networking, databases, and user interfaces Coroutines represent a significant evolution in how C++ programmers can express complex control flow. The ability to write asynchronous code that reads like synchronous code, while maintaining full control over memory and performance, embodies the spirit of C++: abstraction without hidden costs.

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Boost Version 1.90.0 Release report
by rob＠cppalliance.org 26 Jan '26

26 Jan '26

Apologies to everyone for the delay in this release. We had multiple technical issues to work out related to the new Mailman as well as some other technical issues. We've also added some new data points of interest! As always, this is a work in progress, it will continue to grow and be refined. Suggestions and ideas are always welcome! https://downloads.cppalliance.org/reports/boost_1_90_0_release_report.pdf

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[Boost.Multi] Initial feedback
by Andrzej Krzemienski 25 Jan '26

25 Jan '26

Hi Everyone, Given the recent announcement of the upcoming Boost.Multi review, I wanted to offer some initial feedback. I would like to thank Alfredo for writing and sharing the library. I would also thank you for the single header version and the Compiler explorer integration. This is so welcoming not only for the users but also for the reviewers. I am not well familiar with the domain.i only had a look at the docs and played with toy examples in Compiler Explorer. I would like to request a Design Rationale section that would address some of the questions up front and bring some insight into the domain: 1. Is it a common need in the mentioned application fields to add a new dimension to the already stored N-dimensional data? If so, could we see an example of how to do it? 2. Why is c++17 chosen as the minimum? 3. The number of dimensions is static, but the sizes in each dimension are dynamic. Can you provide the rationale for this choice? The design: 1. I am still trying to digest the way by-reference and by-value is handled in the library in the presence of the "ref"/"view" types. It looks like the simple advice for the new users would be: * Always use `auto& ref = x` if you need the reference semantics, where `x` is whatever expression. * Always use `auto val = +x` if you need value semantics, where `x` is any expression. It looks like it is optimum even when `x` is of type `array`. 2. The initialization from values is too similar to the initialization from extents. I cannot easily figure out which initialization is used in `multi::array a({3, 4, 5});`. This is error-prone. I would prefer a longer: `multi::array a(multi::extents{3, 4, 5});`. On the other hand, does the initialization from small manual static sets of data happen often? I would think that for these use cases you would read the data from some external source. 3. If the docs recommend that all functions should be generic to account for subarrays and refs, then this library could offer a concept like `Indexable<Dimensionality, ElementType>` available for C++20 compilers. 4. Are sizes equal to strands? Does .elements() offer contiguous access? 5. For the initialization, did you consider factory functions or tag parameters? ( https://akrzemi1.wordpress.com/2016/06/29/competing-constructors/) The differentiation of meaning by braces/parens seems easy to misinterpret. 6. All the subarrays and dynamic_arrays have function swap, but it is not documented. Does it have a precondition that sizes should match? Documentation: 1.It is very clear already! 2. In the introduction it is worth explaining the term "stride-based layout" or link to the definition. This concept seems crucial to the library. 3. The docs say "or tensors in the 3D case". Tensors are arbitrary dimension. 4. I think that in real, practical use cases the array data is populated from files or datastres rather than from literals (compile-time values in braces). Could the tutorial demonstrate the endorsed way of doing such data population with this library? 5. I really appreciate that you prefix names with `multi::`. The examples could also mention the headers that you need to include. The initial docs examples may be the place where I will learn the headers. 6. The interface discoverability is not great: I wanted to quickly check the contract of `array::elements()`. I cannot find it. The reference section only has repeated text "same as for dynamic_array" (no link). Generally, the "redirect" philosophy in the reference documentation is mean.In order to look up the semantics of array::operator(), I am redirected: first from `array` to `dynamic_array`, then to `array_ref`, and only then to `subarray`. 7. Generally, we need to see a more detailed Reference section. For instance, what is the return type of operator[]? 8. Document if `array` and siblings can have dimensionality 0 (which would mean access to a single element). 9. It is strange to see a section titled "Static arrays" that describes type `dynamic_array`. In C++ "static" and "dynamic" tend to have opposite meanings. Regards, &rzej;

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[boost][multi] Feedback on `restrictions`
by Andrzej Krzemienski 25 Jan '26

25 Jan '26

Hi All, "Restrictions" (lazy arrays) in Boost.Multi look like a useful and practical component. The below feedback may sound negative, but it should be treated as suggestions for improving the feature. I find the name "restriction" surprising. Is this a term of art? "Lazy array" immediately conveys the idea, so I wonder why you decided to go with "restriction". I already complained that the "Reference" section is not serving its purpose well. Regarding "restrictions", they are simply missing from that section. Having read the tutorial, and wanting to use the feature in my program, I need to know: 1. Which header to include 2. What is the type returned by the "wedge" operator 3. Is the return type something that I should be able to name, use? Or is the contract "just assign the result to your array, and don't ask for the type name"? 4. What are the preconditions of the operation? 5. Are there things that I can do wrong when using the function and resulting types? 7. Does the function that I provide need to have the same number of arguments as the number of dimensions in the `extents` that I provide? 8.Do you guarantee that the index values that will be passed to subsequent invocations of my function will come in specific order? Or do I need to make sure that my function is pure/regular? 9. Does the function that I provide need to be copyable? 10. Header `restriction.hpp` has functions `make_restriction()` defined. Are they intended for users? If so, they need to be listed in "Reference"' also. I question the choice of using an arbitrary operator for creating lazy arrays. It makes the user code difficult to read and understand. I imagine that in my company I assign a junior developer to fix something in the code, and they are exposed to these bitwise-xor operators. This is an unnecessary confusion. A named factory function like `make_lazy` would immediately sell the intent: it combines the extents with an "indexes-to-value" function to produce a lazy array. It looks like there is an implied concept in your library, "non-mutable array access"., which probably includes being the RHS of the assignment to a "mutable array access". Now I feel even stronger that it should be given a name and be defined, even if semi-formally. The tutorial for restrictions mentions the function ".home()". Is this intended to be part of the library's interface? If so, it must appear in the "Reference" section. The Reference section defines what is the intended interface of the library as opposed to declarations that happen to exist in the headers for other reasons: as temporary solutions, implementation details, experiments or artifacts. Regards, &rzej;

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Fwd: [Boost.Multi] Initial feedback
by Andrzej Krzemienski 23 Jan '26

23 Jan '26

Forwarding my private reply to the entire group... ---------- Forwarded message --------- Od: Andrzej Krzemienski <akrzemi1(a)gmail.com> Date: czw., 22 sty 2026 o 09:50 Subject: Re: [Boost.Multi] Initial feedback To: Alfredo Correa <alfredo.correa(a)gmail.com> czw., 22 sty 2026 o 04:08 Alfredo Correa <alfredo.correa(a)gmail.com> napisał(a): > On Wed, Jan 21, 2026 at 1:56 PM Andrzej Krzemienski <akrzemi1(a)gmail.com> > wrote: > >> >>>> What do you mean by contract? >>> >> >> All the characteristics that are usually described when documenting the >> Standard Library functions: >> https://cppreference.com/w/cpp/utility/optional/transform.html >> >> Like: return type, constraints, const/constexpr properties, >> postconditions. >> In this case, I was interested in what properties the returned range has: >> random-access, contiguous? I naturally expect that it is a contiguous range >> for multi::array and multi::array_ref, so I wanted to confirm that. I >> suppose it is different for subarrays. I can hardly imagine they would have >> the same range category. >> > > return type: A custom `elements_type`, which is a random access range. > for `multi::array` the type is `multi::subarray<T, 1>` because it can be > contiguous. > > no contraints, .elements() always returns something valid, even if the > array is empty. > it is constexpr. > postcontions, nothing changes, .elements() is just another view. > > I say this now: "As an alternative, the elements can be iterated in a > flat manner, using the `.elements()` member. > This "elements" range also provides the `begin` and `end` iterators > (`.elements().begin()`) and indexing, in the canonical order of the > original arrays (rightmost index changes fastest). > The elements range is always random-access, but it can be contiguous > depending on the original array (`multi::array` generally give contiguous > element ranges.)" > > In the reference section, > ``` > | `elements` | a flatted random-access > view of all the elements rearranged canonically. `A.elements()[0] -> > A[0][0]`, `A.elements()[1] -> A[0][1]`, etc. The type of the result is not > a subarray but a special kind of random-access range. Takes no arguments. > ``` > > And, later for array_ref, > ``` > | `elements` | a flatten random-access and contiguous view of all > the elements in the array in canonical order. (This is overwritten from the > base class, to provide contiguous access) > ``` > Ok, so about these `elements()`: 1. Regarding the array_ref member, I request that you specify this more formally: that the returned type models the concept std::ranges::contiguous_range. This already implies that it is random-access. A range need not be copyable, if you want this to be part of the guarantee, say that the return type is a view that models std::ranges::contiguous_range. 2. Regarding the array member, the fact that it might be contiguous is also a useful guarantee. Could the docs be more specific under what circumstances I get a contiguous range? Regards, &rzej; > I also added that all member functions are constexpr unless specified > differently. (almost all member functions are constexpr, a couple of > exceptions is some destructors and some constructors, due to C++17 > limitations). > > >> >> >>> >>> The search box leads me to: "a flatted view of all the elements >>> rearranged canonically. A.elements()[0] → A[0][0], A.elements()[1] → >>> A[0][1], etc. The type of the result is not a subarray but a special kind >>> of range. Takes no argument." >>> >> >> It takes me to subarray::elements, but that doesn't imply that >> array::elements would have the same contract. >> "special kind of range" is not the level of detail that I expected. I >> think you owe the user the range category. >> > > range category: always random access, contiguous for multi::array. > > Thanks, > Alfredo >

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Moving boost/static_assert.hpp to Config
by Peter Dimov 23 Jan '26

23 Jan '26

As discussed last time, Andrey Semashev and I moved boost/static_assert.hpp from StaticAssert to Config in order to reduce nearly everyone's dependencies by one (there's no point pulling an entire repository for just one header file.) However, this presents some issues going forward. If I change depinst.py to properly "know" that boost/static_assert.hpp is now in Config, a lot of things break. That's because many libraries list StaticAssert as a dependency in their build.jam and CMakeLists.txt files, and since it's no longer used, depinst doesn't install it and there are errors. We could in principle go over all these (there are ~54 of them) and fix them, but in my experience, changes that break things internally for us also usually break things for others as well. So... instead, we could name the Config header boost/config/static_assert.hpp, leave boost/static_assert.hpp in StaticAssert, and have it include the Config one. This is going to be a lot less painful; people who care about the dependency would change their includes, whereas those who do not, will not. Opinions?

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Intro & Request for Boost Stories
by Mark Cooper 21 Jan '26

21 Jan '26

Hello everyone, I'm Mark Cooper, CMO at The C++ Alliance. I just wanted to introduce myself, and let you know that I'm always looking out for new examples of how the community is building / using Boost. So if you're working on anything that you think the C++ world would find interesting, send me an email at mark(a)cppalliance.org. Thank you, Mark

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Boost Libraries are Obsolete
by Vinnie Falco 18 Jan '26

18 Jan '26

I believe some Boost libraries become obsolete by newer versions of C++. For example, boost::filesystem, Boost.CharConv, and Boost.Variant could be considered obsolete in versions C++17 and later as these facilities are in the standard. It can be tricky to figure out what is obsolete. Is boost::shared_ptr obsolete in C++11? Probably not since it has features not found in the standard. Anyway, I'm not trying to figure this out for all the libraries. For boost.org it might be nice to let users specify the "minimum version of C++" which they use. And they can opt in to filtering the Libraries based on this minimum version. Someone who is using C++23 can choose not to see libraries like Boost.Align, Boost.Assign, or Boost.Atomic. We will need to add metadata to each library's repository to know the maximum version. What do you all think about this? -- Regards, Vinnie Follow me on GitHub: https://github.com/vinniefalco

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Boost.Multi (multidimensional arrays) library ready to request a review
by Alfredo Correa 09 Jan '26

09 Jan '26

Hello Boost community, I want to propose Boost.Multi, a modern C++ library for owning and non-owning multidimensional arrays with STL-compatible iteration, slicing, layout control, and lazy arrays/expressions. (The library requires at least C++17) I previewed the library on this mailing list before (see archives), but it is ready for review now and includes a couple of new features (such as lazy expressions, by popular demand) and much more comprehensive documentation. The library is built on current uses (at least two production codes) and on past experience (such as Boost.MultiArray, Blitz, Eigen, and std::mdspan). While mdspan provides a powerful non-owning view abstraction, Boost.Multi focuses on ownership, views, expressive multidimensional manipulation, and generic programming (STL-like iteration and algorithms, allocators, Ranges, Thrust). It is aimed at, but not limited to, numerical, scientific, and HPC-style workloads and emphasizes interoperability. The library has been in active use and refinement for some time, and it may now be ready for Boost review. I would be very grateful for: * Feedback on whether the library is suitable for Boost * Endorsements from those willing to support a formal review. I have an early endorsement from @Vinnie Falco, but additional endorsements are welcome * Guidance on the following steps to start the review process Repository: (Gitlab or Github mirrors, whatever you find more convenient) https://gitlab.com/correaa/boost-multi https://github.com/correaa/boost-multi Documentation: https://correaa.gitlab.io/boost-multi/multi.html https://correaa.github.io/boost-multi/multi.html If you encounter issues before a format review, the most efficient way would be to open an issue on GitLab or on GitHub: https://gitlab.com/correaa/boost-multi/-/issues https://github.com/correaa/boost-multi/issues Impatient? You can download the core library as a single header file https://correaa.gitlab.io/boost-multi/boost-multi.hpp (nightly updated) or try it in Godbolt: https://godbolt.org/z/KxGoP5Kq9 Want to check if it works with your favorite compiler? (probably it does, check compliance here: https://godbolt.org/z/fz6f6erq1) Want to test GPU capabilities? Please get in touch with me. What to chat? Join the Slack channel: https://cpplang.slack.com/archives/C071VGKUA5P Thank you all very much for your time and for maintaining such a valuable ecosystem. Best regards, Alfredo

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