std::ranges::to>(); while (true) { co_yield particles[dist(gen)]; } } 1 2 3 4 5 6 7 8 9 10 11 12 13 18SAMPLE VIEW std::generator (C++23) std::ranges::to>(); while (true) { co_yield particles[dist(gen)]; } } 1 2 3 4 5 6 7 8 9 10 11 12 13 template >(); 8 9 while (true) { 10 co_yield particles[dist(gen)]; 11 } 12 } 13 18.1SAMPLE VIEW std::generator (C++23) template

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the IOLoop that use callbacks. Futures are usually transformed into their result with the await or yield keywords. Examples Here is a sample synchronous function: from tornado.httpclient import HTTPClient tornado import gen @gen.coroutine def async_fetch_gen(url): http_client = AsyncHTTPClient() response = yield http_client.fetch(url) raise gen.Return(response.body) Coroutines are a little magical, but what “native corou- tines”). For compatibility with older versions of Python, you can use “decorated” or “yield-based” coroutines using the tornado.gen.coroutine decorator. Native coroutines are the recommended

the IOLoop that use callbacks. Futures are usually transformed into their result with the await or yield keywords. Examples Here is a sample synchronous function: from tornado.httpclient import HTTPClient gen @gen.coroutine def async_fetch_gen(url): http_client = AsyncHTTPClient() response = yield http_client.fetch(url) raise gen.Return(response.body) Coroutines are a little magical, but “native coroutines”). For compatibility with older versions of Python, you can use “decorated” or “yield-based” coroutines using the tornado.gen.coroutine decorator. Native coroutines are the recommended

Processor(CalculateYield yield_calc) : YieldCalculator_(std::move(yield_calc)){}; // ... auto process(Data& data){ // ... auto yield = YieldCalculator_(data, ...); // ... return yield; } private : CalculateYield captureTEST(Processor, test_yield) { auto y_calculator = [] (const YieldData& ydata){ return ydata.data_*0.01;}; YieldProcessor processor(y_calculator); YieldData rdata{100}; auto yield = processor.process(rdata); process(rdata); EXPECT_EQ(yield.realised, 1); } 32 Bloomberg Dependency Injection via type erasure Injection Dependency Testing VerificationCall any function satisfying a function signature – via

and Functions into a Job System - CppCon 2021 19 / 39 Coroutine Call Examples auto ro = c() co_yield resume() co_return auto ro = c1() co_await c2() co_await + resume() continuation! co_return 0.0f; } Coro coroTest(int i) { co_await thread_index_t{ 0 }; co_yield 10; co_return 0; }Helmut Hlavacs – Combining Co-Routines and Functions into a Job System - CppCon co_await promise.final_suspend(); } Coro coroTest(int i) { co_await thread_index_t{ 0 }; co_yield 10; co_return i; } Return Object Coro using promise_type = Coro_promise; Coroutine returning

11 C++ Iterating with Generic Code Iterator API provided by all containers: – begin() and end() yield iterators • to iterator over elements with ++, !=, *, ... // print all elements: for (auto pos = 12 C++ Iterating with Generic Code Iterator API provided by all containers: – begin() and end() yield iterators • to iterator over elements with ++, !=, *, ... template void printElems(const pos Iterating with Generic Code Iterator API provided by all containers: – begin() and end() yield iterators • to iterator over elements with ++, !=, *, ... template void printElems(const

'Fall'), (4, 'Winter')] 等价于: def enumerate(sequence, start=0): n = start for elem in sequence: yield n, elem n += 1 eval(expression, globals=None, locals=None) 实参是一个字符串，以及可选的 globals 和 locals。globals 如果是代码对象，它将被直接执行。在任 何情况下，被执行的代码都需要和文件输入一样是有效的（见参考手册中关于文件输入的章节）。请注 意即使在传递给exec() 函数的代码的上下文中，return 和 yield 语句也不能在函数定义之外使用。 该函数返回值是 None 。 无论哪种情况，如果省略了可选参数，代码将在当前范围内执行。如果提供了 globals 参数，就必须是 字典类型，而且会被用作全局和本地变量。如果同时提供了 for it in iterators: elem = next(it, sentinel) if elem is sentinel: return result.append(elem) yield tuple(result) 函数会保证可迭代对象按从左至右的顺序被求值。使得可以通过 zip(*[iter(s)]*n) 这样的惯用 形式将一系列数据聚类为长度为 n 的分组。这将重复 同样的迭代器

'Fall'), (4, 'Winter')] 等价于: def enumerate(sequence, start=0): n = start for elem in sequence: yield n, elem n += 1 eval(expression, globals=None, locals=None) 实参是一个字符串，以及可选的 globals 和 locals。globals 如果是代码对象，它将被直接执行。在任 何情况下，被执行的代码都需要和文件输入一样是有效的（见参考手册中关于文件输入的章节）。请注 意即使在传递给exec() 函数的代码的上下文中，return 和 yield 语句也不能在函数定义之外使用。 该函数返回值是 None 。 无论哪种情况，如果省略了可选参数，代码将在当前范围内执行。如果提供了 globals 参数，就必须是 字典类型，而且会被用作全局和本地变量。如果同时提供了 for it in iterators: elem = next(it, sentinel) if elem is sentinel: return result.append(elem) yield tuple(result) 函数会保证可迭代对象按从左至右的顺序被求值。使得可以通过 zip(*[iter(s)]*n) 这样的惯用 形式将一系列数据聚类为长度为 n 的分组。这将重复 同样的迭代器

391 conda, Release 25.1.2.dev1 (continued from previous page) 16 with tmp_env() as prefix: 17 yield prefix 18 19 20 def test_conda_create(env_one: Path, conda_cli: CondaCLIFixture): 21 # verify success! In the fixture named env_one, we create a new environment using the tmp_env fixture. We yield to mark the end of the setup. Since the tmp_env fixture extends tmp_path no additional teardown is command(arguments: list[str]): print("Conda subcommand!") @conda.plugins.hookimpl def conda_subcommands(): yield conda.plugins.CondaSubcommand( name="example", action=command, summary="Example of a conda subcommand"

389 conda, Release 24.11.3.dev2 (continued from previous page) 16 with tmp_env() as prefix: 17 yield prefix 18 19 20 def test_conda_create(env_one: Path, conda_cli: CondaCLIFixture): 21 # verify success! In the fixture named env_one, we create a new environment using the tmp_env fixture. We yield to mark the end of the setup. Since the tmp_env fixture extends tmp_path no additional teardown is command(arguments: list[str]): print("Conda subcommand!") @conda.plugins.hookimpl def conda_subcommands(): yield conda.plugins.CondaSubcommand( name="example", action=command, summary="Example of a conda subcommand"