Twitter @GerardoLijs C# MeetUp Barcelona April 2019 Content What is Asynchronous Programming CPU-bound vs IO-bound Obsolete patterns Tasks and async/await Practical use cases • Responsive user interfaces • Scalability and performance in web applications @GerardoLijs CPU-bound operations • Use Task.Run to execute expensive CPU-bound code in the ThreadPool • Define a Task returning method • In general the time you will need asynchronous to deal with IO-bound operations and the times you will use CPU-bound operations you will probably use a library that provides asynchronous methods for you to interact

“provides an asynchronous, evented and/or continuation passing style API for moving blocking/longish CPU-bound tasks out of Node's event loop to JavaScript threads that run in parallel in the background and

ProcessPoolExecutor is another alternative for long running tasks that do not release the GIL, such as CPU-bound pure Python code. Note, however, that ProcessPoolExecutor builds upon the multiprocessing mod- ule AbstractEventLoop.set_default_executor() is used to change it to something else. Due to the GIL, CPU-bound jobs will block request processing for the current process unless the default Executor is changed Warning: This helper is only to be used for functions that do not perform any blocking I/O or lengthy CPU-bound operations, since the entire async loop will be blocked while the wrapped function is executed.

ProcessPoolExecutor is another alternative for long running tasks that do not release the GIL, such as CPU-bound pure Python code. Note, however, that ProcessPoolExecutor builds upon the multiprocessing mod- ule AbstractEventLoop.set_default_executor() is used to change it to something else. Due to the GIL, CPU-bound jobs will block request processing for the current process unless the default Executor is changed Warning: This helper is only to be used for functions that do not perform any blocking I/O or lengthy CPU-bound operations, since the entire async loop will be blocked while the wrapped function is executed.

ProcessPoolExecutor is another alternative for long running tasks that do not release the GIL, such as CPU-bound pure Python code. Note, however, that ProcessPoolExecutor builds upon the multiprocessing mod- ule AbstractEventLoop.set_default_executor() is used to change it to something else. Due to the GIL, CPU-bound jobs will block request processing for the current process unless the default Executor is changed Warning: This helper is only to be used for functions that do not perform any blocking I/O or lengthy CPU-bound operations, since the entire async loop will be blocked while the wrapped function is executed.

ProcessPoolExecutor is another alternative for long running tasks that do not release the GIL, such as CPU-bound pure Python code. Note, however, that ProcessPoolExecutor builds upon the multiprocessing mod- ule AbstractEventLoop.set_default_executor() is used to change it to something else. Due to the GIL, CPU-bound jobs will block request processing for the current process unless the default Executor is changed Warning: This helper is only to be used for functions that do not perform any blocking I/O or lengthy CPU-bound operations, since the entire async loop will be blocked while the wrapped function is executed.

ProcessPoolExecutor is another alternative for long running tasks that do not release the GIL, such as CPU-bound pure Python code. Note, however, that ProcessPoolExecutor builds upon the multiprocessing mod- ule AbstractEventLoop.set_default_executor() is used to change it to something else. Due to the GIL, CPU-bound jobs will block request processing for the current process unless the default Executor is changed Warning: This helper is only to be used for functions that do not perform any blocking I/O or lengthy CPU-bound operations, since the entire async loop will be blocked while the wrapped function is executed.

ProcessPoolExecutor is another alternative for long running tasks that do not release the GIL, such as CPU-bound pure Python code. Note, however, that ProcessPoolExecutor builds upon the multiprocessing mod- ule AbstractEventLoop.set_default_executor() is used to change it to something else. Due to the GIL, CPU-bound jobs will block request processing for the current process unless the default Executor is changed Warning: This helper is only to be used for functions that do not perform any blocking I/O or lengthy CPU-bound operations, since the entire async loop will be blocked while the wrapped function is executed.

prefork. How- ever, you need to ensure one task doesn’t block the event loop too long. Generally, CPU-bound operations don’t go well with Evenetlet. Also note that some libraries, usually with C extensions routes.MapRoute instance. Examples: task_routes = { 'celery.ping': 'default', 'mytasks.add': 'cpu-bound', 'feed.tasks.*': 'feeds', # <-- glob pattern re.compile(r'(image|video)\.tasks\..*'): 'media' threads executing tasks. If you’re doing mostly I/O you can have more processes, but if mostly CPU-bound, try to keep it close to the number of CPUs on your machine. If not set, the number of CPUs/cores

prefork. How- ever, you need to ensure one task doesn’t block the event loop too long. Generally, CPU-bound operations don’t go well with Evenetlet. Also note that some libraries, usually with C extensions routes.MapRoute instance. Examples: task_routes = { 'celery.ping': 'default', 'mytasks.add': 'cpu-bound', 'feed.tasks.*': 'feeds', # <-- glob pattern re.compile(r'(image|video)\.tasks\..*'): 'media' threads executing tasks. If you’re doing mostly I/O you can have more processes, but if mostly CPU-bound, try to keep it close to the number of CPUs on your machine. If not set, the number of CPUs/cores