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. However, 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 MapRoute instance. Examples: task_routes = { 'celery.ping': 'default', 'mytasks.add': 'cpu-bound', 'feed.tasks.*': 'feeds', # <-- glob pattern re.compile(r'(image|video)\ 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. However, 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 MapRoute instance. Examples: task_routes = { 'celery.ping': 'default', 'mytasks.add': 'cpu-bound', 'feed.tasks.*': 'feeds', # <-- glob pattern re.compile(r'(image|video)\ 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

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. However, 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 MapRoute instance. Examples: task_routes = { 'celery.ping': 'default', 'mytasks.add': 'cpu-bound', 'feed.tasks.*': 'feeds', # <-- glob pattern re.compile(r'(image|video)\ 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

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 routes.MapRoute instance. Examples: CELERY_ROUTES = {"celery.ping": "default", "mytasks.add": "cpu-bound", "video.encode": { "queue": "video", "exchange": "media" "routing_key": "media.video.encode"}} MapRoute instance. Examples: >>> CELERY_ROUTES = {"celery.ping": "default", "mytasks.add": "cpu-bound", "video.encode": { "queue": "video", "exchange": "media" "routing_key": "media.video.encode"}}

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 instance. Examples: CELERY_ROUTES = {"celery.ping": "default", "mytasks.add": "cpu-bound", "video.encode": { "queue": "video", "exchange": Examples: >>> CELERY_ROUTES = {"celery.ping": "default", "mytasks.add": "cpu-bound", "video.encode": { "queue": "video",

prefork. However, you need to ensure one task doesn’t block the event loop too long. Generally, CPU-bound operations don’t go well with Eventlet. Also note that some libraries, usually with C extensions MapRoute instance. Examples: task_routes = { 'celery.ping': 'default', 'mytasks.add': 'cpu-bound', 'feed.tasks.*': 'feeds', # <-- glob pattern re.compile(r'(image|video)\ 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. However, you need to ensure one task doesn’t block the event loop too long. Generally, CPU-bound operations don’t go well with Eventlet. Also note that some libraries, usually with C extensions MapRoute instance. Examples: task_routes = { 'celery.ping': 'default', 'mytasks.add': 'cpu-bound', 'feed.tasks.*': 'feeds', # <-- glob pattern re.compile(r'(image|video)\ 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