update_page_info(url): page = fetch_page.delay(url).get(disable_sync_subtasks=False) info = parse_page.delay(url, page).get(disable_sync_subtasks=False) store_page_info.delay(url, info) @app.task verifying heartbeats), merging event fields together as events come in, making sure time-stamps are in sync, and so on. Combining these you can easily process events in real-time: from celery import Celery bootsteps: >>> app = Celery() >>> app.steps['worker'].add(MyWorkerStep) # < add class, don't instantiate >>> app.steps['consumer'].add(MyConsumerStep) >>> app.steps['consumer'].update([StepA, StepB])

update_page_info(url): page = fetch_page.delay(url).get(disable_sync_subtasks=False) info = parse_page.delay(url, page).get(disable_sync_subtasks=False) store_page_info.delay(url, info) @app.task verifying heartbeats), merging event fields together as events come in, making sure time-stamps are in sync, and so on. Combining these you can easily process events in real-time: from celery import Celery bootsteps: >>> app = Celery() >>> app.steps['worker'].add(MyWorkerStep) # < add class, don't instantiate >>> app.steps['consumer'].add(MyConsumerStep) >>> app.steps['consumer'].update([StepA, StepB])

update_page_info(url): page = fetch_page.delay(url).get(disable_sync_subtasks=False) info = parse_page.delay(url, page).get(disable_sync_subtasks=False) store_page_info.delay(url, info) @app.task verifying heartbeats), merging event fields together as events come in, making sure time-stamps are in sync, and so on. Combining these you can easily process events in real-time: from celery import Celery bootsteps: >>> app = Celery() >>> app.steps['worker'].add(MyWorkerStep) # < add class, don't instantiate >>> app.steps['consumer'].add(MyConsumerStep) >>> app.steps['consumer'].update([StepA, StepB])

update_page_info(url): page = fetch_page.delay(url).get(disable_sync_subtasks=False) info = parse_page.delay(url, page).get(disable_sync_subtasks=False) store_page_info.delay(url, info) @app.task verifying heartbeats), merging event fields together as events come in, making sure time-stamps are in sync, and so on. Combining these you can easily process events in real-time: from celery import Celery bootsteps: >>> app = Celery() >>> app.steps['worker'].add(MyWorkerStep) # < add class, don't instantiate >>> app.steps['consumer'].add(MyConsumerStep) >>> app.steps['consumer'].update([StepA, StepB])

verifying heartbeats), merging event fields together as events come in, making sure time-stamps are in sync, and so on. Combining these you can easily process events in real-time: from celery import Celery bootsteps: >>> app = Celery() >>> app.steps['worker'].add(MyWorkerStep) # < add class, don't instantiate >>> app.steps['consumer'].add(MyConsumerStep) >>> app.steps['consumer'].update([StepA, StepB]) CELERYBEAT_SCHEDULER beat_scheduler CELERYBEAT_SCHEDULE_FILENAME beat_schedule_filename CELERYBEAT_SYNC_EVERY beat_sync_every BROKER_URL broker_url BROKER_TRANSPORT broker_transport BROKER_TRANSPORT_OPTIONS

verifying heartbeats), merging event fields together as events come in, making sure time-stamps are in sync, and so on. Combining these you can easily process events in real-time: from celery import Celery bootsteps: >>> app = Celery() >>> app.steps['worker'].add(MyWorkerStep) # < add class, don't instantiate >>> app.steps['consumer'].add(MyConsumerStep) >>> app.steps['consumer'].update([StepA, StepB]) CELERYBEAT_SCHEDULER beat_scheduler CELERYBEAT_SCHEDULE_FILENAME beat_schedule_filename CELERYBEAT_SYNC_EVERY beat_sync_every BROKER_URL broker_url BROKER_TRANSPORT broker_transport BROKER_TRANSPORT_OPTIONS

proxy models are intended to behave exactly like the model they are proxying for. They are always in sync with the parent model since they directly inherit its fields and managers. The general rules are: instance of that class represents a particular record in the database table. To create an object, instantiate it using keyword arguments to the model class, then call save() to save it to the database. Assuming we suggest you write your ORM code inside a separate, synchronous function and then call that using sync_to_async - see Asynchronous support for more. Querying JSONField Lookups implementation is different

update_page_info(url): page = fetch_page.delay(url).get(disable_sync_subtasks=False) info = parse_page.delay(url, page).get(disable_sync_subtasks=False) store_page_info.delay(url, info) @app.task def verifying heart- beats), merging event fields together as events come in, making sure time-stamps are in sync, and so on. Combining these you can easily process events in real-time: from celery import Celery bootsteps: >>> app = Celery() >>> app.steps['worker'].add(MyWorkerStep) # < add class, don't instantiate >>> app.steps['consumer'].add(MyConsumerStep) >>> app.steps['consumer'].update([StepA, StepB])

update_page_info(url): page = fetch_page.delay(url).get(disable_sync_subtasks=False) info = parse_page.delay(url, page).get(disable_sync_subtasks=False) store_page_info.delay(url, info) @app.task def verifying heart- beats), merging event fields together as events come in, making sure time-stamps are in sync, and so on. Combining these you can easily process events in real-time: from celery import Celery bootsteps: >>> app = Celery() >>> app.steps['worker'].add(MyWorkerStep) # < add class, don't instantiate >>> app.steps['consumer'].add(MyConsumerStep) >>> app.steps['consumer'].update([StepA, StepB])

update_page_info(url): page = fetch_page.delay(url).get(disable_sync_subtasks=False) info = parse_page.delay(url, page).get(disable_sync_subtasks=False) store_page_info.delay(url, info) @app.task def verifying heart- beats), merging event fields together as events come in, making sure time-stamps are in sync, and so on. Combining these you can easily process events in real-time: from celery import Celery bootsteps: >>> app = Celery() >>> app.steps['worker'].add(MyWorkerStep) # < add class, don't instantiate >>> app.steps['consumer'].add(MyConsumerStep) >>> app.steps['consumer'].update([StepA, StepB])