7 and 1.11 Contents: Installation Requirements Compatibility. Configuration name workers daemonize_workers recycle timeout retry. compress save_limit guard_cycle sync queue_limit label settings.py # settings.py example Q_CLUSTER = { 'name': 'myproject', 'workers': 8, 'recycle': 500, 'timeout': 60, 'compress': True, discarded or failed. ## workers The number of workers to use in the cluster. Defaults to CPU count of the current host, but can be set to a custom number. $ ^{[1]} $ ## daemonize_workers Set the daemon flag

○ First steps with Celery. ○ Resources • User Guide Overview Tasks ○ Executing Tasks o Workers Guide o Periodic Tasks ○ Sets of tasks, Subtasks and Callbacks ○ HTTP Callback Tasks (Webhooks) machines. Supports broker clustering and HA when used in combination with RabbitMQ. You can set up new workers without central configuration (e.g. use your grandma's laptop to help if the queue is temporarily globally for all.| |Routing|Using AMQP's flexible routing model you can route tasks to different workers, or select different message topologies, by configuration or even at runtime.| |Remote-control|Worker

2011 (sources $ ^{2} $ ) - Obslolète : quota, web-sql : Web Storage, application-cache : Service Workers • API d'accès à la caméra $ ^{3} $ , avec du webGL $ ^{4} $ ... • Bachelor NIFFF 2014 : une Progressive Enhancement $ ^{17} $ • Rapidité : App Shell $ ^{18} $ , cache • Offline : Service Workers $ ^{19} $ • Install Banner $ ^{20} $ : HTTPS, WebApp Manifest, SW, 2 visits • Tests $ ^{21} $

Performance ## What did I learn? Service Workers: The Practical Bits by Patrick Meenan (Google) @patmeenan http://www.slideshare.net/patrickmeenan/service-workers-for-performance • They are effectively

Steps Resources - User Guide Application o Tasks - Calling Tasks Canvas: Designing Work-flows Workers Guide Daemonization Periodic Tasks Routing Tasks Monitoring and Management Guide o Security between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving st//') @app.task def hello(): return 'hello world' ``` ## Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers

Steps Resources - User Guide Application o Tasks - Calling Tasks Canvas: Designing Work-flows Workers Guide Daemonization Periodic Tasks Routing Tasks Monitoring and Management Guide o Security between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving st//') @app.task def hello(): return 'hello world' ``` ## Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers

between clients and workers. To initiate a task, a client adds a message to the queue, which the broker then delivers to a worker. A Celery system can consist of multiple workers and brokers, giving way ocalhost/') @app.task def hello(): return 'hello world' ## • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers message signing. ## Features ## • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

Steps Resources - User Guide Application Tasks o Calling Tasks Canvas: Designing Work-flows Workers Guide Daemonization Periodic Tasks Routing Tasks Monitoring and Management Guide o Security between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving st//') @app.task def hello(): return 'hello world' ``` ## Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers

Steps Resources - User Guide Application Tasks o Calling Tasks Canvas: Designing Work-flows Workers Guide Daemonization Periodic Tasks Routing Tasks Monitoring and Management Guide o Security between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving st//') @app.task def hello(): return 'hello world' ``` ## Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers

Steps Resources - User Guide Application Tasks o Calling Tasks Canvas: Designing Work-flows Workers Guide Daemonization Periodic Tasks Routing Tasks Monitoring and Management Guide o Security between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving st//') @app.task def hello(): return 'hello world' ``` ## Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers