real-time web monitor is in development. Serial- ization Supports Pickle, JSON, YAML, or easily defined custom schemes. One task invocation can have a different scheme than another. Trace- backs Errors and @task decorator actually creates a class that inherits from Task. The best practice is to only create custom task classes when you want to change generic behavior, and use the decorator to define tasks. See be in the current directory or on the Python path, so that it can be imported. You can also set a custom name for the configuration module by using the CELERY_CONFIG_MODULE environment variable. Let’s

real-time web monitor is in development. Serial- ization Supports Pickle, JSON, YAML, or easily defined custom schemes. One task invocation can have a different scheme than another. Trace- backs Errors and @task decorator actually creates a class that inherits from Task. The best practice is to only create custom task classes when you want to change generic behavior, and use the decorator to define tasks. See be in the current directory or on the Python path, so that it can be imported. You can also set a custom name for the configuration module by using the CELERY_CONFIG_MODULE environment variable. Let’s

real-time web monitor is in development. Serialization Supports Pickle, JSON, YAML, or easily defined custom schemes. One task invocation can have a different scheme than another. Tracebacks Errors and tracebacks @task decorator actually creates a class that inherits from Task. The best practice is to only create custom task classes when you want to change generic behavior, and use the decorator to define tasks. See be in the current directory or on the Python path, so that it can be imported. You can also set a custom name for the configuration module by using the CELERY_CONFIG_MODULE environment variable. Let’s

real-time web monitor is in development. Serial- ization Supports Pickle, JSON, YAML, or easily defined custom schemes. One task invocation can have a different scheme than another. Trace- backs Errors and @task decorator actually creates a class that inherits from Task. The best practice is to only create custom task classes when you want to change generic behavior, and use the decorator to define tasks. See be in the current directory or on the Python path, so that it can be imported. You can also set a custom name for the configuration module by using the CELERY_CONFIG_MODULE environment variable. Let’s

real-time web monitor is in development. Serialization Supports Pickle, JSON, YAML, or easily defined custom schemes. One task invocation can have a different scheme than another. Tracebacks Errors and tracebacks @task decorator actually creates a class that inherits from Task. The best practice is to only create custom task classes when you want to change generic behavior, and use the decorator to define tasks. See be in the current directory or on the Python path, so that it can be imported. You can also set a custom name for the configuration module by using the CELERY_CONFIG_MODULE environment variable. Let’s

real-time web monitor is in development. Serialization Supports Pickle, JSON, YAML, or easily defined custom schemes. One task invocation can have a different scheme than another. Tracebacks Errors and tracebacks @task decorator actually creates a class that inherits from Task. The best practice is to only create custom task classes when you want to change generic behavior, and use the decorator to define tasks. See be in the current directory or on the Python path, so that it can be imported. You can also set a custom name for the configuration module by using the CELERY_CONFIG_MODULE environment variable. Let’s

real-time web monitor is in development. Serial- ization Supports Pickle, JSON, YAML, or easily defined custom schemes. One task invocation can have a different scheme than another. Trace- backs Errors and @task decorator actually creates a class that inherits from Task. The best practice is to only create custom task classes when you want to change generic behavior, and use the decorator to define tasks. See be in the current directory or on the Python path, so that it can be imported. You can also set a custom name for the configuration module by using the CELERY_CONFIG_MODULE environment variable. Let’s

real-time web monitor is in development. Serialization Supports Pickle, JSON, YAML, or easily defined custom schemes. One task invocation can have a different scheme than another. Tracebacks Errors and tracebacks @task decorator actually creates a class that inherits from Task. The best practice is to only create custom task classes when you want to change generic behavior, and use the decorator to define tasks. See be in the current directory or on the Python path, so that it can be imported. You can also set a custom name for the configuration module by using the CELERY_CONFIG_MODULE environment variable. Let’s

optimized settings). • Flexible Almost every part of Celery can be extended or used on its own, Custom pool implementations, serializers, compression schemes, logging, schedulers, consumers, producers Linux. Read more... . • Autoscaling Dynamically resizing the worker pool depending on load, or custom metrics specified by the user, used to limit memory usage in shared hosting/cloud environments or practices • create a custom task base class • add a callback to a group of tasks • split a task into several chunks • optimize the worker • see a list of built-in task states • create custom task states • set

and optimized settings). Flexible Almost every part of Celery can be extended or used on its own, Custom pool implementations, serializers, compression schemes, logging, schedulers, consumers, producers support on Linux. Read more…. Autoscaling Dynamically resizing the worker pool depending on load, or custom metrics specified by the user, used to limit memory usage in shared hosting/cloud environments or create a custom task base class add a callback to a group of tasks split a task into several chunks optimize the worker see a list of built-in task states create custom task states set a custom task name