📚 celeriac - Awesome Go Library for Distributed Systems
Library for adding support for interacting and monitoring Celery workers, tasks and events in Go.
Detailed Description of celeriac
Celeriac
Golang client library for adding support for interacting and monitoring Celery workers and tasks.
It provides functionality to place tasks on the task queue, as well as monitor both task and worker events.
Dependencies
This library depends upon the following packages:
- github.com/rabbitmq/amqp091-go
- github.com/sirupsen/logrus
- github.com/nu7hatch/gouuid
- github.com/mailru/easyjson
Install easyjson
$ go get -u github.com/mailru/easyjson/...
Usage
Installation: go get github.com/svcavallar/celeriac.v1
This imports a new namespace called celeriac
package main
import (
"log"
"os"
"github.com/svcavallar/celeriac.v1"
)
func main() {
taskBrokerURI := "amqp://user:pass@localhost:5672/vhost"
// Connect to RabbitMQ task queue
TaskQueueMgr, err := celeriac.NewTaskQueueMgr(taskBrokerURI)
if err != nil {
log.Printf("Failed to connect to task queue: %v", err)
os.Exit(-1)
}
log.Printf("Service connected to task queue - (URL: %s)", taskBrokerURI)
// Go routine to monitor the Celery events emitted on the celeriac events channel
go func() {
for {
select {
default:
ev := <-TaskQueueMgr.Monitor.EventsChannel
if ev != nil {
if x, ok := ev.(*celeriac.WorkerEvent); ok {
log.Printf("Celery Event Channel: Worker event - %s [Hostname]: %s", x.Type, x.Hostname)
} else if x, ok := ev.(*celeriac.TaskEvent); ok {
log.Printf("Celery Event Channel: Task event - %s [ID]: %s", x.Type, x.UUID)
} else if x, ok := ev.(*celeriac.Event); ok {
log.Printf("Celery Event Channel: General event - %s [Hostname]: %s - [Data]: %v", x.Type, x.Hostname, x.Data)
} else {
log.Printf("Celery Event Channel: Unhandled event: %v", ev)
}
}
}
}
}()
}
Dispatching Tasks
By Name
This will create and dispatch a task incorporating the supplied data. The task will automatically be allocated and identified by a UUID returned in the task object. The UUID is represented in the form of "6ba7b810-9dad-11d1-80b4-00c04fd430c8".
// Dispatch a new task
taskName := "root.test.task"
taskData := map[string]interface{}{
"foo": "bar"
}
routingKey := "root.test"
task, err := TaskQueueMgr.DispatchTask(taskName, taskData, routingKey)
if err != nil {
log.Errorf("Failed to dispatch task to queue: %v", err)
}
By ID & Name
This will create and dispatch a task incorporating the supplied data, and identified by the user-supplied task identifier.
// Dispatch a new task
taskID := "my_task_id_123456789"
taskName := "root.test.task"
taskData := map[string]interface{}{
"foo": "bar"
}
routingKey := "root.test"
task, err := TaskQueueMgr.DispatchTaskWithID(taskID, taskName, taskData, routingKey)
if err != nil {
log.Errorf("Failed to dispatch task to queue: %v", err)
}
Modifying task_event.go
If you modify the properties of any the structs in task_event.go
you will need to re-generate the easyjson
version of this file. This is easily achieved by issuing the following command:
$ easyjson -all task_eventtest.go
Processing Redis Backend Result Automatically
If you are using a Redis backend for storing results you can easily process new/updated entries by subscribing to Redis keyspace events.
This will save polling for results, and is made convenient to integrate by using my golang helper package go-redis-event-sink
, available at the repo https://github.com/svcavallar/go-redis-event-sink
An example on how to use this is provided within the repository. Essentially, just provide it with the Celery task naming mask patten to watch: celery-task-meta-*