ESICelery

ESI API requests library using RabbitMQ, celery tasks queues, and Redis caching.

Installation

pip install ESICelery

Usage

Starting the Celery worker server

From CLI

Set the following environmental variables and then run ESICelery from the CLI. Variables: BrokerUser, BrokerPassword, BrokerHost, BrokerPort, BrokerVhost, ResultBackendUser, ResultBackendPassword, ResultBackendHost, ResultBackendPort, ResultBackendDb

python ESICelery

From your code

From your worker code start the Celery worker server that handles running tasks:

from ESICelery.CeleryApps import CeleryWorker

c = CeleryWorker(broker_user="user", broker_password="pass", broker_host="host", broker_port=5672, broker_vhost="esi",
                 result_user="user", result_password="pass", result_host="host", result_port=6379, result_db=0,
                 header_email="youremail@example.com")

c.start(
    max_concurrency=10)  # Start celery app - equivalent to running "celery worker -l WARNING --autoscale 10,1 -Q queues"

Using ESICelery in your code

From another Python script you can send tasks to the queues and receive results:

from ESICelery.CeleryApps import CeleryWorker
from ESICelery.tasks.Universe import *

c = CeleryWorker(broker_user="user", broker_password="pass", broker_host="host", broker_port=5672, broker_vhost="esi",
                 result_user="user", result_password="pass", result_host="host", result_port=6379, result_db=0,
                 header_email="youremail@example.com")  # only need to call this once in our code to init the tasks
r = SystemInfo().get_sync(timeout=5, system_id=30000142)
print(r)

Current supported endpoints

Examples

See the included example scripts under docs/examples

Copyright Notice

See CCP.md