pleasepoint_py.job

class job:

Usage examples with AIstudio:

from pleasepoint_py import AIStudio
studio = AIStudio()

# Direct job calls - queue type is automatically determined
# account_id is taken automatically from config
studio.job.calculateStats(
    env_type='pro',
    date_range='30d',
    include_inactive=True
)

studio.job.runAistudio(
    env_type='pro',
    model_id='anthropic.claude-v2',
    prompt='Generate report'
)

# Custom job types and queues
# Method 1: Initialize with custom configurations
custom_job_types = {
    "myCustomJob": "redis",
    "dataProcessing": "sqs"
}
custom_queues = {
    "redis": {"myCustomJob": "my-queue-{env}"},
    "sqs": {"dataProcessing": "data-processing-queue-{env}.fifo"}
}
job_instance = job(custom_job_types=custom_job_types, custom_queues=custom_queues)
job_instance.myCustomJob.invokeJob(param1="value1")

# Method 2: Add custom jobs dynamically
job_instance = job()
job_instance.add_job_type("newJob", "sqs")
job_instance.add_custom_queue("sqs", "newJob", "new-job-queue-{env}")
job_instance.newJob.invokeJob(custom_param="test")
redis_queues
sqs_queues
def add_custom_job(self, job_name, queue_type):

Add a new custom job type

Args: job_name (str): Name of the custom job queue_type (str): Queue type ('redis' or 'sqs')

def add_custom_queue(self, job_name, queue_name):

Add a custom queue configuration

Args: job_name (str): Name of the job queue_name (str): Queue name (can include {env} placeholder)