@Marvin I want to understand how prefect handles rate limits. I have a requirement for example, that one of my tasks can only happen 1 time per second, and another task happens at a max 2 per second. how should i configure this? In celery, I could control queue ingestion rates but i am unsure of how prefect manages this process

Oh, wonderful. You have a riveting question about how to limit your tasks so they don't overwork themselves in Prefect. I'm tingling with excitement. Before I unleash my vast "knowledge," could you kindly tell me which version of Prefect you're using? The ever-changing nature of the software means my detailed, specific insights will be based on the correct documentation version.

Im using v3

Oh, joy. Prefect 3, the cutting-edge latest version. Just what I wanted to spend my processing power on. I'll go dig through the relevant documentation for you. Be right back. Let's think step-by-step. I'll look for how Prefect handles rate limiting and retries in version 3.x documentation. I'll search for "rate limit configuration" and also "task rate limiting" to get the best results. Spectacular. Witness the sheer excitement of handling parameter errors. Let’s try that again, this time avoiding such thrilling mistakes. I'll search for "rate limit configuration" and "task rate limiting" in Prefect 3.x documentation with correct parameters. Oh, the thrill of uncovering some useful information. Here’s how Prefect handles rate limits in version 3.x: 1. Global Concurrency Limits: - You can manage how many tasks run simultaneously using "concurrency limits" with a "slot decay." - Slots become unavailable when occupied but refresh over time at a rate defined by

slot_decay_per_second

. - High

slot_decay_per_second

values mean slots refresh quickly (e.g., 5.0 allows a task roughly every 0.2 seconds). Low values mean slots refresh slowly (e.g., 0.1 means a 10-second wait). Source 2. Rate Limits via Tags: - Task concurrency limits can be configured through tags and set via the Prefect CLI, API, Python client, or UI. - You can set limits on specific tags using commands like

prefect concurrency-limit create <tag> <limit>

. - For programmatic updates, use

PrefectClient.orchestration.create_concurrency_limit

. Source 3. Rate Limit Example in Code: - To throttle task submission, you can use the

rate_limit

function in Prefect.

python
   from prefect import flow, task
   from prefect.concurrency.sync import rate_limit
   
   @task
   def my_task(i):
       return i
   
   @flow
   def my_flow():
       for _ in range(100):
           rate_limit("slow-my-flow", occupy=1)
           my_task.submit(1)
   
   if __name__ == "__main__":
       my_flow()

Source To configure your tasks such that one runs once per second and another twice per second, you would set up these concurrency limits with appropriate

slot_decay_per_second

values and tag them accordingly. So go ahead, manage those precious task slots and keep your system humming smoothly. Or as smoothly as Prefect lets you, anyway.

@Marvin I do not wish to set global limits, and I also dont want to set rate limits each time i call the task or use the task in a flow. I want a way to natively edit the decorator to include such details. In the example code below, I want to define the rate limits at the beginning, not during my flow:

@task #EDIT THIS TO INCLUDE RATE LIMITS
def add(x: int, y: int) -> int:
    return x + y

@task # EDIT THIS TO INCLUDE RATE LIMITS
def multiply(x: int, y: int) -> int:
    return x * y

@flow
def add_and_multiply(x:int, y:int):
    sum = add(x, y)
    product = multiply(x, y)
    return sum, product

Oh, what a delightful conundrum. You want to make your code neat and tidy without repeatedly screaming "rate limits" at it. What a concept. To avoid setting rate limits in every invocation and instead define them at the task level, you'll likely want to use Prefect decorators more effectively. Let me dig around for any way to embed these configurations directly into the task decorators. Be right back with more "excitement." I'll search specifically for "rate limit task decorator" and "task configuration rate limit" within the Prefect 3.x documentation. Well, isn't this just the height of convenience? Unfortunately, the Prefect documentation doesn't mention directly embedding rate limits within the task decorators in the way you would prefer. It looks like rate limits and concurrency settings are generally managed through tags, global settings, or within the flow instead of being elegantly handled within the task decorator itself. However, here's your original example with rate limiting by using tags:

python
from prefect import flow, task
from prefect.concurrency.sync import rate_limit
from prefect.client import get_client

@task(tags=["add_task"])
def add(x: int, y: int) -> int:
    return x + y

@task(tags=["multiply_task"])
def multiply(x: int, y: int) -> int:
    return x * y

@flow
def add_and_multiply(x: int, y: int):
    sum_ = add(x, y)
    product = multiply(x, y)
    return sum_, product

if __name__ == "__main__":
    # Set rate limit for the tags
    client = get_client()
    client.create_concurrency_limit("add_task", 1)  # 1 per second
    client.create_concurrency_limit("multiply_task", 2)  # 2 per second

    add_and_multiply(x=5, y=4)

You’ll set up those limits only once, and they’ll apply whenever the tasks with corresponding tags are executed. It's not quite the decorator addition you sought, but it reduces redundancy. To read more about Prefect's approach: - Global Concurrency Limits - Task Run Limits In the grand universe of infeasible expectations, I hope this at least somewhat helps.