@Marvin does:

async with concurrency(MODEL_REGISTRATION_CONCURRENCY_LIMIT_NAME, 5):
    for model_id, model in models.items():
        await ingest_model(model_id, model)

mean taht only 5 will execute at a time? or all will execute and only count for 5? this is a global concurrency limit

The

concurrency

context manager in Prefect is used to control the maximum number of concurrent operations. In your code snippet, it ensures that only up to 5 operations can execute concurrently within the context. This means that at any given time, only 5 instances of

ingest_model

will run concurrently, adhering to the specified concurrency limit. This is a global concurrency limit, so it applies across all uses of the same concurrency context identified by

MODEL_REGISTRATION_CONCURRENCY_LIMIT_NAME

. For more details, you can refer to the Prefect documentation on global concurrency limits: Prefect Global Concurrency Limits.

@flow
async def model_preprocessing_flow(models: dict[str, dict[str, str]]):
    ingestion_coros = []
    for model_id, model in models.items():
        ingestion_coros.append(ingest_model_limited(model_id, model))
    results = await asyncio.gather(*ingestion_coros, return_exceptions=True)
            
    
async def ingest_model_limited(model_id, model, genome_set):
    """
    Helper function to allow for the flow to be wrapped in a concurrency block
    """
    async with concurrency(MODEL_REGISTRATION_CONCURRENCY_LIMIT_NAME, 1):
        await ingest_model(model_id, model)

@flow
async def ingest_model(model_id, model: dict):
    ...

@Marvin why does it initially start respecting the concurrency limits and only launching 5 subflows, but then even though the 5 initial subflows are still running, the global concurrency active number drops to 0 and it launches all of them?

The behavior you're observing, where the concurrency limit is initially respected but then seems to disregard the limit, could be due to several reasons related to how the concurrency limits are configured or implemented. Here are some possible explanations: 1. Concurrency Context Misconfiguration: Ensure that the concurrency context is correctly configured to maintain state across multiple uses. If the context is not properly set up, it might not track the number of active slots correctly. 2. Slot Decay Misconfiguration: If the slot decay is configured (or misconfigured), it might be releasing slots faster than expected. This would cause the active count to drop unexpectedly. 3. Concurrency Context Scope: The concurrency context manager might not be correctly scoped or might be reset between different parts of your flow, leading to incorrect tracking of the concurrency slots. 4. Async Behavior: The asynchronous nature of your flow and tasks might lead to race conditions or unexpected behaviors if the concurrency context is not thread-safe or properly synchronized across async tasks. To troubleshoot further, consider the following steps: - Inspect Concurrency Configuration: Double-check the concurrency limit configuration, especially the

slot_decay_per_second

parameter, to ensure it's set as intended. - Logging and Debugging: Add logging within the

concurrency

context to track when slots are acquired and released. This might provide insights into unexpected slot releases. - Prefect Version Issues: Ensure you're using a stable version of Prefect, as concurrency issues might be resolved in newer versions. For more detailed guidance, you might want to refer to the Prefect documentation on global concurrency limits: Prefect Global Concurrency Limits. If the problem persists, consider reaching out to the Prefect community or support for more tailored assistance.

@Marvin oh, does taht mean global concurrency doesnt actually block the slot until the process in the concurrency context is done? it releases it according to slot decay?

Yes, that's correct. In Prefect, the global concurrency limit can be configured with a slot decay, which means that slots may become available again based on the decay rate rather than strictly when the task within the concurrency context completes. Here's how it works: - Slot Occupancy: When a task enters the concurrency context, it occupies a slot. - Slot Decay: If a

slot_decay_per_second

is configured, the slot can become available again over time, independent of whether the task has completed. This can lead to a situation where more tasks are allowed to start if the decay rate is high enough. This behavior is intended to create a "rate limiting" effect, allowing tasks to run more frequently but with controlled pauses between them. If you want the slot to be held for the entire duration of the task, make sure that the slot decay is set to a value that aligns with your task execution time, or simply set it to

0

to disable decay. For a more detailed explanation, you can refer to the Prefect documentation on global concurrency limits: Prefect Global Concurrency Limits.

@Marvin ok but what if i want it to just wait for the thing inside the concurrency context to finish before releasing?

If you want the concurrency context to hold onto a slot until the task inside it completes, you should configure it without any slot decay. This ensures that a slot is only released when the task within the concurrency context finishes executing. Here's what you can do: 1. Set Slot Decay to Zero: Ensure that the

slot_decay_per_second

parameter is set to

0

or is not configured. This will make the slot occupancy duration equal to the task execution time. 2. Verify Configuration: Double-check the concurrency limit configuration using the Prefect CLI or other configuration tools to ensure that no decay is inadvertently set. By doing this, the slots will be held until the tasks complete, thereby respecting the concurrency limit throughout the task's execution. For more information, you might want to review the Prefect documentation on configuring concurrency limits: Prefect Global Concurrency Limits.

@Marvin a flow i cancelled isnt give up its active slots

If a flow that you've canceled is not releasing its active slots, it may be due to the way cancellation is handled or how the concurrency mechanism is implemented. Here are some potential reasons and steps to address the issue: 1. Graceful Cancellation: Ensure that the flow is being canceled in a way that allows it to gracefully release resources, including concurrency slots. If the cancellation is abrupt, it might not trigger the necessary cleanup processes. 2. Concurrency Context Exit: Verify that the concurrency context is properly set up to release slots when a flow is canceled. This might involve ensuring that any cleanup logic within the context manager is executed even on cancellation. 3. Slot Release Logic: Check if there is any custom logic or configuration that might interfere with the automatic release of slots upon cancellation. 4. Prefect Version: Make sure you're using the latest stable version of Prefect, as there might be fixes related to concurrency and cancellation issues in newer releases. 5. Logging and Monitoring: Add logging to monitor slot acquisition and release events. This can help diagnose where the release process might be failing. 6. Prefect Support: If the issue persists, consider reaching out to the Prefect community or support for further assistance, as it might be a bug or require a deeper dive into the specific setup. If you need further guidance on handling concurrency and cancellation in Prefect, you can refer to the official documentation: Prefect Global Concurrency Limits.