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Reliable concurrency synchronization

neondatabase/neon
Based on 2 comments
Python

When handling concurrent operations, prefer completion signals and proper thread management over arbitrary timeouts. This improves code reliability and prevents hangs or deadlocks.

Concurrency Python

Reviewer Prompt

When handling concurrent operations, prefer completion signals and proper thread management over arbitrary timeouts. This improves code reliability and prevents hangs or deadlocks.

For waiting on asynchronous processes:

  • Instead of arbitrary timeouts that can cause flaky tests:
    # Avoid this
    wait_until(lambda: assert_condition(), timeout=120)
      
    # Prefer this
    env.storage_controller.reconcile_until_idle()
    wait_until(lambda: assert_condition())
    

For operations that might block indefinitely:

  • Use thread pools to prevent the main execution thread from hanging:
    # Instead of potentially blocking code
    ps.restart()  # Could hang waiting for active status
      
    # Use a ThreadPoolExecutor for potentially blocking operations
    with concurrent.futures.ThreadPoolExecutor() as executor:
        future = executor.submit(ps.restart)
        # Continue execution or implement proper timeout handling
    

These patterns ensure that your concurrent code is more predictable, testable, and less prone to timing-dependent issues.

2
Comments Analyzed
Python
Primary Language
Concurrency
Category

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