管理并发# Run tasks concurrently or in parallel Configure a task runner Access results from submitted tasks Mapping over iterables Use multiple task runners Limit concurrent task runs with tags Execution behavior Configure concurrency limits CLI Python client Apply global concurrency and rate limits Manage global concurrency and rate limits Active vs. inactive limits Slot decay Through the UI Through the CLI Using the concurrency context manager Using rate_limit Use concurrency and rate_limit outside of a flow Use cases Throttling task submission Manage database connections Parallel data processing Other ways to limit concurrency