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Concurrency practice problems in Python

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Showing 19 of 19

Status Title Difficulty
A Fetcher Protocol three implementations can satisfy Medium
asyncify: a ParamSpec wrapper that does not block the loop Medium
BackgroundTasks: strong references, and a drain that raises Medium
BoundedBuffer: a blocking queue from one Condition Medium
Bounded concurrency and backpressure Hard
BoundedCounter: check-then-act under 64 threads Medium
Capstone: a typed, cancellable, observable worker pool Hard
Deadline: one budget, many nested scopes Medium
ExceptionGroup, split() and except* Hard
fetch_all: structured fan-out with TaskGroup Medium
map_with_failures: partial success on a thread pool Medium
Placement 5/6: async cancellation Hard
process_stream: a bounded pipeline that cannot hang Medium
request_context: an id that survives tasks and threads Medium
run_sync: the sync boundary a library should expose Easy
run_workers: results, errors and a join deadline Medium
Service.serve: a shutdown that is bounded and returns Hard
Subinterpreters: PEP 734 and the Typed Queue Medium
with_cleanup: bounded cleanup on every exit path Hard