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Depending on the thread scheduler, a busy-wait loop can hog the CPU and make the tests very slow. So convert such loops to loops that have an explicit sleep, allowing the worker threads to do their job.
47 lines
1.1 KiB
Python
47 lines
1.1 KiB
Python
# stress test for the heap by allocating lots of objects within threads
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# allocates about 5mb on the heap
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#
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# MIT license; Copyright (c) 2016 Damien P. George on behalf of Pycom Ltd
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try:
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import utime as time
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except ImportError:
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import time
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import _thread
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def last(l):
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return l[-1]
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def thread_entry(n):
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# allocate a bytearray and fill it
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data = bytearray(i for i in range(256))
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# run a loop which allocates a small list and uses it each iteration
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lst = 8 * [0]
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sum = 0
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for i in range(n):
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sum += last(lst)
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lst = [0, 0, 0, 0, 0, 0, 0, i + 1]
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# check that the bytearray still has the right data
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for i, b in enumerate(data):
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assert i == b
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# print the result of the loop and indicate we are finished
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with lock:
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print(sum, lst[-1])
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global n_finished
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n_finished += 1
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lock = _thread.allocate_lock()
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n_thread = 10
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n_finished = 0
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# spawn threads
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for i in range(n_thread):
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_thread.start_new_thread(thread_entry, (10000,))
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# wait for threads to finish
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while n_finished < n_thread:
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time.sleep(1)
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