Best Python code snippet using localstack_python
test_api.py
Source: test_api.py
...48 app1, [job_id1, job_id2], all=True,49 raise_if_not_exists=True50 ))51@tt.with_setup52def test_get_qsize(app1, job_id1, job_id2):53 nt.assert_equal(api.get_qsize(app1, queued=True, taken=True), 0)54 tt.enqueue(app1, job_id1, )55 tt.enqueue(app1, job_id2, validate_queued=False)56 q = api.get_qbclient().LockingQueue(app1)57 itm = q.get()58 nt.assert_equal(2, api.get_qsize(app1, queued=True, taken=True))59 nt.assert_equal(1, api.get_qsize(app1, queued=False, taken=True))60 nt.assert_equal(1, api.get_qsize(app1, queued=True, taken=False))61 q.put(itm)62 q.consume()63 nt.assert_equal(2, api.get_qsize(app1, queued=True, taken=True))64 nt.assert_equal(0, api.get_qsize(app1, queued=False, taken=True))65 nt.assert_equal(2, api.get_qsize(app1, queued=True, taken=False))66@tt.with_setup67def test_maybe_add_subtask(app1, job_id1, job_id2, job_id3):68 # we don't queue anything if we request queue=False, but we create data for69 # this node if it doesn't exist70 tt.validate_zero_queued_task(app1)71 api.maybe_add_subtask(app1, job_id1, queue=False)72 tt.validate_zero_queued_task(app1)73 # data for this job_id exists, so it can't get queued74 api.maybe_add_subtask(app1, job_id1, priority=4)75 tt.validate_zero_queued_task(app1)76 api.maybe_add_subtask(app1, job_id2, priority=8)77 tt.validate_one_queued_task(app1, job_id2)78 api.maybe_add_subtask(app1, job_id3, priority=5)79 # this should have no effect because it's already queued with priority=5...
parallel_generator.py
Source: parallel_generator.py
...62 i = 063 # before = time.time()64 65 while not self.buffer.full():66 if self.get_qsize():67 buffer_size = self.get_qsize()68 print('Filling train buffer: {}/{}'.format(69 self.get_qsize(),70 str(self.buffer_size).ljust(len(str(buffer_size)))71 ), end='\r')72 else:73 print('Filling {} buffer'.format('train')74 + '.' * i + ' ' * (3 - i), end='\r')75 i += 176 i = i % 477 time.sleep(.5)78 print("Filling {} buffer... Done.".format('train'))79 # print('\n\n\n\n\n TOTAL TIME: ', time.time() - before, '\n\n\n')80 def fill_test_registry(self):81 return cp(self.testing)82 def reset_test(self):83 self.test_registry = cp(self.testing)84 def push(self, buffer):85 """86 Loads and augments datapoint with a seed87 and places it in a multiprocessing buffer.88 BEWARE: This method is called by multiple subprocesses.89 Ensure thread safety!90 """91 # We have to seed the differnt processes or else they 92 # will draw identical samples93 np.random.seed(os.getpid())94 # We also might want to initialize each process95 # on different classes if class balancing is desired.96 while True:97 items = self.get_datapoints(seed=os.getpid())98 for item in items:99 buffer.put(item)100 # print("Process #{} successfully added item of class {} to buffer.".format(os.getpid(), idx))101 # print('Producer {} exiting'.format(os.getpid()))102 def get_datapoints(self, **kwargs):103 """104 Method that from a seed loads a datapoint (x and y) and 105 places returns them in a list for pushing to the buffer.106 This method is the bread and butter of the generator class,107 everything else in this class are simply support methods for 108 maintaining the queue/buffer and sorting the data samples.109 This method should actively load the data point from the drive,110 normalize and augment.111 """112 raise NotImplementedError113 def get_qsize(self):114 try:115 return self.buffer.qsize()116 except NotImplementedError:117 return False118 def dtype_to_order(self, dtype):119 if dtype in [np.int8, np.int16, np.int32, np.int64,120 np.uint8, np.uint16, np.uint32, np.uint64,121 bool, np.bool]:122 return 0123 return 3124 def __call__(self, batch_size, handle='train', patient_handle=None):125 out = []126 if handle == 'train':127 for _ in range(batch_size):...
simple_thread_runner.py
Source: simple_thread_runner.py
...58 self._queue.task_done()59 logger.info(f"Tasks left:{i}")60 def q_producer(self, _data):61 self._queue.put(_data)62 def get_qsize(self) -> int:63 """Get current size of queue, be aware this value is changed frequently64 as multiple threads may produce/consume data to the queue"""65 return self._queue.qsize()66 def q_consumer(self, num_workers: int, fn: Callable[..., Any]):67 """68 Function can be used separately with q_producer69 """70 with self._lock:71 try:72 self.prepare_threads(num_workers, fn)73 finally:74 self.wait_threads()75 def run_threads(self, num_workers: int, fn: Callable[..., Any], iter_data: Iterator[Any], batch_size: int = None):76 """Add batch_size params in case iter_data is huge number"""77 for _ in iter_data:78 self.q_producer(_)79 if batch_size:80 _qsize = self.get_qsize()81 if _qsize >= batch_size:82 self.q_consumer(num_workers, fn)83 _qsize = self.get_qsize()84 if _qsize != 0:...
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