class CountDownLatch(object):
def __init__(self):
self.con = Condition() # 条件变量
def wait(self):
with self.con:
self.con.wait()
def countDown(self):
with self.con:
self.con.notify_all() # 开枪（唤醒所有线程）
def run(
input_image: Array,
new_input_image: Condition,
input_size: (int, int),
output_image: Array,
new_output_image: Condition,
output_size: (int, int),
):
while True:
with new_input_image:
new_input_image.wait()
with input_image.get_lock():
image = Image.frombuffer("RGB", input_size, input_image.get_obj())
result = image.resize(output_size, resample=Image.NEAREST)
with output_image.get_lock():
dest = numpy.frombuffer(output_image.get_obj(), dtype=numpy.uint8).reshape(
(output_size[0], output_size[1], 3)
)
numpy.copyto(dest, numpy.array(result))
with new_output_image:
new_output_image.notify_all()
class MaxPriorityQueue(object):
"""自定义一个最大优先队列"""
def __init__(self):
self.__h_list = []
self.__con = Condition() # 条件变量
self.__index = 0 # 索引
def put(self, value, sort=0):
with self.__con:
# heapq是最小二叉堆，优先级取负就是最大二叉堆了
heapq.heappush(self.__h_list, (-sort, self.__index, value))
self.__index += 1
self.__con.notify() # 随机通知一个阻塞等的线程
def get(self):
with self.__con:
while 1:
# 0 => False
if not self.qsize():
self.__con.wait() # 列表为空则阻塞等
return heapq.heappop(self.__h_list)[-1] # 返回元组最后一个元素（value）
def qsize(self):
return len(self.__h_list)
def __init__(self):
self.con = Condition() # 条件变量
from multiprocessing.dummy import Pool as ThreadPool, Condition
s_list = []
con = Condition()
def Shop(i):
global con
global s_list
# 加锁保护共享资源
for x in range(5):
with con:
s_list.append(x)
print(f"[生产者{i}]生产商品{x}")
con.notify_all() # 通知消费者有货了
def User(i):
global con
global s_list
while True:
with con:
if s_list:
print(f"列表商品：{s_list}")
name = s_list.pop() # 消费商品
print(f"[消费者{i}]消费商品{name}")
print(f"列表剩余：{s_list}")
else:
con.wait()
def __init__(self):
self.__h_list = []
self.__con = Condition() # 条件变量
self.__index = 0 # 索引