def simple_coroutine():
 print('-> start')
 x = yield
 print('-> recived', x)

sc = simple_coroutine()

next(sc)
sc.send('zhexiao')

import inspect

def simple_coroutine(a):
 print('-> start')

 b = yield a
 print('-> recived', a, b)

 c = yield a + b
 print('-> recived', a, b, c)

# run 
sc = simple_coroutine(5)

next(sc)
sc.send(6) # 5, 6
sc.send(7) # 5, 6, 7

def averager():
 total = 0.0
 count = 0
 avg = None

 while True:
  num = yield avg
  total += num
  count += 1
  avg = total/count

# run
ag = averager()
# 预激协程
print(next(ag))  # None

print(ag.send(10)) # 10
print(ag.send(20)) # 15

class DemoException(Exception):
 """
 custom exception
 """

def handle_exception():
 print('-> start')

 while True:
  try:
   x = yield
  except DemoException:
   print('-> run demo exception')
  else:
   print('-> recived x:', x)

 raise RuntimeError('this line should never run')

he = handle_exception()
next(he)
he.send(10) # recived x: 10
he.send(20) # recived x: 20

he.throw(DemoException) # run demo exception

he.send(40) # recived x: 40
he.close()

he.throw(Exception) # run demo exception

def gen():
 for c in 'AB':
  yield c

print(list(gen()))

def gen_new():
 yield from 'AB'

print(list(gen_new()))

from collections import namedtuple

ResClass = namedtuple('Res', 'count average')


# 子生成器
def averager():
 total = 0.0
 count = 0
 average = None

 while True:
  term = yield
  if term is None:
   break
  total += term
  count += 1
  average = total / count

 return ResClass(count, average)


# 委派生成器
def grouper(storages, key):
 while True:
  # 获取averager()返回的值
  storages[key] = yield from averager()


# 客户端代码
def client():
 process_data = {
  'boys_2': [39.0, 40.8, 43.2, 40.8, 43.1, 38.6, 41.4, 40.6, 36.3],
  'boys_1': [1.38, 1.5, 1.32, 1.25, 1.37, 1.48, 1.25, 1.49, 1.46]
 }

 storages = {}
 for k, v in process_data.items():
  # 获得协程
  coroutine = grouper(storages, k)

  # 预激协程
  next(coroutine)

  # 发送数据到协程
  for dt in v:
   coroutine.send(dt)

  # 终止协程
  coroutine.send(None)
 print(storages)

# run
client()

import collections

# time 字段是事件发生时的仿真时间，
# proc 字段是出租车进程实例的编号，
# action 字段是描述活动的字符串。
Event = collections.namedtuple('Event', 'time proc action')


def taxi_process(proc_num, trips_num, start_time=0):
 """
 每次改变状态时创建事件，把控制权让给仿真器
 :param proc_num:
 :param trips_num:
 :param start_time:
 :return:
 """
 time = yield Event(start_time, proc_num, 'leave garage')

 for i in range(trips_num):
  time = yield Event(time, proc_num, 'pick up people')
  time = yield Event(time, proc_num, 'drop off people')

 yield Event(time, proc_num, 'go home')

# run
t1 = taxi_process(1, 1)
a = next(t1) 
print(a) # Event(time=0, proc=1, action='leave garage')
b = t1.send(a.time + 6)
print(b) # Event(time=6, proc=1, action='pick up people')
c = t1.send(b.time + 12)
print(c) # Event(time=18, proc=1, action='drop off people')
d = t1.send(c.time + 1)
print(d) # Event(time=19, proc=1, action='go home')

import collections
import queue
import random

# time 字段是事件发生时的仿真时间，
# proc 字段是出租车进程实例的编号，
# action 字段是描述活动的字符串。
Event = collections.namedtuple('Event', 'time proc action')


def taxi_process(proc_num, trips_num, start_time=0):
 """
 每次改变状态时创建事件，把控制权让给仿真器
 :param proc_num:
 :param trips_num:
 :param start_time:
 :return:
 """
 time = yield Event(start_time, proc_num, 'leave garage')

 for i in range(trips_num):
  time = yield Event(time, proc_num, 'pick up people')
  time = yield Event(time, proc_num, 'drop off people')

 yield Event(time, proc_num, 'go home')


class SimulateTaxi(object):
 """
 模拟出租车控制台
 """

 def __init__(self, proc_map):
  # 保存排定事件的 PriorityQueue 对象，
  # 如果进来的是tuple类型，则默认使用tuple[0]做排序
  self.events = queue.PriorityQueue()
  # procs_map 参数是一个字典,使用dict构建本地副本
  self.procs = dict(proc_map)

 def run(self, end_time):
  """
  排定并显示事件，直到时间结束
  :param end_time:
  :return:
  """
  for _, taxi_gen in self.procs.items():
   leave_evt = next(taxi_gen)
   self.events.put(leave_evt)

  # 仿真系统的主循环
  simulate_time = 0
  while simulate_time < end_time:
   if self.events.empty():
    print('*** end of events ***')
    break

   # 第一个事件的发生
   current_evt = self.events.get()
   simulate_time, proc_num, action = current_evt
   print('taxi:', proc_num, ', at time:', simulate_time, ', ', action)

   # 准备下个事件的发生
   proc_gen = self.procs[proc_num]
   next_simulate_time = simulate_time + self.compute_duration()

   try:
    next_evt = proc_gen.send(next_simulate_time)
   except StopIteration:
    del self.procs[proc_num]
   else:
    self.events.put(next_evt)
  else:
   msg = '*** end of simulation time: {} events pending ***'
   print(msg.format(self.events.qsize()))

 @staticmethod
 def compute_duration():
  """
  随机产生下个事件发生的时间
  :return:
  """
  duration_time = random.randint(1, 20)
  return duration_time


# 生成3个出租车，现在全部都没有离开garage
taxis = {i: taxi_process(i, (i + 1) * 2, i * 5)
   for i in range(3)}

# 模拟运行
st = SimulateTaxi(taxis)
st.run(100)