def select_sort(origin_items, comp=lambda x, y: x < y):
 """簡單選擇排序"""
 items = origin_items[:]
 for i in range(len(items) - 1):
  min_index = i
  for j in range(i + 1, len(items)):
   if comp(items[j], items[min_index]):
    min_index = j
  items[i], items[min_index] = items[min_index], items[i]
 return items
def bubble_sort(origin_items, comp=lambda x, y: x > y):
 """高質(zhì)量冒泡排序(攪拌排序)"""
 items = origin_items[:]
 for i in range(len(items) - 1):
  swapped = False
  for j in range(i, len(items) - 1 - i):
   if comp(items[j], items[j + 1]):
    items[j], items[j + 1] = items[j + 1], items[j]
    swapped = True
  if swapped:
   swapped = False
   for j in range(len(items) - 2 - i, i, -1):
    if comp(items[j - 1], items[j]):
     items[j], items[j - 1] = items[j - 1], items[j]
     swapped = True
  if not swapped:
   break
 return items
def merge_sort(items, comp=lambda x, y: x <= y):
 """歸并排序(分治法)"""
 if len(items) < 2:
  return items[:]
 mid = len(items) // 2
 left = merge_sort(items[:mid], comp)
 right = merge_sort(items[mid:], comp)
 return merge(left, right, comp)


def merge(items1, items2, comp):
 """合并(將兩個有序的列表合并成一個有序的列表)"""
 items = []
 index, index2 = 0, 0
 while index1 < len(items1) and index2 < len(items2):
  if comp(items1[index1], items2[index2]):
   items.append(items1[index1])
   index1 += 1
  else:
   items.append(items2[index2])
   index2 += 1
 items += items1[index1:]
 items += items2[index2:]
 return items
def seq_search(items, key):
 """順序查找"""
 for index, item in enumerate(items):
  if item == key:
   return index
 return -1
def bin_search(items, key):
 """折半查找"""
 start, end = 0, len(items) - 1
 while start <= end:
  mid = (start + end) // 2
  if key > items[mid]:
   start = mid + 1
  elif key < items[mid]:
   end = mid - 1
  else:
   return mid
 return -1

prices = {
 'AAPL': 191.88,
 'GOOG': 1186.96,
 'IBM': 149.24,
 'ORCL': 48.44,
 'ACN': 166.89,
 'FB': 208.09,
 'SYMC': 21.29
}
# 用股票價格大于100元的股票構造一個新的字典
prices2 = {key: value for key, value in prices.items() if value > 100}
print(prices2)

names = ['關羽', '張飛', '趙云', '馬超', '黃忠']
courses = ['語文', '數(shù)學', '英語']
# 錄入五個學生三門課程的成績
# 錯誤 - 參考http://pythontutor.com/visualize.html#mode=edit
# scores = [[None] * len(courses)] * len(names)
scores = [[None] * len(courses) for _ in range(len(names))]
for row, name in enumerate(names):
 for col, course in enumerate(courses):
  scores[row][col] = float(input(f'請輸入{name}的{course}成績: '))
  print(scores)

"""
從列表中找出最大的或最小的N個元素
堆結構(大根堆/小根堆)
"""
import heapq

list1 = [34, 25, 12, 99, 87, 63, 58, 78, 88, 92]
list2 = [
 {'name': 'IBM', 'shares': 100, 'price': 91.1},
 {'name': 'AAPL', 'shares': 50, 'price': 543.22},
 {'name': 'FB', 'shares': 200, 'price': 21.09},
 {'name': 'HPQ', 'shares': 35, 'price': 31.75},
 {'name': 'YHOO', 'shares': 45, 'price': 16.35},
 {'name': 'ACME', 'shares': 75, 'price': 115.65}
]
print(heapq.nlargest(3, list1))
print(heapq.nsmallest(3, list1))
print(heapq.nlargest(2, list2, key=lambda x: x['price']))
print(heapq.nlargest(2, list2, key=lambda x: x['shares']))
"""
迭代工具 - 排列 / 組合 / 笛卡爾積
"""
import itertools

itertools.permutations('ABCD')
itertools.combinations('ABCDE', 3)
itertools.product('ABCD', '123')

"""
找出序列中出現(xiàn)次數(shù)最多的元素
"""
from collections import Counter

words = [
 'look', 'into', 'my', 'eyes', 'look', 'into', 'my', 'eyes',
 'the', 'eyes', 'the', 'eyes', 'the', 'eyes', 'not', 'around',
 'the', 'eyes', "don't", 'look', 'around', 'the', 'eyes',
 'look', 'into', 'my', 'eyes', "you're", 'under'
]
counter = Counter(words)
print(counter.most_common(3))

# 公雞5元一只 母雞3元一只 小雞1元三只
# 用100元買100只雞 問公雞/母雞/小雞各多少只
for x in range(20):
 for y in range(33):
  z = 100 - x - y
  if 5 * x + 3 * y + z // 3 == 100 and z % 3 == 0:
   print(x, y, z)

# A、B、C、D、E五人在某天夜里合伙捕魚 最后疲憊不堪各自睡覺
# 第二天A第一個醒來 他將魚分為5份 扔掉多余的1條 拿走自己的一份
# B第二個醒來 也將魚分為5份 扔掉多余的1條 拿走自己的一份
# 然后C、D、E依次醒來也按同樣的方式分魚 問他們至少捕了多少條魚
fish = 1
while True:
 total = fish
 enough = True
 for _ in range(5):
  if (total - 1) % 5 == 0:
   total = (total - 1) // 5 * 4
  else:
   enough = False
   break
 if enough:
  print(fish)
  break
 fish += 1

"""
貪婪法：在對問題求解時，總是做出在當前看來是最好的選擇，不追求最優(yōu)解，快速找到滿意解。
輸入：
20 6
電腦 200 20
收音機 20 4
鐘 175 10
花瓶 50 2
書 10 1
油畫 90 9
"""
class Thing(object):
 """物品"""

 def __init__(self, name, price, weight):
  self.name = name
  self.price = price
  self.weight = weight

 @property
 def value(self):
  """價格重量比"""
  return self.price / self.weight


def input_thing():
 """輸入物品信息"""
 name_str, price_str, weight_str = input().split()
 return name_str, int(price_str), int(weight_str)


def main():
 """主函數(shù)"""
 max_weight, num_of_things = map(int, input().split())
 all_things = []
 for _ in range(num_of_things):
  all_things.append(Thing(*input_thing()))
 all_things.sort(key=lambda x: x.value, reverse=True)
 total_weight = 0
 total_price = 0
 for thing in all_things:
  if total_weight + thing.weight <= max_weight:
   print(f'小偷拿走了{thing.name}')
   total_weight += thing.weight
   total_price += thing.price
 print(f'總價值: {total_price}美元')


if __name__ == '__main__':
 main()

"""
快速排序 - 選擇樞軸對元素進行劃分，左邊都比樞軸小右邊都比樞軸大
"""
def quick_sort(origin_items, comp=lambda x, y: x <= y):
 items = origin_items[:]
 _quick_sort(items, 0, len(items) - 1, comp)
 return items


def _quick_sort(items, start, end, comp):
 if start < end:
  pos = _partition(items, start, end, comp)
  _quick_sort(items, start, pos - 1, comp)
  _quick_sort(items, pos + 1, end, comp)


def _partition(items, start, end, comp):
 pivot = items[end]
 i = start - 1
 for j in range(start, end):
  if comp(items[j], pivot):
   i += 1
   items[i], items[j] = items[j], items[i]
 items[i + 1], items[end] = items[end], items[i + 1]
 return i + 1

"""
遞歸回溯法：叫稱為試探法，按選優(yōu)條件向前搜索，當搜索到某一步，發(fā)現(xiàn)原先選擇并不優(yōu)或達不到目標時，就退回一步重新選擇，比較經(jīng)典的問題包括騎士巡邏、八皇后和迷宮尋路等。
"""
import sys
import time

SIZE = 5
total = 0


def print_board(board):
 for row in board:
  for col in row:
   print(str(col).center(4), end='')
  print()


def patrol(board, row, col, step=1):
 if row >= 0 and row < SIZE and \
  col >= 0 and col < SIZE and \
  board[row][col] == 0:
  board[row][col] = step
  if step == SIZE * SIZE:
   global total
   total += 1
   print(f'第{total}種走法: ')
   print_board(board)
  patrol(board, row - 2, col - 1, step + 1)
  patrol(board, row - 1, col - 2, step + 1)
  patrol(board, row + 1, col - 2, step + 1)
  patrol(board, row + 2, col - 1, step + 1)
  patrol(board, row + 2, col + 1, step + 1)
  patrol(board, row + 1, col + 2, step + 1)
  patrol(board, row - 1, col + 2, step + 1)
  patrol(board, row - 2, col + 1, step + 1)
  board[row][col] = 0


def main():
 board = [[0] * SIZE for _ in range(SIZE)]
 patrol(board, SIZE - 1, SIZE - 1)


if __name__ == '__main__':
 main()

"""
動態(tài)規(guī)劃 - 適用于有重疊子問題和最優(yōu)子結構性質(zhì)的問題
使用動態(tài)規(guī)劃方法所耗時間往往遠少于樸素解法(用空間換取時間)
"""
def fib(num, temp={}):
 """用遞歸計算Fibonacci數(shù)"""
 if num in (1, 2):
  return 1
 try:
  return temp[num]
 except KeyError:
  temp[num] = fib(num - 1) + fib(num - 2)
  return temp[num]

def main():
 items = list(map(int, input().split()))
 size = len(items)
 overall, partial = {}, {}
 overall[size - 1] = partial[size - 1] = items[size - 1]
 for i in range(size - 2, -1, -1):
  partial[i] = max(items[i], partial[i + 1] + items[i])
  overall[i] = max(partial[i], overall[i + 1])
 print(overall[0])


if __name__ == '__main__':
 main()

items1 = list(map(lambda x: x ** 2, filter(lambda x: x % 2, range(1, 10))))
items2 = [x ** 2 for x in range(1, 10) if x % 2]

def record_time(func):
 """自定義裝飾函數(shù)的裝飾器"""
 
 @wraps(func)
 def wrapper(*args, **kwargs):
  start = time()
  result = func(*args, **kwargs)
  print(f'{func.__name__}: {time() - start}秒')
  return result
  
 return wrapper

from functools import wraps
from time import time


def record(output):
 """自定義帶參數(shù)的裝飾器"""
	
	def decorate(func):
		
		@wraps(func)
		def wrapper(*args, **kwargs):
			start = time()
			result = func(*args, **kwargs)
			output(func.__name__, time() - start)
			return result
   
		return wrapper
	
	return decorate
from functools import wraps
from time import time


class Record():
 """自定義裝飾器類(通過__call__魔術方法使得對象可以當成函數(shù)調(diào)用)"""

 def __init__(self, output):
  self.output = output

 def __call__(self, func):

  @wraps(func)
  def wrapper(*args, **kwargs):
   start = time()
   result = func(*args, **kwargs)
   self.output(func.__name__, time() - start)
   return result

  return wrapper

from functools import wraps


def singleton(cls):
 """裝飾類的裝飾器"""
 instances = {}

 @wraps(cls)
 def wrapper(*args, **kwargs):
  if cls not in instances:
   instances[cls] = cls(*args, **kwargs)
  return instances[cls]

 return wrapper


@singleton
class President():
 """總統(tǒng)(單例類)"""
 pass

from functools import wraps
from threading import Lock


def singleton(cls):
 """線程安全的單例裝飾器"""
 instances = {}
 locker = Lock()

 @wraps(cls)
 def wrapper(*args, **kwargs):
  if cls not in instances:
   with locker:
    if cls not in instances:
     instances[cls] = cls(*args, **kwargs)
  return instances[cls]

 return wrapper

"""
月薪結算系統(tǒng) - 部門經(jīng)理每月15000 程序員每小時200 銷售員1800底薪加銷售額5%提成
"""
from abc import ABCMeta, abstractmethod


class Employee(metaclass=ABCMeta):
 """員工(抽象類)"""

 def __init__(self, name):
  self.name = name

 @abstractmethod
 def get_salary(self):
  """結算月薪(抽象方法)"""
  pass


class Manager(Employee):
 """部門經(jīng)理"""

 def get_salary(self):
  return 15000.0


class Programmer(Employee):
 """程序員"""

 def __init__(self, name, working_hour=0):
  self.working_hour = working_hour
  super().__init__(name)

 def get_salary(self):
  return 200.0 * self.working_hour


class Salesman(Employee):
 """銷售員"""

 def __init__(self, name, sales=0.0):
  self.sales = sales
  super().__init__(name)

 def get_salary(self):
  return 1800.0 + self.sales * 0.05


class EmployeeFactory():
 """創(chuàng)建員工的工廠（工廠模式 - 通過工廠實現(xiàn)對象使用者和對象之間的解耦合）"""

 @staticmethod
 def create(emp_type, *args, **kwargs):
  """創(chuàng)建員工"""
  emp_type = emp_type.upper()
  emp = None
  if emp_type == 'M':
   emp = Manager(*args, **kwargs)
  elif emp_type == 'P':
   emp = Programmer(*args, **kwargs)
  elif emp_type == 'S':
   emp = Salesman(*args, **kwargs)
  return emp


def main():
 """主函數(shù)"""
 emps = [
  EmployeeFactory.create('M', '曹操'), 
  EmployeeFactory.create('P', '荀彧', 120),
  EmployeeFactory.create('P', '郭嘉', 85), 
  EmployeeFactory.create('S', '典韋', 123000),
 ]
 for emp in emps:
  print('%s: %.2f元' % (emp.name, emp.get_salary()))


if __name__ == '__main__':
 main()

"""
經(jīng)驗：符號常量總是優(yōu)于字面常量，枚舉類型是定義符號常量的最佳選擇
"""
from enum import Enum, unique

import random


@unique
class Suite(Enum):
 """花色"""

 SPADE, HEART, CLUB, DIAMOND = range(4)

 def __lt__(self, other):
  return self.value < other.value


class Card():
 """牌"""

 def __init__(self, suite, face):
  """初始化方法"""
  self.suite = suite
  self.face = face

 def show(self):
  """顯示牌面"""
  suites = ['♠️', '♥️', '♣️', '♦️']
  faces = ['', 'A', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'J', 'Q', 'K']
  return f'{suites[self.suite.value]} {faces[self.face]}'

 def __str__(self):
  return self.show()

 def __repr__(self):
  return self.show()


class Poker():
 """撲克"""

 def __init__(self):
  self.index = 0
  self.cards = [Card(suite, face)
      for suite in Suite
      for face in range(1, 14)]

 def shuffle(self):
  """洗牌（隨機亂序）"""
  random.shuffle(self.cards)
  self.index = 0

 def deal(self):
  """發(fā)牌"""
  card = self.cards[self.index]
  self.index += 1
  return card

 @property
 def has_more(self):
  return self.index < len(self.cards)


class Player():
 """玩家"""

 def __init__(self, name):
  self.name = name
  self.cards = []

 def get_one(self, card):
  """摸一張牌"""
  self.cards.append(card)

 def sort(self, comp=lambda card: (card.suite, card.face)):
  """整理手上的牌"""
  self.cards.sort(key=comp)


def main():
 """主函數(shù)"""
 poker = Poker()
 poker.shuffle()
 players = [Player('東邪'), Player('西毒'), Player('南帝'), Player('北丐')]
 while poker.has_more:
  for player in players:
    player.get_one(poker.deal())
 for player in players:
  player.sort()
  print(player.name, end=': ')
  print(player.cards)


if __name__ == '__main__':
 main()

typedef struct_object {
 /* 引用計數(shù) */
 int ob_refcnt;
 /* 對象指針 */
 struct_typeobject *ob_type;
} PyObject;
/* 增加引用計數(shù)的宏定義 */
#define Py_INCREF(op) ((op)->ob_refcnt++)
/* 減少引用計數(shù)的宏定義 */
#define Py_DECREF(op) \ //減少計數(shù)
 if (--(op)->ob_refcnt != 0) \
  ; \
 else \
  __Py_Dealloc((PyObject *)(op))

# 循環(huán)引用會導致內(nèi)存泄露 - Python除了引用技術還引入了標記清理和分代回收
# 在Python 3.6以前如果重寫__del__魔術方法會導致循環(huán)引用處理失效
# 如果不想造成循環(huán)引用可以使用弱引用
list1 = []
list2 = [] 
list1.append(list2)
list2.append(list1)

class SetOnceMappingMixin():
 """自定義混入類"""
 __slots__ = ()

 def __setitem__(self, key, value):
  if key in self:
   raise KeyError(str(key) + ' already set')
  return super().__setitem__(key, value)


class SetOnceDict(SetOnceMappingMixin, dict):
 """自定義字典"""
 pass


my_dict= SetOnceDict()
try:
 my_dict['username'] = 'jackfrued'
 my_dict['username'] = 'hellokitty'
except KeyError:
 pass
print(my_dict)

import threading


class SingletonMeta(type):
 """自定義元類"""

 def __init__(cls, *args, **kwargs):
  cls.__instance = None
  cls.__lock = threading.Lock()
  super().__init__(*args, **kwargs)

 def __call__(cls, *args, **kwargs):
  if cls.__instance is None:
   with cls.__lock:
    if cls.__instance is None:
     cls.__instance = super().__call__(*args, **kwargs)
  return cls.__instance


class President(metaclass=SingletonMeta):
 """總統(tǒng)(單例類)"""
 pass

class StreamHasher():
 """哈希摘要生成器(策略模式)"""

 def __init__(self, alg='md5', size=4096):
  self.size = size
  alg = alg.lower()
  self.hasher = getattr(__import__('hashlib'), alg.lower())()

 def __call__(self, stream):
  return self.to_digest(stream)

 def to_digest(self, stream):
  """生成十六進制形式的摘要"""
  for buf in iter(lambda: stream.read(self.size), b''):
   self.hasher.update(buf)
  return self.hasher.hexdigest()

def main():
 """主函數(shù)"""
 hasher1 = StreamHasher()
 with open('Python-3.7.1.tgz', 'rb') as stream:
  print(hasher1.to_digest(stream))
 hasher2 = StreamHasher('sha1')
 with open('Python-3.7.1.tgz', 'rb') as stream:
  print(hasher2(stream))


if __name__ == '__main__':
 main()

def fib(num):
 """生成器"""
 a, b = 0, 1
 for _ in range(num):
  a, b = b, a + b
  yield a
 
 
class Fib(object):
 """迭代器"""
 
 def __init__(self, num):
  self.num = num
  self.a, self.b = 0, 1
  self.idx = 0
 
 def __iter__(self):
  return self

 def __next__(self):
  if self.idx < self.num:
   self.a, self.b = self.b, self.a + self.b
   self.idx += 1
   return self.a
  raise StopIteration()

"""
面試題：進程和線程的區(qū)別和聯(lián)系？
進程 - 操作系統(tǒng)分配內(nèi)存的基本單位 - 一個進程可以包含一個或多個線程
線程 - 操作系統(tǒng)分配CPU的基本單位
并發(fā)編程（concurrent programming）
1. 提升執(zhí)行性能 - 讓程序中沒有因果關系的部分可以并發(fā)的執(zhí)行
2. 改善用戶體驗 - 讓耗時間的操作不會造成程序的假死
"""
import glob
import os
import threading

from PIL import Image

PREFIX = 'thumbnails'


def generate_thumbnail(infile, size, format='PNG'):
 """生成指定圖片文件的縮略圖"""
	file, ext = os.path.splitext(infile)
	file = file[file.rfind('/') + 1:]
	outfile = f'{PREFIX}/{file}_{size[0]}_{size[1]}.{ext}'
	img = Image.open(infile)
	img.thumbnail(size, Image.ANTIALIAS)
	img.save(outfile, format)


def main():
 """主函數(shù)"""
	if not os.path.exists(PREFIX):
		os.mkdir(PREFIX)
	for infile in glob.glob('images/*.png'):
		for size in (32, 64, 128):
   # 創(chuàng)建并啟動線程
			threading.Thread(
				target=generate_thumbnail, 
				args=(infile, (size, size))
			).start()
			

if __name__ == '__main__':
	main()

"""
多線程程序如果沒有競爭資源處理起來通常也比較簡單
當多個線程競爭臨界資源的時候如果缺乏必要的保護措施就會導致數(shù)據(jù)錯亂
說明：臨界資源就是被多個線程競爭的資源
"""
import time
import threading

from concurrent.futures import ThreadPoolExecutor


class Account(object):
 """銀行賬戶"""

 def __init__(self):
  self.balance = 0.0
  self.lock = threading.Lock()

 def deposit(self, money):
  # 通過鎖保護臨界資源
  with self.lock:
   new_balance = self.balance + money
   time.sleep(0.001)
   self.balance = new_balance


class AddMoneyThread(threading.Thread):
 """自定義線程類"""

 def __init__(self, account, money):
  self.account = account
  self.money = money
  # 自定義線程的初始化方法中必須調(diào)用父類的初始化方法
  super().__init__()

 def run(self):
  # 線程啟動之后要執(zhí)行的操作
  self.account.deposit(self.money)

def main():
 """主函數(shù)"""
 account = Account()
 # 創(chuàng)建線程池
 pool = ThreadPoolExecutor(max_workers=10)
 futures = []
 for _ in range(100):
  # 創(chuàng)建線程的第1種方式
  # threading.Thread(
  #  target=account.deposit, args=(1, )
  # ).start()
  # 創(chuàng)建線程的第2種方式
  # AddMoneyThread(account, 1).start()
  # 創(chuàng)建線程的第3種方式
  # 調(diào)用線程池中的線程來執(zhí)行特定的任務
  future = pool.submit(account.deposit, 1)
  futures.append(future)
 # 關閉線程池
 pool.shutdown()
 for future in futures:
  future.result()
 print(account.balance)


if __name__ == '__main__':
 main()

"""
多個線程競爭一個資源 - 保護臨界資源 - 鎖（Lock/RLock）
多個線程競爭多個資源（線程數(shù)>資源數(shù)） - 信號量（Semaphore）
多個線程的調(diào)度 - 暫停線程執(zhí)行/喚醒等待中的線程 - Condition
"""
from concurrent.futures import ThreadPoolExecutor
from random import randint
from time import sleep

import threading


class Account():
 """銀行賬戶"""

 def __init__(self, balance=0):
  self.balance = balance
  lock = threading.Lock()
  self.condition = threading.Condition(lock)

 def withdraw(self, money):
  """取錢"""
  with self.condition:
   while money > self.balance:
    self.condition.wait()
   new_balance = self.balance - money
   sleep(0.001)
   self.balance = new_balance

 def deposit(self, money):
  """存錢"""
  with self.condition:
   new_balance = self.balance + money
   sleep(0.001)
   self.balance = new_balance
   self.condition.notify_all()


def add_money(account):
 while True:
  money = randint(5, 10)
  account.deposit(money)
  print(threading.current_thread().name, 
    ':', money, '====>', account.balance)
  sleep(0.5)


def sub_money(account):
 while True:
  money = randint(10, 30)
  account.withdraw(money)
  print(threading.current_thread().name, 
    ':', money, '<====', account.balance)
  sleep(1)


def main():
 account = Account()
 with ThreadPoolExecutor(max_workers=10) as pool:
  for _ in range(5):
   pool.submit(add_money, account)
   pool.submit(sub_money, account)


if __name__ == '__main__':
 main()

"""
多進程和進程池的使用
多線程因為GIL的存在不能夠發(fā)揮CPU的多核特性
對于計算密集型任務應該考慮使用多進程
time python3 example22.py
real 0m11.512s
user 0m39.319s
sys  0m0.169s
使用多進程后實際執(zhí)行時間為11.512秒，而用戶時間39.319秒約為實際執(zhí)行時間的4倍
這就證明我們的程序通過多進程使用了CPU的多核特性，而且這臺計算機配置了4核的CPU
"""
import concurrent.futures
import math

PRIMES = [
 1116281,
 1297337,
 104395303,
 472882027,
 533000389,
 817504243,
 982451653,
 112272535095293,
 112582705942171,
 112272535095293,
 115280095190773,
 115797848077099,
 1099726899285419
] * 5


def is_prime(n):
 """判斷素數(shù)"""
 if n % 2 == 0:
  return False

 sqrt_n = int(math.floor(math.sqrt(n)))
 for i in range(3, sqrt_n + 1, 2):
  if n % i == 0:
   return False
 return True


def main():
 """主函數(shù)"""
 with concurrent.futures.ProcessPoolExecutor() as executor:
  for number, prime in zip(PRIMES, executor.map(is_prime, PRIMES)):
   print('%d is prime: %s' % (number, prime))


if __name__ == '__main__':
 main()

"""
異步I/O - async / await
"""
import asyncio


def num_generator(m, n):
 """指定范圍的數(shù)字生成器"""
 yield from range(m, n + 1)


async def prime_filter(m, n):
 """素數(shù)過濾器"""
 primes = []
 for i in num_generator(m, n):
  flag = True
  for j in range(2, int(i ** 0.5 + 1)):
   if i % j == 0:
    flag = False
    break
  if flag:
   print('Prime =>', i)
   primes.append(i)

  await asyncio.sleep(0.001)
 return tuple(primes)


async def square_mapper(m, n):
 """平方映射器"""
 squares = []
 for i in num_generator(m, n):
  print('Square =>', i * i)
  squares.append(i * i)

  await asyncio.sleep(0.001)
 return squares


def main():
 """主函數(shù)"""
 loop = asyncio.get_event_loop()
 future = asyncio.gather(prime_filter(2, 100), square_mapper(1, 100))
 future.add_done_callback(lambda x: print(x.result()))
 loop.run_until_complete(future)
 loop.close()


if __name__ == '__main__':
 main()

import asyncio
import re

import aiohttp

PATTERN = re.compile(r'\<title\>(?P<title>.*)\<\/title\>')


async def fetch_page(session, url):
 async with session.get(url, ssl=False) as resp:
  return await resp.text()


async def show_title(url):
 async with aiohttp.ClientSession() as session:
  html = await fetch_page(session, url)
  print(PATTERN.search(html).group('title'))


def main():
 urls = ('https://www.python.org/',
   'https://git-scm.com/',
   'https://www.jd.com/',
   'https://www.taobao.com/',
   'https://www.douban.com/')
 loop = asyncio.get_event_loop()
 tasks = [show_title(url) for url in urls]
 loop.run_until_complete(asyncio.wait(tasks))
 loop.close()


if __name__ == '__main__':
 main()