# 创建一个用于推导式的列表
numbers = [1, 2, 3, -3, -2, -1]
# 创建一个包含这些数字的方格的新列表
mylist = [x*x for x in numbers][1, 4, 9, 9, 4, 1]
# 为这些数字的幂创建一个新字典
mydict = {x: pow(10, x) for x in numbers} 
# 输出 {1: 10, 2: 100, 3: 1000, -3: 0.001, -2: 0.01, -1: 0.1}
# 创建一组这些数字的绝对值
myset = {abs(x) for x in numbers} 
# 输出 {1, 2, 3}
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列表推导： [expr for x in iterable]
字典推导： {key_expr: value_expr for x in iterable}
集合推导： {expr for x in iterable}
可选条件：
[expr for x in iterable if condition] 
{key_expr: value_expr for x in iterable if condition} 
{expr for x in iterable if condition}
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try:
    a = int(input("Enter numerator:")
    b = int(input("Enter denominator:")
    c = a / b
    print(c)
except ZeroDivisionError as e:
    print(e, " please provide a non zero denominator")
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import sys
try:
   f = open('myfile.txt') 
   s = f.readline()
   i = int(s.strip())
except OSError as err:
   print("OS error: {0}".format(err))
except ValueError:
   print("Could not convert data to an integer.")
except:
   print("Unexpected error:", sys.exc_info()[0])
   raise
finally:
   print("Operation Successfully Done!!")(Example Taken From Official Python Docs)
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from collections import Counter
data = [1,1,1,1,2,3,4,3,3,5,6,7,7]
count = Counter(data)
print(count)

## Counter({1: 4, 3: 3, 7: 2, 2: 1, 4: 1, 5: 1, 6: 1})
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from collections import namedtuple
Direction = namedtuple('Direction','N,S,E,W')
dt = Direction(4,74,0,0)
print(dt)

# Direction(N=4, S=74, E=0, W=0)
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from collections import OrderedDict
dictt = OrderedDict()
dictt['a'] = 5
dictt['d'] = 2
dictt['c'] = 1
dictt['b'] = 3
print(dictt)

# OrderedDict([('a', 5), ('d', 2), ('c', 1), ('b', 3)])
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from collections import defaultdict 
dictt = defaultdict(int) 
dictt['a'] = 2 
print(dictt['a']) ##返回值
print(dictt['b']) ##返回默认值

# 2 
# 0
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from collections import deque
d = deque('abc')  
d.append('d') 
print(d)
# deque(['a', 'b', 'c', 'd'])

# appendleft 添加元素到左端
d.appendleft('e')
print(d)
# deque(['e','a', 'b', 'c', 'd'])

# clear 清除所有元素
d.clear()
print(d)
# deque([])
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def logging_func(original_func):
    def wrapper(*args, **kwargs):
        print(f"Called {original_func.__name__} with", args, kwargs)
        return original_func(*args, **kwargs)
    return wrapper
@logging_func
def add(a, b):
    return a + b
result = add(5, 6)
print(result)
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def fibon(limit):
  a,b = 0,1
  while a < limit:
      yield a
      a, b = b, a + bfor x in fibon(10):
   print (x)
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num =  5
num*6
>> 30
num.__mul__(6)
>>30
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5+6
>>11
"python"+"programming"
>> 'pythonprogramming'
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# Get an string object’s hash value
hash("This is me")
5361907397716593195
 
# Get a tuple object’s hash value
hash((1,2))
-3550055125485641917
 
# Get a list object’s hash value
hash([1, 2, 3])
Traceback (most recent call last):
 File “<stdin>”, line 1, in <module>
TypeError: unhashable type: ‘list’
 
# Get a dict object’s hash value
hash({“a”: 1, “b”: 2})
Traceback (most recent call last):
 File “<stdin>”, line 1, in <module>
TypeError: unhashable type: ‘dict’
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import random
import timeit
# Create a function to check the look up time
def dict_look_up_time(n):
    numbers = list(range(n))
    random.shuffle(numbers)
    d0 = {x: str(x) for x in numbers}
    random_int = random.randint(0, n — 1)
    t0 = timeit.timeit(lambda: d0[random_int], number=10000)
    return t0
for n in (10, 100, 1000, 10000, 100000):
    elapse_time = dict_look_up_time(n)
    print(f”*** N = {n:<8}: {elapse_time:.5f}”)
*** N = 10 : 0.00114
*** N = 100 : 0.00256
*** N = 1000 : 0.00291
*** N = 10000 : 0.00207
*** N = 100000 : 0.00286
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