目录：

1.集合set

2.计数器

3.有序字典

4.默认字典

5.可命名元组

6.队列

7.深浅拷贝

8.函数

9.lambda表达式

10.内置函数

一、集合set

set是一个无序且不重复的元素集合

  1 class set(object):
  2     """
  3     set() -> new empty set object
  4     set(iterable) -> new set object
  5     
  6     Build an unordered collection of unique elements.
  7     """
  8     def add(self, *args, **kwargs): # real signature unknown
  9         """ 添加 """
 10         """
 11         Add an element to a set.
 12         
 13         This has no effect if the element is already present.
 14         """
 15         pass
 16 
 17     def clear(self, *args, **kwargs): # real signature unknown
 18         """ Remove all elements from this set. """
 19         pass
 20 
 21     def copy(self, *args, **kwargs): # real signature unknown
 22         """ Return a shallow copy of a set. """
 23         pass
 24 
 25     def difference(self, *args, **kwargs): # real signature unknown
 26         """
 27         Return the difference of two or more sets as a new set.
 28         
 29         (i.e. all elements that are in this set but not the others.)
 30         """
 31         pass
 32 
 33     def difference_update(self, *args, **kwargs): # real signature unknown
 34         """ 删除当前set中的所有包含在 new set 里的元素 """
 35         """ Remove all elements of another set from this set. """
 36         pass
 37 
 38     def discard(self, *args, **kwargs): # real signature unknown
 39         """ 移除元素 """
 40         """
 41         Remove an element from a set if it is a member.
 42         
 43         If the element is not a member, do nothing.
 44         """
 45         pass
 46 
 47     def intersection(self, *args, **kwargs): # real signature unknown
 48         """ 取交集，新创建一个set """
 49         """
 50         Return the intersection of two or more sets as a new set.
 51         
 52         (i.e. elements that are common to all of the sets.)
 53         """
 54         pass
 55 
 56     def intersection_update(self, *args, **kwargs): # real signature unknown
 57         """ 取交集，修改原来set """
 58         """ Update a set with the intersection of itself and another. """
 59         pass
 60 
 61     def isdisjoint(self, *args, **kwargs): # real signature unknown
 62         """ 如果没有交集，返回true  """
 63         """ Return True if two sets have a null intersection. """
 64         pass
 65 
 66     def issubset(self, *args, **kwargs): # real signature unknown
 67         """ 是否是子集 """
 68         """ Report whether another set contains this set. """
 69         pass
 70 
 71     def issuperset(self, *args, **kwargs): # real signature unknown
 72         """ 是否是父集 """
 73         """ Report whether this set contains another set. """
 74         pass
 75 
 76     def pop(self, *args, **kwargs): # real signature unknown
 77         """ 移除 """
 78         """
 79         Remove and return an arbitrary set element.
 80         Raises KeyError if the set is empty.
 81         """
 82         pass
 83 
 84     def remove(self, *args, **kwargs): # real signature unknown
 85         """ 移除 """
 86         """
 87         Remove an element from a set; it must be a member.
 88         
 89         If the element is not a member, raise a KeyError.
 90         """
 91         pass
 92 
 93     def symmetric_difference(self, *args, **kwargs): # real signature unknown
 94         """ 差集，创建新对象"""
 95         """
 96         Return the symmetric difference of two sets as a new set.
 97         
 98         (i.e. all elements that are in exactly one of the sets.)
 99         """
100         pass
101 
102     def symmetric_difference_update(self, *args, **kwargs): # real signature unknown
103         """ 差集，改变原来 """
104         """ Update a set with the symmetric difference of itself and another. """
105         pass
106 
107     def union(self, *args, **kwargs): # real signature unknown
108         """ 并集 """
109         """
110         Return the union of sets as a new set.
111         
112         (i.e. all elements that are in either set.)
113         """
114         pass
115 
116     def update(self, *args, **kwargs): # real signature unknown
117         """ 更新 """
118         """ Update a set with the union of itself and others. """
119         pass
120 
121     def __and__(self, y): # real signature unknown; restored from __doc__
122         """ x.__and__(y) <==> x&y """
123         pass
124 
125     def __cmp__(self, y): # real signature unknown; restored from __doc__
126         """ x.__cmp__(y) <==> cmp(x,y) """
127         pass
128 
129     def __contains__(self, y): # real signature unknown; restored from __doc__
130         """ x.__contains__(y) <==> y in x. """
131         pass
132 
133     def __eq__(self, y): # real signature unknown; restored from __doc__
134         """ x.__eq__(y) <==> x==y """
135         pass
136 
137     def __getattribute__(self, name): # real signature unknown; restored from __doc__
138         """ x.__getattribute__('name') <==> x.name """
139         pass
140 
141     def __ge__(self, y): # real signature unknown; restored from __doc__
142         """ x.__ge__(y) <==> x>=y """
143         pass
144 
145     def __gt__(self, y): # real signature unknown; restored from __doc__
146         """ x.__gt__(y) <==> x>y """
147         pass
148 
149     def __iand__(self, y): # real signature unknown; restored from __doc__
150         """ x.__iand__(y) <==> x&=y """
151         pass
152 
153     def __init__(self, seq=()): # known special case of set.__init__
154         """
155         set() -> new empty set object
156         set(iterable) -> new set object
157         
158         Build an unordered collection of unique elements.
159         # (copied from class doc)
160         """
161         pass
162 
163     def __ior__(self, y): # real signature unknown; restored from __doc__
164         """ x.__ior__(y) <==> x|=y """
165         pass
166 
167     def __isub__(self, y): # real signature unknown; restored from __doc__
168         """ x.__isub__(y) <==> x-=y """
169         pass
170 
171     def __iter__(self): # real signature unknown; restored from __doc__
172         """ x.__iter__() <==> iter(x) """
173         pass
174 
175     def __ixor__(self, y): # real signature unknown; restored from __doc__
176         """ x.__ixor__(y) <==> x^=y """
177         pass
178 
179     def __len__(self): # real signature unknown; restored from __doc__
180         """ x.__len__() <==> len(x) """
181         pass
182 
183     def __le__(self, y): # real signature unknown; restored from __doc__
184         """ x.__le__(y) <==> x<=y """
185         pass
186 
187     def __lt__(self, y): # real signature unknown; restored from __doc__
188         """ x.__lt__(y) <==> x<y """
189         pass
190 
191     @staticmethod # known case of __new__
192     def __new__(S, *more): # real signature unknown; restored from __doc__
193         """ T.__new__(S, ...) -> a new object with type S, a subtype of T """
194         pass
195 
196     def __ne__(self, y): # real signature unknown; restored from __doc__
197         """ x.__ne__(y) <==> x!=y """
198         pass
199 
200     def __or__(self, y): # real signature unknown; restored from __doc__
201         """ x.__or__(y) <==> x|y """
202         pass
203 
204     def __rand__(self, y): # real signature unknown; restored from __doc__
205         """ x.__rand__(y) <==> y&x """
206         pass
207 
208     def __reduce__(self, *args, **kwargs): # real signature unknown
209         """ Return state information for pickling. """
210         pass
211 
212     def __repr__(self): # real signature unknown; restored from __doc__
213         """ x.__repr__() <==> repr(x) """
214         pass
215 
216     def __ror__(self, y): # real signature unknown; restored from __doc__
217         """ x.__ror__(y) <==> y|x """
218         pass
219 
220     def __rsub__(self, y): # real signature unknown; restored from __doc__
221         """ x.__rsub__(y) <==> y-x """
222         pass
223 
224     def __rxor__(self, y): # real signature unknown; restored from __doc__
225         """ x.__rxor__(y) <==> y^x """
226         pass
227 
228     def __sizeof__(self): # real signature unknown; restored from __doc__
229         """ S.__sizeof__() -> size of S in memory, in bytes """
230         pass
231 
232     def __sub__(self, y): # real signature unknown; restored from __doc__
233         """ x.__sub__(y) <==> x-y """
234         pass
235 
236     def __xor__(self, y): # real signature unknown; restored from __doc__
237         """ x.__xor__(y) <==> x^y """
238         pass
239 
240     __hash__ = None
241 
242 set
set源码

二、计数器（counter）

Counter是对字典类型的补充，用于追踪值出现的次数

ps：具备字典的所有功能+自己的功能

c = Counter('abcdeabcdabcaba')
print c
输出：Counter({'a': 5, 'b': 4, 'c': 3, 'd': 2, 'e': 1})
  1 ########################################################################
  2 ###  Counter
  3 ########################################################################
  4 
  5 class Counter(dict):
  6     '''Dict subclass for counting hashable items.  Sometimes called a bag
  7     or multiset.  Elements are stored as dictionary keys and their counts
  8     are stored as dictionary values.
  9 
 10     >>> c = Counter('abcdeabcdabcaba')  # count elements from a string
 11 
 12     >>> c.most_common(3)                # three most common elements
 13     [('a', 5), ('b', 4), ('c', 3)]
 14     >>> sorted(c)                       # list all unique elements
 15     ['a', 'b', 'c', 'd', 'e']
 16     >>> ''.join(sorted(c.elements()))   # list elements with repetitions
 17     'aaaaabbbbcccdde'
 18     >>> sum(c.values())                 # total of all counts
 19 
 20     >>> c['a']                          # count of letter 'a'
 21     >>> for elem in 'shazam':           # update counts from an iterable
 22     ...     c[elem] += 1                # by adding 1 to each element's count
 23     >>> c['a']                          # now there are seven 'a'
 24     >>> del c['b']                      # remove all 'b'
 25     >>> c['b']                          # now there are zero 'b'
 26 
 27     >>> d = Counter('simsalabim')       # make another counter
 28     >>> c.update(d)                     # add in the second counter
 29     >>> c['a']                          # now there are nine 'a'
 30 
 31     >>> c.clear()                       # empty the counter
 32     >>> c
 33     Counter()
 34 
 35     Note:  If a count is set to zero or reduced to zero, it will remain
 36     in the counter until the entry is deleted or the counter is cleared:
 37 
 38     >>> c = Counter('aaabbc')
 39     >>> c['b'] -= 2                     # reduce the count of 'b' by two
 40     >>> c.most_common()                 # 'b' is still in, but its count is zero
 41     [('a', 3), ('c', 1), ('b', 0)]
 42 
 43     '''
 44     # References:
 45     #   http://en.wikipedia.org/wiki/Multiset
 46     #   http://www.gnu.org/software/smalltalk/manual-base/html_node/Bag.html
 47     #   http://www.demo2s.com/Tutorial/Cpp/0380__set-multiset/Catalog0380__set-multiset.htm
 48     #   http://code.activestate.com/recipes/259174/
 49     #   Knuth, TAOCP Vol. II section 4.6.3
 50 
 51     def __init__(self, iterable=None, **kwds):
 52         '''Create a new, empty Counter object.  And if given, count elements
 53         from an input iterable.  Or, initialize the count from another mapping
 54         of elements to their counts.
 55 
 56         >>> c = Counter()                           # a new, empty counter
 57         >>> c = Counter('gallahad')                 # a new counter from an iterable
 58         >>> c = Counter({'a': 4, 'b': 2})           # a new counter from a mapping
 59         >>> c = Counter(a=4, b=2)                   # a new counter from keyword args
 60 
 61         '''
 62         super(Counter, self).__init__()
 63         self.update(iterable, **kwds)
 64 
 65     def __missing__(self, key):
 66         """ 对于不存在的元素，返回计数器为0 """
 67         'The count of elements not in the Counter is zero.'
 68         # Needed so that self[missing_item] does not raise KeyError
 69         return 0
 70 
 71     def most_common(self, n=None):
 72         """ 数量大于等n的所有元素和计数器 """
 73         '''List the n most common elements and their counts from the most
 74         common to the least.  If n is None, then list all element counts.
 75 
 76         >>> Counter('abcdeabcdabcaba').most_common(3)
 77         [('a', 5), ('b', 4), ('c', 3)]
 78 
 79         '''
 80         # Emulate Bag.sortedByCount from Smalltalk
 81         if n is None:
 82             return sorted(self.iteritems(), key=_itemgetter(1), reverse=True)
 83         return _heapq.nlargest(n, self.iteritems(), key=_itemgetter(1))
 84 
 85     def elements(self):
 86         """ 计数器中的所有元素，注：此处非所有元素集合，而是包含所有元素集合的迭代器 """
 87         '''Iterator over elements repeating each as many times as its count.
 88 
 89         >>> c = Counter('ABCABC')
 90         >>> sorted(c.elements())
 91         ['A', 'A', 'B', 'B', 'C', 'C']
 92 
 93         # Knuth's example for prime factors of 1836:  2**2 * 3**3 * 17**1
 94         >>> prime_factors = Counter({2: 2, 3: 3, 17: 1})
 95         >>> product = 1
 96         >>> for factor in prime_factors.elements():     # loop over factors
 97         ...     product *= factor                       # and multiply them
 98         >>> product
 99 
100         Note, if an element's count has been set to zero or is a negative
101         number, elements() will ignore it.
102 
103         '''
104         # Emulate Bag.do from Smalltalk and Multiset.begin from C++.
105         return _chain.from_iterable(_starmap(_repeat, self.iteritems()))
106 
107     # Override dict methods where necessary
108 
109     @classmethod
110     def fromkeys(cls, iterable, v=None):
111         # There is no equivalent method for counters because setting v=1
112         # means that no element can have a count greater than one.
113         raise NotImplementedError(
114             'Counter.fromkeys() is undefined.  Use Counter(iterable) instead.')
115 
116     def update(self, iterable=None, **kwds):
117         """ 更新计数器，其实就是增加；如果原来没有，则新建，如果有则加一 """
118         '''Like dict.update() but add counts instead of replacing them.
119 
120         Source can be an iterable, a dictionary, or another Counter instance.
121 
122         >>> c = Counter('which')
123         >>> c.update('witch')           # add elements from another iterable
124         >>> d = Counter('watch')
125         >>> c.update(d)                 # add elements from another counter
126         >>> c['h']                      # four 'h' in which, witch, and watch
127 
128         '''
129         # The regular dict.update() operation makes no sense here because the
130         # replace behavior results in the some of original untouched counts
131         # being mixed-in with all of the other counts for a mismash that
132         # doesn't have a straight-forward interpretation in most counting
133         # contexts.  Instead, we implement straight-addition.  Both the inputs
134         # and outputs are allowed to contain zero and negative counts.
135 
136         if iterable is not None:
137             if isinstance(iterable, Mapping):
138                 if self:
139                     self_get = self.get
140                     for elem, count in iterable.iteritems():
141                         self[elem] = self_get(elem, 0) + count
142                 else:
143                     super(Counter, self).update(iterable) # fast path when counter is empty
144             else:
145                 self_get = self.get
146                 for elem in iterable:
147                     self[elem] = self_get(elem, 0) + 1
148         if kwds:
149             self.update(kwds)
150 
151     def subtract(self, iterable=None, **kwds):
152         """ 相减，原来的计数器中的每一个元素的数量减去后添加的元素的数量 """
153         '''Like dict.update() but subtracts counts instead of replacing them.
154         Counts can be reduced below zero.  Both the inputs and outputs are
155         allowed to contain zero and negative counts.
156 
157         Source can be an iterable, a dictionary, or another Counter instance.
158 
159         >>> c = Counter('which')
160         >>> c.subtract('witch')             # subtract elements from another iterable
161         >>> c.subtract(Counter('watch'))    # subtract elements from another counter
162         >>> c['h']                          # 2 in which, minus 1 in witch, minus 1 in watch
163         >>> c['w']                          # 1 in which, minus 1 in witch, minus 1 in watch
164         -1
165 
166         '''
167         if iterable is not None:
168             self_get = self.get
169             if isinstance(iterable, Mapping):
170                 for elem, count in iterable.items():
171                     self[elem] = self_get(elem, 0) - count
172             else:
173                 for elem in iterable:
174                     self[elem] = self_get(elem, 0) - 1
175         if kwds:
176             self.subtract(kwds)
177 
178     def copy(self):
179         """ 拷贝 """
180         'Return a shallow copy.'
181         return self.__class__(self)
182 
183     def __reduce__(self):
184         """ 返回一个元组（类型，元组） """
185         return self.__class__, (dict(self),)
186 
187     def __delitem__(self, elem):
188         """ 删除元素 """
189         'Like dict.__delitem__() but does not raise KeyError for missing values.'
190         if elem in self:
191             super(Counter, self).__delitem__(elem)
192 
193     def __repr__(self):
194         if not self:
195             return '%s()' % self.__class__.__name__
196         items = ', '.join(map('%r: %r'.__mod__, self.most_common()))
197         return '%s({%s})' % (self.__class__.__name__, items)
198 
199     # Multiset-style mathematical operations discussed in:
200     #       Knuth TAOCP Volume II section 4.6.3 exercise 19
201     #       and at http://en.wikipedia.org/wiki/Multiset
202     #
203     # Outputs guaranteed to only include positive counts.
204     #
205     # To strip negative and zero counts, add-in an empty counter:
206     #       c += Counter()
207 
208     def __add__(self, other):
209         '''Add counts from two counters.
210 
211         >>> Counter('abbb') + Counter('bcc')
212         Counter({'b': 4, 'c': 2, 'a': 1})
213 
214         '''
215         if not isinstance(other, Counter):
216             return NotImplemented
217         result = Counter()
218         for elem, count in self.items():
219             newcount = count + other[elem]
220             if newcount > 0:
221                 result[elem] = newcount
222         for elem, count in other.items():
223             if elem not in self and count > 0:
224                 result[elem] = count
225         return result
226 
227     def __sub__(self, other):
228         ''' Subtract count, but keep only results with positive counts.
229 
230         >>> Counter('abbbc') - Counter('bccd')
231         Counter({'b': 2, 'a': 1})
232 
233         '''
234         if not isinstance(other, Counter):
235             return NotImplemented
236         result = Counter()
237         for elem, count in self.items():
238             newcount = count - other[elem]
239             if newcount > 0:
240                 result[elem] = newcount
241         for elem, count in other.items():
242             if elem not in self and count < 0:
243                 result[elem] = 0 - count
244         return result
245 
246     def __or__(self, other):
247         '''Union is the maximum of value in either of the input counters.
248 
249         >>> Counter('abbb') | Counter('bcc')
250         Counter({'b': 3, 'c': 2, 'a': 1})
251 
252         '''
253         if not isinstance(other, Counter):
254             return NotImplemented
255         result = Counter()
256         for elem, count in self.items():
257             other_count = other[elem]
258             newcount = other_count if count < other_count else count
259             if newcount > 0:
260                 result[elem] = newcount
261         for elem, count in other.items():
262             if elem not in self and count > 0:
263                 result[elem] = count
264         return result
265 
266     def __and__(self, other):
267         ''' Intersection is the minimum of corresponding counts.
268 
269         >>> Counter('abbb') & Counter('bcc')
270         Counter({'b': 1})
271 
272         '''
273         if not isinstance(other, Counter):
274             return NotImplemented
275         result = Counter()
276         for elem, count in self.items():
277             other_count = other[elem]
278             newcount = count if count < other_count else other_count
279             if newcount > 0:
280                 result[elem] = newcount
281         return result
282 
283 Counter
284 
285 Counter
counter源码

三、有序字典

orderdDict是对字典类型的补充，他记住了字典元素添加的顺序

例：

dic = collections.OrderedDict()
dic['k1']='v1'
dic['k2']='v2'
dic['k3']='v3'
print(dic)

操作方法与字典操作方法相同

四、默认字典

dic=collections.defaultdict(list)
dic['k1'].append('cat')
print(dic)

操作方法与字典操作方法相同

五、可命名元组(namedtuple)

根据nametuple可以创建一个包含tuple所有功能以及其他功能的类型。

import collections
 
Mytuple = collections.namedtuple('Mytuple',['x', 'y', 'z'])

六、队列

双向队列(deque)：

d = collections.deque()
d.append('1')    #添加数据到队列
d.appendleft('10')    #添加数据到队列左边
d.appendleft('1')
print(d)
r = d.count('1')    #查看1在队列里的个数
print(r)
d.extend(['yy','uu','ii'])    #添加多个元素到列表
d.extendleft(['y1y','u1u','i1i'])    #添加多个元素到列表左边
print(d)
d.rotate(5)    #将右边的值按顺序放到左边，括号里的值为要取值的个数
print(d)

单向队列(queue):

import queue

q = queue.Queue()
q.put('123')
q.put('678')    #将数据添加到队列
print(q.qsize())    #获取队列中数据的个数
print(q.get())    #拿取队列中的数据（先进先出原则）

七、深浅拷贝

对于 数字 和 字符串 而言，赋值、浅拷贝和深拷贝无意义，因为其永远指向同一个内存地址。

import copy
# ######### 数字、字符串 #########
n1 = 123
# n1 = "i am alex age 10"
print(id(n1))
# ## 赋值 ##
n2 = n1
print(id(n2))
# ## 浅拷贝 ##
n2 = copy.copy(n1)
print(id(n2))
 
# ## 深拷贝 ##
n3 = copy.deepcopy(n1)
print(id(n3))

对于字典、元祖、列表 而言，进行赋值、浅拷贝和深拷贝时，其内存地址的变化是不同的。

 

赋值，只是创建一个变量，该变量指向原来内存地址，如：

n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}
 
n2 = n1

 

浅拷贝，在内存中只额外创建第一层数据

import copy
 
n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}
 
n3 = copy.copy(n1)

 

深拷贝，在内存中将所有的数据重新创建一份（排除最后一层，即：python内部对字符串和数字的优化）

import copy
 
n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}
 
n4 = copy.deepcopy(n1)

八、函数

一、背景

在学习函数之前，一直遵循：面向过程编程，即：根据业务逻辑从上到下实现功能，其往往用一长段代码来实现指定功能，开发过程中最常见的操作就是粘贴复制，也就是将之前实现的代码块复制到现需功能处，如下：

while True：
    if cpu利用率 > 90%:
        #发送邮件提醒
        连接邮箱服务器
        发送邮件
        关闭连接
   
    if 硬盘使用空间 > 90%:
        #发送邮件提醒
        连接邮箱服务器
        发送邮件
        关闭连接
   
    if 内存占用 > 80%:
        #发送邮件提醒
        连接邮箱服务器
        发送邮件
        关闭连接

仔细一看上述代码，if条件语句下的内容可以被提取出来公用，如下：

def 发送邮件(内容)
    #发送邮件提醒
    连接邮箱服务器
    发送邮件
    关闭连接
   
while True：
   
    if cpu利用率 > 90%:
        发送邮件('CPU报警')
   
    if 硬盘使用空间 > 90%:
        发送邮件('硬盘报警')
   
    if 内存占用 > 80%:

对于上述的两种实现方式，第二次必然比第一次的重用性和可读性要好，其实这就是函数式编程和面向过程编程的区别：

  • 函数式：将某功能代码封装到函数中，日后便无需重复编写，仅调用函数即可
  • 面向对象：对函数进行分类和封装，让开发“更快更好更强...”

函数式编程最重要的是增强代码的重用性和可读性

二、定义和使用

def 函数名(参数):
      
    ...
    函数体
    ...

函数的定义主要有如下要点：

  • def：表示函数的关键字
  • 函数名：函数的名称，日后根据函数名调用函数
  • 函数体：函数中进行一系列的逻辑计算，如：发送邮件、计算出 [11,22,38,888,2]中的最大数等...
  • 参数：为函数体提供数据
  • 返回值：当函数执行完毕后，可以给调用者返回数据。

以上要点中，比较重要有参数和返回值：

1、返回值

函数是一个功能块，该功能到底执行成功与否，需要通过返回值来告知调用者。

def 发送短信():
      
    发送短信的代码...
  
    if 发送成功:
        return True
    else:
        return False
  
  
while True:
      
    # 每次执行发送短信函数，都会将返回值自动赋值给result
    # 之后，可以根据result来写日志，或重发等操作
  
    result = 发送短信()
    if result == False:
        记录日志，短信发送失败...

2、参数

为什么要有参数？

 1 def 发送邮件(邮件内容)
 2 
 3     #发送邮件提醒
 4     连接邮箱服务器
 5     发送邮件
 6     关闭连接
 7 
 8  
 9 while True：
10  
11     if cpu利用率 > 90%:
12         发送邮件("CPU报警了。")
13  
14     if 硬盘使用空间 > 90%:
15         发送邮件("硬盘报警了。")
16  
17     if 内存占用 > 80%:
18         发送邮件("内存报警了。")
有参数实现
 1 def CPU报警邮件()
 2     #发送邮件提醒
 3     连接邮箱服务器
 4     发送邮件
 5     关闭连接
 6 
 7 def 硬盘报警邮件()
 8     #发送邮件提醒
 9     连接邮箱服务器
10     发送邮件
11     关闭连接
12 
13 def 内存报警邮件()
14     #发送邮件提醒
15     连接邮箱服务器
16     发送邮件
17     关闭连接
18  
19 while True：
20  
21     if cpu利用率 > 90%:
22         CPU报警邮件（）
23  
24     if 硬盘使用空间 > 90%:
25         硬盘报警邮件（）
26  
27     if 内存占用 > 80%:
28         内存报警邮件（）
无参数实现

 

函数的有三中不同的参数：

  • 普通参数
  • 默认参数
  • 动态参数
1 # ######### 定义函数 ######### 
2 
3 # name 叫做函数func的形式参数，简称：形参
4 def func(name):
5     print name
6 
7 # ######### 执行函数 ######### 
8 #  'spykdis' 叫做函数func的实际参数，简称：实参
9 func('spykdis')
普通参数
 1 def func(name, age = 18):
 2     
 3     print "%s:%s" %(name,age)
 4 
 5 # 指定参数
 6 func('cat', 19)
 7 # 使用默认参数
 8 func('tom')
 9 
10 注：默认参数需要放在参数列表最后
默认参数
 1 def func(*args):
 2 
 3     print args
 4 
 5 
 6 # 执行方式一
 7 func(11,33,4,4454,5)
 8 
 9 # 执行方式二
10 li = [11,2,2,3,3,4,54]
11 func(*li)
动态参数-序列
 1 def func(**kwargs):
 2 
 3     print args
 4 
 5 
 6 # 执行方式一
 7 func(name＝'tom',age=18)
 8 
 9 # 执行方式二
10 li = {'name':'tom', age:18, 'gender':'male'}
11 func(**li)
动态参数-字典
1 def func(*args, **kwargs):
2 
3     print args
4     print kwargs
动态参数-序列和字典

九、lambda表达式

学习条件运算时，对于简单的 if else 语句，可以使用三元运算来表示，即：

# 普通条件语句
if 1 == 1:
    name = 'wupeiqi'
else:
    name = 'alex'
  
# 三元运算
name = 'wupeiqi' if 1 == 1 else 'alex'

对于简单的函数，也存在一种简便的表示方式，即：lambda表达式

# ###################### 普通函数 ######################
# 定义函数（普通方式）
def func(arg):
    return arg + 1
  
# 执行函数
result = func(123)
  
# ###################### lambda ######################
  
# 定义函数（lambda表达式）
my_lambda = lambda arg : arg + 1
  
# 执行函数
result = my_lambda(123)

lambda存在意义就是对简单函数的简洁表示

十、内置函数

详细见python文档，猛击这里

map

遍历序列，对序列中每个元素进行操作，最终获取新的序列。

 

1 li = [11, 22, 33]
2 
3 new_list = map(lambda a: a + 100, li)
每个元素增加100
1 li = [11, 22, 33]
2 sl = [1, 2, 3]
3 new_list = map(lambda a, b: a + b, li, sl)
两个列表相同元素相加

 

filter

对于序列中的元素进行筛选，最终获取符合条件的序列

 

1 li = [11, 22, 33]
2 
3 new_list = filter(lambda arg: arg > 22, li)
4 
5 #filter第一个参数为空，将获取原来序列
获取列表中大于12的所有元素集合

 

reduce

对于序列内所有元素进行累计操作

1 li = [11, 22, 33]
2 
3 result = reduce(lambda arg1, arg2: arg1 + arg2, li)
4 
5 # reduce的第一个参数，函数必须要有两个参数
6 # reduce的第二个参数，要循环的序列
7 # reduce的第三个参数，初始值
获取序列中所有元素的和