Python高手之路【三】python基礎之函數
基本數據類型補充：
set 是一個無序且不重複的元素集合html
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 """
10 Add an element to a set，添加元素 11
12 This has no effect if the element is already present. 13 """
14 pass
15
16 def clear(self, *args, **kwargs): # real signature unknown
17 """ Remove all elements from this set. 清除內容"""
18 pass
19
20 def copy(self, *args, **kwargs): # real signature unknown
21 """ Return a shallow copy of a set. 淺拷貝 """
22 pass
23
24 def difference(self, *args, **kwargs): # real signature unknown
25 """
26 Return the difference of two or more sets as a new set. A中存在，B中不存在 27
28 (i.e. all elements that are in this set but not the others.) 29 """
30 pass
31
32 def difference_update(self, *args, **kwargs): # real signature unknown
33 """ Remove all elements of another set from this set. 從當前集合中刪除和B中相同的元素"""
34 pass
35
36 def discard(self, *args, **kwargs): # real signature unknown
37 """
38 Remove an element from a set if it is a member. 39
40 If the element is not a member, do nothing. 移除指定元素，不存在不保錯 41 """
42 pass
43
44 def intersection(self, *args, **kwargs): # real signature unknown
45 """
46 Return the intersection of two sets as a new set. 交集 47
48 (i.e. all elements that are in both sets.) 49 """
50 pass
51
52 def intersection_update(self, *args, **kwargs): # real signature unknown
53 """ Update a set with the intersection of itself and another. 取交集並更更新到A中 """
54 pass
55
56 def isdisjoint(self, *args, **kwargs): # real signature unknown
57 """ Return True if two sets have a null intersection. 若是沒有交集，返回True，不然返回False"""
58 pass
59
60 def issubset(self, *args, **kwargs): # real signature unknown
61 """ Report whether another set contains this set. 是不是子序列"""
62 pass
63
64 def issuperset(self, *args, **kwargs): # real signature unknown
65 """ Report whether this set contains another set. 是不是父序列"""
66 pass
67
68 def pop(self, *args, **kwargs): # real signature unknown
69 """
70 Remove and return an arbitrary set element. 71 Raises KeyError if the set is empty. 移除元素 72 """
73 pass
74
75 def remove(self, *args, **kwargs): # real signature unknown
76 """
77 Remove an element from a set; it must be a member. 78
79 If the element is not a member, raise a KeyError. 移除指定元素，不存在保錯 80 """
81 pass
82
83 def symmetric_difference(self, *args, **kwargs): # real signature unknown
84 """
85 Return the symmetric difference of two sets as a new set. 對稱差集 86
87 (i.e. all elements that are in exactly one of the sets.) 88 """
89 pass
90
91 def symmetric_difference_update(self, *args, **kwargs): # real signature unknown
92 """ Update a set with the symmetric difference of itself and another. 對稱差集，並更新到a中 """
93 pass
94
95 def union(self, *args, **kwargs): # real signature unknown
96 """
97 Return the union of sets as a new set. 並集 98
99 (i.e. all elements that are in either set.) 100 """
101 pass
102
103 def update(self, *args, **kwargs): # real signature unknown
104 """ Update a set with the union of itself and others. 更新 """
105 pass
1：建立
1 s = set() 2 s = {11,22,33,55}
2：轉換
1 li = [11,22,33,44] 2 tu = (11,22,33,44) 3 st = '123'
4 s = set(li)
3：intersection , intersection_update方法
a = {11,22,33,44} b = {22,66,77,88} ret = a.intersection(b) print(ret)
intersection取得兩個集合中的交集元素，並將這些元素以一個新的集合返回給一個變量接收node
a = {11,22,33,44} b = {22,66,77,88} a.intersection_update(b) print(a)
intersection_update取得兩個集合的交集元素，並更新a集合python
4：isdisjoint , issubset , issuperset方法
1 s = {11,22,33,44} 2 b = {11,22,77,55} 3 ret = s.isdisjoint(b)#有交集返回False，沒有交集返回True
4 print(ret) 5 ## False
issubset判斷是否爲子集c++
a = {11,22,33,44} b = {11,44} ret = b.issubset(a) print(ret) ##########################################
True
issuperset判斷是否爲父集git
a = {11,22,33,44} b = {11,44} ret = a.issubset(b) print(ret) ##########################################
False
5：discard , remove , pop
1 s = {11,22,33,44} 2 s.remove(11) 3 print(s) 4 s.discard(22) 5 print(s) 6 s.pop() 7 print(s)
三者都能達到移除元素的效果，區別在於remove移除集合中不存在的元素時會報錯，discard移除不存在的元素是不會報錯，pop沒法精確控制移除哪一個元素，按其自身的規則隨機移除元素，返回被移除的元素，可使用變量接收其返回值web
6：symmetric_difference取差集
1 s = {11,22,33,44} 2 b = {11,22,77,55} 3 r1 = s.difference(b) 4 r2 = b.difference(s) 5 print(r1) 6 print(r2) 7 ret = s.symmetric_difference(b) 8 print(ret) 9 ## set([33, 44])
10 ## set([77, 55])
11 ## set([33, 44, 77, 55])
symmetric_difference返回兩個集合中不是交集的元素數據庫
上面的代碼中，將symmetric_difference換成symmetric_difference_update則表示將兩個集合中不是交集的部分賦值給sapi
7：union , update方法
1 s = {11,22,33,44} 2 b = {11,22,77,55} 3 ret = s.union(b) 4 print(ret) 5 ## set([33, 11, 44, 77, 22, 55])
union方法合併兩個集合安全
1 s = {11,22,33,44} 2 b = {11,22,77,55} 3 s.update(b) 4 print(s) 5 ## set([33, 11, 44, 77, 22, 55])
update方法更新s集合，將b集合中的元素添加到s集合中！update方法也能夠傳遞一個列表，如：update([23,45,67])bash
練習題：有下面兩個字典
要求：
1）兩個字典中有相同鍵的，則將new_dict中的值更新到old_dict對應鍵的值
2）old_dict中存在的鍵且new_dict中沒有的鍵，在old_dict中刪除，並把new_dict中的鍵值更新到old_dict中
3）最後輸出old_dict
1 # 數據庫中原有
2 old_dict = { 3 "#1":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 80 }, 4 "#2":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 80 }, 5 "#3":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 80 } 6 } 7
8 # cmdb 新彙報的數據
9 new_dict = { 10 "#1":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 800 }, 11 "#3":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 80 }, 12 "#4":{ 'hostname':'c2', 'cpu_count': 2, 'mem_capicity': 80 } 13 }
old_keys = set(old_dict.keys()) new_keys = set(new_dict.keys()) #須要更新元素的鍵 update_keys = old_keys.intersection(new_keys) print(update_keys) #須要刪除元素的鍵 del_keys = old_keys.difference(new_keys) #須要添加元素的鍵 add_keys = new_keys.difference(old_keys) print(del_keys) print(add_keys) update_keys = list(update_keys) for i in update_keys : old_dict[i] = new_dict[i] del_keys = list(del_keys) for j in del_keys : del old_dict[j] for k in list(add_keys) : old_dict[k] = new_dict[k] print(old_dict) ######################################## {'#3': {'hostname': 'c1', 'cpu_count': 2, 'mem_capicity': 80}, '#1': {'hostname': 'c1', 'cpu_count': 2, 'mem_capicity': 800}, '#4': {'hostname': 'c2', 'cpu_count': 2, 'mem_capicity': 80}}
collections系列
1、計數器（counter）
Counter是對字典類型的補充，用於追蹤值的出現次數。
ps：具有字典的全部功能 + 本身的功能
c = Counter('abcdeabcdabcaba')
print c
輸出：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 """ 對於不存在的元素，返回計數器爲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 """ 數量大於等n的全部元素和計數器 """ 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 """ 計數器中的全部元素，注：此處非全部元素集合，而是包含全部元素集合的迭代器 """ 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 """ 更新計數器，其實就是增長；若是原來沒有，則新建，若是有則加一 """ 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 """ 相減，原來的計數器中的每個元素的數量減去後添加的元素的數量 """ 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 """ 拷貝 """ 180 'Return a shallow copy.' 181 return self.__class__(self) 182 183 def __reduce__(self): 184 """ 返回一個元組（類型，元組） """ 185 return self.__class__, (dict(self),) 186 187 def __delitem__(self, elem): 188 """ 刪除元素 """ 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
2、有序字典(orderedDict )
orderdDict是對字典類型的補充，他記住了字典元素添加的順序
1 class OrderedDict(dict): 2 'Dictionary that remembers insertion order' 3 # An inherited dict maps keys to values. 4 # The inherited dict provides __getitem__, __len__, __contains__, and get. 5 # The remaining methods are order-aware. 6 # Big-O running times for all methods are the same as regular dictionaries. 7 8 # The internal self.__map dict maps keys to links in a doubly linked list. 9 # The circular doubly linked list starts and ends with a sentinel element. 10 # The sentinel element never gets deleted (this simplifies the algorithm). 11 # Each link is stored as a list of length three: [PREV, NEXT, KEY]. 12 13 def __init__(self, *args, **kwds): 14 '''Initialize an ordered dictionary. The signature is the same as 15 regular dictionaries, but keyword arguments are not recommended because 16 their insertion order is arbitrary. 17 18 ''' 19 if len(args) > 1: 20 raise TypeError('expected at most 1 arguments, got %d' % len(args)) 21 try: 22 self.__root 23 except AttributeError: 24 self.__root = root = [] # sentinel node 25 root[:] = [root, root, None] 26 self.__map = {} 27 self.__update(*args, **kwds) 28 29 def __setitem__(self, key, value, dict_setitem=dict.__setitem__): 30 'od.__setitem__(i, y) <==> od[i]=y' 31 # Setting a new item creates a new link at the end of the linked list, 32 # and the inherited dictionary is updated with the new key/value pair. 33 if key not in self: 34 root = self.__root 35 last = root[0] 36 last[1] = root[0] = self.__map[key] = [last, root, key] 37 return dict_setitem(self, key, value) 38 39 def __delitem__(self, key, dict_delitem=dict.__delitem__): 40 'od.__delitem__(y) <==> del od[y]' 41 # Deleting an existing item uses self.__map to find the link which gets 42 # removed by updating the links in the predecessor and successor nodes. 43 dict_delitem(self, key) 44 link_prev, link_next, _ = self.__map.pop(key) 45 link_prev[1] = link_next # update link_prev[NEXT] 46 link_next[0] = link_prev # update link_next[PREV] 47 48 def __iter__(self): 49 'od.__iter__() <==> iter(od)' 50 # Traverse the linked list in order. 51 root = self.__root 52 curr = root[1] # start at the first node 53 while curr is not root: 54 yield curr[2] # yield the curr[KEY] 55 curr = curr[1] # move to next node 56 57 def __reversed__(self): 58 'od.__reversed__() <==> reversed(od)' 59 # Traverse the linked list in reverse order. 60 root = self.__root 61 curr = root[0] # start at the last node 62 while curr is not root: 63 yield curr[2] # yield the curr[KEY] 64 curr = curr[0] # move to previous node 65 66 def clear(self): 67 'od.clear() -> None. Remove all items from od.' 68 root = self.__root 69 root[:] = [root, root, None] 70 self.__map.clear() 71 dict.clear(self) 72 73 # -- the following methods do not depend on the internal structure -- 74 75 def keys(self): 76 'od.keys() -> list of keys in od' 77 return list(self) 78 79 def values(self): 80 'od.values() -> list of values in od' 81 return [self[key] for key in self] 82 83 def items(self): 84 'od.items() -> list of (key, value) pairs in od' 85 return [(key, self[key]) for key in self] 86 87 def iterkeys(self): 88 'od.iterkeys() -> an iterator over the keys in od' 89 return iter(self) 90 91 def itervalues(self): 92 'od.itervalues -> an iterator over the values in od' 93 for k in self: 94 yield self[k] 95 96 def iteritems(self): 97 'od.iteritems -> an iterator over the (key, value) pairs in od' 98 for k in self: 99 yield (k, self[k]) 100 101 update = MutableMapping.update 102 103 __update = update # let subclasses override update without breaking __init__ 104 105 __marker = object() 106 107 def pop(self, key, default=__marker): 108 '''od.pop(k[,d]) -> v, remove specified key and return the corresponding 109 value. If key is not found, d is returned if given, otherwise KeyError 110 is raised. 111 112 ''' 113 if key in self: 114 result = self[key] 115 del self[key] 116 return result 117 if default is self.__marker: 118 raise KeyError(key) 119 return default 120 121 def setdefault(self, key, default=None): 122 'od.setdefault(k[,d]) -> od.get(k,d), also set od[k]=d if k not in od' 123 if key in self: 124 return self[key] 125 self[key] = default 126 return default 127 128 def popitem(self, last=True): 129 '''od.popitem() -> (k, v), return and remove a (key, value) pair. 130 Pairs are returned in LIFO order if last is true or FIFO order if false. 131 132 ''' 133 if not self: 134 raise KeyError('dictionary is empty') 135 key = next(reversed(self) if last else iter(self)) 136 value = self.pop(key) 137 return key, value 138 139 def __repr__(self, _repr_running={}): 140 'od.__repr__() <==> repr(od)' 141 call_key = id(self), _get_ident() 142 if call_key in _repr_running: 143 return '...' 144 _repr_running[call_key] = 1 145 try: 146 if not self: 147 return '%s()' % (self.__class__.__name__,) 148 return '%s(%r)' % (self.__class__.__name__, self.items()) 149 finally: 150 del _repr_running[call_key] 151 152 def __reduce__(self): 153 'Return state information for pickling' 154 items = [[k, self[k]] for k in self] 155 inst_dict = vars(self).copy() 156 for k in vars(OrderedDict()): 157 inst_dict.pop(k, None) 158 if inst_dict: 159 return (self.__class__, (items,), inst_dict) 160 return self.__class__, (items,) 161 162 def copy(self): 163 'od.copy() -> a shallow copy of od' 164 return self.__class__(self) 165 166 @classmethod 167 def fromkeys(cls, iterable, value=None): 168 '''OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S. 169 If not specified, the value defaults to None. 170 171 ''' 172 self = cls() 173 for key in iterable: 174 self[key] = value 175 return self 176 177 def __eq__(self, other): 178 '''od.__eq__(y) <==> od==y. Comparison to another OD is order-sensitive 179 while comparison to a regular mapping is order-insensitive. 180 181 ''' 182 if isinstance(other, OrderedDict): 183 return dict.__eq__(self, other) and all(_imap(_eq, self, other)) 184 return dict.__eq__(self, other) 185 186 def __ne__(self, other): 187 'od.__ne__(y) <==> od!=y' 188 return not self == other 189 190 # -- the following methods support python 3.x style dictionary views -- 191 192 def viewkeys(self): 193 "od.viewkeys() -> a set-like object providing a view on od's keys" 194 return KeysView(self) 195 196 def viewvalues(self): 197 "od.viewvalues() -> an object providing a view on od's values" 198 return ValuesView(self) 199 200 def viewitems(self): 201 "od.viewitems() -> a set-like object providing a view on od's items" 202 return ItemsView(self) 203 204 OrderedDict
3、默認字典(defaultdict)
defaultdict是對字典的類型的補充，他默認給字典的值設置了一個類型。
1 class defaultdict(dict): 2 """ 3 defaultdict(default_factory[, ...]) --> dict with default factory 4 5 The default factory is called without arguments to produce 6 a new value when a key is not present, in __getitem__ only. 7 A defaultdict compares equal to a dict with the same items. 8 All remaining arguments are treated the same as if they were 9 passed to the dict constructor, including keyword arguments. 10 """ 11 def copy(self): # real signature unknown; restored from __doc__ 12 """ D.copy() -> a shallow copy of D. """ 13 pass 14 15 def __copy__(self, *args, **kwargs): # real signature unknown 16 """ D.copy() -> a shallow copy of D. """ 17 pass 18 19 def __getattribute__(self, name): # real signature unknown; restored from __doc__ 20 """ x.__getattribute__('name') <==> x.name """ 21 pass 22 23 def __init__(self, default_factory=None, **kwargs): # known case of _collections.defaultdict.__init__ 24 """ 25 defaultdict(default_factory[, ...]) --> dict with default factory 26 27 The default factory is called without arguments to produce 28 a new value when a key is not present, in __getitem__ only. 29 A defaultdict compares equal to a dict with the same items. 30 All remaining arguments are treated the same as if they were 31 passed to the dict constructor, including keyword arguments. 32 33 # (copied from class doc) 34 """ 35 pass 36 37 def __missing__(self, key): # real signature unknown; restored from __doc__ 38 """ 39 __missing__(key) # Called by __getitem__ for missing key; pseudo-code: 40 if self.default_factory is None: raise KeyError((key,)) 41 self[key] = value = self.default_factory() 42 return value 43 """ 44 pass 45 46 def __reduce__(self, *args, **kwargs): # real signature unknown 47 """ Return state information for pickling. """ 48 pass 49 50 def __repr__(self): # real signature unknown; restored from __doc__ 51 """ x.__repr__() <==> repr(x) """ 52 pass 53 54 default_factory = property(lambda self: object(), lambda self, v: None, lambda self: None) # default 55 """Factory for default value called by __missing__().""" 56 57 defaultdict
使用方法：
1 import collections 2 dic = collections.defaultdict(list) 3 dic['k1'].append('alext') 4 print(dic)
練習：
1 有以下值集合 [11,22,33,44,55,66,77,88,99,90...]，將全部大於 66 的值保存至字典的第一個key中，將小於 66 的值保存至第二個key的值中。 2 即： {'k1': 大於66 , 'k2': 小於66}
1 values = [11, 22, 33,44,55,66,77,88,99,90] 2 3 my_dict = {} 4 5 for value in values: 6 if value>66: 7 if my_dict.has_key('k1'): 8 my_dict['k1'].append(value) 9 else: 10 my_dict['k1'] = [value] 11 else: 12 if my_dict.has_key('k2'): 13 my_dict['k2'].append(value) 14 else: 15 my_dict['k2'] = [value]
1 from collections import defaultdict 2 3 values = [11, 22, 33,44,55,66,77,88,99,90] 4 5 my_dict = defaultdict(list) 6 7 for value in values: 8 if value>66: 9 my_dict['k1'].append(value) 10 else: 11 my_dict['k2'].append(value) 12 13 defaultdict字典解決方法 14 15 默認字典
4、可命名元組(namedtuple)
根據nametuple能夠建立一個包含tuple全部功能以及其餘功能的類型。
import collections
MytupleClass = collections.namedtuple('MytupleClass',['x','y','z'])
obj = MytupleClass(11,33,44)
print(obj.x)
print(obj.y)
print(obj.z)
class Mytuple(__builtin__.tuple) | Mytuple(x, y) | | Method resolution order: | Mytuple | __builtin__.tuple | __builtin__.object | | Methods defined here: | | __getnewargs__(self) | Return self as a plain tuple. Used by copy and pickle. | | __getstate__(self) | Exclude the OrderedDict from pickling | | __repr__(self) | Return a nicely formatted representation string | | _asdict(self) | Return a new OrderedDict which maps field names to their values | | _replace(_self, **kwds) | Return a new Mytuple object replacing specified fields with new values | | ---------------------------------------------------------------------- | Class methods defined here: | | _make(cls, iterable, new=<built-in method __new__ of type object>, len=<built-in function len>) from __builtin__.type | Make a new Mytuple object from a sequence or iterable | | ---------------------------------------------------------------------- | Static methods defined here: | | __new__(_cls, x, y) | Create new instance of Mytuple(x, y) | | ---------------------------------------------------------------------- | Data descriptors defined here: | | __dict__ | Return a new OrderedDict which maps field names to their values | | x | Alias for field number 0 | | y | Alias for field number 1 | | ---------------------------------------------------------------------- | Data and other attributes defined here: | | _fields = ('x', 'y') | | ---------------------------------------------------------------------- | Methods inherited from __builtin__.tuple: | | __add__(...) | x.__add__(y) <==> x+y | | __contains__(...) | x.__contains__(y) <==> y in x | | __eq__(...) | x.__eq__(y) <==> x==y | | __ge__(...) | x.__ge__(y) <==> x>=y | | __getattribute__(...) | x.__getattribute__('name') <==> x.name | | __getitem__(...) | x.__getitem__(y) <==> x[y] | | __getslice__(...) | x.__getslice__(i, j) <==> x[i:j] | | Use of negative indices is not supported. | | __gt__(...) | x.__gt__(y) <==> x>y | | __hash__(...) | x.__hash__() <==> hash(x) | | __iter__(...) | x.__iter__() <==> iter(x) | | __le__(...) | x.__le__(y) <==> x<=y | | __len__(...) | x.__len__() <==> len(x) | | __lt__(...) | x.__lt__(y) <==> x<y | | __mul__(...) | x.__mul__(n) <==> x*n | | __ne__(...) | x.__ne__(y) <==> x!=y | | __rmul__(...) | x.__rmul__(n) <==> n*x | | __sizeof__(...) | T.__sizeof__() -- size of T in memory, in bytes | | count(...) | T.count(value) -> integer -- return number of occurrences of value | | index(...) | T.index(value, [start, [stop]]) -> integer -- return first index of value. | Raises ValueError if the value is not present. Mytuple
5、雙向隊列(deque)
一個線程安全的雙向隊列
class deque(object): """ deque([iterable[, maxlen]]) --> deque object Build an ordered collection with optimized access from its endpoints. """ def append(self, *args, **kwargs): # real signature unknown """ Add an element to the right side of the deque. """ pass def appendleft(self, *args, **kwargs): # real signature unknown """ Add an element to the left side of the deque. """ pass def clear(self, *args, **kwargs): # real signature unknown """ Remove all elements from the deque. """ pass def count(self, value): # real signature unknown; restored from __doc__ """ D.count(value) -> integer -- return number of occurrences of value """ return 0 def extend(self, *args, **kwargs): # real signature unknown """ Extend the right side of the deque with elements from the iterable """ pass def extendleft(self, *args, **kwargs): # real signature unknown """ Extend the left side of the deque with elements from the iterable """ pass def pop(self, *args, **kwargs): # real signature unknown """ Remove and return the rightmost element. """ pass def popleft(self, *args, **kwargs): # real signature unknown """ Remove and return the leftmost element. """ pass def remove(self, value): # real signature unknown; restored from __doc__ """ D.remove(value) -- remove first occurrence of value. """ pass def reverse(self): # real signature unknown; restored from __doc__ """ D.reverse() -- reverse *IN PLACE* """ pass def rotate(self, *args, **kwargs): # real signature unknown """ Rotate the deque n steps to the right (default n=1). If n is negative, rotates left. """ pass def __copy__(self, *args, **kwargs): # real signature unknown """ Return a shallow copy of a deque. """ pass def __delitem__(self, y): # real signature unknown; restored from __doc__ """ x.__delitem__(y) <==> del x[y] """ pass def __eq__(self, y): # real signature unknown; restored from __doc__ """ x.__eq__(y) <==> x==y """ pass def __getattribute__(self, name): # real signature unknown; restored from __doc__ """ x.__getattribute__('name') <==> x.name """ pass def __getitem__(self, y): # real signature unknown; restored from __doc__ """ x.__getitem__(y) <==> x[y] """ pass def __ge__(self, y): # real signature unknown; restored from __doc__ """ x.__ge__(y) <==> x>=y """ pass def __gt__(self, y): # real signature unknown; restored from __doc__ """ x.__gt__(y) <==> x>y """ pass def __iadd__(self, y): # real signature unknown; restored from __doc__ """ x.__iadd__(y) <==> x+=y """ pass def __init__(self, iterable=(), maxlen=None): # known case of _collections.deque.__init__ """ deque([iterable[, maxlen]]) --> deque object Build an ordered collection with optimized access from its endpoints. # (copied from class doc) """ pass def __iter__(self): # real signature unknown; restored from __doc__ """ x.__iter__() <==> iter(x) """ pass def __len__(self): # real signature unknown; restored from __doc__ """ x.__len__() <==> len(x) """ pass def __le__(self, y): # real signature unknown; restored from __doc__ """ x.__le__(y) <==> x<=y """ pass def __lt__(self, y): # real signature unknown; restored from __doc__ """ x.__lt__(y) <==> x<y """ pass @staticmethod # known case of __new__ def __new__(S, *more): # real signature unknown; restored from __doc__ """ T.__new__(S, ...) -> a new object with type S, a subtype of T """ pass def __ne__(self, y): # real signature unknown; restored from __doc__ """ x.__ne__(y) <==> x!=y """ pass def __reduce__(self, *args, **kwargs): # real signature unknown """ Return state information for pickling. """ pass def __repr__(self): # real signature unknown; restored from __doc__ """ x.__repr__() <==> repr(x) """ pass def __reversed__(self): # real signature unknown; restored from __doc__ """ D.__reversed__() -- return a reverse iterator over the deque """ pass def __setitem__(self, i, y): # real signature unknown; restored from __doc__ """ x.__setitem__(i, y) <==> x[i]=y """ pass def __sizeof__(self): # real signature unknown; restored from __doc__ """ D.__sizeof__() -- size of D in memory, in bytes """ pass maxlen = property(lambda self: object(), lambda self, v: None, lambda self: None) # default """maximum size of a deque or None if unbounded""" __hash__ = None deque deque
注：既然有雙向隊列，也有單項隊列（先進先出 FIFO ）
class Queue: """Create a queue object with a given maximum size. If maxsize is <= 0, the queue size is infinite. """ def __init__(self, maxsize=0): self.maxsize = maxsize self._init(maxsize) # mutex must be held whenever the queue is mutating. All methods # that acquire mutex must release it before returning. mutex # is shared between the three conditions, so acquiring and # releasing the conditions also acquires and releases mutex. self.mutex = _threading.Lock() # Notify not_empty whenever an item is added to the queue; a # thread waiting to get is notified then. self.not_empty = _threading.Condition(self.mutex) # Notify not_full whenever an item is removed from the queue; # a thread waiting to put is notified then. self.not_full = _threading.Condition(self.mutex) # Notify all_tasks_done whenever the number of unfinished tasks # drops to zero; thread waiting to join() is notified to resume self.all_tasks_done = _threading.Condition(self.mutex) self.unfinished_tasks = 0 def task_done(self): """Indicate that a formerly enqueued task is complete. Used by Queue consumer threads. For each get() used to fetch a task, a subsequent call to task_done() tells the queue that the processing on the task is complete. If a join() is currently blocking, it will resume when all items have been processed (meaning that a task_done() call was received for every item that had been put() into the queue). Raises a ValueError if called more times than there were items placed in the queue. """ self.all_tasks_done.acquire() try: unfinished = self.unfinished_tasks - 1 if unfinished <= 0: if unfinished < 0: raise ValueError('task_done() called too many times') self.all_tasks_done.notify_all() self.unfinished_tasks = unfinished finally: self.all_tasks_done.release() def join(self): """Blocks until all items in the Queue have been gotten and processed. The count of unfinished tasks goes up whenever an item is added to the queue. The count goes down whenever a consumer thread calls task_done() to indicate the item was retrieved and all work on it is complete. When the count of unfinished tasks drops to zero, join() unblocks. """ self.all_tasks_done.acquire() try: while self.unfinished_tasks: self.all_tasks_done.wait() finally: self.all_tasks_done.release() def qsize(self): """Return the approximate size of the queue (not reliable!).""" self.mutex.acquire() n = self._qsize() self.mutex.release() return n def empty(self): """Return True if the queue is empty, False otherwise (not reliable!).""" self.mutex.acquire() n = not self._qsize() self.mutex.release() return n def full(self): """Return True if the queue is full, False otherwise (not reliable!).""" self.mutex.acquire() n = 0 < self.maxsize == self._qsize() self.mutex.release() return n def put(self, item, block=True, timeout=None): """Put an item into the queue. If optional args 'block' is true and 'timeout' is None (the default), block if necessary until a free slot is available. If 'timeout' is a non-negative number, it blocks at most 'timeout' seconds and raises the Full exception if no free slot was available within that time. Otherwise ('block' is false), put an item on the queue if a free slot is immediately available, else raise the Full exception ('timeout' is ignored in that case). """ self.not_full.acquire() try: if self.maxsize > 0: if not block: if self._qsize() == self.maxsize: raise Full elif timeout is None: while self._qsize() == self.maxsize: self.not_full.wait() elif timeout < 0: raise ValueError("'timeout' must be a non-negative number") else: endtime = _time() + timeout while self._qsize() == self.maxsize: remaining = endtime - _time() if remaining <= 0.0: raise Full self.not_full.wait(remaining) self._put(item) self.unfinished_tasks += 1 self.not_empty.notify() finally: self.not_full.release() def put_nowait(self, item): """Put an item into the queue without blocking. Only enqueue the item if a free slot is immediately available. Otherwise raise the Full exception. """ return self.put(item, False) def get(self, block=True, timeout=None): """Remove and return an item from the queue. If optional args 'block' is true and 'timeout' is None (the default), block if necessary until an item is available. If 'timeout' is a non-negative number, it blocks at most 'timeout' seconds and raises the Empty exception if no item was available within that time. Otherwise ('block' is false), return an item if one is immediately available, else raise the Empty exception ('timeout' is ignored in that case). """ self.not_empty.acquire() try: if not block: if not self._qsize(): raise Empty elif timeout is None: while not self._qsize(): self.not_empty.wait() elif timeout < 0: raise ValueError("'timeout' must be a non-negative number") else: endtime = _time() + timeout while not self._qsize(): remaining = endtime - _time() if remaining <= 0.0: raise Empty self.not_empty.wait(remaining) item = self._get() self.not_full.notify() return item finally: self.not_empty.release() def get_nowait(self): """Remove and return an item from the queue without blocking. Only get an item if one is immediately available. Otherwise raise the Empty exception. """ return self.get(False) # Override these methods to implement other queue organizations # (e.g. stack or priority queue). # These will only be called with appropriate locks held # Initialize the queue representation def _init(self, maxsize): self.queue = deque() def _qsize(self, len=len): return len(self.queue) # Put a new item in the queue def _put(self, item): self.queue.append(item) # Get an item from the queue def _get(self): return self.queue.popleft() Queue.Queue
三元運算
三元運算（三目運算），是對簡單的條件語句的縮寫。
1 # 書寫格式
2 result = 值1 if 條件 else 值2 3 # 若是條件成立，那麼將 「值1」 賦值給result變量，不然，將「值2」賦值給result變量
1 a = 1
2 name = 'poe' if a == 1 else 'jet'
3 print(name)
深淺拷貝
1、數字和字符串
對於 數字 和 字符串 而言，賦值、淺拷貝和深拷貝無心義，由於其永遠指向同一個內存地址。
1 import copy 2 # ######### 數字、字符串 #########
3 n1 = 123
4 # n1 = "i am alex age 10"
5 print(id(n1)) 6 # ## 賦值 ##
7 n2 = n1 8 print(id(n2)) 9 # ## 淺拷貝 ##
10 n2 = copy.copy(n1) 11 print(id(n2)) 12
13 # ## 深拷貝 ##
14 n3 = copy.deepcopy(n1) 15 print(id(n3))
2、其餘基本數據類型
對於字典、元祖、列表 而言，進行賦值、淺拷貝和深拷貝時，其內存地址的變化是不一樣的。
一、賦值
賦值，只是建立一個變量，該變量指向原來內存地址，如：
1 n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]} 2
3 n2 = n1
二、淺拷貝
淺拷貝，在內存中只額外建立第一層數據
1 import copy 2
3 n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]} 4
5 n3 = copy.copy(n1)
三、深拷貝
深拷貝，在內存中將全部的數據從新建立一份（排除最後一層，即：python內部對字符串和數字的優化）
1 import copy 2
3 n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]} 4
5 n4 = copy.deepcopy(n1)
函數
1：函數的定義
def 函數名(參數): ... 函數體 ... 返回值
函數的定義主要有以下要點：
def：表示函數的關鍵字
函數名：函數的名稱，往後根據函數名調用函數
函數體：函數中進行一系列的邏輯計算，如：發送郵件、計算出 [11,22,38,888,2]中的最大數等...
參數：爲函數體提供數據
返回值：當函數執行完畢後，能夠給調用者返回數據。
2：返回值
函數是一個功能塊，該功能到底執行成功與否，須要經過返回值來告知調用者。
以上要點中，比較重要有參數和返回值：
def 發送短信(): 發送短信的代碼... if 發送成功: return True else: return False while True: # 每次執行發送短信函數，都會將返回值自動賦值給result
# 以後，能夠根據result來寫日誌，或重發等操做
result = 發送短信() if result == False: 記錄日誌，短信發送失敗...
3：參數
函數有三種不一樣的參數：
普通參數
# ######### 定義函數 #########
# name 叫作函數func的形式參數，簡稱：形參
def func(name): print name # ######### 執行函數 ######### # 'wupeiqi' 叫作函數func的實際參數，簡稱：實參
func('poe')
默認參數
def func(name, age = 18): print "%s:%s" %(name,age) # 指定參數
func('poe', 19) # 使用默認參數
func('gin') 注：默認參數須要放在參數列表最後
動態參數
def f1(*a): print(a,type(a)) f1(123,456,[1,2,3],'who') ## ((123, 456, [1, 2, 3], 'who'), <type 'tuple'>)
def func(**kwargs): print args
# 執行方式一
func(name＝'poe',age=18) # 執行方式二
li = {'name':'poe', age:18, 'gender':'male'} func(**li)
def f1(*a,**b) :#一個星的參數必須在前，兩個星的參數必須在後
print(a,type(a)) print(b,type(b)) f1(11,22,33,k1=1234,k2=456) ## ((11, 22, 33), <type 'tuple'>)({'k2': 456, 'k1': 1234}, <type 'dict'>)
爲動態參數傳入列表，元組，字典：（注：這幾種數據類型在函數傳參的時候只有引用傳遞，沒有值傳遞）
def f1(*args) : print(args,type(args)) li = [1,2,3,4] f1(li) f1(*li) ## (([1, 2, 3, 4],), <type 'tuple'>) ## ((1, 2, 3, 4), <type 'tuple'>)
def f2(**kwargs) : print(kwargs,type(kwargs)) dic = {'k1':123,'k2':456} f2(k1 = dic) f2(**dic) ## ({'k1': {'k2': 456, 'k1': 123}}, <type 'dict'>) ## ({'k2': 456, 'k1': 123}, <type 'dict'>)
4：內置函數
注：查看詳細猛擊這裏
數據類型轉換函數
- chr(i) 函數返回ASCII碼對應的字符串
-
print(chr(65)) print(chr(66)) print(chr(65)+chr(66)) ########################################## A B AB - complex(real[,imaginary]) 函數可把字符串或數字轉換爲複數
-
print(complex("2+1j")) print(complex("2")) print(complex(2,1)) ########################################## (2+1j) (2+0j) (2+1j) - float(x) 函數把一個數字或字符串轉換成浮點數
-
print(float(12)) print(float(12.2)) ########################################## 12.0 12.2 - long(x[,base]) 函數把數字和字符串轉換成長整數，base爲可選的基數
- list(x) 函數可將序列對象轉換成列表
- min(x[,y,z...]) 函數返回給定參數的最小值，參數能夠爲序列
- max(x[,y,z...]) 函數返回給定參數的最大值，參數能夠爲序列
- ord(x) 函數返回一個字符串參數的ASCII碼或Unicode值
-
print(ord('a')) print(ord(u"A")) ########################################## 97 65 - str(obj) 函數把對象轉換成可打印字符串
- tuple(x) 函數把序列對象轉換成tuple
- type(x) 能夠接收任何東西做爲參數――並返回它的數據類型。整型、字符串、列表、字典、元組、函數、類、模塊，甚至類型對象均可以做爲參數被 type 函數接受
abs()函數：取絕對值
print(abs(-1.2))
all()函數與any函數：
all(iterable)：若是iterable的任意一個元素爲0、''、False，則返回False，不然返回True
print(all(['a','b','c','d']))#True
print(all(['a','b','','d']))#False #注意：空元組、空列表返回值爲True，這裏要特別注意
any(iterable)：若是iterable的全部元素都爲0、''、False，則返回False，不然返回True
print(any(['a','b','c','d']))#True
print(any(['a',0,' ',False]))#True
print(any([0,'',False]))#False
ascii(object) 函數：
返回一個可打印的對象字符串方式表示，若是是非ascii字符就會輸出\x，\u或\U等字符來表示。與python2版本里的repr()是等效的函數。
print(ascii(1)) print(ascii('a')) print(ascii(123)) print(ascii('中文'))#非ascii字符 ##########################################
1
'a'
123
'\u4e2d\u6587'
lambda表達式：
學習條件運算時，對於簡單的 if else 語句，可使用三元運算來表示，即：
# 普通條件語句
if 1 == 1: name = 'poe'
else: name = 'bruce'
# 三元運算
name = 'poe' if 1 == 1 else 'bruce'
對於簡單的函數，也存在一種簡便的表示方式，即：lambda表達式
# ###################### 普通函數 ###################### # 定義函數（普通方式） def func(arg): return arg + 1 # 執行函數 result = func(123) # ###################### lambda ###################### # 定義函數（lambda表達式） my_lambda = lambda arg : arg + 1 # 執行函數 result = my_lambda(123)
生成隨機數：
import random chars = ''
for i in range(4) : rand_num = random.randrange(0,4) if rand_num == 3 or rand_num == 1: rand_digit = random.randrange(0,10) chars += str(rand_digit) else: rand_case = random.randrange(65,90) case = chr(rand_case) chars += case print(chars)
filter函數
filter()函數是 Python 內置的另外一個有用的高階函數，filter()函數接收一個函數 f 和一個list，這個函數 f 的做用是對每一個元素進行判斷，返回 True或 False，filter()根據判斷結果自動過濾掉不符合條件的元素，返回由符合條件元素組成的新list。
例1，要從一個list [1, 4, 6, 7, 9, 12, 17]中刪除偶數，保留奇數，首先，要編寫一個判斷奇數的函數：
# filter(fn,iterable)
def is_odd(x) : return x % 2 == 1 li = [1, 4, 6, 7, 9, 12, 17] result = filter(is_odd,li) print(result) ##########################################
[1, 7, 9, 17]
例2：刪除 列表中的None 或者空字符串
li = ['test', None, '', 'str', ' ', 'END'] def is_not_empty(s) : return s and len(s.strip()) > 0 print(filter(is_not_empty,li)) ##########################################
['test', 'str', 'END']
例3：請利用filter()過濾出1~100中平方根是整數的數，即結果應該是：[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
import math def is_sqr(x) : return math.sqrt(x) % 1 == 0 print filter(is_sqr,range(1,101))
以上三個函數均可以使用lambda表達式的寫法來書寫，如：
result = filter(lambda x : x % 2 == 1,[1,4,6,9,12,7,17]) print(result)
map()函數
map()是 Python 內置的高階函數，它接收一個函數 f 和一個 list，並經過把函數 f 依次做用在 list 的每一個元素上，獲得一個新的 list 並返回
例如，對於list [1, 2, 3, 4, 5, 6, 7, 8, 9]若是但願把list的每一個元素都做平方，就能夠用map()函數
li = [1, 2, 3, 4, 5, 6, 7, 8, 9] print(li) def f(x) : return x*x r = list(map(f,[1, 2, 3, 4, 5, 6, 7, 8, 9])) print(r)
注：在python3裏面，map()的返回值已經再也不是list,而是iterators, 因此想要使用，只用將iterator 轉換成list 便可， 好比 list(map()) 。
進制轉換函數（如下四個函數能夠實現各進制間的互相轉換）
bin(x) ：將整數x轉換爲二進制字符串，若是x不爲Python中int類型，x必須包含方法__index__()而且返回值爲integer
oct(x)：將一個整數轉換成8進制字符串。若是傳入浮點數或者字符串均會報錯
hex(x)：將一個整數轉換成16進制字符串。
int()：
- 傳入數值時，調用其__int__()方法，浮點數將向下取整
-
print(int(3))#3 print(int(3.6))#3 - 傳入字符串時，默認以10進制進行轉換
-
print(int('36'))#36 - 字符串中容許包含"+"、"-"號，可是加減號與數值間不能有空格，數值後、符號前可出現空格
-
print(int('+36'))#36 - 傳入字符串，並指定了進制，則按對應進制將字符串轉換成10進制整數
-
print(int('10',2))#2 print(int('0o7',8))#7 print(int('0x15',16))#21
open函數，該函數用於文件處理
操做文件時，通常須要經歷以下步驟：
- 打開文件
- 操做文件
一：打開文件
文件句柄 = open('文件路徑', '模式')
打開文件時，須要指定文件路徑和以何等方式打開文件，打開後，便可獲取該文件句柄，往後經過此文件句柄對該文件操做。
打開文件的模式有：
- r ，只讀模式【默認】
- w，只寫模式【不可讀；不存在則建立；存在則清空內容；】
- x， 只寫模式【不可讀；不存在則建立，存在則報錯】
- a， 追加模式【可讀； 不存在則建立；存在則只追加內容；】
f = open('test.log','r') data = f.read() f.close() print(data)
"+" 表示能夠同時讀寫某個文件
- r+， 讀寫【可讀，可寫】
- w+，寫讀【可讀，可寫】
- x+ ，寫讀【可讀，可寫】
- a+， 寫讀【可讀，可寫】
# r+ 模式
f = open('test.log','r+',encoding='utf-8') print(f.tell())#打印當前指針所在的位置，此時爲0
data = f.read() print(data) print(f.tell())#此時當前指針在文件最末尾
f.close()
# w+模式：先清空文件，再寫入文件，寫入文件後才能夠讀文件
f = open('test.log','w+',encoding="utf-8") f.write('python')#寫完後，指針到了最後
f.seek(0)#移動指針到開頭
data = f.read() f.close() print(data)
# a+模式：打開的同時，指針已經到最後， # 寫時，追加，指針到最後
f = open('test.log','a+',encoding="utf-8") print(f.tell())#讀取當前指針位置，此時指針已經到最後
f.write('c++') print(f.tell()) #此時要讀文件必須把指針移動到文件開頭
f.seek(0) data = f.read(); print(data) f.close()
"b"表示以字節的方式操做
- rb 或 r+b
- wb 或 w+b
- xb 或 w+b
- ab 或 a+b
注：以b方式打開時，讀取到的內容是字節類型，寫入時也須要提供字節類型
二：文件操做
class file(object) def close(self): # real signature unknown; restored from __doc__
關閉文件 """ close() -> None or (perhaps) an integer. Close the file. Sets data attribute .closed to True. A closed file cannot be used for further I/O operations. close() may be called more than once without error. Some kinds of file objects (for example, opened by popen()) may return an exit status upon closing. """
def fileno(self): # real signature unknown; restored from __doc__
文件描述符 """ fileno() -> integer "file descriptor". This is needed for lower-level file interfaces, such os.read(). """
return 0 def flush(self): # real signature unknown; restored from __doc__
刷新文件內部緩衝區 """ flush() -> None. Flush the internal I/O buffer. """
pass
def isatty(self): # real signature unknown; restored from __doc__
判斷文件是不是贊成tty設備 """ isatty() -> true or false. True if the file is connected to a tty device. """
return False def next(self): # real signature unknown; restored from __doc__
獲取下一行數據，不存在，則報錯 """ x.next() -> the next value, or raise StopIteration """
pass
def read(self, size=None): # real signature unknown; restored from __doc__
讀取指定字節數據 """ read([size]) -> read at most size bytes, returned as a string. If the size argument is negative or omitted, read until EOF is reached. Notice that when in non-blocking mode, less data than what was requested may be returned, even if no size parameter was given. """
pass
def readinto(self): # real signature unknown; restored from __doc__
讀取到緩衝區，不要用，將被遺棄 """ readinto() -> Undocumented. Don't use this; it may go away. """
pass
def readline(self, size=None): # real signature unknown; restored from __doc__
僅讀取一行數據 """ readline([size]) -> next line from the file, as a string. Retain newline. A non-negative size argument limits the maximum number of bytes to return (an incomplete line may be returned then). Return an empty string at EOF. """
pass
def readlines(self, size=None): # real signature unknown; restored from __doc__
讀取全部數據，並根據換行保存值列表 """ readlines([size]) -> list of strings, each a line from the file. Call readline() repeatedly and return a list of the lines so read. The optional size argument, if given, is an approximate bound on the total number of bytes in the lines returned. """
return [] def seek(self, offset, whence=None): # real signature unknown; restored from __doc__
指定文件中指針位置 """ seek(offset[, whence]) -> None. Move to new file position. Argument offset is a byte count. Optional argument whence defaults to (offset from start of file, offset should be >= 0); other values are 1 (move relative to current position, positive or negative), and 2 (move relative to end of file, usually negative, although many platforms allow seeking beyond the end of a file). If the file is opened in text mode, only offsets returned by tell() are legal. Use of other offsets causes undefined behavior. Note that not all file objects are seekable. """
pass
def tell(self): # real signature unknown; restored from __doc__
獲取當前指針位置 """ tell() -> current file position, an integer (may be a long integer). """
pass
def truncate(self, size=None): # real signature unknown; restored from __doc__
截斷數據，僅保留指定以前數據 """ truncate([size]) -> None. Truncate the file to at most size bytes. Size defaults to the current file position, as returned by tell(). """
pass
def write(self, p_str): # real signature unknown; restored from __doc__
寫內容 """ write(str) -> None. Write string str to file. Note that due to buffering, flush() or close() may be needed before the file on disk reflects the data written. """
pass
def writelines(self, sequence_of_strings): # real signature unknown; restored from __doc__
將一個字符串列表寫入文件 """ writelines(sequence_of_strings) -> None. Write the strings to the file. Note that newlines are not added. The sequence can be any iterable object producing strings. This is equivalent to calling write() for each string. """
pass
def xreadlines(self): # real signature unknown; restored from __doc__
可用於逐行讀取文件，非所有 """ xreadlines() -> returns self. For backward compatibility. File objects now include the performance optimizations previously implemented in the xreadlines module. """
pass
2.x
class TextIOWrapper(_TextIOBase): """ Character and line based layer over a BufferedIOBase object, buffer. encoding gives the name of the encoding that the stream will be decoded or encoded with. It defaults to locale.getpreferredencoding(False). errors determines the strictness of encoding and decoding (see help(codecs.Codec) or the documentation for codecs.register) and defaults to "strict". newline controls how line endings are handled. It can be None, '', '\n', '\r', and '\r\n'. It works as follows: * On input, if newline is None, universal newlines mode is enabled. Lines in the input can end in '\n', '\r', or '\r\n', and these are translated into '\n' before being returned to the caller. If it is '', universal newline mode is enabled, but line endings are returned to the caller untranslated. If it has any of the other legal values, input lines are only terminated by the given string, and the line ending is returned to the caller untranslated. * On output, if newline is None, any '\n' characters written are translated to the system default line separator, os.linesep. If newline is '' or '\n', no translation takes place. If newline is any of the other legal values, any '\n' characters written are translated to the given string. If line_buffering is True, a call to flush is implied when a call to write contains a newline character. """
def close(self, *args, **kwargs): # real signature unknown
關閉文件 pass
def fileno(self, *args, **kwargs): # real signature unknown
文件描述符 pass
def flush(self, *args, **kwargs): # real signature unknown
刷新文件內部緩衝區 pass
def isatty(self, *args, **kwargs): # real signature unknown
判斷文件是不是贊成tty設備 pass
def read(self, *args, **kwargs): # real signature unknown
讀取指定字節數據 pass
def readable(self, *args, **kwargs): # real signature unknown
是否可讀 pass
def readline(self, *args, **kwargs): # real signature unknown
僅讀取一行數據 pass
def seek(self, *args, **kwargs): # real signature unknown
指定文件中指針位置 pass
def seekable(self, *args, **kwargs): # real signature unknown
指針是否可操做 pass
def tell(self, *args, **kwargs): # real signature unknown
獲取指針位置 pass
def truncate(self, *args, **kwargs): # real signature unknown
截斷數據，僅保留指定以前數據 pass
def writable(self, *args, **kwargs): # real signature unknown
是否可寫 pass
def write(self, *args, **kwargs): # real signature unknown
寫內容 pass
def __getstate__(self, *args, **kwargs): # real signature unknown
pass
def __init__(self, *args, **kwargs): # real signature unknown
pass @staticmethod # known case of __new__
def __new__(*args, **kwargs): # real signature unknown
""" Create and return a new object. See help(type) for accurate signature. """
pass
def __next__(self, *args, **kwargs): # real signature unknown
""" Implement next(self). """
pass
def __repr__(self, *args, **kwargs): # real signature unknown
""" Return repr(self). """
pass buffer = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
closed = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
encoding = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
errors = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
line_buffering = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
name = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
newlines = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
_CHUNK_SIZE = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
_finalizing = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
3.x
三：管理上下文
爲了不打開文件後忘記關閉，能夠經過管理上下文，即：
with open('log','r') as f: ...
如此方式，當with代碼塊執行完畢時，內部會自動關閉並釋放文件資源。
在Python 2.7 及之後，with又支持同時對多個文件的上下文進行管理，即：
with open('log1') as obj1, open('log2') as obj2: pass
可以使用此方法對一個文件進行讀操做，同時把數據又寫入到另外一個打開的文件中！
read()、readline() 和 readlines()
每種方法能夠接受一個變量以限制每次讀取的數據量，但它們一般不使用變量。 .read() 每次讀取整個文件，它一般用於將文件內容放到一個字符串變量中。然而 .read() 生成文件內容最直接的字符串表示，但對於連續的面向行的處理，它倒是沒必要要的，而且若是文件大於可用內存，則不可能實現這種處理。
.readline() 和 .readlines() 很是類似。它們都在相似於如下的結構中使用：
fh = open('c:\\autoexec.bat') for line in fh.readlines(): print line
.readline() 和 .readlines() 之間的差別是後者一次讀取整個文件，象 .read() 同樣。.readlines() 自動將文件內容分析成一個行的列表，該列表能夠由 Python 的 for ... in ... 結構進行處理。另外一方面，.readline() 每次只讀取一行，一般比 .readlines() 慢得多。僅當沒有足夠內存能夠一次讀取整個文件時，才應該使用 .readline()。
練習題：用戶名與密碼的驗證
首先新建一個文件，這裏爲test.log文件，內容爲兩行以下：
admin$123 ginvip$123456
1：讓用戶選擇1或2，1爲登陸，2爲註冊
2：若是用戶選擇1，用戶輸入用戶名與密碼，而後與test.log文件中的用戶名與密碼進行驗證，驗證成功輸出「登陸成功」，不然「登陸失敗」
3：若是用戶選擇2，讓用戶輸入用戶名與密碼，並與test.log文件中的用戶名驗證，若是test.log中用戶名已經存在，則輸出「該用戶名已經存在」，不然將用戶輸入的用戶與密碼以上面test.log文件中的形式寫入test.log文件中
1 def check_user(user) : 2 with open('test.log','r',encoding='utf-8') as f : 3 for line in f : 4 user_list = line.strip() 5 user_list = user_list.split('$') 6 if user == user_list[0] : 7 return True 8 return False 9 def register(user,pwd) : 10 with open('test.log','a',encoding='utf-8') as f : 11 user_info = '\n' + user + '$' + pwd 12 if f.write(user_info) : 13 return True 14 return False 15 def login(user,pwd) : 16 with open('test.log','r',encoding='utf-8') as f : 17 for line in f: 18 user_list = line.strip() 19 user_list = user_list.split('$') 20 if user == user_list[0] and pwd == user_list[1]: 21 return True 22 return False 23 def main() : 24 print('welcome to my website') 25 choice = input('1:login 2:register') 26 if choice == '2': 27 user = input('input username :') 28 pwd = input('input password : ') 29 if check_user(user) : 30 print('the username is exist') 31 else: 32 if register(user,pwd) : 33 print('register success') 34 else: 35 print('register failed') 36 elif choice == '1': 37 user = input('input username :') 38 pwd = input('input password : ') 39 if login(user,pwd) : 40 print('login success') 41 else: 42 print('login failed') 43 main()
冒泡排序
冒泡排序的原理：
def Bubble_sort(args) : for i in range(len(args)-1) : for j in range(len(args) -1): if args[j] > args[j+1]: temp = args[j] args[j] = args[j+1] args[j+1] = temp return args li = [33,2,10,1,9,3,8] print(Bubble_sort(li))
練習題
一、簡述普通參數、指定參數、默認參數、動態參數的區別
二、寫函數，計算傳入字符串中【數字】、【字母】、【空格] 以及 【其餘】的個數
digit = 0 case = 0 space = 0 other = 0 def func2(s) : global digit,case,space,other if not isinstance(s,basestring) : print('the data type wrong!') return False for i in s : if i.isdigit() : digit += 1
elif i.isalpha() : case += 1
elif i.isspace() : space += 1
else: other += 1 s = 'I love python , is num 1 , o_k' a = [1,2,3] func2(s) print(digit) print(case) print(space) print(other) ########################################
1
18
8
3 問題：判斷是否是字符串後直接退出函數，而不執行下面的代碼？
三、寫函數，判斷用戶傳入的對象（字符串、列表、元組）長度是否大於5。
def func3(v) : if len(v) > 5 : return True else: return False a = 'I love python , is num 1 , o_k' l = [1,2,3] t = (5,7,9,10,45,10) print(func3(t))
四、寫函數，檢查用戶傳入的對象（字符串、列表、元組）的每個元素是否含有空內容。
五、寫函數，檢查傳入列表的長度，若是大於2，那麼僅保留前兩個長度的內容，並將新內容返回給調用者。
def func5(lis) : if len(lis) > 2 : return lis[0:2] else : return False li = [1,2,3] print(func5(li)) ##########################################
[1, 2]
六、寫函數，檢查獲取傳入列表或元組對象的全部奇數位索引對應的元素，並將其做爲新列表返回給調用者。
def func6(lis) : new_lis = [] for k in range(len(lis)) : if k % 2 == 1 : new_lis.append(lis[k]) return new_lis li = [1,2,3,8,10,44,77] tu = ('poe','andy','jet','bruce','jacky') print(func6(tu)) ##########################################
['andy', 'bruce']
七、寫函數，檢查傳入字典的每個value的長度,若是大於2，那麼僅保留前兩個長度的內容，並將新內容返回給調用者。
dic = {"k1": "v1v1", "k2": [11,22,33,44]} PS:字典中的value只能是字符串或列表
def func7(d) : v = d.values() li = [] for i in v : if len(i) > 2: li.append(i[0:2]) return li print(func7(dic)) ##########################################
[[11, 22], 'v1']
八、寫函數，利用遞歸獲取斐波那契數列中的第 10 個數，並將該值返回給調用者
def fabonacci(n) : if n == 0 : return 0 elif n == 1: return 1 else: return fabonacci(n-1) + fabonacci(n-2) print(fabonacci(10))
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