三元运算
三元运算（三目运算），是对简单的条件语句的缩写。
# 书写格式 #result = 值1 if 条件 else 值2 # 如果条件成立，那么将 “值1” 赋值给result变量，否则，将“值2”赋值给result变量 >>> a1='winter' if 1>2 else 'winter2' >>> a1 'winter2'
collection系列
1、计数器（counter）
Counter是对字典类型的补充，用于追踪值的出现次数。
ps：具备字典的所有功能 + 自己的功能
#!/usr/bin/env python # -*- coding:utf-8 -*- import collections collections.Counter class Counter(dict): '''Dict subclass for counting hashable items. Sometimes called a bag or multiset. Elements are stored as dictionary keys and their counts are stored as dictionary values. >>> c = Counter('abcdeabcdabcaba') # count elements from a string >>> c.most_common(3) # three most common elements [('a', 5), ('b', 4), ('c', 3)] >>> sorted(c) # list all unique elements ['a', 'b', 'c', 'd', 'e'] >>> ''.join(sorted(c.elements())) # list elements with repetitions 'aaaaabbbbcccdde' >>> sum(c.values()) # total of all counts 15 >>> c['a'] # count of letter 'a' 5 >>> for elem in 'shazam': # update counts from an iterable ... c[elem] += 1 # by adding 1 to each element's count >>> c['a'] # now there are seven 'a' 7 >>> del c['b'] # remove all 'b' >>> c['b'] # now there are zero 'b' 0 >>> d = Counter('simsalabim') # make another counter >>> c.update(d) # add in the second counter >>> c['a'] # now there are nine 'a' 9 >>> c.clear() # empty the counter >>> c Counter() Note: If a count is set to zero or reduced to zero, it will remain in the counter until the entry is deleted or the counter is cleared: >>> c = Counter('aaabbc') >>> c['b'] -= 2 # reduce the count of 'b' by two >>> c.most_common() # 'b' is still in, but its count is zero [('a', 3), ('c', 1), ('b', 0)] ''' # References: # http://en.wikipedia.org/wiki/Multiset # http://www.gnu.org/software/smalltalk/manual-base/html_node/Bag.html # http://www.demo2s.com/Tutorial/Cpp/0380__set-multiset/Catalog0380__set-multiset.htm # http://code.activestate.com/recipes/259174/ # Knuth, TAOCP Vol. II section 4.6.3 def __init__(*args, **kwds): '''Create a new, empty Counter object. And if given, count elements from an input iterable. Or, initialize the count from another mapping of elements to their counts. >>> c = Counter() # a new, empty counter >>> c = Counter('gallahad') # a new counter from an iterable >>> c = Counter({'a': 4, 'b': 2}) # a new counter from a mapping >>> c = Counter(a=4, b=2) # a new counter from keyword args ''' if not args: raise TypeError("descriptor '__init__' of 'Counter' object " "needs an argument") self, *args = args if len(args) > 1: raise TypeError('expected at most 1 arguments, got %d' % len(args)) super(Counter, self).__init__() self.update(*args, **kwds) def __missing__(self, key): 'The count of elements not in the Counter is zero. Counter({'r': 2, 'e': 2, 't': 2, 'i': 2, 'w': 2, 'n': 2}) >> > c1.__missing__('v') 0 >> > c1.__missing__('w') 0 不清楚使用方法，不论是用v还是w，一个存在的，一个不存在的都是返回0. ' # Needed so that self[missing_item] does not raise KeyError return 0 def most_common(self, n=None): '''List the n most common elements and their counts from the most common to the least. If n is None, then list all element counts. >>> Counter('abcdeabcdabcaba').most_common(3) [('a', 5), ('b', 4), ('c', 3)] 取前面几位,注意并列的不会取，只会按字母排序取最前面的。 >>> a1=a.most_common(4) >>> a1 [('k', 6), ('d', 5), ('e', 3), ('s', 3)] >>> a Counter({'k': 6, 'd': 5, 'e': 3, 's': 3, 'i': 3, 'l': 2, 'w': 1, 'a': 1, 'o': 1}) >>> ''' # Emulate Bag.sortedByCount from Smalltalk if n is None: return sorted(self.items(), key=_itemgetter(1), reverse=True) return _heapq.nlargest(n, self.items(), key=_itemgetter(1)) def elements(self): '''Iterator over elements repeating each as many times as its count. >>> c = Counter('ABCABC') >>> sorted(c.elements()) ['A', 'A', 'B', 'B', 'C', 'C'] # Knuth's example for prime factors of 1836: 2**2 * 3**3 * 17**1 >>> prime_factors = Counter({2: 2, 3: 3, 17: 1}) >>> product = 1 >>> for factor in prime_factors.elements(): # loop over factors ... product *= factor # and multiply them >>> product 1836 Note, if an element's count has been set to zero or is a negative number, elements() will ignore it. 注意注意，如果某元素counter为0，element会忽略他。 ''' # Emulate Bag.do from Smalltalk and Multiset.begin from C++. return _chain.from_iterable(_starmap(_repeat, self.items())) # Override dict methods where necessary @classmethod def fromkeys(cls, iterable, v=None): # There is no equivalent method for counters because setting v=1 # means that no element can have a count greater than one. #不能使用了吗？调用的时候，确实出向下面的一样的错误 raise NotImplementedError( 'Counter.fromkeys() is undefined. Use Counter(iterable) instead.') def update(*args, **kwds): '''Like dict.update() but add counts instead of replacing them. Source can be an iterable, a dictionary, or another Counter instance. >>> c = Counter('which') >>> c.update('witch') # add elements from another iterable >>> d = Counter('watch') >>> c.update(d) # add elements from another counter >>> c['h'] # four 'h' in which, witch, and watch 4 增加对应的统计数值。 >>> d1=collections.Counter('wi') >>> d2=collections.Counter('vi') >>> d1.update(d2) >>> d1 Counter({'i': 2, 'v': 1, 'w': 1}) >>> ''' # The regular dict.update() operation makes no sense here because the # replace behavior results in the some of original untouched counts # being mixed-in with all of the other counts for a mismash that # doesn't have a straight-forward interpretation in most counting # contexts. Instead, we implement straight-addition. Both the inputs # and outputs are allowed to contain zero and negative counts. if not args: raise TypeError("descriptor 'update' of 'Counter' object " "needs an argument") self, *args = args if len(args) > 1: raise TypeError('expected at most 1 arguments, got %d' % len(args)) iterable = args[0] if args else None if iterable is not None: if isinstance(iterable, Mapping): if self: self_get = self.get for elem, count in iterable.items(): self[elem] = count + self_get(elem, 0) else: super(Counter, self).update(iterable) # fast path when counter is empty else: _count_elements(self, iterable) if kwds: self.update(kwds) def subtract(*args, **kwds): '''Like dict.update() but subtracts counts instead of replacing them. Counts can be reduced below zero. Both the inputs and outputs are allowed to contain zero and negative counts. Source can be an iterable, a dictionary, or another Counter instance. 计算减少，而且可以为负数。 修改数据，不返回结果。 注意与__sub__的不同。 >>> d1 Counter({'i': 3, 'v': 2, 'w': 1}) >>> d1.subtract(d2) >>> d1 Counter({'i': 2, 'v': 1, 'w': 1}) >>> d3=collections.Counter('aa') >>> d1.subtract(d3) >>> d1 Counter({'i': 2, 'v': 1, 'w': 1, 'a': -2}) >>> c = Counter('which') >>> c.subtract('witch') # subtract elements from another iterable >>> c.subtract(Counter('watch')) # subtract elements from another counter >>> c['h'] # 2 in which, minus 1 in witch, minus 1 in watch 0 >>> c['w'] # 1 in which, minus 1 in witch, minus 1 in watch -1 ''' if not args: raise TypeError("descriptor 'subtract' of 'Counter' object " "needs an argument") self, *args = args if len(args) > 1: raise TypeError('expected at most 1 arguments, got %d' % len(args)) iterable = args[0] if args else None if iterable is not None: self_get = self.get if isinstance(iterable, Mapping): for elem, count in iterable.items(): self[elem] = self_get(elem, 0) - count else: for elem in iterable: self[elem] = self_get(elem, 0) - 1 if kwds: self.subtract(kwds) def copy(self): 'Return a shallow copy.' return self.__class__(self) def __reduce__(self): return self.__class__, (dict(self),) def __delitem__(self, elem): 'Like dict.__delitem__() but does not raise KeyError for missing values.' if elem in self: super().__delitem__(elem) def __repr__(self): if not self: return '%s()' % self.__class__.__name__ try: items = ', '.join(map('%r: %r'.__mod__, self.most_common())) return '%s({%s})' % (self.__class__.__name__, items) except TypeError: # handle case where values are not orderable return '{0}({1!r})'.format(self.__class__.__name__, dict(self)) # Multiset-style mathematical operations discussed in: # Knuth TAOCP Volume II section 4.6.3 exercise 19 # and at http://en.wikipedia.org/wiki/Multiset # # Outputs guaranteed to only include positive counts. # # To strip negative and zero counts, add-in an empty counter: # c += Counter() def __add__(self, other): '''Add counts from two counters. >>> Counter('abbb') + Counter('bcc') Counter({'b': 4, 'c': 2, 'a': 1}) ''' if not isinstance(other, Counter): return NotImplemented result = Counter() for elem, count in self.items(): newcount = count + other[elem] if newcount > 0: result[elem] = newcount for elem, count in other.items(): if elem not in self and count > 0: result[elem] = count return result def __sub__(self, other): ''' Subtract count, but keep only results with positive counts. 减少，但是不保留负数的计数, 不改变数据。substract是修改数据，不返回结果。 >>> Counter('abbbc') - Counter('bccd') Counter({'b': 2, 'a': 1}) ''' if not isinstance(other, Counter): return NotImplemented result = Counter() for elem, count in self.items(): newcount = count - other[elem] if newcount > 0: result[elem] = newcount for elem, count in other.items(): if elem not in self and count < 0: result[elem] = 0 - count return result def __or__(self, other): '''Union is the maximum of value in either of the input counters. >>> Counter('abbb') | Counter('bcc') Counter({'b': 3, 'c': 2, 'a': 1}) ''' if not isinstance(other, Counter): return NotImplemented result = Counter() for elem, count in self.items(): other_count = other[elem] newcount = other_count if count < other_count else count if newcount > 0: result[elem] = newcount for elem, count in other.items(): if elem not in self and count > 0: result[elem] = count return result def __and__(self, other): ''' Intersection is the minimum of corresponding counts. >>> Counter('abbb') & Counter('bcc') Counter({'b': 1}) ''' if not isinstance(other, Counter): return NotImplemented result = Counter() for elem, count in self.items(): other_count = other[elem] newcount = count if count < other_count else other_count if newcount > 0: result[elem] = newcount return result def __pos__(self): 'Adds an empty counter, effectively stripping negative and zero counts' result = Counter() for elem, count in self.items(): if count > 0: result[elem] = count return result def __neg__(self): '''Subtracts from an empty counter. Strips positive and zero counts, and flips the sign on negative counts. ''' result = Counter() for elem, count in self.items(): if count < 0: result[elem] = 0 - count return result def _keep_positive(self): '''Internal method to strip elements with a negative or zero count''' nonpositive = [elem for elem, count in self.items() if not count > 0] for elem in nonpositive: del self[elem] return self def __iadd__(self, other): '''Inplace add from another counter, keeping only positive counts. >>> c = Counter('abbb') >>> c += Counter('bcc') >>> c Counter({'b': 4, 'c': 2, 'a': 1}) ''' for elem, count in other.items(): self[elem] += count return self._keep_positive() def __isub__(self, other): '''Inplace subtract counter, but keep only results with positive counts. >>> c = Counter('abbbc') >>> c -= Counter('bccd') >>> c Counter({'b': 2, 'a': 1}) ''' for elem, count in other.items(): self[elem] -= count return self._keep_positive() def __ior__(self, other): '''Inplace union is the maximum of value from either counter. >>> c = Counter('abbb') >>> c |= Counter('bcc') >>> c Counter({'b': 3, 'c': 2, 'a': 1}) ''' for elem, other_count in other.items(): count = self[elem] if other_count > count: self[elem] = other_count return self._keep_positive() def __iand__(self, other): '''Inplace intersection is the minimum of corresponding counts. >>> c = Counter('abbb') >>> c &= Counter('bcc') >>> c Counter({'b': 1}) ''' for elem, count in self.items(): other_count = other[elem] if other_count < count: self[elem] = other_count return self._keep_positive()
2、有序字典(orderedDict )
orderdDict是对字典类型的补充，他记住了字典元素添加的顺序
#!/usr/bin/env python # -*- coding:utf-8 -*- import collections collections.OrderedDict >>> a=collections.OrderedDict() >>> a['k1']='winter1' >>> a['k2']='winter2' >>> a OrderedDict([('k1', 'winter1'), ('k2', 'winter2')]) class OrderedDict(dict): 'Dictionary that remembers insertion order' # An inherited dict maps keys to values. # The inherited dict provides __getitem__, __len__, __contains__, and get. # The remaining methods are order-aware. # Big-O running times for all methods are the same as regular dictionaries. # The internal self.__map dict maps keys to links in a doubly linked list. # The circular doubly linked list starts and ends with a sentinel element. # The sentinel element never gets deleted (this simplifies the algorithm). # The sentinel is in self.__hardroot with a weakref proxy in self.__root. # The prev links are weakref proxies (to prevent circular references). # Individual links are kept alive by the hard reference in self.__map. # Those hard references disappear when a key is deleted from an OrderedDict. def __init__(*args, **kwds): '''Initialize an ordered dictionary. The signature is the same as regular dictionaries, but keyword arguments are not recommended because their insertion order is arbitrary. ''' if not args: raise TypeError("descriptor '__init__' of 'OrderedDict' object " "needs an argument") self, *args = args if len(args) > 1: raise TypeError('expected at most 1 arguments, got %d' % len(args)) try: self.__root except AttributeError: self.__hardroot = _Link() self.__root = root = _proxy(self.__hardroot) root.prev = root.next = root self.__map = {} self.__update(*args, **kwds) def __setitem__(self, key, value, dict_setitem=dict.__setitem__, proxy=_proxy, Link=_Link): 'od.__setitem__(i, y) <==> od[i]=y' # Setting a new item creates a new link at the end of the linked list, # and the inherited dictionary is updated with the new key/value pair. if key not in self: self.__map[key] = link = Link() root = self.__root last = root.prev link.prev, link.next, link.key = last, root, key last.next = link root.prev = proxy(link) dict_setitem(self, key, value) def __delitem__(self, key, dict_delitem=dict.__delitem__): 'od.__delitem__(y) <==> del od[y]' # Deleting an existing item uses self.__map to find the link which gets # removed by updating the links in the predecessor and successor nodes. dict_delitem(self, key) link = self.__map.pop(key) link_prev = link.prev link_next = link.next link_prev.next = link_next link_next.prev = link_prev link.prev = None link.next = None def __iter__(self): 'od.__iter__() <==> iter(od)' # Traverse the linked list in order. root = self.__root curr = root.next while curr is not root: yield curr.key curr = curr.next def __reversed__(self): 'od.__reversed__() <==> reversed(od)' # Traverse the linked list in reverse order. root = self.__root curr = root.prev while curr is not root: yield curr.key curr = curr.prev def clear(self): 'od.clear() -> None. Remove all items from od.' root = self.__root root.prev = root.next = root self.__map.clear() dict.clear(self) def popitem(self, last=True): '''od.popitem() -> (k, v), return and remove a (key, value) pair. Pairs are returned in LIFO order if last is true or FIFO order if false. 从最后一个开始取。 ''' if not self: raise KeyError('dictionary is empty') root = self.__root if last: link = root.prev link_prev = link.prev link_prev.next = root root.prev = link_prev else: link = root.next link_next = link.next root.next = link_next link_next.prev = root key = link.key del self.__map[key] value = dict.pop(self, key) return key, value def move_to_end(self, key, last=True): '''Move an existing element to the end (or beginning if last==False). Raises KeyError if the element does not exist. When last=True, acts like a fast version of self[key]=self.pop(key). >>> a.move_to_end('k1') >>> a OrderedDict([('k2', 'winter2'), ('k3', 'winter3'), ('k1', 'winter1')]) >>> ''' link = self.__map[key] link_prev = link.prev link_next = link.next link_prev.next = link_next link_next.prev = link_prev root = self.__root if last: last = root.prev link.prev = last link.next = root last.next = root.prev = link else: first = root.next link.prev = root link.next = first root.next = first.prev = link def __sizeof__(self): sizeof = _sys.getsizeof n = len(self) + 1 # number of links including root size = sizeof(self.__dict__) # instance dictionary size += sizeof(self.__map) * 2 # internal dict and inherited dict size += sizeof(self.__hardroot) * n # link objects size += sizeof(self.__root) * n # proxy objects return size update = __update = MutableMapping.update def keys(self): "D.keys() -> a set-like object providing a view on D's keys" return _OrderedDictKeysView(self) def items(self): "D.items() -> a set-like object providing a view on D's items" return _OrderedDictItemsView(self) def values(self): "D.values() -> an object providing a view on D's values" return _OrderedDictValuesView(self) __ne__ = MutableMapping.__ne__ __marker = object() def pop(self, key, default=__marker): '''od.pop(k[,d]) -> v, remove specified key and return the corresponding value. If key is not found, d is returned if given, otherwise KeyError is raised. ''' if key in self: result = self[key] del self[key] return result if default is self.__marker: raise KeyError(key) return default def setdefault(self, key, default=None): 'od.setdefault(k[,d]) -> od.get(k,d), also set od[k]=d if k not in od' # a['k4']=None # a.setdefault('k4') if key in self: return self[key] self[key] = default return default @_recursive_repr() def __repr__(self): 'od.__repr__() <==> repr(od)' if not self: return '%s()' % (self.__class__.__name__,) return '%s(%r)' % (self.__class__.__name__, list(self.items())) def __reduce__(self): 'Return state information for pickling' inst_dict = vars(self).copy() for k in vars(OrderedDict()): inst_dict.pop(k, None) return self.__class__, (), inst_dict or None, None, iter(self.items()) def copy(self): 'od.copy() -> a shallow copy of od' return self.__class__(self) @classmethod def fromkeys(cls, iterable, value=None): '''OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S. If not specified, the value defaults to None. ''' self = cls() for key in iterable: self[key] = value return self def __eq__(self, other): '''od.__eq__(y) <==> od==y. Comparison to another OD is order-sensitive while comparison to a regular mapping is order-insensitive. ''' if isinstance(other, OrderedDict): return dict.__eq__(self, other) and all(map(_eq, self, other)) return dict.__eq__(self, other)
3、默认字典(defaultdict)
defaultdict是对字典的类型的补充，他默认给字典的值设置了一个类型。
from collections import defaultdict values = [11, 22, 33,44,55,66,77,88,99,90] my_dict = defaultdict(list) #创建 for value in values: if value>66: my_dict['k1'].append(value) #不管原来有没有k1都可以添加上去。 else: my_dict['k2'].append(value) defaultdict字典解决方法
#!/usr/bin/env python # -*- coding:utf-8 -*- import collections collections.defaultdict class defaultdict(dict): """ defaultdict(default_factory[, ...]) --> dict with default factory The default factory is called without arguments to produce a new value when a key is not present, in __getitem__ only. A defaultdict compares equal to a dict with the same items. All remaining arguments are treated the same as if they were passed to the dict constructor, including keyword arguments. """ def copy(self): # real signature unknown; restored from __doc__ """ D.copy() -> a shallow copy of D. """ pass def __copy__(self, *args, **kwargs): # real signature unknown """ D.copy() -> a shallow copy of D. """ pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __init__(self, default_factory=None, **kwargs): # known case of _collections.defaultdict.__init__ """ defaultdict(default_factory[, ...]) --> dict with default factory The default factory is called without arguments to produce a new value when a key is not present, in __getitem__ only. A defaultdict compares equal to a dict with the same items. All remaining arguments are treated the same as if they were passed to the dict constructor, including keyword arguments. # (copied from class doc) """ pass def __missing__(self, key): # real signature unknown; restored from __doc__ """ __missing__(key) # Called by __getitem__ for missing key; pseudo-code: if self.default_factory is None: raise KeyError((key,)) self[key] = value = self.default_factory() return value """ pass def __reduce__(self, *args, **kwargs): # real signature unknown """ Return state information for pickling. """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass default_factory = property(lambda self: object(), lambda self, v: None, lambda self: None) # default """Factory for default value called by __missing__()."""
4、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。
#!/usr/bin/env python # -*- coding:utf-8 -*- import collections collections.namedtuple() #与其他的不同，他需要自己创建对应的类 nt=collections.namedtuple('winter',['x','y','z']) #创建易格类 winterxyz=nt(11,22,33) print(winterxyz.x) print(winterxyz.y) print(winterxyz.z) >>> winterxyz=nt(11,22,33) >>> winterxyz.x 11 >>> winterxyz.y 22 >>> winterxyz.z 33 def namedtuple(typename, field_names, verbose=False, rename=False): """Returns a new subclass of tuple with named fields. >>> Point = namedtuple('Point', ['x', 'y']) >>> Point.__doc__ # docstring for the new class 'Point(x, y)' >>> p = Point(11, y=22) # instantiate with positional args or keywords >>> p[0] + p[1] # indexable like a plain tuple 33 >>> x, y = p # unpack like a regular tuple >>> x, y (11, 22) >>> p.x + p.y # fields also accessable by name 33 >>> d = p._asdict() # convert to a dictionary >>> d['x'] 11 >>> Point(**d) # convert from a dictionary Point(x=11, y=22) >>> p._replace(x=100) # _replace() is like str.replace() but targets named fields Point(x=100, y=22) """ # Validate the field names. At the user's option, either generate an error # message or automatically replace the field name with a valid name. if isinstance(field_names, str): field_names = field_names.replace(',', ' ').split() field_names = list(map(str, field_names)) typename = str(typename) if rename: seen = set() for index, name in enumerate(field_names): if (not name.isidentifier() or _iskeyword(name) or name.startswith('_') or name in seen): field_names[index] = '_%d' % index seen.add(name) for name in [typename] + field_names: if type(name) != str: raise TypeError('Type names and field names must be strings') if not name.isidentifier(): raise ValueError('Type names and field names must be valid ' 'identifiers: %r' % name) if _iskeyword(name): raise ValueError('Type names and field names cannot be a ' 'keyword: %r' % name) seen = set() for name in field_names: if name.startswith('_') and not rename: raise ValueError('Field names cannot start with an underscore: ' '%r' % name) if name in seen: raise ValueError('Encountered duplicate field name: %r' % name) seen.add(name) # Fill-in the class template class_definition = _class_template.format( typename = typename, field_names = tuple(field_names), num_fields = len(field_names), arg_list = repr(tuple(field_names)).replace("'", "")[1:-1], repr_fmt = ', '.join(_repr_template.format(name=name) for name in field_names), field_defs = '\n'.join(_field_template.format(index=index, name=name) for index, name in enumerate(field_names)) ) # Execute the template string in a temporary namespace and support # tracing utilities by setting a value for frame.f_globals['__name__'] namespace = dict(__name__='namedtuple_%s' % typename) exec(class_definition, namespace) result = namespace[typename] result._source = class_definition if verbose: print(result._source) # For pickling to work, the __module__ variable needs to be set to the frame # where the named tuple is created. Bypass this step in environments where # sys._getframe is not defined (Jython for example) or sys._getframe is not # defined for arguments greater than 0 (IronPython). try: result.__module__ = _sys._getframe(1).f_globals.get('__name__', '__main__') except (AttributeError, ValueError): pass return result
5、双向队列(deque)
一个线程安全的双向队列
#!/usr/bin/env python # -*- coding:utf-8 -*- import collections collections.deque d=collections.deque() class deque(object): """ deque([iterable[, maxlen]]) --> deque object A list-like sequence optimized for data accesses near its endpoints. """ def append(self, *args, **kwargs): # real signature unknown """ Add an element to the right side of the deque. >>> d=collections.deque() >>> d deque([]) >>> d.append('winter') >>> d.append('winter') >>> d.append('winter') >>> d deque(['winter', 'winter', 'winter']) """ pass def appendleft(self, *args, **kwargs): # real signature unknown """ Add an element to the left side of the deque. >>> d.appendleft('winter2') >>> d deque(['winter2', 'winter', 'winter', 'winter']) """ pass def clear(self, *args, **kwargs): # real signature unknown """ Remove all elements from the deque. """ pass def copy(self, *args, **kwargs): # real signature unknown """ Return a shallow copy of a deque. """ pass def count(self, value): # real signature unknown; restored from __doc__ """ D.count(value) -> integer -- return number of occurrences of value >>> d.count('winter') 3 """ return 0 def extend(self, *args, **kwargs): # real signature unknown """ Extend the right side of the deque with elements from the iterable 多个元素添加 >>> d.extend([11,22,33]) >>> d deque(['winter2', 'winter', 'winter', 'winter', 11, 22, 33]) >>> d.extend({'k1':'winter1','k2':'winter2'}) >>> d deque(['winter2', 'winter', 'winter', 'winter', 11, 22, 33, 'k2', 'k1']) """ pass def extendleft(self, *args, **kwargs): # real signature unknown """ Extend the left side of the deque with elements from the iterable """ pass def index(self, value, start=None, stop=None): # real signature unknown; restored from __doc__ """ D.index(value, [start, [stop]]) -> integer -- return first index of value. Raises ValueError if the value is not present. >>> d.index('winter') 1 """ return 0 def insert(self, index, p_object): # real signature unknown; restored from __doc__ """ D.insert(index, object) -- insert object before index """ 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. >>> d deque(['winter2', 'winter', 'winter', 'winter', 11, 22, 33, 'k2', 'k1']) >>> d.rotate() >>> d deque(['k1', 'winter2', 'winter', 'winter', 'winter', 11, 22, 33, 'k2']) >>> d.rotate(5) >>> d deque(['winter', 11, 22, 33, 'k2', 'k1', 'winter2', 'winter', 'winter']) """ pass def __add__(self, *args, **kwargs): # real signature unknown """ Return self+value. """ pass def __bool__(self, *args, **kwargs): # real signature unknown """ self != 0 """ pass def __contains__(self, *args, **kwargs): # real signature unknown """ Return key in self. """ pass def __copy__(self, *args, **kwargs): # real signature unknown """ Return a shallow copy of a deque. """ pass def __delitem__(self, *args, **kwargs): # real signature unknown """ Delete self[key]. """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __getitem__(self, *args, **kwargs): # real signature unknown """ Return self[key]. """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __iadd__(self, *args, **kwargs): # real signature unknown """ Implement self+=value. """ pass def __imul__(self, *args, **kwargs): # real signature unknown """ Implement self*=value. """ pass def __init__(self, iterable=(), maxlen=None): # known case of _collections.deque.__init__ """ deque([iterable[, maxlen]]) --> deque object A list-like sequence optimized for data accesses near its endpoints. # (copied from class doc) """ pass def __iter__(self, *args, **kwargs): # real signature unknown """ Implement iter(self). """ pass def __len__(self, *args, **kwargs): # real signature unknown """ Return len(self). """ pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass def __mul__(self, *args, **kwargs): # real signature unknown """ Return self*value.n """ 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 __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown """ Return state information for pickling. """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __reversed__(self): # real signature unknown; restored from __doc__ """ D.__reversed__() -- return a reverse iterator over the deque """ pass def __rmul__(self, *args, **kwargs): # real signature unknown """ Return self*value. """ pass def __setitem__(self, *args, **kwargs): # real signature unknown """ Set self[key] to value. """ 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
注：既然有双向队列，也有单项队列（先进先出 FIFO ）
#!/usr/bin/env python # -*- coding:utf-8 -*- import queue queue.Queue >>> import queue >>> q=queue.Queue() >>> q.put(1) #放入数据，数据只能先进先出，单向队列 >>> q.put(11) >>> q.put(111) >>> q.qsize() 3 >>> print (q.get()) #取数据，先取先进入队列的。 1 >>> print (q.get()) 11 >>> print (q.get()) 111 >>> q.qsize() 0 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. ''' with self.all_tasks_done: 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 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. ''' with self.all_tasks_done: while self.unfinished_tasks: self.all_tasks_done.wait() def qsize(self): '''Return the approximate size of the queue (not reliable!).''' with self.mutex: return self._qsize() def empty(self): '''Return True if the queue is empty, False otherwise (not reliable!). This method is likely to be removed at some point. Use qsize() == 0 as a direct substitute, but be aware that either approach risks a race condition where a queue can grow before the result of empty() or qsize() can be used. To create code that needs to wait for all queued tasks to be completed, the preferred technique is to use the join() method. ''' with self.mutex: return not self._qsize() def full(self): '''Return True if the queue is full, False otherwise (not reliable!). This method is likely to be removed at some point. Use qsize() >= n as a direct substitute, but be aware that either approach risks a race condition where a queue can shrink before the result of full() or qsize() can be used. ''' with self.mutex: return 0 < self.maxsize <= self._qsize() 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). 放入数据。 get是取出数据 ''' with self.not_full: 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() 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). 取数据 ''' with self.not_empty: 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 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, block=False) 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(block=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): 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()
深浅拷贝
一、数字和字符串
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)
二、其他基本数据类型
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。
1、赋值
赋值，只是创建一个变量，该变量指向原来内存地址，如：
n2=n1
2、浅拷贝
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) >>> id(n1) 53984264 >>> id(n3) 53998920 >>> id(n1['k1']) 53963776 >>> id(n3['k1']) 53963776 >>>
3、深拷贝
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) >>> n4 = copy.deepcopy(n1) >>> id(n4) 53998728 >>> id(n1) 53984264 >>> id(n3) 53998920 >>> id(n1['k1']) 53963776 >>> id(n3['k1']) 53963776 >>> id(n4['k1']) 53963776 >>> id(n3['k3']) 53998216 >>> id(n1['k3']) 53998216 >>> id(n4['k3']) 53998472
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：
- 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 ... 返回值
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。
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。
以上要点中，比较重要有参数和返回值：
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？
更加方便，重用性更高。
函数的有三中不同的参数：
- 普通参数
- 默认参数
- 动态参数
1、普通参数 # ######### 定义函数 ######### # name 叫做函数func的形式参数，简称：形参 def func(name): print name # ######### 执行函数 ######### # 'winter' 叫做函数func的实际参数，简称：实参 func('winter') # ######### 默认参数 ######### def func(name=‘winter’): print name # ######### 执行函数 ######### # 'winter' 为默认参数 func() #没有输入参数的时候，按默认参数执行 func('eric') #有输入参数的时候，按输入参数执行。 #### 多个参数的时候，有默认参数的形参一定要在最后 def func(name, age = 18): print "%s:%s" %(name,age) # 指定参数 func('winter', 19) # 使用默认参数 func('eric') 注：默认参数需要放在参数列表最后 #----------动态参数---------------- #有2种，*arg 标识列表。 **kwargs 表示字典 def func(*args, **kwargs): print args print kwargs def func(*args): print args # 执行方式一 func(11,33,4,4454,5) # 执行方式二 li = [11,2,2,3,3,4,54] func(*li) def func(**kwargs): print args # 执行方式一 func(name＝'wupeiqi',age=18) # 执行方式二 li = {'name':'wupeiqi', age:18, 'gender':'male'} func(**li) #当易格def有多个参数的，输入的实参带上* 表示特定的输入。
#!/usr/bin/env python # -*- coding:utf-8 -*- import smtplib from email.mime.text import MIMEText from email.utils import formataddr def mail(user): ret=True try: msg=MIMEText('邮件内容','plain','utf-8') msg["From"]=formataddr(['winter','hostspaces@sina.cn']) msg["To"]=formataddr(['winter2','winter@ik.com']) msg["Subject"]='主题' server=smtplib.SMTP('smtp.sina.cn',25) server.login('hostspaces@sina.cn','open.xunyun') server.sendmail('hostspaces@sina.cn',[user,],msg.as_string()) server.quit() except Exception: ret=False return ret ret=mail('winter@ik.com') if ret: print('发送成功') else: print('发送失败') ret2=mail('winter@hostspaces.net') if ret2: print('发送成功') else: print('发送失败')
内置函数
all()判断所有的元素内是否全部为Ture。
any()只有有一个元素为Ture 则返回Ture。
ascii() 实际上就是执行对应对象的class里面的__repr__ 的结果。
验证方法
class winter: #创建一个类 def __repr__(self): #在类里面定义一个__repr__的函数 return "what you can see" #这个函数什么都不做，只返回一个文本 f=winter() #建议个class winter的对象 a=ascii(f) #对这个对象执行ascii print(a) #打印结果 C:\Python\Python35\python.exe D:/winter_py/practice/winshen_python/day3/004_test.py what you can see Process finished with exit code 0 查看的结果为函数的返回值。
chr 将数字转为ascii吗 ord 将ascci 码转为数字 再做验证码的时候可以使用，用随机数转为ascci，把收到输入，转回数字对比。
complie（）编译使用，把字符串编译为python的代码。
delattr getattr setattr 在发射时候使用。
dir（） 当前变量 vars（） 比 dir更深，变量提供keys 和所在内存位置。
eval（） 把字符串进行技术。 eval('8*8') 64
filter 与 map ：
li=[11,22,33,44] l2=map(lambda i:i*10,li) for i in l2: print(i) 110 220 330 440 def fun(i) return i*10 l2=map(fun,li) #-------filter----------------------------- def func(i): if i>33: return True else: return False l2=filter(func,l1) 44
format() format(7) int.__format__
frozenset()
globals（） 当前所有的全局变量
hash() 用于存储超大的字符串，把超大的字符串转为hash再存储
hex() 16进制
id() 内存位置，不是真实位置，而是python预先调用的内存
round() 四舍五入
zip()
x=[1,2,3] y=[4,5,6] zipped=zip[x,y] list(zipped) [(1,4),(2,5),(3,6)] 把多个数值组合为一个新数值。 爬虫里面常用。
open函数，该函数用于文件处理
操作文件时，一般需要经历如下步骤：
- 打开文件
- 操作文件
一、打开文件
文件句柄 = open('文件路径', '模式')
打开文件时，需要指定文件路径和以何等方式打开文件，打开后，即可获取该文件句柄，日后通过此文件句柄对该文件操作。
打开文件的模式有：
- r ，只读模式【默认】
- w，只写模式【不可读；不存在则创建；存在则清空内容；】
- x， 只写模式【不可读；不存在则创建，存在则报错】
- a， 追加模式【可读； 不存在则创建；存在则只追加内容；】
"+" 表示可以同时读写某个文件
- r+， 读写【可读，可写】
- w+，写读【可读，可写】
- x+ ，写读【可读，可写】
- a+， 写读【可读，可写】
‘U’ 表示在读取时，可以将\r \n \r\n 自动转换为\n (与 r或 r+ 模式相同）
- rU
- r+U
"b"表示以字节的方式操作
- rb 或 r+b
- wb 或 w+b
- xb 或 w+b
- ab 或 a+b
注：以b方式打开时，读取到的内容是字节类型，写入时也需要提供字节类型
二、操作
#!/usr/bin/env python # -*- coding:utf-8 -*- f=open('test.log','r',encoding='utf-8') class TextIOWrapper(_TextIOBase) 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 关闭文件 pass def fileno(self, *args, **kwargs): # real signature unknown 文件描述符 pass def flush(self, *args, **kwargs): # real signature unknown 刷新文件内部缓冲区 pass def isatty(self, *args, **kwargs): # real signature unknown 判断文件是否是同意tty设备 pass def read(self, *args, **kwargs): # real signature unknown 读取指定字节数据 f.read(3) #读3个字符 python3 里面的数值为字符 python2里面的为字节 read为以当前指针位置读取后面的所有的数据 pass def readable(self, *args, **kwargs): # real signature unknown 是否可读 pass def readline(self, *args, **kwargs): # real signature unknown 仅读取一行数据 读完后把指针移动到下一行 pass def seek(self, *args, **kwargs): # real signature unknown 指定文件中指针位置 重要 pass def seekable(self, *args, **kwargs): # real signature unknown 指针是否可操作 pass def tell(self, *args, **kwargs): # real signature unknown 获取指针位置 重要 pass def truncate(self, *args, **kwargs): # real signature unknown 截断数据，仅保留指定之前数据 从指针位置开始截断数据，只取指针前面的数据 pass def writable(self, *args, **kwargs): # real signature unknown 是否可写 pass def write(self, *args, **kwargs): # real signature unknown 写内容 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
为了避免打开文件后忘记关闭，可以通过管理上下文，即：
with open('log','r') as f: ...
如此方式，当with代码块执行完毕时，内部会自动关闭并释放文件资源。
在Python 2.7 及以后，with又支持同时对多个文件的上下文进行管理，即：
with open('log1') as obj1, open('log2') as obj2: pass
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