1 介紹

　　從我開始學(xué)習(xí)Python時我就決定維護一個經(jīng)常使用的“竅門”列表。不論何時當我看到一段讓我覺得“酷，這樣也行！”的代碼時（在一個例子中、在StackOverflow、在開源碼軟件中，等等），我會嘗試它直到理解它，然后把它添加到列表中。這篇文章是清理過列表的一部分。如果你是一個有經(jīng)驗的Python程序員，盡管你可能已經(jīng)知道一些，但你仍能發(fā)現(xiàn)一些你不知道的。如果你是一個正在學(xué)習(xí)Python的C、C++或java程序員，或者剛開始學(xué)習(xí)編程，那么你會像我一樣發(fā)現(xiàn)它們中的很多非常有用。

　　每個竅門或語言特性只能通過實例來驗證，無需過多解釋。雖然我已盡力使例子清晰，但它們中的一些仍會看起來有些復(fù)雜，這取決于你的熟悉程度。所以如果看過例子后還不清楚的話，標題能夠提供足夠的信息讓你通過Google獲取詳細的內(nèi)容。

　　列表按難度排序，常用的語言特征和技巧放在前面。

　　1.1   分拆

>>> a, b, c = 1, 2, 3>>> a, b, c(1, 2, 3)>>> a, b, c = [1, 2, 3]>>> a, b, c(1, 2, 3)>>> a, b, c = (2 * i + 1 for i in range(3))>>> a, b, c(1, 3, 5)>>> a, (b, c), d = [1, (2, 3), 4]>>> a1>>> b2>>> c3>>> d4

　　1.2   交換變量分拆

>>> a, b = 1, 2>>> a, b = b, a>>> a, b(2, 1)

　　1.3   拓展分拆 (Python 3下適用)

>>> a, *b, c = [1, 2, 3, 4, 5]>>> a1>>> b[2, 3, 4]>>> c5

　　1.4   負索引

>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]>>> a[-1]10>>> a[-3]8

　　1.5   列表切片 (a[start:end])

>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]>>> a[2:8][2, 3, 4, 5, 6, 7]

　　1.6   使用負索引的列表切片

>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]>>> a[-4:-2][7, 8]

　　1.7   帶步進值的列表切片 (a[start:end:step])

>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]>>> a[::2][0, 2, 4, 6, 8, 10]>>> a[::3][0, 3, 6, 9]>>> a[2:8:2][2, 4, 6]

　　1.8   負步進值得列表切片

>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]>>> a[::-1][10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]>>> a[::-2][10, 8, 6, 4, 2, 0]

　　1.9   列表切片賦值

>>> a = [1, 2, 3, 4, 5]>>> a[2:3] = [0, 0]>>> a[1, 2, 0, 0, 4, 5]>>> a[1:1] = [8, 9]>>> a[1, 8, 9, 2, 0, 0, 4, 5]>>> a[1:-1] = []>>> a[1, 5]

　　1.10   命名切片 (slice(start, end, step))

>>> a = [0, 1, 2, 3, 4, 5]>>> LASTTHREE = slice(-3, None)>>> LASTTHREEslice(-3, None, None)>>> a[LASTTHREE][3, 4, 5]

　　1.11   zip打包解包列表和倍數(shù)

>>> a = [1, 2, 3]>>> b = ['a', 'b', 'c']>>> z = zip(a, b)>>> z[(1, 'a'), (2, 'b'), (3, 'c')]>>> zip(*z)[(1, 2, 3), ('a', 'b', 'c')]

　　1.12   使用zip合并相鄰的列表項

>>> a = [1, 2, 3, 4, 5, 6]>>> zip(*([iter(a)] * 2))[(1, 2), (3, 4), (5, 6)]>>> group_adjacent = lambda a, k: zip(*([iter(a)] * k))>>> group_adjacent(a, 3)[(1, 2, 3), (4, 5, 6)]>>> group_adjacent(a, 2)[(1, 2), (3, 4), (5, 6)]>>> group_adjacent(a, 1)[(1,), (2,), (3,), (4,), (5,), (6,)]>>> zip(a[::2], a[1::2])[(1, 2), (3, 4), (5, 6)]>>> zip(a[::3], a[1::3], a[2::3])[(1, 2, 3), (4, 5, 6)]>>> group_adjacent = lambda a, k: zip(*(a[i::k] for i in range(k)))>>> group_adjacent(a, 3)[(1, 2, 3), (4, 5, 6)]>>> group_adjacent(a, 2)[(1, 2), (3, 4), (5, 6)]>>> group_adjacent(a, 1)[(1,), (2,), (3,), (4,), (5,), (6,)]

　　1.13  使用zip和iterators生成滑動窗口 (n -grams) 

>>> from itertools import islice>>> def n_grams(a, n):...     z = (islice(a, i, None) for i in range(n))...     return zip(*z)...>>> a = [1, 2, 3, 4, 5, 6]>>> n_grams(a, 3)[(1, 2, 3), (2, 3, 4), (3, 4, 5), (4, 5, 6)]>>> n_grams(a, 2)[(1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]>>> n_grams(a, 4)[(1, 2, 3, 4), (2, 3, 4, 5), (3, 4, 5, 6)]

　　1.14   使用zip反轉(zhuǎn)字典

>>> m = {'a': 1, 'b': 2, 'c': 3, 'd': 4}>>> m.items()[('a', 1), ('c', 3), ('b', 2), ('d', 4)]>>> zip(m.values(), m.keys())[(1, 'a'), (3, 'c'), (2, 'b'), (4, 'd')]>>> mi = dict(zip(m.values(), m.keys()))>>> mi{1: 'a', 2: 'b', 3: 'c', 4: 'd'}

　　1.15   攤平列表:

>>> a = [[1, 2], [3, 4], [5, 6]]>>> list(itertools.chain.from_iterable(a))[1, 2, 3, 4, 5, 6]>>> sum(a, [])[1, 2, 3, 4, 5, 6]>>> [x for l in a for x in l][1, 2, 3, 4, 5, 6]>>> a = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]>>> [x for l1 in a for l2 in l1 for x in l2][1, 2, 3, 4, 5, 6, 7, 8]>>> a = [1, 2, [3, 4], [[5, 6], [7, 8]]]>>> flatten = lambda x: [y for l in x for y in flatten(l)] if type(x) is list else [x]>>> flatten(a)[1, 2, 3, 4, 5, 6, 7, 8]注意: 根據(jù)Python的文檔，itertools.chain.from_iterable是首選。

　　1.16   生成器表達式

>>> g = (x ** 2 for x in xrange(10))>>> next(g)0>>> next(g)1>>> next(g)4>>> next(g)9>>> sum(x ** 3 for x in xrange(10))2025>>> sum(x ** 3 for x in xrange(10) if x % 3 == 1)408

　　1.17   迭代字典

>>> m = {x: x ** 2 for x in range(5)}>>> m{0: 0, 1: 1, 2: 4, 3: 9, 4: 16}>>> m = {x: 'A' + str(x) for x in range(10)}>>> m{0: 'A0', 1: 'A1', 2: 'A2', 3: 'A3', 4: 'A4', 5: 'A5', 6: 'A6', 7: 'A7', 8: 'A8', 9: 'A9'}

　　1.18   通過迭代字典反轉(zhuǎn)字典

>>> m = {'a': 1, 'b': 2, 'c': 3, 'd': 4}>>> m{'d': 4, 'a': 1, 'b': 2, 'c': 3}>>> {v: k for k, v in m.items()}{1: 'a', 2: 'b', 3: 'c', 4: 'd'}

　　1.19   命名序列 (collections.namedtuple)

>>> Point = collections.namedtuple('Point', ['x', 'y'])>>> p = Point(x=1.0, y=2.0)>>> pPoint(x=1.0, y=2.0)>>> p.x1.0>>> p.y2.0

　　1.20   命名列表的繼承:

>>> class Point(collections.namedtuple('PointBase', ['x', 'y'])):...     __slots__ = ()...     def __add__(self, other):...             return Point(x=self.x + other.x, y=self.y + other.y)...>>> p = Point(x=1.0, y=2.0)>>> q = Point(x=2.0, y=3.0)>>> p + qPoint(x=3.0, y=5.0)

　　1.21   集合及集合操作

>>> A = {1, 2, 3, 3}>>> Aset([1, 2, 3])>>> B = {3, 4, 5, 6, 7}>>> Bset([3, 4, 5, 6, 7])>>> A | Bset([1, 2, 3, 4, 5, 6, 7])>>> A & Bset([3])>>> A - Bset([1, 2])>>> B - Aset([4, 5, 6, 7])>>> A ^ Bset([1, 2, 4, 5, 6, 7])>>> (A ^ B) == ((A - B) | (B - A))True

　　1.22   多重集及其操作 (collections.Counter)

>>> A = collections.Counter([1, 2, 2])>>> B = collections.Counter([2, 2, 3])>>> ACounter({2: 2, 1: 1})>>> BCounter({2: 2, 3: 1})>>> A | BCounter({2: 2, 1: 1, 3: 1})>>> A & BCounter({2: 2})>>> A + BCounter({2: 4, 1: 1, 3: 1})>>> A - BCounter({1: 1})>>> B - ACounter({3: 1})

　　1.23   迭代中最常見的元素 (collections.Counter)

>>> A = collections.Counter([1, 1, 2, 2, 3, 3, 3, 3, 4, 5, 6, 7])>>> ACounter({3: 4, 1: 2, 2: 2, 4: 1, 5: 1, 6: 1, 7: 1})>>> A.most_common(1)[(3, 4)]>>> A.most_common(3)[(3, 4), (1, 2), (2, 2)]

　　1.24   雙端隊列 (collections.deque)

>>> Q = collections.deque()>>> Q.append(1)>>> Q.appendleft(2)>>> Q.extend([3, 4])>>> Q.extendleft([5, 6])>>> Qdeque([6, 5, 2, 1, 3, 4])>>> Q.pop()4>>> Q.popleft()6>>> Qdeque([5, 2, 1, 3])>>> Q.rotate(3)>>> Qdeque([2, 1, 3, 5])>>> Q.rotate(-3)>>> Qdeque([5, 2, 1, 3])

　　1.25   有最大長度的雙端隊列 (collections.deque)

>>> last_three = collections.deque(maxlen=3)>>> for i in xrange(10):...     last_three.append(i)...     
　　1.26   字典排序 (collections.OrderedDict)
>>> m = dict((str(x), x) for x in range(10))>>> print ', '.join(m.keys())1, 0, 3, 2, 5, 4, 7, 6, 9, 8>>> m = collections.OrderedDict((str(x), x) for x in range(10))>>> print ', '.join(m.keys())0, 1, 2, 3, 4, 5, 6, 7, 8, 9>>> m = collections.OrderedDict((str(x), x) for x in range(10, 0, -1))>>> print ', '.join(m.keys())10, 9, 8, 7, 6, 5, 4, 3, 2, 1
　　1.27   缺省字典 (collections.defaultdict)
>>> m = dict()>>> m['a']Traceback (most recent call last):  File "<stdin>", line 1, in <module>KeyError: 'a'>>>>>> m = collections.defaultdict(int)>>> m['a']0>>> m['b']0>>> m = collections.defaultdict(str)>>> m['a']''>>> m['b'] += 'a'>>> m['b']'a'>>> m = collections.defaultdict(lambda: '[default value]')>>> m['a']'[default value]'>>> m['b']'[default value]'
　　1.28   用缺省字典表示簡單的樹
>>> import json>>> tree = lambda: collections.defaultdict(tree)>>> root = tree()>>> root['menu']['id'] = 'file'>>> root['menu']['value'] = 'File'>>> root['menu']['menuitems']['new']['value'] = 'New'>>> root['menu']['menuitems']['new']['onclick'] = 'new();'>>> root['menu']['menuitems']['open']['value'] = 'Open'>>> root['menu']['menuitems']['open']['onclick'] = 'open();'>>> root['menu']['menuitems']['close']['value'] = 'Close'>>> root['menu']['menuitems']['close']['onclick'] = 'close();'>>> print json.dumps(root, sort_keys=True, indent=4, separators=(',', ': ')){    "menu": {        "id": "file",        "menuitems": {            "close": {                "onclick": "close();",                "value": "Close"            },            "new": {                "onclick": "new();",                "value": "New"            },            "open": {                "onclick": "open();",                "value": "Open"            }        },        "value": "File"    }}(到https://gist.github.com/hrldcpr/2012250查看詳情)
　　1.29   映射對象到唯一的序列數(shù) (collections.defaultdict)
>>> import itertools, collections>>> value_to_numeric_map = collections.defaultdict(itertools.count().next)>>> value_to_numeric_map['a']0>>> value_to_numeric_map['b']1>>> value_to_numeric_map['c']2>>> value_to_numeric_map['a']0>>> value_to_numeric_map['b']1
　　1.30   最大最小元素 (heapq.nlargest和heapq.nsmallest)
>>> a = [random.randint(0, 100) for __ in xrange(100)]>>> heapq.nsmallest(5, a)[3, 3, 5, 6, 8]>>> heapq.nlargest(5, a)[100, 100, 99, 98, 98]
　　1.31   笛卡爾乘積 (itertools.product)
>>> for p in itertools.product([1, 2, 3], [4, 5]):(1, 4)(1, 5)(2, 4)(2, 5)(3, 4)(3, 5)>>> for p in itertools.product([0, 1], repeat=4):...     print ''.join(str(x) for x in p)...0000000100100011010001010110011110001001101010111100110111101111
　　1.32   組合的組合和置換 (itertools.combinations 和 itertools.combinations_with_replacement)
>>> for c in itertools.combinations([1, 2, 3, 4, 5], 3):...     print ''.join(str(x) for x in c)...123124125134135145234235245345>>> for c in itertools.combinations_with_replacement([1, 2, 3], 2):...     print ''.join(str(x) for x in c)...111213222333
　　1.33   排序 (itertools.permutations)
>>> for p in itertools.permutations([1, 2, 3, 4]):...     print ''.join(str(x) for x in p)...123412431324134214231432213421432314234124132431312431423214324134123421412341324213423143124321
　　1.34   鏈接的迭代 (itertools.chain)
>>> a = [1, 2, 3, 4]>>> for p in itertools.chain(itertools.combinations(a, 2), itertools.combinations(a, 3)):...     print p...(1, 2)(1, 3)(1, 4)(2, 3)(2, 4)(3, 4)(1, 2, 3)(1, 2, 4)(1, 3, 4)(2, 3, 4)>>> for subset in itertools.chain.from_iterable(itertools.combinations(a, n) for n in range(len(a) + 1))...     print subset...()(1,)(2,)(3,)(4,)(1, 2)(1, 3)(1, 4)(2, 3)(2, 4)(3, 4)(1, 2, 3)(1, 2, 4)(1, 3, 4)(2, 3, 4)(1, 2, 3, 4)
　　1.35   按給定值分組行 (itertools.groupby)
>>> from Operator import itemgetter>>> import itertools>>> with open('contactlenses.csv', 'r') as infile:...     data = [line.strip().split(',') for line in infile]...>>> data = data[1:]>>> def print_data(rows):...     print '/n'.join('/t'.join('{: <16}'.format(s) for s in row) for row in rows)...>>> print_data(data)young               myope                   no                      reduced                 noneyoung               myope                   no                      normal                  softyoung               myope                   yes                     reduced                 noneyoung               myope                   yes                     normal                  hardyoung               hypermetrope            no                      reduced                 noneyoung               hypermetrope            no                      normal                  softyoung               hypermetrope            yes                     reduced                 noneyoung               hypermetrope            yes                     normal                  hardpre-presbyopic      myope                   no                      reduced                 nonepre-presbyopic      myope                   no                      normal                  softpre-presbyopic      myope                   yes                     reduced                 nonepre-presbyopic      myope                   yes                     normal                  hardpre-presbyopic      hypermetrope            no                      reduced                 nonepre-presbyopic      hypermetrope            no                      normal                  softpre-presbyopic      hypermetrope            yes                     reduced                 nonepre-presbyopic      hypermetrope            yes                     normal                  nonepresbyopic          myope                   no                      reduced                 nonepresbyopic          myope                   no                      normal                  nonepresbyopic          myope                   yes                     reduced                 nonepresbyopic          myope                   yes                     normal                  hardpresbyopic          hypermetrope            no                      reduced                 nonepresbyopic          hypermetrope            no                      normal                  softpresbyopic          hypermetrope            yes                     reduced                 nonepresbyopic          hypermetrope            yes                     normal                  none>>> data.sort(key=itemgetter(-1))>>> for value, group in itertools.groupby(data, lambda r: r[-1]):...     print '-----------'...     print 'Group: ' + value...     print_data(group)...-----------Group: hardyoung               myope                   yes                     normal                  hardyoung               hypermetrope            yes                     normal                  hardpre-presbyopic      myope                   yes                     normal                  hardpresbyopic          myope                   yes                     normal                  hard-----------Group: noneyoung               myope                   no                      reduced                 noneyoung               myope                   yes                     reduced                 noneyoung               hypermetrope            no                      reduced                 noneyoung               hypermetrope            yes                     reduced                 nonepre-presbyopic      myope                   no                      reduced                 nonepre-presbyopic      myope                   yes                     reduced                 nonepre-presbyopic      hypermetrope            no                      reduced                 nonepre-presbyopic      hypermetrope            yes                     reduced                 nonepre-presbyopic      hypermetrope            yes                     normal                  nonepresbyopic          myope                   no                      reduced                 nonepresbyopic          myope                   no                      normal                  nonepresbyopic          myope                   yes                     reduced                 nonepresbyopic          hypermetrope            no                      reduced                 nonepresbyopic          hypermetrope            yes                     reduced                 nonepresbyopic          hypermetrope            yes                     normal                  none-----------Group: softyoung               myope                   no                      normal                  softyoung               hypermetrope            no                      normal                  softpre-presbyopic      myope                   no                      normal                  softpre-presbyopic      hypermetrope            no                      normal                  softpresbyopic          hypermetrope            no                      normal                  soft
　　原文地址：http://sahandsaba.com/thirty-python-language-features-and-tricks-you-may-not-know.html