你可能不知道的30个Python语言的特点技巧
1 介绍
从我开始学习Python时我就决定维护一个经常使用的“窍门”列表。不论何时当我看到一段让我觉得“酷,这样也行!”的代码时(在一个例子中、在 StackOverflow、在开源码软件中,等等),我会尝试它直到理解它,然后把它添加到列表中。这篇文章是清理过列表的一部分。如果你是一个有经验的Python程序员,尽管你可能已经知道一些,但你仍能发现一些你不知道的。如果你是一个正在学习Python的C、C++或Java程序员,或者刚开始学习编程,那么你会像我一样发现它们中的很多非常有用。
每个窍门或语言特性只能通过实例来验证,无需过多解释。虽然我已尽力使例子清晰,但它们中的一些仍会看起来有些复杂,这取决于你的熟悉程度。所以如果看过例子后还不清楚的话,标题能够提供足够的信息让你通过Google获取详细的内容。
列表按难度排序,常用的语言特征和技巧放在前面。
1.1 分拆
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 </td> | >>> 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] >>> a 1 >>> b 2 >>> c 3 >>> d 4 | </tr> </tbody> </table> </div> </div>
1 2 3 4 </td> | >>> a, b = 1, 2 >>> a, b = b, a >>> a, b (2, 1) | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 </td> | >>> a, *b, c = [1, 2, 3, 4, 5] >>> a 1 >>> b [2, 3, 4] >>> c 5 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 </td> | >>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] >>> a[-1] 10 >>> a[-3] 8 | </tr> </tbody> </table> </div> </div>
1 2 3 </td> | >>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] >>> a[2:8] [2, 3, 4, 5, 6, 7] | </tr> </tbody> </table> </div> </div>
1 2 3 </td> | >>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] >>> a[-4:-2] [7, 8] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 </td> | >>> 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] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 </td> | >>> 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] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 </td> | >>> 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] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 </td> | >>> a = [0, 1, 2, 3, 4, 5] >>> LASTTHREE = slice(-3, None) >>> LASTTHREE slice(-3, None, None) >>> a[LASTTHREE] [3, 4, 5] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 </td> | >>> 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')] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 </td> | >>> 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,)] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 </td> | >>> 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)] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 </td> | >>> 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'} | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 </td> | >>> 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: 根据Python的文档,itertools.chain.from_iterable是首选。 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 </td> | >>> 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 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 </td> | >>> 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'} | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 </td> | >>> 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'} | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 </td> | >>> Point = collections.namedtuple('Point', ['x', 'y']) >>> p = Point(x=1.0, y=2.0) >>> p Point(x=1.0, y=2.0) >>> p.x 1.0 >>> p.y 2.0 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 </td> | >>> 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 + q Point(x=3.0, y=5.0) | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 </td> | >>> A = {1, 2, 3, 3} >>> A set([1, 2, 3]) >>> B = {3, 4, 5, 6, 7} >>> B set([3, 4, 5, 6, 7]) >>> A | B set([1, 2, 3, 4, 5, 6, 7]) >>> A & B set([3]) >>> A - B set([1, 2]) >>> B - A set([4, 5, 6, 7]) >>> A ^ B set([1, 2, 4, 5, 6, 7]) >>> (A ^ B) == ((A - B) | (B - A)) True | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 </td> | >>> A = collections.Counter([1, 2, 2]) >>> B = collections.Counter([2, 2, 3]) >>> A Counter({2: 2, 1: 1}) >>> B Counter({2: 2, 3: 1}) >>> A | B Counter({2: 2, 1: 1, 3: 1}) >>> A & B Counter({2: 2}) >>> A + B Counter({2: 4, 1: 1, 3: 1}) >>> A - B Counter({1: 1}) >>> B - A Counter({3: 1}) | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 </td> | >>> A = collections.Counter([1, 1, 2, 2, 3, 3, 3, 3, 4, 5, 6, 7]) >>> A Counter({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)] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 </td> | >>> Q = collections.deque() >>> Q.append(1) >>> Q.appendleft(2) >>> Q.extend([3, 4]) >>> Q.extendleft([5, 6]) >>> Q deque([6, 5, 2, 1, 3, 4]) >>> Q.pop() 4 >>> Q.popleft() 6 >>> Q deque([5, 2, 1, 3]) >>> Q.rotate(3) >>> Q deque([2, 1, 3, 5]) >>> Q.rotate(-3) >>> Q deque([5, 2, 1, 3]) | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 </td> | >>> last_three = collections.deque(maxlen=3) >>> for i in xrange(10): ... last_three.append(i) ... print ', '.join(str(x) for x in last_three) ... 0 0, 1 0, 1, 2 1, 2, 3 2, 3, 4 3, 4, 5 4, 5, 6 5, 6, 7 6, 7, 8 7, 8, 9 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 </td> | >>> 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 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 </td> | >>> 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]' | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 </td> | >>> 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查看详情) | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 </td> | >>> 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 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 </td> | >>> 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] | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 </td> | >>> 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) ... 0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 </td> | >>> for c in itertools.combinations([1, 2, 3, 4, 5], 3): ... print ''.join(str(x) for x in c) ... 123 124 125 134 135 145 234 235 245 345 >>> for c in itertools.combinations_with_replacement([1, 2, 3], 2): ... print ''.join(str(x) for x in c) ... 11 12 13 22 23 33 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 </td> | >>> for p in itertools.permutations([1, 2, 3, 4]): ... print ''.join(str(x) for x in p) ... 1234 1243 1324 1342 1423 1432 2134 2143 2314 2341 2413 2431 3124 3142 3214 3241 3412 3421 4123 4132 4213 4231 4312 4321 | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 </td> | >>> 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) | </tr> </tbody> </table> </div> </div>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | >>> 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 none young myope no normal soft young myope yes reduced none young myope yes normal hard young hypermetrope no reduced none young hypermetrope no normal soft young hypermetrope yes reduced none young hypermetrope yes normal hard pre-presbyopic myope no reduced none pre-presbyopic myope no normal soft pre-presbyopic myope yes reduced none pre-presbyopic myope yes normal hard pre-presbyopic hypermetrope no reduced none pre-presbyopic hypermetrope no normal soft pre-presbyopic hypermetrope yes reduced none pre-presbyopic hypermetrope yes normal none presbyopic myope no reduced none presbyopic myope no normal none presbyopic myope yes reduced none presbyopic myope yes normal hard presbyopic hypermetrope no reduced none presbyopic hypermetrope no normal soft presbyopic hypermetrope yes reduced none presbyopic 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: hard young myope yes normal hard young hypermetrope yes normal hard pre-presbyopic myope yes normal hard presbyopic myope yes normal hard ----------- Group: none young myope no reduced none young myope yes reduced none young hypermetrope no reduced none young hypermetrope yes reduced none pre-presbyopic myope no reduced none pre-presbyopic myope yes reduced none pre-presbyopic hypermetrope no reduced none pre-presbyopic hypermetrope yes reduced none pre-presbyopic hypermetrope yes normal none presbyopic myope no reduced none presbyopic myope no normal none presbyopic myope yes reduced none presbyopic hypermetrope no reduced none presbyopic hypermetrope yes reduced none presbyopic hypermetrope yes normal none ----------- Group: soft young myope no normal soft young hypermetrope no normal soft pre-presbyopic myope no normal soft pre-presbyopic hypermetrope no normal soft presbyopic hypermetrope no normal |
来自:http://simpleblog.cn/qxl#article_id=82