从我在麦子学院开始学习python的时候，我就尝试着自己总结一个python小技巧的集合。后来当我什么时候在Stack Overflow或者在某个开源软件里看到一段很酷代码的时候，我就很惊讶：原来还能这么做！当时我会努力的自己尝试一下这段代码，直到我懂了它的整体思路以后，我就把这段代码加到我的集合里。这篇文章其实就是这个集合整理后一部分的公开亮相。如果你已经是个python大牛，那么基本上你应该知道这里面的大多数用法了，但我想你应该也能发现一些你不知道的新技巧。而如果你之前是一个c,c++,java的程序员 ，同时在学习python，或者干脆就是一个刚刚学习编程的新手，那么你应该会看到很多特别有用能让你感到惊奇的实用技巧，就像我当初一样。 每一个技巧和语言用法都会在一个个实例中展示给大家，也不需要有其他的说明。我已经尽力把每个例子弄的通俗易懂，但是因为读者对python的熟悉程度不同，仍然可能难免有一些晦涩的地方。所以如果这些例子本身无法让你读懂，至少这个例子的标题在你后面去google搜索的时候会帮到你。 整个集合大概是按照难易程度排序，简单常见的在前面，比较少见的在最后。 1.1 拆箱 >>> 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 inrange(3)) >>> a, b, c (1, 3, 5) >>> a, (b, c), d = [1, (2, 3), 4] >>> a 1 >>> b 2 >>> c 3 >>> d 4 1.2 拆箱变量交换 >>> a, b = 1, 2 >>> a, b = b, a >>> a, b (2, 1) 1.3 扩展拆箱（只兼容python3） >>> a, *b, c = [1, 2, 3, 4, 5] >>> a 1 >>> b [2, 3, 4] >>> c 5 1.4 负数索引 >>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8,9, 10] >>> a[-1] 10 >>> a[-3] 8 1.5 切割列表 >>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8,9, 10] >>> a[2:8] [2, 3, 4, 5, 6, 7] 1.6 负数索引切割列表 >>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8,9, 10] >>> a[-4:-2] [7, 8] 1.7指定步长切割列表 >>> 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 负数步长切割列表 >>> 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 列表切割赋值 >>> 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 命名列表切割方式 >>> a = [0, 1, 2, 3, 4, 5] >>> LASTTHREE = slice(-3, None) >>> LASTTHREE slice(-3, None, None) >>> a[LASTTHREE] [3, 4, 5] 1.11 列表以及迭代器的压缩和解压缩 >>> 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 列表相邻元素压缩器 >>> 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 在列表中用压缩器和迭代器滑动取值窗口 >>> def n_grams(a, n): ... z = [iter(a[i:])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 用压缩器反转字典 >>> 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 列表展开 >>> 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 forx 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 inx for y in flatten(l)] if type(x) is list else [x] >>> flatten(a) [1, 2, 3, 4, 5, 6, 7, 8] 1.16 生成器表达式 >>> 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 字典推导 >>> m = {x: x ** 2 for x inrange(5)} >>> m {0: 0, 1: 1, 2: 4, 3: 9, 4: 16} >>> m = {x: 'A' + str(x) for x inrange(10)} >>> m {0: 'A0', 1: 'A1', 2: 'A2', 3: 'A3', 4: 'A4',5: 'A5', 6: 'A6', 7: 'A7', 8: 'A8', 9: 'A9'} 1.18 用字典推导反转字典 >>> 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 命名元组 >>> 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 1.20 继承命名元组 >>> classPoint(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) 1.21 操作集合 >>> 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,
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