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 in range(3))>>> a, b, c(1, 3, 5)>>> a, (b, c), d = [1, (2, 3), 4]>>> a1>>> b2>>> c3>>> d4
2、使用拆箱进行变量交换
>>> a, b = 1, 2>>> a, b = b, a>>> a, b(2, 1)
3、扩展的拆箱(Python 3支持)
>>> a, *b, c = [1, 2, 3, 4, 5]>>> a1>>> b[2, 3, 4]>>> c5
4、负数索引
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]>>> a[-1]10>>> a[-3]8
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]
6、负数索引的列表切片
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]>>> a[-4:-2][7, 8]
7、带步数的列表切片(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]
8、负数步数的列表切片
>>> 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]
9、列表切片赋值
>>> 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]
10、切片命名(slice(start, end, step))
>>> a = [0, 1, 2, 3, 4, 5]>>> LASTTHREE = slice(-3, None)>>> LASTTHREEslice(-3, None, None)>>> a[LASTTHREE][3, 4, 5]
11、遍历列表索引和值(enumerate)
>>> a = ["Hello", "world", "!"]>>> for i, x in enumerate(a):... print "{}: {}".format(i, x)...0: Hello1: world2: !
12、遍历字典的KEY和VALUE(dict.iteritems)
>>> m = {"a": 1, "b": 2, "c": 3, "d": 4}>>> for k, v in m.iteritems():... print "{}: {}".format(k, v)...a: 1c: 3b: 2d: 4# 注意：Python 3中要使用dict.items
13、压缩 & 解压列表和可遍历对象
>>> 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")]
14、使用zip分组相邻列表项
>>> a = [1, 2, 3, 4, 5, 6]>>> # Using iterators>>> 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,)]>>> # Using slices>>> from itertools import islice>>> group_adjacent = lambda a, k: zip(*(islice(a, i, None, 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,)]
15、使用zip & iterators实现推拉窗(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)]
16、使用zip反相字典对象
>>> 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"}
17、合并列表
>>> 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]Note: according to Python"s documentation on sum, itertools.chain.from_iterable is the preferred method for this.
18、生成器
>>> 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
19、字典解析
>>> 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"}
20、使用字典解析反相字典对象
>>> 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"}
21、命名的tuples(collections.namedtuple)
>>> Point = collections.namedtuple("Point", ["x", "y"])>>> p = Point(x=4.0, y=2.0)>>> pPoint(x=4.0, y=2.0)>>> p.x4.0>>> p.y2.0
22、继承命名tuples
>>> 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=4.0, y=2.0)>>> q = Point(x=2.0, y=3.0)>>> p + qPoint(x=6.0, y=5.0)
23、Set & Set运算
>>> 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
24、Multisets运算(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})
25、列表中出现最多的元素(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)]
26、双向队列(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])
27、限制长度的双向队列(collections.deque)
>>> last_three = collections.deque(maxlen=3)>>> for i in xrange(10):... last_three.append(i)... print ", ".join(str(x) for x in last_three)...00, 10, 1, 21, 2, 32, 3, 43, 4, 54, 5, 65, 6, 76, 7, 87, 8, 9
28、排序字典(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
29、默认字典(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]"
30、使用defaultdict代表tree
>>> 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"}}# 查看更多：https://gist.github.com/hrldcpr/2012250
31、映射对象到唯一的计数数字(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
32、最大 & 最小元素(heapq.nlargest and 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]
33、笛卡尔积(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
34、组合(itertools.combinations and 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
35、排列(itertools.permutations)
>>> for p in itertools.permutations([1, 2, 3, 4]):... print "".join(str(x) for x in p)...123412431324134214231432213421432314234124132431312431423214324134123421412341324213423143124321
36、链接可遍历对象(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)
37、根据给定的KEY分组(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 " ".join(" ".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
38、在任意目录启动HTTP服务
python -m SimpleHTTPServer 5000Serving HTTP on 0.0.0.0 port 5000 ...
39、Python之禅
>>> import thisThe Zen of Python, by Tim PetersBeautiful is better than ugly.Explicit is better than implicit.Simple is better than complex.Complex is better than complicated.Flat is better than nested.Sparse is better than dense.Readability counts.Special cases aren"t special enough to break the rules.Although practicality beats purity.Errors should never pass silently.Unless explicitly silenced.In the face of ambiguity, refuse the temptation to guess.There should be one-- and preferably only one --obvious way to do it.Although that way may not be obvious at first unless you"re Dutch.Now is better than never.Although never is often better than *right* now.If the implementation is hard to explain, it"s a bad idea.If the implementation is easy to explain, it may be a good idea.Namespaces are one honking great idea -- let"s do more of those!
40、使用C风格的大括号代替Python缩进来表示作用域
>>> from __future__ import braces
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