讓你瞬間萌比的35個python小技巧
今天在看python算法的時候，看到一篇關於python的小技巧。瞬間萌比了，原來python也能夠這樣玩，太神奇了。萌比的是原來這麼簡單的東西本身都不知道，雖然會寫。廢話很少說了，開始上菜。python
一、拆箱算法
>>> 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
二、拆箱變量交換json
>>> a,b,c = 1,2,3 >>> a,b,c = b,c,a >>> a,b,c (2, 3, 1)
三、擴展拆箱（只兼容python3）app
>>> a, *b, c = [1, 2, 3, 4, 5] >>> a 1 >>> b [2, 3, 4] >>> c 5
四、負數索引dom
>>> a = [1,2,3,4,5,6,7,8,9,0] >>> a[-1] 0 >>> a[-3] 8
五、切割列表ui
>>> a = [1,2,3,4,5,6,7,8,9,0] >>> a[2:6] [3, 4, 5, 6]
六、負數索引切割列表spa
>>> a = [1,2,3,4,5,6,7,8,9,] >>> a[-4:-3] [6] >>> a[-4:-7] [] >>> a[-7:-4] [3, 4, 5]
七、指定不長切割列表orm
>>> a=[1,2,3,4,5,6,7,8,9,0] >>> a[::3] [1, 4, 7, 0] >>> a[::2] [1, 3, 5, 7, 9] >>> a[2:8:2] [3, 5, 7] >>> a[:2:8] [1]
八、負數步長切割列表對象
>>> a=[1,2,3,4,5,6,7,8,9,10,11,12,13,14] >>> a[::-3] [14, 11, 8, 5, 2] >>> a[::-5] [14, 9, 4] >>> a[-2:-3:-4] [13]
九、列表切割賦值blog
>>> a=[1,2,3,4,5] >>> a[2:3] [3] >>> a[2:3]=[0,0] >>> a [1, 2, 0, 0, 4, 5] >>> a[1:1] [] >>> a[1:1]=[8,9] >>> a [1, 8, 9, 2, 0, 0, 4, 5] >>> a[1:-1] [8, 9, 2, 0, 0, 4] >>> a[1:-1]=[] >>> a [1, 5]
十、命名列表切割方式
>>> a=[1,2,3,4,5] >>> LASTTHREE = slice(-3,None) >>> LASTTHREE slice(-3, None, None) >>> a[LASTTHREE] [3, 4, 5]
十一、列表以及迭代器的壓縮和解壓
>>> a=[1,2,3,4,5]
>>> b=['a', 'b', 'c']
>>> z=zip(a,b)
>>> z
[(1, 'a'), (2, 'b'), (3, 'c')]
>>> zip(*z)
[(1, 2, 3), ('a', 'b', 'c')]
十二、列表相鄰元素壓縮器
>>> a=[1,2,3,4,5] >>> zip(*([iter(a)] * 2)) [(1, 2), (3, 4)] >>> 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,)]
1三、在列表中用壓縮器和迭代器滑動取值窗口
>>> def n_grams(a,n): ... z=[iter(a[i:]) for i in range(n)] ... return zip(*z) ... >>> a=[1,2,3,4,5,6,7,8,9] >>> n_grams(a,3) [(1, 2, 3), (2, 3, 4), (3, 4, 5), (4, 5, 6), (5, 6, 7), (6, 7, 8), (7, 8, 9)] >>> n_grams(a,2) [(1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (7, 8), (8, 9)] >>> n_grams(a,4) [(1, 2, 3, 4), (2, 3, 4, 5), (3, 4, 5, 6), (4, 5, 6, 7), (5, 6, 7, 8), (6, 7, 8, 9)]
1四、用壓縮器反轉字典
>>> 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'}
1五、列表展開
>>> import itertools >>> 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]
1六、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
1七、字典推導
>>> m = {x: x ** 2 for x in range(5)}
>>> m
{0: 0, 1: 1, 2: 4, 3: 9, 4: 16}
>>> m = {x: 'B' + str(x) for x in range(10)}
>>> m
{0: 'B0', 1: 'B1', 2: 'B2', 3: 'B3', 4: 'B4', 5: 'B5', 6: 'B6', 7: 'B7', 8: 'B8', 9: 'B9'}
1八、用字典推導反轉字典
>>> m={'a':1,'b':2,'c':3,'d':4}
>>> m
{'a': 1, 'c': 3, 'b': 2, 'd': 4}
>>> {v:k for k,v in m.items()}
{1: 'a', 2: 'b', 3: 'c', 4: 'd'}
1九、命名元組
>>> import collections
>>> point = collections.namedtuple('point', ['x', 'y'])
>>> p = point(x=1.0, y=2.0)
>>> p.x
1.0
>>> p.y
2.0
20、繼承命名元組
>>> import collections
>>> 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
PointBase(x=3.0, y=5.0)
2一、操做集合
>>> A = {1, 2, 3, 4}
>>> A
set([1, 2, 3, 4])
>>> 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, 4])
>>> A - B
set([1, 2])
>>> B - A
set([5, 6, 7])
>>> A ^ B
set([1, 2, 5, 6, 7])
>>> (A ^ B) == ((A - B) | (B - A))
True
2二、操做多重集合
>>> 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})
2三、統計在可迭代器中最常出現的元素
>>> 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(2)
[(3, 4), (1, 2)]
>>> A.most_common(3)
[(3, 4), (1, 2), (2, 2)]
2四、兩端均可操做的隊列
>>> 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])
2五、有最大長度的雙端隊列
>>> 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
2六、可排序詞典
>>> 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
2七、默認詞典
>>> 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]'
2八、默認字典的簡單樹狀表達
>>> 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"
}
}
2九、對象到惟一計數的映射
>>> 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
30、最大和最小的幾個列表元素
>>> 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]
3一、兩個列表的笛卡爾積
>>> 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
3二、列表組合和列表元素替代組合
>>> 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
3三、列表元素排列組合
>>> 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
3四、可連接迭代器
>>> 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)
3五、根據文件指定列類聚
>>> 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=lambda r: r[-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 soft
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