30 个你可能不知道的 Python 语言特性和技巧

1.1   Unpacking

>>> 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   Unpacking for swapping variables

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

1.3   Extended unpacking (Python 3 only)

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

1.4   Negative indexing

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

1.5   List slices (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   List slices with negative indexing

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

1.7   List slices with step (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   List slices with negative step

>>> 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   List slice assignment

>>> 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   Naming slices (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   Zipping and unzipping lists and iterables

>>> 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   Grouping adjacent list items using zip

>>> 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   Sliding windows (n -grams) using zip and iterators

>>> def n_grams(a, n):...     def advance(iterator, k):...         for __ in range(k):...             next(iterator)...         return iterator...     z = [advance(iter(a), k) for k 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   Inverting a dictionary using zip

>>> 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   Flattening lists:

>>> 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.

1.16   Generator expressions

>>> 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   Dictionary comprehensions

>>> 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   Inverting a dictionary using a dictionary comprehension

>>> 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   Named tuples (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   Inheriting from named 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=1.0, y=2.0)>>> q = Point(x=2.0, y=3.0)>>> p + qPoint(x=3.0, y=5.0)

1.21   Sets and set operations

>>> 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   Multisets and multiset operations (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   Most common elements in an iterable (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   Double-ended queue (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   Double-ended queue with maximum length (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

1.26   Ordered dictionaries (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   Default dictionaries (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   Using default dictionaries to represent simple trees

>>> 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"    }}

(See https://gist.github.com/hrldcpr/2012250 for more on this.)

1.29   Mapping objects to unique counting numbers (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   Largest and smallest elements (heapq.nlargest andheapq.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   Cartesian products (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   Combinations and combinations with replacement (itertools.combinations anditertools.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   Permutations (itertools.permutations)

>>> for p in itertools.permutations([1, 2, 3, 4]):...     print ''.join(str(x) for x in p)...123412431324134214231432213421432314234124132431312431423214324134123421412341324213423143124321

1.34   Chaining iterables (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   Grouping rows by a given key (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

 

 
转自http://sahandsaba.com/thirty-python-language-features-and-tricks-you-may-not-know.html
                                             
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