# Python Learning: 35 Language Features and Programming Skills

Since I started learning python, I've started to summarize a collection of Python tips myself. Later, when I saw a cool piece of code in Stack Overflow or in some open source software, I was surprised: I could have done that! At that time, I would try this code on my own, until I understood its overall idea, I would add this code to my collection. This blog is actually the public appearance of the last part of this collection. If you're already a python bull, you probably know most of the usage here, but I think you should also discover some new techniques that you don't know. And if you've been a c,c++,java programmer, learning python, or just a beginner in programming, you should see a lot of useful practical skills that surprise you, just like I did.

Every skill and language usage will be shown in one instance, and no other explanation is needed. I've tried to make each example easy to understand, but there may still be some obscurity due to the different familiarity with python. So if the examples themselves don't make sense to you, at least the title of the example will help you when you go back to Google.

The whole set is probably sorted according to the degree of difficulty, simple and common in the front, relatively rare in the last.

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] >>> a 1 >>> b 2 >>> c 3 >>> d 4

2 Unpacking Variable Exchange

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

3 Extended unboxing (only compatible with Python 3)

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

4 Negative Index

What I don't know in the process of learning can be added to me? python learning communication deduction qun, 784758214 There are good learning video tutorials, development tools and e-books in the group. Share with you the current talent needs of python enterprises and how to learn python from zero foundation, and what to learn >>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] >>> a[-1] 10 >>> a[-3] 8

5 Cut List

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

6 Negative Index Cut List

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

7 specified step cut list

>>> 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 Negative Step Cutting List

>>> 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 list cut 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]

10 Named List Cutting Method

>>> a = [0, 1, 2, 3, 4, 5] >>> LASTTHREE = slice(-3, None) >>> LASTTHREE slice(-3, None, None) >>> a[LASTTHREE] [3, 4, 5]

11 Lists and Compression and Decompression of Iterators

>>> 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')]

12-List Contiguous Element Compressor

>>> 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,)]

13 Slide the Value Window in the List with Compressor and Iterator

>>> 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)]

14 Inversion of Dictionary with Compressor

>>> 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'}

15 List Expansion

>>> 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]

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

17 Dictionary Derivation

>>> 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'}

18 Derivation of Reversed Dictionary by Dictionary

>>> 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'}

19 Named tuples

>>> 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

20 Inheritance 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 + q Point(x=3.0, y=5.0)

21 Operational Set

>>> 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

22 Operational Multiple Sets

>>> 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})

23 Statistics are the most common elements in iterators

>>> 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)]

24 Queues that are operable at both ends

>>> 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])

25 Double-ended Queue with Maximum Length

>>> 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

26 sortable dictionary

What I don't know in the process of learning can be added to me? python learning communication deduction qun, 784758214 There are good learning video tutorials, development tools and e-books in the group. Share with you the current talent needs of python enterprises and how to learn python from zero foundation, and what to learn >>> 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

27 Default Dictionary

>>> 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]'

28 Simple Tree Representation of Default Dictionary

>>> 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" } }

Mapping 29 Objects to Unique Counts

>>> 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 Maximum and Minimum List Elements

>>> 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]

Cartesian Product of 31 Two Lists

>>> 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

32 List Combinations and List Element Replacement Combinations

>>> 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

33 List Element Arrangement and Combination

>>> 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

34 Linkable Iterator

>>> 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)

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35 Specify column clustering by file

>>> 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