分分钟学会Python3

Python was created by Guido Van Rossum in the early 90s. It is now one of the most popular
languages in existence. I fell in love with Python for its syntactic clarity. It’s basically
executable pseudocode.

Feedback would be highly appreciated! You can reach me at @louiedinh or louiedinh [at] [google’s email service]

Note: This article applies to Python 3 specifically. Check out here if you want to learn the old Python 2.7


语言: python3
贡献者:

- ["Louie Dinh", "http://pythonpracticeprojects.com"]  
- ["Steven Basart", "http://github.com/xksteven"]  
- ["Andre Polykanine", "https://github.com/Oire"]  
- ["Zachary Ferguson", "http://github.com/zfergus2"]  
- ["evuez", "http://github.com/evuez"]  

filename: learnpython3.py
译者:

- ["ChangingFond", "http://blog.fangchengjin.cn"]

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862

# Single line comments start with a number symbol.

""" Multiline strings can be written
using three "s, and are often used
as comments
"""

####################################################
## 1. Primitive Datatypes and Operators
####################################################

# You have numbers
3 # => 3

# Math is what you would expect
1 + 1 # => 2
8 - 1 # => 7
10 * 2 # => 20

# Except division which returns floats, real numbers, by default
35 / 5 # => 7.0

# Result of integer division truncated down both for positive and negative.
5 // 3 # => 1
5.0 // 3.0 # => 1.0 # works on floats too
-5 // 3 # => -2
-5.0 // 3.0 # => -2.0

# When you use a float, results are floats
3 * 2.0 # => 6.0

# Modulo operation
7 % 3 # => 1

# Exponentiation (x**y, x to the yth power)
2**4 # => 16

# Enforce precedence with parentheses
(1 + 3) * 2 # => 8

# Boolean values are primitives (Note: the capitalization)
True
False

# negate with not
not True # => False
not False # => True

# Boolean Operators
# Note "and" and "or" are case-sensitive
True and False # => False
False or True # => True

# Note using Bool operators with ints
0 and 2 # => 0
-5 or 0 # => -5
0 == False # => True
2 == True # => False
1 == True # => True

# Equality is ==
1 == 1 # => True
2 == 1 # => False

# Inequality is !=
1 != 1 # => False
2 != 1 # => True

# More comparisons
1 < 10 # => True
1 > 10 # => False
2 <= 2 # => True
2 >= 2 # => True

# Comparisons can be chained!
1 < 2 < 3 # => True
2 < 3 < 2 # => False

# (is vs. ==) is checks if two variables refer to the same object, but == checks
# if the objects pointed to have the same values.
a = [1, 2, 3, 4] # Point a at a new list, [1, 2, 3, 4]
b = a # Point b at what a is pointing to
b is a # => True, a and b refer to the same object
b == a # => True, a's and b's objects are equal
b = [1, 2, 3, 4] # Point b at a new list, [1, 2, 3, 4]
b is a # => False, a and b do not refer to the same object
b == a # => True, a's and b's objects are equal

# Strings are created with " or '
"This is a string."
'This is also a string.'

# Strings can be added too! But try not to do this.
"Hello " + "world!" # => "Hello world!"
# Strings can be added without using '+'
"Hello " "world!" # => "Hello world!"

# A string can be treated like a list of characters
"This is a string"[0] # => 'T'

# You can find the length of a string
len("This is a string") # => 16

# .format can be used to format strings, like this:
"{} can be {}".format("Strings", "interpolated") # => "Strings can be interpolated"

# You can repeat the formatting arguments to save some typing.
"{0} be nimble, {0} be quick, {0} jump over the {1}".format("Jack", "candle stick")
# => "Jack be nimble, Jack be quick, Jack jump over the candle stick"

# You can use keywords if you don't want to count.
"{name} wants to eat {food}".format(name="Bob", food="lasagna") # => "Bob wants to eat lasagna"

# If your Python 3 code also needs to run on Python 2.5 and below, you can also
# still use the old style of formatting:
"%s can be %s the %s way" % ("Strings", "interpolated", "old") # => "Strings can be interpolated the old way"


# None is an object
None # => None

# Don't use the equality "==" symbol to compare objects to None
# Use "is" instead. This checks for equality of object identity.
"etc" is None # => False
None is None # => True

# None, 0, and empty strings/lists/dicts all evaluate to False.
# All other values are True
bool(0) # => False
bool("") # => False
bool([]) # => False
bool({}) # => False


####################################################
## 2. Variables and Collections
####################################################

# Python has a print function
print("I'm Python. Nice to meet you!") # => I'm Python. Nice to meet you!

# By default the print function also prints out a newline at the end.
# Use the optional argument end to change the end character.
print("Hello, World", end="!") # => Hello, World!

# Simple way to get input data from console
input_string_var = input("Enter some data: ") # Returns the data as a string
# Note: In earlier versions of Python, input() method was named as raw_input()

# No need to declare variables before assigning to them.
# Convention is to use lower_case_with_underscores
some_var = 5
some_var # => 5

# Accessing a previously unassigned variable is an exception.
# See Control Flow to learn more about exception handling.
some_unknown_var # Raises a NameError

# if can be used as an expression
# Equivalent of C's '?:' ternary operator
"yahoo!" if 3 > 2 else 2 # => "yahoo!"

# Lists store sequences
li = []
# You can start with a prefilled list
other_li = [4, 5, 6]

# Add stuff to the end of a list with append
li.append(1) # li is now [1]
li.append(2) # li is now [1, 2]
li.append(4) # li is now [1, 2, 4]
li.append(3) # li is now [1, 2, 4, 3]
# Remove from the end with pop
li.pop() # => 3 and li is now [1, 2, 4]
# Let's put it back
li.append(3) # li is now [1, 2, 4, 3] again.

# Access a list like you would any array
li[0] # => 1
# Look at the last element
li[-1] # => 3

# Looking out of bounds is an IndexError
li[4] # Raises an IndexError

# You can look at ranges with slice syntax.
# (It's a closed/open range for you mathy types.)
li[1:3] # => [2, 4]
# Omit the beginning
li[2:] # => [4, 3]
# Omit the end
li[:3] # => [1, 2, 4]
# Select every second entry
li[::2] # =>[1, 4]
# Return a reversed copy of the list
li[::-1] # => [3, 4, 2, 1]
# Use any combination of these to make advanced slices
# li[start:end:step]

# Make a one layer deep copy using slices
li2 = li[:] # => li2 = [1, 2, 4, 3] but (li2 is li) will result in false.

# Remove arbitrary elements from a list with "del"
del li[2] # li is now [1, 2, 3]

# Remove first occurrence of a value
li.remove(2) # li is now [1, 3]
li.remove(2) # Raises a ValueError as 2 is not in the list

# Insert an element at a specific index
li.insert(1, 2) # li is now [1, 2, 3] again

# Get the index of the first item found matching the argument
li.index(2) # => 1
li.index(4) # Raises a ValueError as 4 is not in the list

# You can add lists
# Note: values for li and for other_li are not modified.
li + other_li # => [1, 2, 3, 4, 5, 6]

# Concatenate lists with "extend()"
li.extend(other_li) # Now li is [1, 2, 3, 4, 5, 6]

# Check for existence in a list with "in"
1 in li # => True

# Examine the length with "len()"
len(li) # => 6


# Tuples are like lists but are immutable.
tup = (1, 2, 3)
tup[0] # => 1
tup[0] = 3 # Raises a TypeError

# Note that a tuple of length one has to have a comma after the last element but
# tuples of other lengths, even zero, do not.
type((1)) # => <class 'int'>
type((1,)) # => <class 'tuple'>
type(()) # => <class 'tuple'>

# You can do most of the list operations on tuples too
len(tup) # => 3
tup + (4, 5, 6) # => (1, 2, 3, 4, 5, 6)
tup[:2] # => (1, 2)
2 in tup # => True

# You can unpack tuples (or lists) into variables
a, b, c = (1, 2, 3) # a is now 1, b is now 2 and c is now 3
# You can also do extended unpacking
a, *b, c = (1, 2, 3, 4) # a is now 1, b is now [2, 3] and c is now 4
# Tuples are created by default if you leave out the parentheses
d, e, f = 4, 5, 6
# Now look how easy it is to swap two values
e, d = d, e # d is now 5 and e is now 4


# Dictionaries store mappings
empty_dict = {}
# Here is a prefilled dictionary
filled_dict = {"one": 1, "two": 2, "three": 3}

# Note keys for dictionaries have to be immutable types. This is to ensure that
# the key can be converted to a constant hash value for quick look-ups.
# Immutable types include ints, floats, strings, tuples.
invalid_dict = {[1,2,3]: "123"} # => Raises a TypeError: unhashable type: 'list'
valid_dict = {(1,2,3):[1,2,3]} # Values can be of any type, however.

# Look up values with []
filled_dict["one"] # => 1

# Get all keys as an iterable with "keys()". We need to wrap the call in list()
# to turn it into a list. We'll talk about those later. Note - Dictionary key
# ordering is not guaranteed. Your results might not match this exactly.
list(filled_dict.keys()) # => ["three", "two", "one"]


# Get all values as an iterable with "values()". Once again we need to wrap it
# in list() to get it out of the iterable. Note - Same as above regarding key
# ordering.
list(filled_dict.values()) # => [3, 2, 1]


# Check for existence of keys in a dictionary with "in"
"one" in filled_dict # => True
1 in filled_dict # => False

# Looking up a non-existing key is a KeyError
filled_dict["four"] # KeyError

# Use "get()" method to avoid the KeyError
filled_dict.get("one") # => 1
filled_dict.get("four") # => None
# The get method supports a default argument when the value is missing
filled_dict.get("one", 4) # => 1
filled_dict.get("four", 4) # => 4

# "setdefault()" inserts into a dictionary only if the given key isn't present
filled_dict.setdefault("five", 5) # filled_dict["five"] is set to 5
filled_dict.setdefault("five", 6) # filled_dict["five"] is still 5

# Adding to a dictionary
filled_dict.update({"four":4}) # => {"one": 1, "two": 2, "three": 3, "four": 4}
#filled_dict["four"] = 4 #another way to add to dict

# Remove keys from a dictionary with del
del filled_dict["one"] # Removes the key "one" from filled dict

# From Python 3.5 you can also use the additional unpacking options
{'a': 1, **{'b': 2}} # => {'a': 1, 'b': 2}
{'a': 1, **{'a': 2}} # => {'a': 2}



# Sets store ... well sets
empty_set = set()
# Initialize a set with a bunch of values. Yeah, it looks a bit like a dict. Sorry.
some_set = {1, 1, 2, 2, 3, 4} # some_set is now {1, 2, 3, 4}

# Similar to keys of a dictionary, elements of a set have to be immutable.
invalid_set = {[1], 1} # => Raises a TypeError: unhashable type: 'list'
valid_set = {(1,), 1}

# Can set new variables to a set
filled_set = some_set

# Add one more item to the set
filled_set.add(5) # filled_set is now {1, 2, 3, 4, 5}

# Do set intersection with &
other_set = {3, 4, 5, 6}
filled_set & other_set # => {3, 4, 5}

# Do set union with |
filled_set | other_set # => {1, 2, 3, 4, 5, 6}

# Do set difference with -
{1, 2, 3, 4} - {2, 3, 5} # => {1, 4}

# Do set symmetric difference with ^
{1, 2, 3, 4} ^ {2, 3, 5} # => {1, 4, 5}

# Check if set on the left is a superset of set on the right
{1, 2} >= {1, 2, 3} # => False

# Check if set on the left is a subset of set on the right
{1, 2} <= {1, 2, 3} # => True

# Check for existence in a set with in
2 in filled_set # => True
10 in filled_set # => False



####################################################
## 3. Control Flow and Iterables
####################################################

# Let's just make a variable
some_var = 5

# Here is an if statement. Indentation is significant in python!
# prints "some_var is smaller than 10"
if some_var > 10:
print("some_var is totally bigger than 10.")
elif some_var < 10: # This elif clause is optional.
print("some_var is smaller than 10.")
else: # This is optional too.
print("some_var is indeed 10.")


"""
For loops iterate over lists
prints:
dog is a mammal
cat is a mammal
mouse is a mammal
"""
for animal in ["dog", "cat", "mouse"]:
# You can use format() to interpolate formatted strings
print("{} is a mammal".format(animal))

"""
"range(number)" returns an iterable of numbers
from zero to the given number
prints:
0
1
2
3
"""
for i in range(4):
print(i)

"""
"range(lower, upper)" returns an iterable of numbers
from the lower number to the upper number
prints:
4
5
6
7
"""
for i in range(4, 8):
print(i)

"""
"range(lower, upper, step)" returns an iterable of numbers
from the lower number to the upper number, while incrementing
by step. If step is not indicated, the default value is 1.
prints:
4
6
"""
for i in range(4, 8, 2):
print(i)
"""

While loops go until a condition is no longer met.
prints:
0
1
2
3
"""
x = 0
while x < 4:
print(x)
x += 1 # Shorthand for x = x + 1

# Handle exceptions with a try/except block
try:
# Use "raise" to raise an error
raise IndexError("This is an index error")
except IndexError as e:
pass # Pass is just a no-op. Usually you would do recovery here.
except (TypeError, NameError):
pass # Multiple exceptions can be handled together, if required.
else: # Optional clause to the try/except block. Must follow all except blocks
print("All good!") # Runs only if the code in try raises no exceptions
finally: # Execute under all circumstances
print("We can clean up resources here")

# Instead of try/finally to cleanup resources you can use a with statement
with open("myfile.txt") as f:
for line in f:
print(line)

# Python offers a fundamental abstraction called the Iterable.
# An iterable is an object that can be treated as a sequence.
# The object returned the range function, is an iterable.

filled_dict = {"one": 1, "two": 2, "three": 3}
our_iterable = filled_dict.keys()
print(our_iterable) # => dict_keys(['one', 'two', 'three']). This is an object that implements our Iterable interface.

# We can loop over it.
for i in our_iterable:
print(i) # Prints one, two, three

# However we cannot address elements by index.
our_iterable[1] # Raises a TypeError

# An iterable is an object that knows how to create an iterator.
our_iterator = iter(our_iterable)

# Our iterator is an object that can remember the state as we traverse through it.
# We get the next object with "next()".
next(our_iterator) # => "one"

# It maintains state as we iterate.
next(our_iterator) # => "two"
next(our_iterator) # => "three"

# After the iterator has returned all of its data, it gives you a StopIterator Exception
next(our_iterator) # Raises StopIteration

# You can grab all the elements of an iterator by calling list() on it.
list(filled_dict.keys()) # => Returns ["one", "two", "three"]


####################################################
## 4. Functions
####################################################

# Use "def" to create new functions
def add(x, y):
print("x is {} and y is {}".format(x, y))
return x + y # Return values with a return statement

# Calling functions with parameters
add(5, 6) # => prints out "x is 5 and y is 6" and returns 11

# Another way to call functions is with keyword arguments
add(y=6, x=5) # Keyword arguments can arrive in any order.

# You can define functions that take a variable number of
# positional arguments
def varargs(*args):
return args

varargs(1, 2, 3) # => (1, 2, 3)

# You can define functions that take a variable number of
# keyword arguments, as well
def keyword_args(**kwargs):
return kwargs

# Let's call it to see what happens
keyword_args(big="foot", loch="ness") # => {"big": "foot", "loch": "ness"}


# You can do both at once, if you like
def all_the_args(*args, **kwargs):
print(args)
print(kwargs)
"""
all_the_args(1, 2, a=3, b=4) prints:
(1, 2)
{"a": 3, "b": 4}
"""

# When calling functions, you can do the opposite of args/kwargs!
# Use * to expand tuples and use ** to expand kwargs.
args = (1, 2, 3, 4)
kwargs = {"a": 3, "b": 4}
all_the_args(*args) # equivalent to foo(1, 2, 3, 4)
all_the_args(**kwargs) # equivalent to foo(a=3, b=4)
all_the_args(*args, **kwargs) # equivalent to foo(1, 2, 3, 4, a=3, b=4)

# Returning multiple values (with tuple assignments)
def swap(x, y):
return y, x # Return multiple values as a tuple without the parenthesis.
# (Note: parenthesis have been excluded but can be included)

x = 1
y = 2
x, y = swap(x, y) # => x = 2, y = 1
# (x, y) = swap(x,y) # Again parenthesis have been excluded but can be included.

# Function Scope
x = 5

def set_x(num):
# Local var x not the same as global variable x
x = num # => 43
print (x) # => 43

def set_global_x(num):
global x
print (x) # => 5
x = num # global var x is now set to 6
print (x) # => 6

set_x(43)
set_global_x(6)


# Python has first class functions
def create_adder(x):
def adder(y):
return x + y
return adder

add_10 = create_adder(10)
add_10(3) # => 13

# There are also anonymous functions
(lambda x: x > 2)(3) # => True
(lambda x, y: x ** 2 + y ** 2)(2, 1) # => 5

# There are built-in higher order functions
list(map(add_10, [1, 2, 3])) # => [11, 12, 13]
list(map(max, [1, 2, 3], [4, 2, 1])) # => [4, 2, 3]

list(filter(lambda x: x > 5, [3, 4, 5, 6, 7])) # => [6, 7]

# We can use list comprehensions for nice maps and filters
# List comprehension stores the output as a list which can itself be a nested list
[add_10(i) for i in [1, 2, 3]] # => [11, 12, 13]
[x for x in [3, 4, 5, 6, 7] if x > 5] # => [6, 7]

# You can construct set and dict comprehensions as well.
{x for x in 'abcddeef' if x not in 'abc'} # => {'d', 'e', 'f'}
{x: x**2 for x in range(5)} # => {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}


####################################################
## 5. Modules
####################################################

# You can import modules
import math
print(math.sqrt(16)) # => 4.0

# You can get specific functions from a module
from math import ceil, floor
print(ceil(3.7)) # => 4.0
print(floor(3.7)) # => 3.0

# You can import all functions from a module.
# Warning: this is not recommended
from math import *

# You can shorten module names
import math as m
math.sqrt(16) == m.sqrt(16) # => True

# Python modules are just ordinary python files. You
# can write your own, and import them. The name of the
# module is the same as the name of the file.

# You can find out which functions and attributes
# defines a module.
import math
dir(math)

# If you have a Python script named math.py in the same
# folder as your current script, the file math.py will
# be loaded instead of the built-in Python module.
# This happens because the local folder has priority
# over Python's built-in libraries.


####################################################
## 6. Classes
####################################################

# We use the "class" operator to get a class
class Human:

# A class attribute. It is shared by all instances of this class
species = "H. sapiens"

# Basic initializer, this is called when this class is instantiated.
# Note that the double leading and trailing underscores denote objects
# or attributes that are used by python but that live in user-controlled
# namespaces. Methods(or objects or attributes) like: __init__, __str__,
# __repr__ etc. are called magic methods (or sometimes called dunder methods)
# You should not invent such names on your own.
def __init__(self, name):
# Assign the argument to the instance's name attribute
self.name = name

# Initialize property
self.age = 0

# An instance method. All methods take "self" as the first argument
def say(self, msg):
print ("{name}: {message}".format(name=self.name, message=msg))

# Another instance method
def sing(self):
return 'yo... yo... microphone check... one two... one two...'

# A class method is shared among all instances
# They are called with the calling class as the first argument
@classmethod
def get_species(cls):
return cls.species

# A static method is called without a class or instance reference
@staticmethod
def grunt():
return "*grunt*"

# A property is just like a getter.
# It turns the method age() into an read-only attribute
# of the same name.
@property
def age(self):
return self._age

# This allows the property to be set
@age.setter
def age(self, age):
self._age = age

# This allows the property to be deleted
@age.deleter
def age(self):
del self._age


# When a Python interpreter reads a source file it executes all its code.
# This __name__ check makes sure this code block is only executed when this
# module is the main program.
if __name__ == '__main__':
# Instantiate a class
i = Human(name="Ian")
i.say("hi") # "Ian: hi"
j = Human("Joel")
j.say("hello") # "Joel: hello"
# i and j are instances of type Human, or in other words: they are Human objects

# Call our class method
i.say(i.get_species()) # "Ian: H. sapiens"
# Change the shared attribute
Human.species = "H. neanderthalensis"
i.say(i.get_species()) # => "Ian: H. neanderthalensis"
j.say(j.get_species()) # => "Joel: H. neanderthalensis"

# Call the static method
print(Human.grunt()) # => "*grunt*"
print(i.grunt()) # => "*grunt*"

# Update the property for this instance
i.age = 42
# Get the property
i.say(i.age) # => 42
j.say(j.age) # => 0
# Delete the property
del i.age
# i.age # => this would raise an AttributeError


####################################################
## 6.1 Multiple Inheritance
####################################################

# Another class definition
class Bat:

species = 'Baty'

def __init__(self, can_fly=True):
self.fly = can_fly

# This class also has a say method
def say(self, msg):
msg = '... ... ...'
return msg

# And its own method as well
def sonar(self):
return '))) ... ((('

if __name__ == '__main__':
b = Bat()
print(b.say('hello'))
print(b.fly)


# from "filename-without-extension" import "function-or-class"
from human import Human
from bat import Bat

# Batman inherits from both Human and Bat
class Batman(Human, Bat):

# Batman has its own value for the species class attribute
species = 'Superhero'

def __init__(self, *args, **kwargs):
# Typically to inherit attributes you have to call super:
#super(Batman, self).__init__(*args, **kwargs)
# However we are dealing with multiple inheritance here, and super()
# only works with the next base class in the MRO list.
# So instead we explicitly call __init__ for all ancestors.
# The use of *args and **kwargs allows for a clean way to pass arguments,
# with each parent "peeling a layer of the onion".
Human.__init__(self, 'anonymous', *args, **kwargs)
Bat.__init__(self, *args, can_fly=False, **kwargs)
# override the value for the name attribute
self.name = 'Sad Affleck'

def sing(self):
return 'nan nan nan nan nan batman!'


if __name__ == '__main__':
sup = Batman()

# Instance type checks
if isinstance(sup, Human):
print('I am human')
if isinstance(sup, Bat):
print('I am bat')
if type(sup) is Batman:
print('I am Batman')

# Get the Method Resolution search Order used by both getattr() and super().
# This attribute is dynamic and can be updated
print(Batman.__mro__) # => (<class '__main__.Batman'>, <class 'human.Human'>, <class 'bat.Bat'>, <class 'object'>)

# Calls parent method but uses its own class attribute
print(sup.get_species()) # => Superhero

# Calls overloaded method
print(sup.sing()) # => nan nan nan nan nan batman!

# Calls method from Human, because inheritance order matters
sup.say('I agree') # => Sad Affleck: I agree

# Call method that exists only in 2nd ancestor
print(sup.sonar()) # => ))) ... (((

# Inherited class attribute
sup.age = 100
print(sup.age)

# Inherited attribute from 2nd ancestor whose default value was overridden.
print('Can I fly? ' + str(sup.fly))



####################################################
## 7. Advanced
####################################################

# Generators help you make lazy code.
def double_numbers(iterable):
for i in iterable:
yield i + i

# Generators are memory-efficient because they only load the data needed to
# process the next value in the iterable. This allows them to perform
# operations on otherwise prohibitively large value ranges.
# NOTE: `range` replaces `xrange` in Python 3.
for i in double_numbers(range(1, 900000000)): # `range` is a generator.
print(i)
if i >= 30:
break

# Just as you can create a list comprehension, you can create generator
# comprehensions as well.
values = (-x for x in [1,2,3,4,5])
for x in values:
print(x) # prints -1 -2 -3 -4 -5 to console/terminal

# You can also cast a generator comprehension directly to a list.
values = (-x for x in [1,2,3,4,5])
gen_to_list = list(values)
print(gen_to_list) # => [-1, -2, -3, -4, -5]


# Decorators
# In this example `beg` wraps `say`. If say_please is True then it
# will change the returned message.
from functools import wraps


def beg(target_function):
@wraps(target_function)
def wrapper(*args, **kwargs):
msg, say_please = target_function(*args, **kwargs)
if say_please:
return "{} {}".format(msg, "Please! I am poor :(")
return msg

return wrapper


@beg
def say(say_please=False):
msg = "Can you buy me a beer?"
return msg, say_please


print(say()) # Can you buy me a beer?
print(say(say_please=True)) # Can you buy me a beer? Please! I am poor :(

Ready For More?

Free Online

Dead Tree

作者

ChangingFond

发布于

2016-10-28

更新于

2022-04-29

许可协议

评论