Hướng dẫn is it faster to iterate through list or set python? - Lặp qua danh sách hoặc đặt python có nhanh hơn không?

Trong Python, Setis, một bộ sưu tập dữ liệu không có thứ tự là có thể sử dụng được, có thể thay đổi và không có các yếu tố trùng lặp. Có rất nhiều cách có thể được sử dụng để lặp lại trên một tập hợp. Một số cách này cung cấp thực hiện thời gian nhanh hơn so với những cách khác. Một số cách này bao gồm, lặp lại sử dụng/trong khi các vòng lặp, toàn bộ, trình lặp và biến thể của chúng. Chúng ta hãy xem tất cả các cách khác nhau mà chúng ta có thể lặp lại trong một tập hợp trong Python. Ước tính sơ bộ về thời gian mỗi kỹ thuật mất để lặp lại trên một bộ nhất định. Random.seed (21) đã được thêm vào mỗi tập lệnh để cố định các số ngẫu nhiên được tạo mỗi khi chương trình được thực thi. Sử dụng hạt giống không đổi giúp chúng tôi xác định kỹ thuật nào là tốt nhất cho một tập hợp được tạo ngẫu nhiên nhất định .Method #1: Lặp lại trên một tập hợp sử dụng đơn giản cho vòng lặp. & NBSP;Setis an unordered collection of data type that is iterable, mutable and has no duplicate elements.
There are numerous ways that can be used to iterate over a Set. Some of these ways provide faster time execution as compared to others. Some of these ways include, iterating using for/while loops, comprehensions, iterators and their variations. Let’s see all the different ways we can iterate over a set in Python.
Analysis of each method: 
For explaining the working of each way/technique, time per set(randomly generated set) has been calculated for 5-times to get a rough estimate on how much time every technique takes for iterating over a given set. random.seed(21) has been added to each script to fixate over the random numbers that are generated every time the program is executed. Using constant seed helps us to determine which technique is best for a given particular randomly generated set.
Method #1: Iterating over a set using simple for loop.
 

Python3

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
8
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
0
0 E
1 e
2 k
3 g
4 s
1
0 E
1 e
2 k
3 g
4 s
2
0 E
1 e
2 k
3 g
4 s
3

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
5
0 E
1 e
2 k
3 g
4 s
6

Output:

k
s
e
g
E

Analysis:   
 

Python3

0 E
1 e
2 k
3 g
4 s
7
0 E
1 e
2 k
3 g
4 s
8
0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
0

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
2

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
4

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
5
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
6

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
0 E
1 e
2 k
3 g
4 s
1
0 E
1 e
2 k
3 g
4 s
2
0 E
1 e
2 k
3 g
4 s
3

g
k
E
s
e
2
g
k
E
s
e
3
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
g
k
E
s
e
5

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

0 E
1 e
2 k
3 g
4 s
4
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
3
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
g
k
E
s
e
3
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
2

g
k
E
s
e
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
k s e g E
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
0
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7__77777778

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
2

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
e
E
g
s
k
4

g
k
E
s
e
2
e
E
g
s
k
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
0

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
8
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
9__100
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
01

Output:   
 

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189

& nbsp; Phương thức #2: lặp qua một tập hợp sử dụng được liệt kê cho vòng lặp. & nbsp;
Method #2: Iterating over a set using enumerated for loop.
 

Python3

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
8
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
09
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
10
0 E
1 e
2 k
3 g
4 s
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
12
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
13

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
09
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
18

Output:   
 

0 E
1 e
2 k
3 g
4 s

Analysis:   
 

Python3

0 E
1 e
2 k
3 g
4 s
7
0 E
1 e
2 k
3 g
4 s
8
0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
0

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
2

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
4

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
5
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
6

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
0 E
1 e
2 k
3 g
4 s
1
0 E
1 e
2 k
3 g
4 s
2
0 E
1 e
2 k
3 g
4 s
3

g
k
E
s
e
2
g
k
E
s
e
3
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
g
k
E
s
e
5

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

0 E
1 e
2 k
3 g
4 s
4
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
3
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
g
k
E
s
e
3
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
2

g
k
E
s
e
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
k s e g E
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
0
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7__77777778

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
2

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
e
E
g
s
k
4

g
k
E
s
e
2
e
E
g
s
k
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
8
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
9__100
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
01

Output:  
 

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114

& nbsp; Phương thức #2: lặp qua một tập hợp sử dụng được liệt kê cho vòng lặp. & nbsp;
Method #3: Iterating over a set as indexed list. 
 

Python3

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
8
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
09
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
10
0 E
1 e
2 k
3 g
4 s
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
12
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
13

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
0

Output:   
 

g
k
E
s
e

Analysis:   
 

Python3

0 E
1 e
2 k
3 g
4 s
7
0 E
1 e
2 k
3 g
4 s
8
0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
0

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
2

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
4

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
5
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
6

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
0 E
1 e
2 k
3 g
4 s
1
0 E
1 e
2 k
3 g
4 s
2
0 E
1 e
2 k
3 g
4 s
3

g
k
E
s
e
2
g
k
E
s
e
3
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
g
k
E
s
e
5

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

0 E
1 e
2 k
3 g
4 s
4
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
3
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
g
k
E
s
e
3
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
2

g
k
E
s
e
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
k s e g E
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
0
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7__77777778

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
2

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
e
E
g
s
k
4

g
k
E
s
e
2
e
E
g
s
k
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
0

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
8
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
9__100
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
01

Output:  
 

0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405

& nbsp; Phương thức #2: lặp qua một tập hợp sử dụng được liệt kê cho vòng lặp. & nbsp;
Method #4: Iterating over a set using comprehension and list constructor/initializer.
 

Python3

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
8
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
09
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0 E
1 e
2 k
3 g
4 s
04______312

0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
19
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
20

Output:   
 

k s e g E

Analysis:   
 

Python3

0 E
1 e
2 k
3 g
4 s
7
0 E
1 e
2 k
3 g
4 s
8
0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
0

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
2

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
4

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
5
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
6

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
04
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
12
0 E
1 e
2 k
3 g
4 s
0
0 E
1 e
2 k
3 g
4 s
1
0 E
1 e
2 k
3 g
4 s
2
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
16

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

0 E
1 e
2 k
3 g
4 s
4
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
3
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
g
k
E
s
e
3
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
2

g
k
E
s
e
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
k s e g E
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
0
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7__77777778

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
2

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
e
E
g
s
k
4

g
k
E
s
e
2
e
E
g
s
k
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
0

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
8
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
9__100
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
01

Output:  
 

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486

& nbsp; & nbsp; Phương thức #5: lặp qua một tập hợp bằng cách sử dụng sự hiểu biết. & nbsp; & nbsp;
Method #5: Iterating over a set using comprehension. 
 

Python3

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
8
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
09__15

Output:

e
E
g
s
k

Analysis:   
 

Python3

0 E
1 e
2 k
3 g
4 s
7
0 E
1 e
2 k
3 g
4 s
8
0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
0

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
2

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
4

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
5
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
6

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
04
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
12
0 E
1 e
2 k
3 g
4 s
0
0 E
1 e
2 k
3 g
4 s
1
0 E
1 e
2 k
3 g
4 s
2
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
16

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

0 E
1 e
2 k
3 g
4 s
4
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
3
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
g
k
E
s
e
3
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
2

g
k
E
s
e
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
k s e g E
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
0
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7__77777778

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
2

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
e
E
g
s
k
4

g
k
E
s
e
2
e
E
g
s
k
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
0

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
8
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
9__100
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
01

Output:  
 

0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638

& nbsp; & nbsp; Phương thức #5: lặp qua một tập hợp bằng cách sử dụng sự hiểu biết. & nbsp; & nbsp;
Method #6: Iterating over a set using map, lambda and list comprehension 
 

Python3

0 E
1 e
2 k
3 g
4 s
7
0 E
1 e
2 k
3 g
4 s
8
0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
0

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
2

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
4

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
5
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
6

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
04
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
12
0 E
1 e
2 k
3 g
4 s
0
0 E
1 e
2 k
3 g
4 s
1
0 E
1 e
2 k
3 g
4 s
2
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
16

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
g
k
E
s
e
3
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
2

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
g
k
E
s
e
3
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
2

g
k
E
s
e
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
k s e g E
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
0
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7__77777778

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
2

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
e
E
g
s
k
4

g
k
E
s
e
2
e
E
g
s
k
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
0

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
8
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
9__100
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
01

Output:  
 

& nbsp; & nbsp; Phương thức #5: lặp qua một tập hợp bằng cách sử dụng sự hiểu biết. & nbsp; & nbsp;

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
8
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9
Method #7: Iterating over a set using iterator. 
 

Python3

0 E
1 e
2 k
3 g
4 s
7
0 E
1 e
2 k
3 g
4 s
8
0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
0

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
2

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
4

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
5
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
6

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
04
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
12
0 E
1 e
2 k
3 g
4 s
0
0 E
1 e
2 k
3 g
4 s
1
0 E
1 e
2 k
3 g
4 s
2
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
16

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

0 E
1 e
2 k
3 g
4 s
4
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
3
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
g
k
E
s
e
3
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
2

g
k
E
s
e
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
k s e g E
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
0
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7__77777778

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
2

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
e
E
g
s
k
4

g
k
E
s
e
2
e
E
g
s
k
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
0

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
8
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
9__100
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
01

Output:  
 

& nbsp; & nbsp; Phương thức #5: lặp qua một tập hợp bằng cách sử dụng sự hiểu biết. & nbsp; & nbsp;

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
8
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9
Method #8: Iterating over a set using iterator and while loop.
 

Python3

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
8
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
09__15

0 E
1 e
2 k
3 g
4 s
4
g
k
E
s
e
20
0 E
1 e
2 k
3 g
4 s
0
0 E
1 e
2 k
3 g
4 s
1
0 E
1 e
2 k
3 g
4 s
2
g
k
E
s
e
08

0 E
1 e
2 k
3 g
4 s
4
k s e g E
43
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
48
k s e g E
49

& nbsp; & nbsp; Phương thức #6: lặp qua một bộ bằng cách sử dụng bản đồ, lambda và danh sách hiểu & nbsp; & nbsp;

g
k
E
s
e
2
k s e g E
54

Output:  

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
2

0 E
1 e
2 k
3 g
4 s
4
g
k
E
s
e
02
g
k
E
s
e
93
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
g
k
E
s
e
95
g
k
E
s
e
96
 
 

Python3

0 E
1 e
2 k
3 g
4 s
7
0 E
1 e
2 k
3 g
4 s
8
0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
0

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
2

0 E
1 e
2 k
3 g
4 s
9
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
4

0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
5
0.1306622320007591
0.13657568199778325
0.13797824799985392
0.1386374360008631
0.1424286179972114
6

0 E
1 e
2 k
3 g
4 s
4
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
3
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
0

g
k
E
s
e
2
k s e g E
43
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
k s e g E
48
k s e g E
79

& nbsp; & nbsp; Phương thức #7: lặp qua một bộ bằng cách sử dụng iterator. & nbsp; & nbsp;

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
k s e g E
54

g
k
E
s
e
6
g
k
E
s
e
7
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
0
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
1

0 E
1 e
2 k
3 g
4 s
4
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
3
0.20036015100049553
0.2557020290005312
0.4601482660000329
0.2161413249996258
0.18769703499856405
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
9

0 E
1 e
2 k
3 g
4 s
4
0 E
1 e
2 k
3 g
4 s
0
g
k
E
s
e
3
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
k s e g E
2

g
k
E
s
e
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
4
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
6
k s e g E
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
0
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0 E
1 e
2 k
3 g
4 s
2
k s e g E
0
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7__77777778

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
1
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
2

0.1662169310002355
0.1783527520019561
0.21661155100082397
0.19131610199838178
0.19931397800246486
9
e
E
g
s
k
4

g
k
E
s
e
2
e
E
g
s
k
6
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
0

g
k
E
s
e
2
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
2
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
5
e
E
g
s
k
8

g
k
E
s
e
2
0 E
1 e
2 k
3 g
4 s
5
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
7
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
8
0.11386321299869451
0.111869686999853
0.1092844699996931
0.11223735699968529
0.10928539399901638
9__100
0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
01

Output:   
 

0.06303901899809716
0.06756918999963091
0.06692574200133095
0.067220498000097
0.06748137499744189
3

Kết luận: & nbsp; Trong số tất cả các kỹ thuật vòng lặp, đơn giản để lặp lặp và lặp qua iterators hoạt động tốt nhất, trong khi so sánh tất cả các kỹ thuật, sử dụng MAP với Lambda trên Set hoặc iterator của Set Works. . Điều khá đáng chú ý là các ví dụ trên chỉ có quyền truy cập một lần của các thành phần được đặt trên mỗi lần lặp, trong khi nếu chúng ta tăng số lần một thành phần được đặt được truy cập mỗi lần lặp Đầu ra bị ràng buộc với thay đổi. Lý do đằng sau sự thay đổi của mức tiêu thụ thời gian là sự phụ thuộc của máy móc về khả năng xử lý của bộ xử lý hệ thống cá nhân. & NBSP; 
Among all the looping techniques, simple for loop iteration and looping over iterators works best, while comparing all the techniques, using map with lambda over set or iterator of set works best giving a performance of a million set iterations under 10 milliseconds. It is quite noticeable that above examples only have single access of set components per iteration, whereas if we increase the number of times a set component is accessed per iteration, it may change the time taken per iteration.
Note: Values mentioned above in the example output are bound to vary. The reason behind the variation of time consumption is machine dependency of processing power of individual’s system processor.
 


Có lặp lại thông qua một bộ nhanh hơn một danh sách?

Trên thực tế, các bộ không nhanh hơn danh sách trong mọi kịch bản. Nói chung các danh sách nhanh hơn các bộ. Nhưng trong trường hợp tìm kiếm một phần tử trong bộ sưu tập, các bộ nhanh hơn vì các bộ đã được thực hiện bằng cách sử dụng các bảng băm.sets are not faster than lists in every scenario. Generally the lists are faster than sets. But in the case of searching for an element in a collection, sets are faster because sets have been implemented using hash tables.

Được đặt hiệu quả hơn danh sách Python?

Ví dụ, các bộ thực hiện các bài kiểm tra thành viên hiệu quả hơn rất nhiều so với danh sách.Trong trường hợp bạn đến từ một nền tảng khoa học máy tính, điều này là do độ phức tạp thời gian trường hợp trung bình của các bài kiểm tra thành viên trong các bộ là O (1) so với O (N) cho các danh sách.sets do membership tests a lot more efficiently than lists. In case you are from a computer science background, this is because the average case time complexity of membership tests in sets are O(1) vs O(n) for lists.

Các hoạt động được thiết lập có nhanh hơn trong Python không?

Đặt nhanh như nó được.Tuy nhiên, nếu bạn viết lại mã của mình để tạo tập hợp một lần và không thay đổi nó, bạn có thể sử dụng loại tích hợp Frozenset.Nó hoàn toàn giống nhau ngoại trừ bất biến.Nếu bạn vẫn gặp vấn đề về tốc độ, bạn cần tăng tốc chương trình của mình theo những cách khác, chẳng hạn như bằng cách sử dụng pypy thay vì cpython.. However, if you rewrite your code to create the set once, and not change it, you can use the frozenset built-in type. It's exactly the same except immutable. If you're still having speed problems, you need to speed your program up in other ways, such as by using PyPy instead of cPython.

Tại sao một tập hợp nhanh hơn một danh sách?

Các bộ không thể chứa các bản sao, và chúng sẽ đơn giản biến mất.Bộ sử dụng băm để thực hiện các cái nhìn giúp chúng nhanh hơn danh sách về vấn đề này.(Trong ví dụ thực tế, mã sử dụng danh sách mất khoảng 45 giây để chạy, trong khi mã với các bộ mất ít hơn một phần mười giây!)Sets use hashing to perform look ups which makes them way faster than lists in this regard. (In the practical example the code using lists took about 45 seconds to run, whereas the code with sets took less than a tenth of a second!)