Features and skills of 30 Python languages you may not know

Each trick or language feature can only be verified by an instance, without too much explanation. Although I have tried my best to make the examples clear, some of them still seem complicated, depending on your familiarity. So if you still don't know the example, I decided to maintain a frequently used "tip" list from the beginning when I learned Python. Whenever I see a piece that makes me feel "cool, that's okay !" (In an example, in StackOverflow, in open source software, etc.), I will try it until I understand it and then add it to the list. This article is part of the list. If you are an experienced Python programmer, although you may already know something, you can still find something you don't know. If you are a C, C ++, or Java programmer learning Python, or you are learning programming at the beginning, you will find many of them very useful like me.

Each trick or language feature can only be verified by an instance, without too much explanation. Although I have tried my best to make the examples clear, some of them still seem complicated, depending on your familiarity. Therefore, if you are not clear about the example, the title can provide enough information for you to obtain detailed content through Google.

The list is sorted by difficulty. Common language features and skills are placed at the beginning.

1.30 max and min elements (heapq. nlargest and heapq. nsmallest)

>>> A = [random. randint (0,100) for _ in xrange (100)]

>>> Heapq. nsmallest (5,)

[3, 3, 5, 6, 8]

>>> Heapq. nlargest (5,)

[100,100, 99, 98, 98]

1.31 Cartesian product (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)

...

0000

0001

0010

0011

0100

0101

0110

0111

1000

1001

1010

1011

1100

1101

1110

1111

1.32 combination and replacement (itertools. combinations and itertools. combinations_with_replacement)

>>> 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

1.33 sorting (itertools. permutations)

>>> 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

1.34 link iteration (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 group rows by given value (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 supported CED none

Young myope no normal soft

Young myope yes reduced none

Young myope yes normal hard

Young hypermetrope no supported CED none

Young hypermetrope no normal soft

Young hypermetrope yes reduced none

Young hypermetrope yes normal hard

Pre-presbyopic myope no supported CED none

Pre-presbyopic myope no normal soft

Pre-presbyopic myope yes already CED none

Pre-presbyopic myope yes normal hard

Pre-presbyopic hypermetrope no supported CED none

Pre-presbyopic hypermetrope no normal soft

Pre-presbyopic hypermetrope yes already CED none

Pre-presbyopic hypermetrope yes normal none

Presbyopic myope no supported CED none

Presbyopic myope no normal none

Presbyopic myope yes reduced none

Presbyopic myope yes normal hard

Presbyopic hypermetrope no supported CED none

Presbyopic hypermetrope no normal soft

Presbyopic hypermetrope yes reduced none

Presbyopic 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: hard

Young myope yes normal hard

Young hypermetrope yes normal hard

Pre-presbyopic myope yes normal hard

Presbyopic myope yes normal hard

-----------

Group: none

Young myope no supported CED none

Young myope yes reduced none

Young hypermetrope no supported CED none

Young hypermetrope yes reduced none

Pre-presbyopic myope no supported CED none

Pre-presbyopic myope yes already CED none

Pre-presbyopic hypermetrope no supported CED none

Pre-presbyopic hypermetrope yes already CED none

Pre-presbyopic hypermetrope yes normal none

Presbyopic myope no supported CED none

Presbyopic myope no normal none

Presbyopic myope yes reduced none

Presbyopic hypermetrope no supported CED none

Presbyopic hypermetrope yes reduced none

Presbyopic hypermetrope yes normal none

-----------

Group: soft

Young myope no normal soft

Young hypermetrope no normal soft

Pre-presbyopic myope no normal soft

Pre-presbyopic hypermetrope no normal soft

Presbyopic hypermetrope no normal soft