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This article mainly explains "what Python commonly used minimalist code", interested friends may wish to take a look. The method introduced in this paper is simple, fast and practical. Let's let Xiaobian take you to learn "what Python common minimalist code"!

1. duplicate element determination

The following method checks for duplicates in a given list, using the set() function to remove all duplicates.

def all_unique(lst): return len(lst)== len(set(lst)) x = [1,1,2,2,3,2,3,4,5,6] y = [1,2,3,4,5] all_unique(x) # False all_unique(y) # True

2. Character element composition judgment

Check whether the elements of two strings are the same.

from collections import Counter def anagram(first, second): return Counter(first) == Counter(second) anagram("abcd3", "3acdb") # True

3. memory footprint

import sys variable = 30 print(sys.getsizeof(variable)) # 24

4. byte occupancy

The following code block checks the number of bytes occupied by a string.

def byte_size(string): return(len(string.encode('utf-8'))) byte_size('') # 4 byte_size('Hello World') # 11

5. Print string N times

This code block prints the string N times without loop statements.

n = 2 s ="Programming" print(s * n) # ProgrammingProgramming

6. Capital first letter

The following code block uses the title() method to capitalize the first letter of each word in the string.

s = "programming is awesome" print(s.title()) # Programming Is Awesome

7. block

Given a specific size, define a function to slice the list by that size.

from math import ceil def chunk(lst, size): return list( map(lambda x: lst[x * size:x * size + size], list(range(0, ceil(len(lst) / size))))) chunk([1,2,3,4,5],2) # [[1,2],[3,4],5]

8. compression

This method removes Boolean values, such as (False, None, 0,""), using the filter() function.

def compact(lst): return list(filter(bool, lst)) compact([0, 1, False, 2, '', 3, 'a', 's', 34]) # [ 1, 2, 3, 'a', 's', 34 ]

9. unpacking

The following code snippet unpacks a packed pairwise list into two distinct tuples.

array = [['a', 'b'], ['c', 'd'], ['e', 'f']] transposed = zip(*array) print(transposed) # [('a', 'c', 'e'), ('b', 'd', 'f')]

10. chain correlation

We can compare several different elements in one line of code using different operators.

a = 3 print( 2

< a < 8) # True print(1 == a < 2) # False 11. 逗号连接 下面的代码可以将列表连接成单个字符串，且每一个元素间的分隔方式设置为了逗号。 hobbies = ["basketball", "football", "swimming"] print("My hobbies are: " + ", ".join(hobbies)) # My hobbies are: basketball, football, swimming 12. 元音统计 以下方法将统计字符串中的元音 (‘a’, ‘e’, ‘i’, ‘o’, ‘u’) 的个数，它是通过正则表达式做的。 import re def count_vowels(str): return len(len(re.findall(r'[aeiou]', str, re.IGNORECASE))) count_vowels('foobar') # 3 count_vowels('gym') # 0 13. 首字母小写 如下方法将令给定字符串的第一个字符统一为小写。 def decapitalize(string): return str[:1].lower() + str[1:] decapitalize('FooBar') # 'fooBar' decapitalize('FooBar') # 'fooBar' 14. 展开列表 该方法将通过递归的方式将列表的嵌套展开为单个列表。 def spread(arg): ret = [] for i in arg: if isinstance(i, list): ret.extend(i) else: ret.append(i) return ret def deep_flatten(lst): result = [] result.extend( spread(list(map(lambda x: deep_flatten(x) if type(x) == list else x, lst)))) return result deep_flatten([1, [2], [[3], 4], 5]) # [1,2,3,4,5] 15. 列表的差 该方法将返回第一个列表的元素，其不在第二个列表内。如果同时要反馈第二个列表独有的元素，还需要加一句 set_b.difference(set_a)。 def difference(a, b): setset_a = set(a) setset_b = set(b) comparison = set_a.difference(set_b) return list(comparison) difference([1,2,3], [1,2,4]) # [3] 16. 通过函数取差 如下方法首先会应用一个给定的函数，然后再返回应用函数后结果有差别的列表元素。 def difference_by(a, b, fn): b = set(map(fn, b)) return [item for item in a if fn(item) not in b] from math import floor difference_by([2.1, 1.2], [2.3, 3.4],floor) # [1.2] difference_by([{ 'x': 2 }, { 'x': 1 }], [{ 'x': 1 }], lambda v : v['x']) # [ { x: 2 } ] 17. 链式函数调用 你可以在一行代码内调用多个函数。 def add(a, b): return a + b def subtract(a, b): return a - b a, b = 4, 5 print((subtract if a >

b else add)(a, b)) # 9

18. check for duplicates

The following code checks both lists for duplicates.

def has_duplicates(lst): return len(lst) != len(set(lst)) x = [1,2,3,4,5,5] y = [1,2,3,4,5] has_duplicates(x) # True has_duplicates(y) # False

19. Merge two dictionaries

The following method will be used to merge two dictionaries.

def merge_two_dicts(a, b): c = a.copy() # make a copy of a c.update(b) # modify keys and values of a with the once from b return c a={'x':1,'y':2} b={'y':3,'z':4} print(merge_two_dicts(a,b)) #{'y':3,'x':1,'z':4}

In Python 3.5 or later, we can also merge dictionaries in the following ways:

def merge_dictionaries(a, b) return {**a, **b} a = { 'x': 1, 'y': 2} b = { 'y': 3, 'z': 4} print(merge_dictionaries(a, b)) # {'y': 3, 'x': 1, 'z': 4}

20. Convert two lists to dictionaries

The following method converts two lists into a single dictionary.

def to_dictionary(keys, values): return dict(zip(keys, values)) keys = ["a", "b", "c"] values = [2, 3, 4] print(to_dictionary(keys, values)) #{'a': 2, 'c': 4, 'b': 3}

21. using an enumeration

We often use the For loop to traverse a list, and we can also enumerate the index and value of the list.

list = ["a", "b", "c", "d"] for index, element in enumerate(list): print("Value", element, "Index ", index, ) # ('Value', 'a', 'Index ', 0) # ('Value', 'b', 'Index ', 1) #('Value', 'c', 'Index ', 2) # ('Value', 'd', 'Index ', 3)

22. execution time

The following code block can be used to calculate the time it takes to execute a particular code.

import time start_time = time.time() a = 1 b = 2 c = a + b print(c) #3 end_time = time.time() total_time = end_time - start_time print("Time: ", total_time) # ('Time: ', 1.1205673217773438e-05)

23. Try else

We can also add an else clause to the try/except statement, which runs if no error is triggered.

try: 2*3 except TypeError: print("An exception was raised") else: print("Thank God, no exceptions were raised. ") #Thank God, no exceptions were raised.

24. element frequency

The following method takes the most common elements in the list based on their frequency.

def most_frequent(list): return max(set(list), key = list.count) list = [1,2,1,2,3,2,1,4,2] most_frequent(list)

25. palindromic sequence

The following method checks whether a given string is a palindrome sequence by first converting all letters to lowercase and removing non-alphabetic symbols. Finally, it compares the string to the inverted string for equality, which is expressed as a palindrome sequence.

def palindrome(string): from re import sub s = sub('[\W_]', '', string.lower()) return s == s[::-1] palindrome('taco cat') # True

26. Do not use if-else calculators

This piece of code can be added, subtracted, multiplied, divided, and raised without using conditional statements. It is implemented through the dictionary data structure:

import operator action = { "+": operator.add, "-": operator.sub, "/": operator.truediv, "*": operator.mul, "**": pow } print(action['-'](50, 25)) # 25

27. Shuffle

This algorithm disorders the list elements, and it primarily sorts new lists using Fisher-Yates algorithm:

from copy import deepcopy from random import randint def shuffle(lst): temp_lst = deepcopy(lst) m = len(temp_lst) while (m): m -= 1 i = randint(0, m) temp_lst[m], temp_lst[i] = temp_lst[i], temp_lst[m] return temp_lst foo = [1,2,3] shuffle(foo) # [2,3,1] , foo = [1,2,3]

28. expand the list

Expands all elements in a list, including sublists, into a list.

def spread(arg): ret = [] for i in arg:if isinstance(i, list): ret.extend(i) else: ret.append(i) return ret spread([1,2,3,[4,5,6],[7],8,9]) # [1,2,3,4,5,6,7,8,9]

29. swap value

You can swap the values of two variables without additional operations.

def swap(a, b): return b, a a, b = -1, 14 swap(a, b) # (14, -1) spread([1,2,3,[4,5,6],[7],8,9]) # [1,2,3,4,5,6,7,8,9]

30. dictionary defaults

The default value can be set in the following way by taking the corresponding Value value of Key. If the get() method doesn't have a default value, it returns None if it encounters a Key that doesn't exist.

d = {'a': 1, ' b': 2} print(d.get ('c ', 3))#3 At this point, I believe that everyone has a deeper understanding of "what Python commonly used minimalist code", may wish to actually operate it! Here is the website, more related content can enter the relevant channels for inquiry, pay attention to us, continue to learn!

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