# 20段极简Python代码：这些小技巧你都Get了么

Python 是机器学习最广泛采用的编程语言，它最重要的优势在于编程的易用性。 如果读者对基本的 Python 语法已经有一些了解，那么这篇文章可能会给你一些启发。 作者简单概览了 20 段代码，它们都是平常非常实用的技巧，我们只要花几分钟就能从头到尾浏览一遍。

1.重复元素判定

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.字符元素组成判定

from collections import Counter

def anagram(first, second):
return Counter(first) == Counter(second)

anagram("abcd3", "3acdb") # True

3.内存占用

import sys

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

4.字节占用

def byte_size(string):
return(len(string.encode( utf-8 )))

byte_size( :grinning: ) # 4
byte_size( Hello World ) # 11


5. 打印 N 次字符串

n = 2;
s ="Programming";

print(s * n);
# ProgrammingProgramming


6. 大写第一个字母

s = "programming is awesome"

print(s.title())
# Programming Is Awesome

7. 分块

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. 压缩

def compact(lst):
return list(filter(bool, lst))

compact([0, 1, False, 2, , 3,  a ,  s , 34])
# [ 1, 2, 3,  a ,  s , 34 ]


9.解包

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

10. 链式对比

a = 3
print( 2 < a < 8) # True
print(1 == a < 2) # False


11. 逗号连接

hobbies = ["basketball", "football", "swimming"]

print("My hobbies are: " + ", ".join(hobbies))
# My hobbies are: basketball, football, swimming


12. 逗号连接

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

def decapitalize(string):
return str[:1].lower() + str[1:]

decapitalize( FooBar ) #  fooBar
decapitalize( FooBar ) #  fooBar


14. 展开列表

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]


1 5.列表的差

def difference(a, b):
set_a = set(a)
set_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

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 } ]


1 7.链式函数调用

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.检查重复项

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.合并两个字典

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 ones 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}


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.将两 列表转化为字典

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}