點(diǎn)擊上方“小白學(xué)視覺”，選擇加"星標(biāo)"或“置頂”

重磅干貨，第一時(shí)間送達(dá)

來源：https://medium.com

翻譯：小馬

Python的可讀性和簡(jiǎn)單性是其廣受歡迎的兩大原因，本文介紹20個(gè)常用的Python技巧來提高代碼的可讀性，并能幫助你節(jié)省大量時(shí)間，下面的技巧將在你的日常編碼練習(xí)中非常實(shí)用。

1.字符串反轉(zhuǎn)

使用Python切片反轉(zhuǎn)字符串：

# Reversing a string using slicing

my_string = "ABCDE"
reversed_string = my_string[::-1]

print(reversed_string)

# Output
# EDCBA

2.每個(gè)單詞的第一個(gè)字母大寫

使用title函數(shù)方法：

my_string = "my name is chaitanya baweja"

# using the title() function of string class
new_string = my_string.title()

print(new_string)

# Output
# My Name Is Chaitanya Baweja

3. 字符串查找唯一元素

使用集合的概念查找字符串的唯一元素:

my_string = "aavvccccddddeee"

# converting the string to a set
temp_set = set(my_string)

# stitching set into a string using join
new_string = ''.join(temp_set)

print(new_string)

# output
# cdvae

4.重復(fù)打印字符串和列表n次

你可以使用乘法符號(hào)（*）打印字符串或列表多次：

n = 3 # number of repetitions

my_string = "abcd"
my_list = [1,2,3]

print(my_string*n)
# abcdabcdabcd

print(my_list*n)
# [1,2,3,1,2,3,1,2,3]

5.列表生成

# Multiplying each element in a list by 2

original_list = [1,2,3,4]

new_list = [2*x for x in original_list]

print(new_list)
# [2,4,6,8]

6.變量交換

a = 1
b = 2

a, b = b, a

print(a) # 2
print(b) # 1

7.字符串拆分為子字符串列表

使用.split()函數(shù)：

string_1 = "My name is Chaitanya Baweja"
string_2 = "sample/ string 2"

# default separator ' '
print(string_1.split())
# ['My', 'name', 'is', 'Chaitanya', 'Baweja']

# defining separator as '/'
print(string_2.split('/'))
# ['sample', ' string 2']

8.多個(gè)字符串組合為一個(gè)字符串

list_of_strings = ['My', 'name', 'is', 'Chaitanya', 'Baweja']

# Using join with the comma separator
print(','.join(list_of_strings))

# Output
# My,name,is,Chaitanya,Baweja

9.檢測(cè)字符串是否為回文

my_string = "abcba"

if my_string == my_string[::-1]:
    print("palindrome")
else:
    print("not palindrome")

# Output
# palindrome

10. 統(tǒng)計(jì)列表中元素的次數(shù)

# finding frequency of each element in a list
from collections import Counter

my_list = ['a','a','b','b','b','c','d','d','d','d','d']
count = Counter(my_list) # defining a counter object

print(count) # Of all elements
# Counter({'d': 5, 'b': 3, 'a': 2, 'c': 1})

print(count['b']) # of individual element
# 3

print(count.most_common(1)) # most frequent element
# [('d', 5)]

11.判斷兩個(gè)字符串是否為Anagrams

Anagrams的含義為兩個(gè)單詞中，每個(gè)英文單詞（不含大小寫）出現(xiàn)的次數(shù)相同，使用Counter類判斷兩個(gè)字符串是否為Anagrams。

from collections import Counter

str_1, str_2, str_3 = "acbde", "abced", "abcda"
cnt_1, cnt_2, cnt_3  = Counter(str_1), Counter(str_2), Counter(str_3)

if cnt_1 == cnt_2:
    print('1 and 2 anagram')
if cnt_1 == cnt_3:
    print('1 and 3 anagram')

# output
# 1 and 2 anagram

12. 使用try-except-else-block模塊

except獲取異常處理：

a, b = 1,0

try:
    print(a/b)
    # exception raised when b is 0
except ZeroDivisionError:
    print("division by zero")
else:
    print("no exceptions raised")
finally:
    print("Run this always")

# output
# division by zero
# Run this always

13. 使用枚舉函數(shù)得到key/value對(duì)

my_list = ['a', 'b', 'c', 'd', 'e']

for index, value in enumerate(my_list):
    print('{0}: {1}'.format(index, value))

# 0: a
# 1: b
# 2: c
# 3: d
# 4: e

14.檢查對(duì)象的內(nèi)存使用情況

import sys

num = 21

print(sys.getsizeof(num))

# In Python 2, 24
# In Python 3, 28

15.合并字典

dict_1 = {'apple': 9, 'banana': 6}
dict_2 = {'banana': 4, 'orange': 8}

combined_dict = {**dict_1, **dict_2}

print(combined_dict)
# Output
# {'apple': 9, 'banana': 4, 'orange': 8}

16.計(jì)算執(zhí)行一段代碼所花費(fèi)的時(shí)間

使用time類計(jì)算運(yùn)行一段代碼所花費(fèi)的時(shí)間：

import time

start_time = time.time()
# Code to check follows
for i in range(10**5):
    a, b = 1,2
    c = a+ b
# Code to check ends
end_time = time.time()
time_taken_in_micro = (end_time- start_time)*(10**6)

print(time_taken_in_micro)

# output
# 18770.217895507812

17. 列表展開

from iteration_utilities import deepflatten

# if you only have one depth nested_list, use this
def flatten(l):
  return [item for sublist in l for item in sublist]

l = [[1,2,3],[3]]
print(flatten(l))
# [1, 2, 3, 3]

# if you don't know how deep the list is nested
l = [[1,2,3],[4,[5],[6,7]],[8,[9,[10]]]]

print(list(deepflatten(l, depth=3)))
# [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

18. 列表采樣

import random

my_list = ['a', 'b', 'c', 'd', 'e']
num_samples = 2

samples = random.sample(my_list,num_samples)
print(samples)
# [ 'a', 'e'] this will have any 2 random values

19.數(shù)字化

將整數(shù)轉(zhuǎn)化成數(shù)字列表：

num = 123456

# using map
list_of_digits = list(map(int, str(num)))

print(list_of_digits)
# [1, 2, 3, 4, 5, 6]

# using list comprehension
list_of_digits = [int(x) for x in str(num)]

print(list_of_digits)
# [1, 2, 3, 4, 5, 6]

20.檢查列表元素的唯一性

檢查列表中每個(gè)元素是否為唯一的：

def unique(l):
    if len(l)==len(set(l)):
        print("All elements are unique")
    else:
        print("List has duplicates")

unique([1,2,3,4])
# All elements are unique

unique([1,1,2,3])
# List has duplicates

歡迎掃碼關(guān)注：

   

    下載1：OpenCV-Contrib擴(kuò)展模塊中文版教程
    

   
   

    在「小白學(xué)視覺」公眾號(hào)后臺(tái)回復(fù)：擴(kuò)展模塊中文教程，即可下載全網(wǎng)第一份OpenCV擴(kuò)展模塊教程中文版，涵蓋擴(kuò)展模塊安裝、SFM算法、立體視覺、目標(biāo)跟蹤、生物視覺、超分辨率處理等二十多章內(nèi)容。
   
   

    

   
   

    下載2：Python視覺實(shí)戰(zhàn)項(xiàng)目52講
   
   

    在「小白學(xué)視覺」公眾號(hào)后臺(tái)回復(fù)：Python視覺實(shí)戰(zhàn)項(xiàng)目，即可下載包括圖像分割、口罩檢測(cè)、車道線檢測(cè)、車輛計(jì)數(shù)、添加眼線、車牌識(shí)別、字符識(shí)別、情緒檢測(cè)、文本內(nèi)容提取、面部識(shí)別等31個(gè)視覺實(shí)戰(zhàn)項(xiàng)目，助力快速學(xué)校計(jì)算機(jī)視覺。
   
   

    

   
   

    下載3：OpenCV實(shí)戰(zhàn)項(xiàng)目20講
   
   

    在「小白學(xué)視覺」公眾號(hào)后臺(tái)回復(fù)：OpenCV實(shí)戰(zhàn)項(xiàng)目20講，即可下載含有20個(gè)基于OpenCV實(shí)現(xiàn)20個(gè)實(shí)戰(zhàn)項(xiàng)目，實(shí)現(xiàn)OpenCV學(xué)習(xí)進(jìn)階。
   
   

    

   
交流群

歡迎加入公眾號(hào)讀者群一起和同行交流，目前有SLAM、三維視覺、傳感器、自動(dòng)駕駛、計(jì)算攝影、檢測(cè)、分割、識(shí)別、醫(yī)學(xué)影像、GAN、算法競(jìng)賽等微信群（以后會(huì)逐漸細(xì)分），請(qǐng)掃描下面微信號(hào)加群，備注：”昵稱+學(xué)校/公司+研究方向“，例如：”張三 + 上海交大 + 視覺SLAM“。請(qǐng)按照格式備注，否則不予通過。添加成功后會(huì)根據(jù)研究方向邀請(qǐng)進(jìn)入相關(guān)微信群。請(qǐng)勿在群內(nèi)發(fā)送廣告，否則會(huì)請(qǐng)出群，謝謝理解~