Python学习之12个常用基础语法详解

目录

• 前言
• 1.多个字符串组合为一个字符串
• 2.字符串http://www.cppcns.com拆分为子字符串列表
• 3.统计列表中元素的次数
• 4.使用try-except-else-block模块
• 5.使用枚举函数得到key/value对
• 6.检查对象的内存使用情况
• 7.合并字典
• 8.计算执行一段代码所花费的时间
• 9.列表展开
• 10.列表采样
• 11.数字化
• 12.检查列表元素的唯一性

前言

前几天写了一篇关于python高级语法的文章：python进阶从青铜到王者一定会用上的Python技巧。

有读者私信说：怎么看自己是不是入门python了呢？ 开发中高频python基础语法有哪些呢？

下面通过12个小案例，包含了日常开发中非常实用的语法，大家一起来检验下你会几个呢？

1. 多个字符串组合为一个字符串

list_of_strings = ['My', 'name', 'is', 'Dragon']

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

# Output
# My name is Dragon

2. 字符串拆分为子字符串列表

string_1 = "My name is Dragon"
string_2 = "sample/ string 2"

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

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

3. 统计列表中元素的次数

# 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']编程客栈
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)]

4. 使用try-except-else-block模块

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

5. 使用枚举函数得到key/value对

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

for index, value in enumerate(my_list):
    prihttp://www.cppcns.comnt('{0}: {1}'.format(index, value))

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

6. 检查对象的内存使用情况

import sys
num = 21
print(sys.getsizeof(num))
# In Python 3, 28

7. 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}

8. 计算执行一段代码所花费的时间

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
# 28770.217895507812

9. 列表展开

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]

10. 列表采样

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

11. 数字化

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]

12. 检查列表元素的唯一性

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

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

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

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