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']
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):
print('{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:
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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