10 Python code optimization tips

PythonIt is a powerful interpreted programming language.我們可以通過下面的10optimization techniques to reduce the amount of code and improve the efficiency of the code.

1. Make good use of the list（list）推導式

問題：輸出1The square of each number within ten thousand. Found that using list comprehensions takes less time.

from timeit import default_timer as timer

start = timer()
square =[]
for n in range(10000):
    square.append(pow(n,2))
end = timer()
print("優化前耗時：",end - start)

#優化後
start2=timer()
square=[pow(n,2) for n in range(10000)]
end2=timer()
print("優化後耗時：",end2 - start2)
print(square)

2. 用PythonGenerators save runtime memory

如果對1Sum the squares of each number within ten thousand,換用PythonGenerator to store process data,We found that it takes up less memory.

import sys
square = [n**2 for n in range(10000)]  
print(sum(square))
print(sys.getsizeof(square),'字節') #優化後
square = (n\*\*2 for n in range(10000))
print(sum(square))
print(sys.getsizeof(square),'字節')

3. 用sorted()The function quickly implements the ascending order of sequence elements,用reverse=True實現降序

lst=[20, 40, 20, 20, 40, 60, 70]
print(sorted(list(lst),reverse=True))

4. 用集合setQuickly filter out duplicate elements

lst=[20, 40, 20, 20, 40, 60, 70]
# print(sorted(list(lst),reverse=True))
print(set(lst))

5. 用enumerateTraverse the positions and values ​​of elements in the output sequence structure 用enumerate後,The output result remains unchanged,But the code is more concise.

dogs = ['Harley', 'Phantom', 'Lucky', 'Dingo']
count = 1
for name in dogs:
    print(count, name)
    count += 1
#優化後
print('優化後')
for i,name in enumerate(dogs,start=1):
    print(i,name)

6. 用字典dictionary中get() 和setdefault()Set the value of the default key

roman_nums = {'I':1, 'II':2, 'III':3, 'IV':4 }
# value=roman_nums['V']  # An error will be reported when accessing a non-existing key value KeyError: 'V'
value=roman_nums.get('V',5)
print('value=',value)
print(roman_nums)
value = roman_nums.setdefault('V',5)
print(roman_nums)

7. 用CounterCounts the most frequently occurring elements in the sequence structure

#統計出現次數最多的元素
#This method is introduced first
from collections import Counter
s='hello'
print(Counter(s)) 

#法二
print([(x,s.count(x)) for x in set(s)])

8. f-Strings (Python 3.6+)格式化字符串

name,major = "world","computer science"

s="Hello, %s. I major in %s." % (name,major)
s1="Hello, {}. I major in {}.".format(name, major)
s2=f"Hello, {name}. I major in {major}." #推薦用法
print(s,s1,s2,sep='\n')

9. join()Implement substring concatenation

s=['H','e','l','l','o']
s1=''
for x in s:
    s1+=x
print(s1)

s1=''.join(s)#推薦用法
print(s1)

10. Dictionary mergedN種方法

#法一
x = {'a': 1, 'b': 2}
y = {'b': 10, 'c': 11}
x.update(y)
print(x)
#法二 Python3.9+
z = x | y
print(z)
#法三 Python3.5+
z = {**x, **y}
print(z)
#法四
z = dict(list(x.items()) + list(y.items()))
print(z)

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