How to make your Python code more pythonic?-Python Tutorial-php.cn

How to make your Python code more pythonic?

高洛峰

Release： 2016-10-17 17:22:33

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Pythonic is very pythonic if translated into Chinese. There are many uses of the noun structure "very +" in China, such as: "very girly", "very national football team", "very CCTV", etc. ·

For the sake of simplicity below, we use P to represent the pythonic writing method, and NP to represent the non-pythonic writing method. Of course, this P-NP is not that P-NP.

Why pursue pythonic?

Compared with NP, P’s writing method is concise, clear, and elegant. Most of the time, the execution efficiency is high, and the less code, the less error-prone it is. I think that good programmers should pursue the correctness, simplicity and readability of the code when writing code. This is exactly the spirit of pythonic.

For programmers (such as myself) who have experience in other programming languages and are new to Python, recognizing the pythonic writing method will bring more convenience and efficiency when writing Python code, and the main readers of this article It will also be this group of programmers.

N examples of P and NP will be given below for readers’ reference.

P vs. NP example

Chained comparison

a = 3
b = 1
1 <= b <= a < 10  #True

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NP:

a = 3
b = 1
b >= 1 and b <= a and a < 10 #True

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P is a grammar that elementary school students can understand, simple and direct Provincial code ~

Truth Test

name = &#39;Tim&#39;
langs = [&#39;AS3&#39;, &#39;Lua&#39;, &#39;C&#39;]
info = {&#39;name&#39;: &#39;Tim&#39;, &#39;sex&#39;: &#39;Male&#39;, &#39;age&#39;:23 }    
  
if name and langs and info:
    print(&#39;All True!&#39;)  #All True!

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NP:

if name != &#39;&#39; and len(langs) > 0 and info != {}:
    print(&#39;All True!&#39;) #All True!

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In short, the way P is written is to directly judge whether it is true or false for any object without writing judgment conditions. , which can not only ensure correctness, but also reduce the amount of code.

True and false value table (you can save a lot of code if you remember false!)

True False

Any non-empty string Empty string''

Any non-0 number Number 1

P’s writing method is simple, and after testing, it is more efficient.

If used to detect palindromes, it is a sentence of input == input[::-1], how elegant!

Connection of string lists

def reverse_str( s ):
    return s[::-1]

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NP:

def reverse_str( s ):
    t = &#39;&#39;
    for x in xrange(len(s)-1,-1,-1):
        t += s[x]
    return t

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string.join() is often used to connect strings in the list, compared to NP, P The method is very efficient and error-free.

List sum, maximum, minimum, product

strList = ["Python", "is", "good"]  
  
res =  &#39; &#39;.join(strList) #Python is good

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NP:

res = &#39;&#39;
for s in strList:
    res += s + &#39; &#39;
#Python is good
#最后还有个多余空格

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After simple testing, in num When the length of List is 10000000 , summing the list on my machine, P takes 0.6s, NP takes 1.3s, nearly twice the difference. So don’t reinvent your own wheel.

List comprehension

numList = [1,2,3,4,5]   
sum = sum(numList)  #sum = 15
maxNum = max(numList) #maxNum = 5
minNum = min(numList) #minNum = 1
from operator import mul
prod = reduce(mul, numList, 1) #prod = 120 默认值传1以防空列表报错

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NP:

sum = 0
maxNum = -float(&#39;inf&#39;)
minNum = float(&#39;inf&#39;)
prod = 1
for num in numList:
    if num > maxNum:
        maxNum = num
    if num < minNum:
        minNum = num
    sum += num
    prod *= num
# sum = 15 maxNum = 5 minNum = 1 prod = 120

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You see, using the list comprehension of P, building a new list becomes so simple and intuitive!

The default value of the dictionary

l = [x*x for x in range(10) if x % 3 == 0]
#l = [0, 9, 36, 81]

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NP:

l = []
for x in range(10):
    if x % 3 == 0:
        l.append(x*x)
#l = [0, 9, 36, 81]

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The get(key,default) method of

dict is used to get the value of key in the dictionary, if it does not exist For this key, the key is assigned the default value default.

Compared with NP, P has less if...else..., which is really the first choice for people who hate if...else...!

for...else... statement

dic = {&#39;name&#39;:&#39;Tim&#39;, &#39;age&#39;:23}  
  
dic[&#39;workage&#39;] = dic.get(&#39;workage&#39;,0) + 1
#dic = {&#39;age&#39;: 23, &#39;workage&#39;: 1, &#39;name&#39;: &#39;Tim&#39;}

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NP:

if &#39;workage&#39; in dic:
    dic[&#39;workage&#39;] += 1
else:
    dic[&#39;workage&#39;] = 1
#dic = {&#39;age&#39;: 23, &#39;workage&#39;: 1, &#39;name&#39;: &#39;Tim&#39;}

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The else part of

for...else... is used to handle the else part that is not interrupted from the for loop Condition. With it, we don't need to set state variables to check whether the for loop breaks out, which is simple and convenient.

Replacement of ternary symbols

for x in xrange(1,5):
    if x == 5:
        print &#39;find 5&#39;
        break
else:
    print &#39;can not find 5!&#39;
#can not find 5!

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NP:

find = False
for x in xrange(1,5):
    if x == 5:
        find = True
        print &#39;find 5&#39;
        break
if not find:
    print &#39;can not find 5!&#39;
#can not find 5!

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If you have programming experience in C, you will look for alternatives to A ? B : C . You may find that A and B or C look fine, but b = a > 1 and False or True returns True, when the actual intention should be to return False.

Using b = False if a > 1 else True will return False correctly, so it is an authentic ternary symbol replacement.

Enumerate

a = 3  
  
b = 2 if a > 2 else 1
#b = 2

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NP:

if a > 2:
    b = 2
else:
    b = 1
#b = 2

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Using enumerate can take out the index and value at one time, avoiding using the index to get the value, and the second parameter of enumerate can Adjust the starting position of the index subscript, the default is 0.

Use zip to create key-value pairs

array = [1, 2, 3, 4, 5]
  
for i, e in enumerate(array,0):
    print i, e
#0 1
#1 2
#2 3
#3 4
#4 5

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NP:

for i in xrange(len(array)):
    print i, array[i]
#0 1
#1 2
#2 3
#3 4
#4 5

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The zip method returns a tuple, use it to create key-value pairs, simple and clear .