Table of Contents
map can map the specified sequence according to the provided function. It accepts
In Python,
The zip function accepts any number (including 0 and 1) sequences as parameters and returns a tuple list
filter out
Each
Home Backend Development Python Tutorial Sharing of built-in functions in Python

Sharing of built-in functions in Python

Jul 18, 2017 pm 01:20 PM
python function share

Python has some very clever and powerful built-in functions, which are generally not used by beginners. I only discovered after using python for a while, wow, there is such a good thing. Function, this function is classic and has been rigorously tested. It can save you a lot of things at once. The code is not only more concise and easy to read, but also you don’t have to create it behind closed doors. It is convenient for you and reduces the cost. Bug. 1.sorted()

1) For sorting a list

sorted([100, 98, 102, 1, 40])
>>>[1, 40, 98, 100, 102]
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2)By key parameter/function

For example, there are many dictionary elements nested in a long list. We need to sort according to the length of each element

L = [{1:5,3:4},{1:3,6:3},{1:1,2:4,5:6},{1:9}]
new_line=sorted(L,key=lambda x:len(x))
print(new_line)
>>>[{1: 9}, {1: 5, 3: 4}, {1: 3, 6: 3}, {1: 1, 2: 4, 5: 6}]
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3) Sort the List composed of tuples

For example, the following is a list of the ages of students

students = [('wang', 'A', 15), ('li', 'B', 12), ('zhang', 'B', 10)]   
print(sorted(students, key=lambda student : student[2]))  
>>>[('zhang', 'B', 10), ('li', 'B', 12), ('wang', 'A', 15)]
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4) Use the cmp function to sort

students = [('wang', 'A', 15), ('li', 'B', 12), ('zhang', 'B', 10)]   
print(sorted(students, cmp=lambda x,y : cmp(x[0], y[0])) )
>>>[('li', 'B', 12), ('wang', 'A', 15), ('zhang', 'B', 10)]
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In fact, the sorting in python should be carefully explained. It takes a whole article to talk about its sorting algorithm. There is a lot of content. If you are interested, you can take a look at the source code to see how it is designed. I just click here first.

2.map()

map can map the specified sequence according to the provided function. It accepts

a function f and a list

, and applies the function f to each element on the list, and then returns A new list, the input parameters of the map function can also be multiple. Note that this function must have a return value (the value is important three times). Otherwise, a new list will be returned, similar to [None, None, None, None, None, None, None, None, None]

Suitable The scenario requires repeated operations on some elements in the list, which can be easily done with map.

3.enumerate()

In Python,

Iteration

is always taken out The element itself, not the index of the element. Sometimes we need to know the index of the element. For example, there are some website names in a long list. We hope that the index can also be listed when printing. If there is no such function, we need to add a variable and increment the counting variable when printing in the loop. Now that we have enumerate, we don’t have to go to such trouble. We can do it directly.

4.zip()

The zip function accepts any number (including 0 and 1) sequences as parameters and returns a tuple list

x = [1, 2, 3]
y = [4, 5, 6]
z = [7, 8, 9]
xyz = zip(x, y, z)
>>print xyz
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This function is especially useful in building dictionary sequences It is very convenient (this trick is very clever, you can carefully

figure it out

)

##5.filter()

filter function accepts A function f and a list. The function of this function f is to judge each element and return True or False. This can

filter out

some elements that

do not meet the conditions , and then return Qualified list.

def is_even(x):
	return x%2==0
print(filter(is_even,[1,2,3,4,5]))
>>>[2, 4]
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Especially when processing files, need to remove some spaces, carriage returns and empty characters


6.reduce()

The usage of the reduce function is very similar to map. It is also a function f and a list, but the entry parameter of the function must be

Each

, reduce is also called repeatedly for each element, and finally returns the final value, while map returns a list

Note that reduce in python3

has been removed from the global function. If you need to use it, please

from functools import reduceFinally, I insist on originality. If what I write is helpful to everyone, please Everyone encourage

,

retweet or follow it, long press to send the QR code, which is also a little support for me.

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