List advanced functions in python

This article mainly introduces the advanced functions of list in python in detail. Interested friends can refer to it

use a list as a stack: #Like Use a list like a stack

stack = [3, 4, 5] 
stack.append(6) 
stack.append(7) 
stack 
[3, 4, 5, 6, 7] 
stack.pop() #删除最后一个对象 
7 
stack 
[3, 4, 5, 6] 
stack.pop() 
6 
stack.pop() 
5 
stack 
[3, 4]

##use a list as a queue: #Use a list like a queue

> from collections import deque #这里需要使用模块deque 
> queue = deque(["Eric", "John", "Michael"])
> queue.append("Terry")      # Terry arrives
> queue.append("Graham")     # Graham arrives
> queue.popleft()         # The first to arrive now leaves
'Eric'
> queue.popleft()         # The second to arrive now leaves
'John'
> queue              # Remaining queue in order of arrival
deque(['Michael', 'Terry', 'Graham'])

Three built-in functions: Three important built-in functions

filter(), map(), and reduce(). 1), filter(function, sequence)::
According to the function function Rules filter data in the list sequence

> def f(x): return x % 3 == 0 or x % 5 == 0
... #f函数为定义整数对象x,x性质为是3或5的倍数
> filter(f, range(2, 25)) #筛选
[3, 5, 6, 9, 10, 12, 15, 18, 20, 21, 24]

2), map(function, sequence):

The map function implements the list sequence according to the rules of the function function Do the same processing,
The sequence here is not limited to lists, tuples can also be used.

> def cube(x): return x*x*x #这里是立方计算 还可以使用 x**3的方法
...
> map(cube, range(1, 11)) #对列表的每个对象进行立方计算
[1, 8, 27, 64, 125, 216, 343, 512, 729, 1000]

Note: The parameter list here is not fixed. It mainly depends on the number of parameters of the custom function. The map function can be transformed into: def func( x,y) map(func, sequence1, sequence2) Example:

 seq = range(8)  #定义一个列表
> def add(x, y): return x+y #自定义函数，有两个形参
...
> map(add, seq, seq) #使用map函数，后两个参数为函数add对应的操作数，如果列表长度不一致会出现错误
[0, 2, 4, 6, 8, 10, 12, 14]

3), reduce(function, sequence):

reduce function function is Operate the data in the sequence according to the function function, such as performing a function operation on the first number and the second number in the list, and perform a function operation on the result and the next data in the list, and the loop continues...
Example:

def add(x,y): return x+y
...
reduce(add, range(1, 11))
55

List comprehensions:
Here we will introduce several applications of lists:
squares = [ x**2 for x in range(10)]
#Generate a list. The list is the result of square calculation of the list generated by the list range(10).
[(x, y) for x in [1,2,3] for y in [3,1,4] if x != y]
#[(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)] Here is a list generated , each item of the list is a tuple, each tuple is composed of x and y, x is provided by the list [1,2,3], y comes from [3,1,4], and satisfies the rule x! =y.

Nested List Comprehensions：
It’s difficult to translate here, so let’s give an example:

matrix = [          #此处定义一个矩阵
...   [1, 2, 3, 4],
...   [5, 6, 7, 8],
...   [9, 10, 11, 12],
... ]
[[row[i] for row in matrix] for i in range(4)]
#[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

Here Two levels of nesting is troublesome. Let me explain briefly: For the matrix matrix, for row in matrix is ​​used to extract each row of the matrix. row[i] is used to extract the i-th (subscript) in the list of each row, generate a list, and then i again comes from for i in range(4), which generates a list of lists.

The del statement: Delete the specified data in the list, for example:

> a = [-1, 1, 66.25, 333, 333, 1234.5]
>del a[0] #删除下标为0的元素
>a
[1, 66.25, 333, 333, 1234.5]
>del a[2:4] #从列表中删除下标为2，3的元素
>a
[1, 66.25, 1234.5]
>del a[:] #全部删除 效果同 del a
>a
[]

Sets: Collection

> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
>>> fruit = set(basket)        # create a set without duplicates
>>> fruit
set(['orange', 'pear', 'apple', 'banana'])
>>> 'orange' in fruit         # fast membership testing
True
>>> 'crabgrass' in fruit
False

>>> # Demonstrate set operations on unique letters from two words
...
>>> a = set('abracadabra')
>>> b = set('alacazam')
>>> a                 # unique letters in a
set(['a', 'r', 'b', 'c', 'd'])
>>> a - b               # letters in a but not in b
set(['r', 'd', 'b'])
>>> a | b               # letters in either a or b
set(['a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'])
>>> a & b               # letters in both a and b
set(['a', 'c'])
>>> a ^ b               # letters in a or b but not both
set(['r', 'd', 'b', 'm', 'z', 'l'])

Dictionaries: Dictionaries

>>> tel = {'jack': 4098, 'sape': 4139}
>>> tel['guido'] = 4127 #相当于向字典中添加数据
>>> tel
{'sape': 4139, 'guido': 4127, 'jack': 4098}
>>> tel['jack'] #取数据
4098
>>> del tel['sape'] #删除数据
>>> tel['irv'] = 4127   #修改数据
>>> tel
{'guido': 4127, 'irv': 4127, 'jack': 4098}
>>> tel.keys()    #取字典的所有key值
['guido', 'irv', 'jack']
>>> 'guido' in tel #判断元素的key是否在字典中
True
>>> tel.get('irv') #取数据
4127

You can also use rules to generate a dictionary:

>>> {x: x**2 for x in (2, 4, 6)}
{2: 4, 4: 16, 6: 36}

enumerate(): Traverse elements and subscriptsenumerate function is used to traverse The elements in the sequence and their subscripts:

>>> for i, v in enumerate(['tic', 'tac', 'toe']):
...   print i, v
...
0 tic
1 tac
2 toe

zip():
zip() is an inner function of Python Create a function that accepts a series of iterable objects as parameters, packs the corresponding elements in the objects into tuples, and then returns a list composed of these tuples. If the lengths of the parameters passed in are not equal, the length of the returned list will be the same as the object with the shortest length among the parameters. Using the * operator, you can unzip (decompress) the list.

>>> questions = ['name', 'quest', 'favorite color']
>>> answers = ['lancelot', 'the holy grail', 'blue']
>>> for q, a in zip(questions, answers):
...   print 'What is your {0}? It is {1}.'.format(q, a)
...
What is your name? It is lancelot.
What is your quest? It is the holy grail.
What is your favorite color? It is blue.

Give a simple example about zip:

>>> a = [1,2,3]
>>> b = [4,5,6]
>>> c = [4,5,6,7,8]
>>> zipped = zip(a,b)
[(1, 4), (2, 5), (3, 6)]
>>> zip(a,c)
[(1, 4), (2, 5), (3, 6)]
>>> zip(*zipped)
[(1, 2, 3), (4, 5, 6)]

reversed(): reverse

>>> for i in reversed(xrange(1,10,2)):
...   print i
...

sorted(): sort

> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
> for f in sorted(set(basket)):       #这里使用了set函数
...   print f
...
apple
banana
orange
pear

Python's set is similar to other languages. It is a basic function including relationship testing and eliminating duplicate elements.

To change a sequence you are iterating over while inside the loop (for example to duplicate certain items), it is recommended that you first make a copy. Looping over a sequence does not implicitly make a copy. The slice notation makes this especially convenient:

>>> words = ['cat', 'window', 'defenestrate']
>>> for w in words[:]: # Loop over a slice copy of the entire list.
...   if len(w) > 6:
...     words.insert(0, w)
...
>>> words
['defenestrate', 'cat', 'window', 'defenestrate']

The above is the entire content of this article, I hope it will be helpful to everyone's study.

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