Python Built in Higher Order Function Details
- 2021-12-12 05:01:02
- OfStack
1. Built-in higher-order functions of Python
1.1 map()
map()
The specified sequence is mapped according to the provided function
Syntax format:
map(function, iterable, ...)
The first parameter
function
The function function is called with every 1 element in the parameter sequence,
The second parameter
iterable
1 or more sequences
Returns every time that contains
function
A new list of values returned by the function.
Sample code:
list1 = [1, 2, 4, 5, 56, 12, 5, 2, 34]
# Generate 1 Functions
def func(lt): # Returns even numbers, odd numbers +1 Return
if lt % 2 == 0:
return lt
else:
return lt + 1
list2 = map(func, list1) # Never add ()
# Use lambda Keyword
list3 = map(lambda i: i if i % 2 == 0 else i + 1, list1)
print(list(list3)) # [2, 2, 4, 6, 56, 12, 6, 2, 34]
print(list(list2)) # [2, 2, 4, 6, 56, 12, 6, 2, 34]
1.2 reduce () Function
reduce()
Function in
Python2x
Is a built-in function of the system, to
Python3x
Has been classified into
functools
It's in the library
reduce()
The function accumulates the elements in the parameter sequence.
Function to perform the following operations on all data in a data set (linked list, tuple, etc.)
map(function, iterable, ...)0
The function function (with two parameters) in the set first operates on the first and second elements, and the result is then used with the third data
function
Function operation, and finally get a result.
Grammatical format
reduce(function, iterable[, initializer])
function
--function with two arguments
iterable
--Iterable objects
initializer
--Optional, initial parameters
Returns the result of a function evaluation.
Sample code:
from functools import reduce
list1 = [1, 2, 3, 4, 5, 6, 7]
value = reduce(lambda x, y: x + y, list1)
print(value) # 28 = 1+2+3+4+5+6+7
The calculation results are stored in x and accumulated each time.
initializer
Is to set the initial value of x
1.3 reduce () Function
filter()
The list () function is used to filter the sequence, filter out the elements that do not meet the requirements, and return 1 iterator object. If you want to convert it to a list, you can use list () to convert it.
It receives two parameters, the first is a function and the second is a sequence. Each element of the sequence is passed as a parameter to the function for judgment, and then returns True or False, and finally returns
True
To the new list.
Grammatical structure:
filter(function, iterable)
function
--Judgment function.
iterable
--Iterable objects.
Returns 1 iterable object
1.4 sorted () Function
sorted()
The list function sorts all iterable objects and returns a new list.
Grammatical structure:
sorted(iterable, cmp=None, key=None, reverse=False)
iterable
--Iterable objects.
cmp
The function of comparison, which has two parameters, the values of which are taken from the iterable object. The rule that this function must abide by is that if it is greater than, it will return 1, if it is less than-1, and if it is equal to, it will return 0.
key
-is mainly used for comparison of elements, only one parameter, the specific function parameters are taken from the iterable object, the iterable object specified in one element to sort.
reverse
--Collation rules,
reverse = True
In descending order,
reverse = False
Ascending (default).
Returns a reordered list.
Sample code:
students = [
{'name': 'tom', 'age': 20},
{'name': 'lucy', 'age': 15},
{'name': 'lily', 'age': 13},
{'name': 'mark', 'age': 21},
{'name': 'jack', 'age': 13},
{'name': 'steven', 'age': 18},
]
# Find out all the people who are older than 18 Students aged
result = filter(lambda x: x['age'] > 18, students)
print(list(result)) # [{'name': 'tom', 'age': 20}, {'name': 'mark', 'age': 21}]
# Sorted by age from small to large
students = sorted(students, key=lambda x: x['age'], reverse=True) # Utilization key
print(students)
'''
[{'name': 'mark', 'age': 21}, {'name': 'tom', 'age': 20},
{'name': 'steven', 'age': 18}, {'name': 'lucy', 'age': 15},
{'name': 'lily', 'age': 13}, {'name': 'jack', 'age': 13}]
'''