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十分钟入门Python函数式编程

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该文档是国外的Brandon Skerritt写的python函数式编程教科书，十分钟完全可以学会，一起加油！

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2018/8/18 Learn Functional Python in 10 Minutes – Hacker Noon

https://hackernoon.com/learn-functional-python-in-10-minutes-to-2d1651dece6f 1/16

ApplausefromJamesLe,AakashNain,and889others

BrandonSkerritt

Iwriteaboutobscurecomputersciencetopicsthatareextremelyinteresting.Followmeto

learnmore.https://skerritt.tech

Jul30 · 10minread

LearnFunctionalPythonin10Minutes

In this article, you’ll learn what the functional paradigm is as well as

how to use functional programming in Python. You’ll also learn about

list comprehensions and other forms of comprehensions.

. . .

Functionalparadigm

In an imperative paradigm, you get things done by giving the computer

a sequence of tasks and then it executes them. While executing them, it

can change states. For example, let’s say you originally set A to 5, then

later on you change the value of A. You have variables in the sense that

the value inside the variable varies.

In a functional paradigm, you don’t tell the computer what to do but

rather you tell it what stu is. What the greatest common divisor of a

number is, what the product from 1 to n is and so on.

PhotobyChrisRiedonUnsplash

2018/8/18 Learn Functional Python in 10 Minutes – Hacker Noon

https://hackernoon.com/learn-functional-python-in-10-minutes-to-2d1651dece6f 2/16

Because of this, variables cannot vary. Once you set a variable, it stays

that way forever (note, in purely functional languages they are not

called variables). Because of this, functions have no side eects in the

functional paradigm. A side eect is where the function changes

something outside of it. Let’s look at an example of some typical Python

code:

The output for this code is 5. In the functional paradigm, changing

variables is a big no-no and having functions aect things outside of

their scope is also a big no-no. The only thing a function can do is

calculate something and return it as a result.

Now you might be thinking: “no variables, no side eects? Why is this

good?”. Good question, gnarly stranger reading this.

If a function is called twice with the same parameters, it’s guaranteed

to return the same result. If you’ve learnt about mathematical

functions, you’ll know to appreciate this benet. This is called

referential transparency. Because functions have no side eects, if you

are building a program which computes things, you can speed up the

program. If the program knows that func(2) equates to 3, we can store

this in a table. This prevents the program from repeatedly running the

same function when we already know the answer.

Typically, in functional programming, we do not use loops. We use

recursion. Recursion is a mathematical concept, usually, it means

“feeding into itself”. With a recursive function, the function repeatedly

calls itself as a sub-function. Here’s a nice example of a recursive

function in Python:

a = 3

def some_func():

global a

a = 5

some func()

def factorial_recursive(n):

# Base case: 1! = 1

if n == 1:

return 1

# Recursive case: n! = n * (n-1)!

2018/8/18 Learn Functional Python in 10 Minutes – Hacker Noon

https://hackernoon.com/learn-functional-python-in-10-minutes-to-2d1651dece6f 3/16

Some programming languages are also lazy. This means that they don’t

compute or do anything until the very last second. If you write some

code to perform 2 + 2, a functional program will only calculate that

when you actually need to use the resultant. We’ll explore laziness in

Python soon.

. . .

Map

To understand map, let’s rst look at what iterables are. An iterable is

anything you can iterate over. Typically these are lists or arrays, but

Python has many dierent types of iterables. You can even create your

own objects which are iterable by implementing magic methods. A

magic method is like an API that helps your objects become more

Pythonic. You need to implement 2 magic methods to make an object

an iterable:

The rst magic method, “__iter__” or dunder iter (double underscore

iter) returns the iterative object, this is often used at the start of a loop.

Dunder next returns what the next object is.

Let’s go into a quick terminal session and check this out:

This will print

class Counter:

def __init__(self, low, high):

# set class attributes inside the magic metho

# for "inistalise"

self.current = low

self.high = high

def __iter__(self):

# first magic method to make this object iter

return self

def __next__(self):

# d i th d

for c in Counter(3, 8):

print(c)

2018/8/18 Learn Functional Python in 10 Minutes – Hacker Noon

https://hackernoon.com/learn-functional-python-in-10-minutes-to-2d1651dece6f 4/16

In Python, an iterator is an object which only has an __iter__ magic

method. This means that you can access positions in the object, but

cannot iterate through the object. Some objects will have the magic

method __next__ and not the __iter__ magic method, such as sets

(talked about later in this article). For this article, we’ll assume

everything we touch is an iterable object.

So now we know what an iterable object is, let’s go back to the map

function. The map function lets us apply a function to every item in an

iterable. Typically we want to apply a function to every item in a list,

but know that it’s possible for most iterables. Map takes 2 inputs, the

function to apply and the iterable object.

Let’s say we have a list of numbers like so:

[1, 2, 3, 4, 5]

And we want to square every number, we can write code like this:

Functional functions in Python are lazy. If we didn’t include the “list()”

the function would store the denition of the iterable, not the list itself.

We need to explicitly tell Python “turn this into a list” for us to use this.

w r

❤

map(function, iterable)

x = [1, 2, 3, 4, 5]

def square(num):

return num*num

i (li ( ( )))

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