Examples of usages of functions in Python tutorial _python

This paper takes the numerical calculation as an example to explain the use of functions in Python and share them for reference. Specifically as follows:

We all know that the area of the circle is calculated by:

S =ΠR2

When we know the value of radius r, we can calculate the area according to the formula. Let's say we need to calculate the size of 3 circles of different sizes:

R1 = 12.34
r2 = 9.08 R3 = 73.1 S1 = 3.14 * R1 * R1 s2 = 3.14 * R2 * R2
s3 = 3.14 * R3 * * R3

When the code is regularly repeated, you need to be careful, write 3.14 * x x is not only very troublesome, and if you want to change 3.14 to 3.14159265359, you have to replace it all.

With a function, we no longer write the S = 3.14 * x x each time, but rather write a more meaningful function call S = area_of_circle (x), and the function area_of_circle itself can be invoked multiple times only once.

Basically all the high-level languages support functions, and Python is no exception. Python not only has the flexibility to define functions, but it also has built-in many useful functions that can be invoked directly.

Abstract

Abstraction is a very common concept in mathematics. As an example:

Calculation of the sum of the series, such as: 1 + 2 + 3 + ... + 100, writing is very inconvenient, so mathematicians invented the summation symbol ∑, can be 1 + 2 + 3 + ... + 100:

∑n
N=1

This kind of abstract notation is very powerful, because we see ∑ can be understood as summation, rather than reduced to lower-level addition operations.

Moreover, this abstract notation is extensible, such as:

∑ (n2+1)
n=1

The reduction into the addition operation becomes:

(1 x 1 + 1) + (2 x 2 + 1) + (3 x 3 + 1) + ... + (x 100 + 1)

Visible, with the aid of abstraction, we can not care about the bottom of the specific calculation process, and directly at a higher level of thinking.

Writing a computer program is the same as a function is the most basic way of code abstraction. Flexible application helps to improve programming efficiency.

I hope the examples described in this article will help you with Python programming.