PEP 8 in Python | what is the purpose of PEP 8 in Python?

In this tutorial, we will learn what PEP-8 is and how we can use it in Python coding. We will discuss the guidelines for using PEP in programming-this tutorial is aimed at beginners to intermediate. We will also discuss the benefits of using PEP-8 while coding.

What is PEP?

The PEP is an abbreviation form of Python Enterprise Proposal. Writing code with proper logic is a key factor of programming, but many other important factors can affect the code’s quality. The developer’s coding style makes the code much reliable, and every developer should keep in mind that Python strictly follows the way of order and format of the string.

Adaptive a nice coding style makes the code more readable. The code becomes easy for end-user.

PEP 8 is a document that provides various guidelines to write the readable in Python. PEP 8 describes how the developer can write beautiful code. It was officially written in 2001 by Guido van Rossum, Barry Warsaw, and Nick Coghlan. The main aim of PEP is to enhance the readability and consistency of code.

Why PEP 8 is Important?

PEP 8 enhances the readability of the Python code, but why is readability so important? Let’s understand this concept.

Creator of Python, Guido van Rossum said, “Code is much more often than it is written.” The code can be written in a few minutes, a few hours, or a whole day but once we have written the code, we will never rewrite it again. But sometimes, we need to read the code again and again.

At this point, we must have an idea of why we wrote the particular line in the code. The code should reflect the meaning of each line. That’s why readability is so much important.

We will describe few important guidelines for writing effective code that can be read by others as well.

Naming Convention

When we write the code, we need to assign name to many things such as variables, functions, classes, packages, and a lot more things. Selecting a proper name will save time and energy. When we look back to the file after sometime, we can easily recall what a certain variable, function, or class represents. Developers should avoid choosing inappropriate names.

The naming convention in Python is slightly messy, but there are certain conventions that we can follow easily. Let’s see the following naming convention.

Example –

Single lowercase letter

<br />
a = 10<br />

Single upper case letter

<br />
A = 10<br />

Lowercase

<br />
var = 10<br />

Lower_case_with_underscores

<br />
number_of_apple = 5<br />

UPPERCASE

<br />
VAR = 6<br />

UPPER_CASE_WITH_UNDERSCORES

<br />
NUM_OF_CARS =20<br />

CapitalizedWords (or CamelCase)

<br />
NumberOfBooks = 100<br />

Note: While using abbreviations in CapWords, capitalize all the letters of the abbreviation. Thus HTTPServerError is better than HttpServerError.

Name Style

Below is the table that specifies some of the common naming styles in Python. Consider the following table.

Type	Naming Convention	Examples
Function	We should use the lowercase words or separates words by the underscore.	myfunction, my_function
Variable	We should use a lowercase letter, words, or separate words to enhance the readability.	a, var, variable_name
Class	The first letter of class name should be capitalized; use camel case. Do not separate words with the underscore.	MyClass, Form, Model
Method	We should use a lowercase letter, words, or separate words to enhance readability.	class_method, method
Constant	We should use a short, uppercase letter, words, or separate words to enhance the readability.	MYCONSTANT, CONSTANT, MY_CONSTANT
Module	We should use a lowercase letter, words, or separate words to enhance the readability.	Module_name.py, module.py
Package	We should use a lowercase letter, words, or separate words to enhance the readability. Do not separate words with the underscore.	package, mypackage,

Above are some common naming conventions that are useful to beautify the Python code. For additional improvement, we should choose the name carefully.

Code Layout

The code layout defines how much the code is readable. In this section, we will learn how to use whitespace to improve code readability.

Indentation

Unlike other programming languages, the indentation is used to define the code block in Python. The indentations are the important part of the Python programming language and it determines the level of lines of code. Generally, we use the 4 space for indentation. Let’s understand the following example.

Example –

<br />
x = 5<br />
if x ==  5:<br />
    print(‘x is larger than 5’)<br />

In the above example, the indented print statement will get executed if the condition of if statement is true. This indentation defines the code block and tells us what statements execute when a function is called or condition trigger.

Tabs vs. Space

We can also use the tabs to provide the consecutive spaces to indicate the indentation, but whitespaces are the most preferable. Python 2 allows the mixing of tabs and spaces but we will get an error in Python 3.

Indentation following Line Break

It is essential to use indentation when using line continuations to keep the line to fewer than 79 characters. It provides the flexibility to determining between two lines of code and a single line of code that extends two lines. Let’s understand the following example.

Example –

<br />
# Correct Way:</p>
<p># Aligned with opening delimiter.<br />obj = func_name(argument_one, argument_two,<br />                         argument_three, argument_four<br />

We can use the following structure.

<br />
# first line doesn’t has any argument<br />
# We add 4 spaces from the second line to discriminate arguments from the rest.<br />
def function_name(<br />
        argument_one, argument_two, argument_three,<br />
        argument_four):<br />
    print(argument_two)</p>
<p># 4 space indentation to add a level.<br />foo = long_function_name(<br />    var_one, var_two,<br />    var_three, var_four)<br />

Use docstring

Python provides the two types of document strings or docstring – single line and multiple lines. We use the triple quotes to define a single line or multiline quotes. Basically, these are used to describe the function or particular program. Let’s understand the following example.

Example –

<br />
def add(a, b):<br />
    “””This is simple add method”””</p>
<p>    “””This is<br />    a<br />   simple add program to add<br />   the two numbers. “””<br />

Should a Line Break Before or After a Binary Operator?

The lines break before or after a binary operation is a traditional approach. But it affects the readability extensively because the operators are scattered across the different screens, and each operator is kept away from its operand and onto the previous line. Let’s understand the following example.

Example –

<br />
# Wrong:<br />
# operators sit far away from their operands<br />
marks = (engilsh_marks +<br />
          math_marks +<br />
          (science_marks – biology_marks) +<br />
          Physics_marks<br />

As we can see in the above example, it seems quite messy to read. We can solve such types of problems by using the following structure.

Example –

<br />
# Correct:<br />
# easy to match operators with operands<br />
Total_marks = (English_marks<br />
          + math_marks<br />
          + (science_marks – biology_marks)<br />
          + physics_marks<br />

Python allows us to break line before or after a binary operator, as long as the convention is consistent locally.

Importing module

We should import the modules in the separates line as follows.

<br />
import pygame<br />
import os<br />
import sys<br />

Wrong

<br />
import sys, os<br />

We can also use the following approach.

<br />
from subprocess import Popen, PIPE<br />

The import statement should be written at the top of the file or just after any module comment. Absolute imports are the recommended because they are more readable and tend to be better behaved.

<br />
import mypkg.sibling<br />
from mypkg import sibling<br />
from mypkg.sibling import example<br />

However, we can use the explicit relative imports instead of absolutes imports, especially dealing with complex packages.

Blank Lines

Blank lines can be improved the readability of Python code. If many lines of code bunched together the code will become harder to read. We can remove this by using the many blank vertical lines, and the reader might need to scroll more than necessary. Follow the below instructions to add vertical whitespace.

Top-level function and classes with two lines – Put the extra vertical space around them so that it can be understandable.

<br />
class FirstClass:<br />
    pass</p>
<p>class SecondClass:<br />    pass</p>
<p>def main_function():</p>
<p>    return None<br />

Single blank line inside classes – The functions that we define in the class is related to one another. Let’s see the following example –

<br />class FirstClass:<br />    def method_one(self):<br />        return None</p>
<p>    def second_two(self):<br />        return None<br />

Use blank lines inside the function – Sometimes, we need to write a complicated function has consists of several steps before the return statement. So we can add the blank line between each step. Let’s understand the following example.

<br />def cal_variance(n_list):<br />    list_sum = 0<br />    for n in n_list:<br />        list_sum = list_sum + n<br />    mean = list_sum / len(n_list)</p>
<p>    square_sum = 0<br />    for n in n_list:<br />        square_sum = square_sum + n**2<br />    mean_squares = square_sum / len(n_list)</p>
<p>    return mean_squares – mean**2<br />

The above way can remove the whitespaces to improve the readability of code.

Put the Closing Braces

We can break lines inside parentheses, brackets using the Line continuations. PEP 8 allows us to use closing braces in implies line continuations. Let’s understand the following example.

Line up the closing brace with the first non-whitespace.

<br />
    list_numbers = [<br />
    5, 4, 1,<br />
    4, 6, 3,<br />
    7, 8, 9<br />
     ]<br />

Line up the closing braces with the first character of line.

<br />
list_numbers = [<br />
    5, 4, 1,<br />
    4, 6, 3,<br />
    7, 8, 9<br />
]<br />

Both methods are suitable to use, but consistency is key, so choose any one and continue with it.

Comments

Comments are the integral part of the any programming language. These are the best way to explain the code. When we documented our code with the proper comments anyone can able to understand the code. But we should remember the following points.

Start with the capital latter, and write complete sentence.
Update the comment in case of a change in code.
Limit the line length of comments and docstrings to 72 characters.

Block Comment

Block comments are the good choice for the small section of code. Such comments are useful when we write several line codes to perform a single action such as iterating a loop. They help us to understand the purpose of the code.

PEP 8 provides the following rules to write comment block.

Indent block comment should be at the same level.
Start each line with the # followed by a single space.
Separate line using the single #.

Let’s see the following code.

<br />
for i in range(0, 5):<br />
    # Loop will iterate over i five times and print out the value of i<br />
    # new line character<br />
    print(i, ‘/n’)<br />

We can use more than paragraph for the technical code. Let’s understand the following example.

Inline Comments

Inline comments are used to explain the single statement in a piece of code. We can quickly get the idea of why we wrote that particular line of code. PEP 8 specifies the following rules for the inline comments.

Start comments with the # and single space.
Use inline comments carefully.
We should separate the inline comments on the same line as the statement they refer.

Following is the example of inline comments.

<br />
a = 10    # The a is variable that holds integer value.<br />

Sometimes, we can use the naming convention to replace the inline comment.

<br />
x = ‘Peter Decosta’ #This is a student name<br />

We can use the following naming convention.

<br />
Student_name = ‘Peter Decosta’<br />

Inline comments are essential but block comments make the code more readable.

Avoid Unnecessary Adding Whitespaces

In some cases, use of whitespaces can make the code much harder to read. Too much whitespaces can make code overly sparse and difficult to understand. We should avoid adding whitespaces at the end of a line. This is known as trailing whitespaces.

Let’s see the following example.

Example – 1

<br />
# Recommended<br />
list1 = [1, 2, 3]</p>
<p># Not recommended<br />List1 = [ 1, 2, 3, ]<br />

Example – 3

<br />
x = 5<br />
y = 6</p>
<p># Recommended<br />print(x, y)</p>
<p># Not recommended<br />print(x , y)<br />

Programming Recommendation

As we know that, there are several methods to perform similar tasks in Python. In this section, we will see some of the suggestions of PEP 8 to improve the consistency.

Avoid comparing Boolean values using the equivalence operator

<br />
# Not recommended<br />
bool_value = 10 > 5<br />
if bool_value == True:<br />
    return ’10 is bigger than 5′<br />

We shouldn’t use the equivalence operator == to compare the Boolean values. It can only take the True or False. Let’s see following example.

<br />
# Recommended<br />
if my_bool:<br />
    return ’10 is bigger than 5′<br />

This approach is simple that’s why PEP 8 encourages it.

Empty sequences are false in if statements

If we want to check whether a given list is empty, we might need to check the length of list, so we need to avoid the following approach.

<br />
# Not recommended<br />
list1 = []<br />
if not len(list1):<br />
    print(‘List is empty!’)<br />

However, if there is any empty list, set, or tuple. We can use the following way to check.

<br />
# Recommended<br />
list1 = []<br />
if not list1:<br />
    print(‘List is empty!’)<br />

The second method is more appropriate; that’s why PEP 8 encourages it.

Don’t use not is in if statement

There are two options to check whether a variable has a defined value. The first option is with x is not None, as in the following example.

<br />
# Recommended<br />
if x is not None:<br />
    return ‘x exists!’<br />

A second option is to evaluate x is None and if statement based on not the outcome.

<br />
# Not recommended<br />
if not x is None:<br />
    return ‘x exists!’<br />

Both options are correct but the first one is simple, so PEP 8 encourages it.

Conclusion

We have discussed the PEP 8 guidelines to make the code remove ambiguity and enhance readability. These guidelines improve the code, especially when sharing the code with potential employees or collaborators. We have discussed what PEP is and why it uses, how to write code that is PEP 8 compliant. Moreover, we have a brief introduction to the naming conventions. If you want more information regarding the PEP 8, you can read the full documentation or visit PEP8.org.

原创文章，作者：ItWorker，如若转载，请注明出处：https://blog.ytso.com/tech/courses/263538.html

PEP 8 in Python | what is the purpose of PEP 8 in Python?

PEP 8 in Python | what is the purpose of PEP 8 in Python?

What is PEP?

Why PEP 8 is Important?

Naming Convention

Note: While using abbreviations in CapWords, capitalize all the letters of the abbreviation. Thus HTTPServerError is better than HttpServerError.

Name Style

Code Layout

Indentation

Indentation following Line Break

Use docstring

Should a Line Break Before or After a Binary Operator?

Importing module

Blank Lines

Put the Closing Braces

Comments

Block Comment

Inline Comments

Avoid Unnecessary Adding Whitespaces

Programming Recommendation

Avoid comparing Boolean values using the equivalence operator

Empty sequences are false in if statements

Don’t use not is in if statement

Conclusion

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