Python programming language is innocent and easy to comprehend and this is why many developers use it. Nevertheless, to come up with excellent Python code, there is a need to know more beyond syntax. It means implementing the standards and techniques that would govern the nature, quality, and sustenance of the code. Here are 7 of the best practices that will ease the methods of coding in Python programming language.
The PEP 8 is Python official style guide and it details how code in Python programming language should be written and code's nature, quality, and sustenance formatted. It prescribes rules for writing easily comprehensible code and avoiding repetition of style which may be juvenile or amateurish, specific to indentations, line breaks or spaces, names of variables or comments.
● There should be 4 spaces available to denote one indentation level.
Moreso, the number of lines in any particular paragraph should not exceed seventy nine characters.
Examples: Avoid leading CM_ on enums, use KMN_ instead of KML_ for logical condition variables.
● Give the post comments and docstrings here so as to explain the working of the code.
Structure your code into numerous, sortable functions and modules and go on abstractions so that you feel comfortable coding. This makes it easier to comprehend, assess for testing purposes and in turn fix when it is broken. The guidelines for good functions are revisited, with an emphasis on the fact that they should be both long and complex if at all possible.
● Use the function and the class and their combination as a tool in encapsulation of the function capabilities.
● Grouping related functions into modules promote orderliness of the program.
● Do not write the same code over and over again, use functions/subroutines and classes whenever they are needed.
The ones reported here are just a few of the many ready-made tools you can use in your Python programming, and all are part of Python’s standard library! As a start, you need to comprehend some core modules, including limited, random, datetime, os, sys, collections and itertools.
● Avoid coding from scratch whenever possible, or build a function for reusing code.
● Try to navigate into the standard library documentation as there can be several useful modules there.
Test-Driven Development (TDD) is a methodology where you write tests before writing the actual code. This helps ensure your code works as expected and reduces the likelihood of bugs.
● Write unit tests for your functions and classes.
● Use testing frameworks like unittest or pytest.
● Run tests frequently to catch issues early.
List comprehensions and generators provide a concise way to create lists and iterate over sequences. They make your code more readable and efficient.
● Use list comprehensions for simple list transformations.
● Use generators for large datasets to save memory.
● Avoid complex comprehensions that reduce readability.
This is because the selection of functions inside the Python language and the choice of complements that enable the alteration of the sequence of algorithm to be more efficient can really enhance the speed of a given algorithm.
● Android provides many efficient built-in functions like map(), filter() and sorted() functions that can be used for better performance.
● Losing element in a list: to handle this, you must pick the right data structures (such as list, set, dictionary etc. ).
● Incorporate fine-grained building blocks where possible and implement key areas with efficient algorithms.
Documentation is critical to code readability and it helps programmers to manage the source code with ease. Make comments or use comments along with Docstrings to make an explanation on the code you wrote along with how to use it.
● Ensure all modules, classes, functions, methods, etc., which are to be exported, contain descriptions in form of docstrings.
● Use comments effectively to explain any complicated logic used especially in programs that are a bit complicated to understand.
● Draw interfaces for the larger projects where the documentation will be shared outside of the company.