Python Best Practices: Writing Clean and Maintainable Code

The Zen of Python

ByOscar Dyremyhr
~ 4 min read

Python is known for its simplicity and readability, making it an excellent choice for beginners and experts alike. However, writing Python code that is not only functional but also clean and maintainable requires following certain best practices. This is often referred to as The Zen of Python, a set of guideline principles. You can read the 19 of them them by importing this in python.

1import this 2 3# Output 4 5Beautiful is better than ugly. 6Explicit is better than implicit. 7Simple is better than complex. 8Complex is better than complicated. 9Flat is better than nested. 10Sparse is better than dense. 11Readability counts. 12Special cases aren't special enough to break the rules. 13Although practicality beats purity. 14Errors should never pass silently. 15Unless explicitly silenced. 16In the face of ambiguity, refuse the temptation to guess. 17There should be one-- and preferably only one --obvious way to do it. 18Although that way may not be obvious at first unless you're Dutch. 19Now is better than never. 20Although never is often better than *right* now. 21If the implementation is hard to explain, it's a bad idea. 22If the implementation is easy to explain, it may be a good idea. 23Namespaces are one honking great idea -- let's do more of those! 24

Here are some key tips accompanied by code examples to help you write better Python code.

Use Descriptive Naming for Variables and Functions

Names should reflect purpose and context. Avoid vague names like list1 or doThing and opt for descriptive ones like customer_names or calculate_tax.

1# Bad Practice 2def calc(a, b): 3 return a * 1.1 + b 4 5# Good Practice 6def calculate_total_price(exclusive_price, tax_rate): 7 return exclusive_price * (1 + tax_rate) 8

Follow the PEP 8 Style Guide

PEP 8 is Python’s official style guide. It includes rules for formatting your code which helps maintain consistency and readability.

1# Bad Practice 2import sys, os 3 4def foo_bar(*args,**kwargs): print("Hello World") 5 6# Good Practice 7import os 8import sys 9 10def foo_bar(*args, **kwargs): 11 print("Hello World") 12

Leverage List Comprehensions for Conciseness

List comprehensions provide a concise way to create lists. Use them to write cleaner and more efficient code.

1# Bad Practice 2squared_numbers = [] 3for x in range(10): 4 squared_numbers.append(x * x) 5 6# Good Practice 7squared_numbers = [x * x for x in range(10)] 8

Utilize Docstrings for Documentation

Docstrings are a way to document your functions, methods, and classes.

1# Bad Practice 2def add(a, b): 3 return a + b 4 5# Good Practice 6def add(a, b): 7 """Add two numbers and return the result. 8 9 Args: 10 a (int/float): First number to add. 11 b (int/float): Second number to add. 12 13 Returns: 14 int/float: The sum of a and b. 15 """ 16 return a + b 17

Write Functions with a Single Functionality

Each function should have a single responsibility. This makes your code more testable and reusable.

1# Bad Practice 2def process_data(data): 3 # Multiple functionalities within a single function 4 pass 5 6# Good Practice 7def clean_data(data): 8 pass 9 10def analyze_data(data): 11 pass 12

Handle Exceptions with Specificity

Catching exceptions is crucial, but you should always aim to catch specific exceptions rather than all exceptions.

1# Bad Practice 2try: 3 risky_operation() 4except Exception as e: 5 pass 6 7# Good Practice 8try: 9 risky_operation() 10except ValueError as e: 11 pass 12

Use Underscores for Large Numbers

Underscores can be used for visual separation in large numbers, which makes them more readable.

1# Bad Practice 2number_of_stars = 1000000 3 4# Good Practice 5number_of_stars = 1_000_000 6

Avoid Global Variables

Global variables can make your code harder to understand and debug. Pass variables to functions as parameters instead.

1# Bad Practice 2counter = 0 3 4def increment(): 5 global counter 6 counter += 1 7 8# Good Practice 9def increment(counter): 10 return counter + 1 11

Use Context Managers for Resource Management

Context managers ensure resources are properly managed, for example when working with file operations.

1# Bad Practice 2file = open('example.txt', 'w') 3file.write('Hello, World!') 4file.close() 5 6# Good Practice 7with open('example.txt', 'w') as file: 8 file.write('Hello, World!') 9

By incorporating these best practices into your daily coding routine, you’ll improve not only the quality of your code but also your efficiency and effectiveness as a Python developer. Remember, writing code is often a collaborative effort, so clean and maintainable code is crucial for teamwork and long-term project success.

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