2024-09-09
Python Best Practices: Writing Clean, Efficient, and Maintainable Code
Master Python with comprehensive coverage of best practices, design patterns, and advanced features for professional development.
Python's simplicity and power make it one of the most popular programming languages. This guide covers best practices, design patterns, and advanced features that will elevate your Python code from functional to professional.
Code Style and PEP 8
Follow PEP 8 guidelines for consistent, readable code:
# Good: Clear naming and proper spacing
def calculate_total_price(items: list[float], tax_rate: float) -> float:
"""Calculate total price including tax."""
subtotal = sum(items)
tax_amount = subtotal * tax_rate
return subtotal + tax_amount
# Bad: Poor naming and formatting
def calc(x,tr):
s=sum(x)
return s+s*tr
Pythonic Patterns
List Comprehensions
# Pythonic way
squares = [x**2 for x in range(10) if x % 2 == 0]
# Instead of
squares = []
for x in range(10):
if x % 2 == 0:
squares.append(x**2)
Context Managers
# Always use context managers for resources
with open('file.txt', 'r') as f:
content = f.read()
# Custom context manager
from contextlib import contextmanager
@contextmanager
def database_connection():
conn = create_connection()
try:
yield conn
finally:
conn.close()
Type Hints and Documentation
from typing import Optional, Union, List, Dict
from dataclasses import dataclass
@dataclass
class User:
"""Represents a user in the system."""
name: str
email: str
age: Optional[int] = None
def process_users(
users: List[User],
filters: Optional[Dict[str, Union[str, int]]] = None
) -> List[User]:
"""
Process and filter users based on criteria.
Args:
users: List of User objects
filters: Optional filtering criteria
Returns:
Filtered list of users
"""
# Implementation here
pass
Performance Optimization
Use Built-in Functions
Built-in functions like map(), filter(), and sum() are optimized in C and faster than Python loops.
Leverage Generators
Use generators for memory-efficient iteration over large datasets.
Profile Before Optimizing
Use cProfile and timeit to identify actual bottlenecks before optimization.
Published on 2024-09-09 • Category: Programming
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