Python Design Patterns - Anti

Neha Kumawat

5 months ago

Python Design Patterns - Anti | insideAIML
Table of Contents
  • Introduction
  • Important features of anti-patterns
  • Correctness
  • Maintainability
  • Example of anti-pattern


          Anti-patterns follow a strategy in opposition to predefined design patterns. The strategy includes common approaches to common problems, which can be formalized and can be generally considered as a good development practice. Usually, anti-patterns are opposite and undesirable. Anti- patterns are certain patterns used in software development, which are considered as bad programming practices.

Important features of anti-patterns

          Let us now see a few important features of anti-patterns.


         These patterns literally break your code and make you do wrong things. Following is a simple illustration of this −

class Rectangle(object):
def __init__(self, width, height):
self._width = width
self._height = height
r = Rectangle(5, 6)
# direct access of protected member
print("Width: {:d}".format(r._width))


          A program is said to be maintainable if it is easy to understand and modify as per the requirement. Importing module can be considered as an example of maintainability.

import math
x = math.ceil(y)
# or
import multiprocessing as mp
pool = mp.pool(8)

Example of anti-pattern

          Following example helps in the demonstration of anti-patterns −

def filter_for_foo(l):
   r = [e for e in l if e.find("foo") != -1]
   if not check_some_critical_condition(r):
      return None
   return r

res = filter_for_foo(["bar","foo","faz"])

if res is not None:
   #continue processing

def filter_for_foo(l):
   r = [e for e in l if e.find("foo") != -1]
   if not check_some_critical_condition(r):
      raise SomeException("critical condition unmet!")
   return r

   res = filter_for_foo(["bar","foo","faz"])
   #continue processing

except SomeException:
   i = 0
while i < 10:
   #we forget to increment i
Like the Blog, then Share it with your friends and colleagues to make this AI community stronger. 
To learn more about nuances of Artificial Intelligence, Python Programming, Deep Learning, Data Science and Machine Learning, visit our insideAIML blog page.
Keep Learning. Keep Growing. 

Submit Review