Python Coding Techniques and Programming Practices


Python Coding techniques and programming practices are  one of the features of a professional programmer. While writing  code to solve a problem programmer should make simple choices and  have to use basic techniques. This completely depends on the programmer's skill and expertise and how wisely he make choices.

Coding techniques are basically focused on improvising the readability and maintainability of the code. 

  • Readability of source code has a direct impact on the developer so, while coding one should try to write code that can make easy others read and understand.
  • Code  maintainability  focuses on making enhancements to existed software system such as adding new features, modifying existed features, fixing bugs and performance improvement easily.

Programming practices are  mainly focused on the performance of the code and its enhancements.

Coding Techniques:

 coding techniques serve developers as a guide for developing a standard code for a software system. These are categorised into three sections.

  1. Names
  3. Format


  Names are most influenceable part  to understand the logical flow or concept of the code what it mean to be or what it  do . ( use related words as variables )

  •  Camel case Notation :  variable name is formed with more than a single word  next words begin with a uppercase letter so that we can identify words.
    • Class level varibale names should starts with uppercase letters
    • attribute, method names should starts with lowercase  letters
    • Examples:   isActive, UserRegistration(class), UserLogin, totalPrice, userDetails(attribute), calculateDiscount(method) 
  • Delemeter Notation :  variable name is formed with multile words , these words use a delemeter to join and form variable.
    • in genereal  "_" is used as delimeter.
    •  is_active, User_Registration(class), User_Login, total_price, user_details(attribute), calculate_discount(method)
  • Tips: 
    • variable names should be as small as possible and meaningful
    • don't use nagative logic for varibales names (ex: is_not_logged_in )
    • think 3-4 minutes about variable names.


  • comments are used in coding for writing help text
  • comments provide a short description of the code
  • use comments when they are needed don't write comments on unnecessary things

Format :

It is very important when we are coding for larger projects because the code is altered by a team. so, programmer should format the code in such way that others can easily debug the code and can modify it easily. 

  • Don't write clumsy code use line breaks wherever required or use variables. It makes the code more readable.
  • Use proper indentation

  follow  pep8 standards  

Python code optimizations:

1. Looping over numbers:

result = []
for i in range(100):
     if  i% 5 == 0:

Final output: 
result = 
[0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95]

Better way

result = range(0,100,5)
# range(start, end, step)


2.  Looping over a list

colours = ['red', 'green', 'blue', 'yellow']
for i in range(len(colours)):
     print colours[i]

Better way

for colour in colours:
     print colour

3. Looping over a list and its idices

for i in range(len(colours)):
     print i, '-->', colours[i]

Better way

for i, colour in enumerate(colours):
     print i, '-->', colour

4. Looping backwards

for i in range(len(colours), -1, -1, -1):
     print colours[i]

Better way

for colour in reversed(colours):
      print colour


5. sorting  in ascending order

for colour in sorted(colours):
     print colour

6. sorting in descending order

for colour in sorted(colours, reversed=True): 
     print colour

7. looping over two collections 

names = ['Anji', 'Ben', 'Catherin']
colours = ['red', 'green', 'blue', 'yellow']
n = min(len(colours), len(names))
for i in range(n):
     print names[i], '-->', colours[i]

Better way

for name, colour in zip(names, colours):
      print name, '-->', colour

8. looping over dictionary keys and values

for key in dict:
    print key, '-->', d[key]

Better way

for key, value in dict.items():
     print key, value

Best way

for key, value  in dict.iteritems():
     print key, '-->', value 

10. construct a dictionary from two lists

names = ['Steve Jobs','Bill Gates ','Jeff Bezos']
org = ['Apple', 'Microsoft', 'Amazon']
d = dict(zip(names, org))

Better way

from itertools import izip
d = dict(izip(names, org))

izip is faster than zip,   zip computes all the list at once, izip computes the elements only when requested. One important difference is that 'zip' returns an actual list, 'izip' returns an 'izip object', which is not a list and does not support list-specific features (such as indexing).

11. using comparison operator 

is_master = None
if role == 'master':
    is_master = True
    is_master =  False

Best way 

is_master = role == 'master'

note: comparison operator always returns a boolean[True, False]

12. achieve  switch/case in python with dict

def switch(case):
      cases = {1: 'case 1',
                    2: 'case 2',
                    3: 'case 3'}
         return cases.get(case, "default")

13. convert  a list of strings to numbers

str_numbers = ['1', '2', '3', '4', '5', '6', '7', '8', '9']
numbers = []
for i in str_numbers:

Best way 

numbers = map(int, str_numbers)

14. multiplying numbers  a list of numbers

numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9]
result = 1
for num in numbers:
     result  *= num

Best way is 

def multiply(a, b):
      return a*b
result = reduce(multiply, numbers)

15. finding multiples of 3  from a random set of numbers

numbers = [2, 7, 5, 4, 6, 1, 8, 9, 7, 3, 7, 5, 9, 3, 8, 4, 9, 6, 8, 5, 9, 7, 2, 6, 8, 8, 7, 6, 5, 9, 1, 1, 5, 5, 7, 4, 1, 0, 1, 1, 5, 4, 8, 4, 8, 7, 7, 8, 0, 1, 6, 8, 4]
list = []
for num in numbers:
      if num % 3 == 0:
            list.append( num )

Better way is 

def devide3(n):
      return n%3 == 0
list = filter(devide3, numbers)

Posted On 12 June 2014 By MicroPyramid

About Micropyramid

Micropyramid is a software development and cloud consulting partner for enterprise businesses across the world. We work on python, Django, Salesforce, Angular, Reactjs, React Native, MySQL, PostgreSQL, Docker, Linux, Ansible, git, amazon web services. We are Amazon and salesforce consulting partner with 5 years of cloud architect experience. We develop e-commerce, retail, banking, machine learning, CMS, CRM web and mobile applications.

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