Mastering Pythonic Code: Top 3 Shortcuts For Faster Development

Become pythonic now — if this is your goal, this article is tailored for you!

The best of the best python developers know that writing clean, efficient, and maintainable code is key to their success. If you are reading this, it is likely because you want to improve your skillset in this language which will surely take you one step closer to reaching your goals.

Fortunately, Python provides several helpful shortcuts that can make their lives easier and their code better.

In this article, we’ll dive into three of these developer shortcuts that can help you write better code, faster:

1. Lambda Expressions

A lambda expression in Python is a small anonymous function that can have any number of arguments, but can only have one expression.

Sample Code

# Define a list of dictionary of name, gender, and age.
listOfPeople = [
  { 'Name': 'Kilo', 'Gender': 'Male', 'Age': 14 },
  { 'Name': 'Bella', 'Gender': 'Female', 'Age': 65},
]

# Perform filter on listOfPeople manually.
filtered = []

for dict in enumerate(listOfPeople):
  if (dict['Gender'] == 'Male' and dict['Age'] < 25):
    filtered.append(dict)

# Print and format output.
print(f"{filtered['Name']} is a {filtered['Age']} yr old {filtered['Gender']}.")

# Sample Output:
# Kilo is a 14 yr old Male.

The equivalent expression using a lambda expression is:

# Define a list of dictionary of name, gender, and age.
listOfPeople = [
  { 'Name': 'Kilo', 'Gender': 'Male', 'Age': 14 },
  { 'Name': 'Bella', 'Gender': 'Female', 'Age': 65},
]

# Lambda for filtering only male people under 25 years of age.
genderAndAge = lambda x: x['Gender'] == 'Male' and x['Age'] < 25

# Perform filter on listOfPeople using lambda.
filtered = list(filter(genderAndAge, listOfPeople)
print(f"{filtered['Name']} is a {filtered['Age']} yr old {filtered['Gender']}.")

# Sample Output:
# Kilo is a 14 yr old Male.

2. List Comprehension

List comprehensions provide a concise way to create lists based on existing sequences or other iterables.

They allow you to create a new list by applying an expression to each element of an existing list, with optional filtering and mapping.

Sample Code

# Initialize a list with bunch of words.
words = ['apple', 'banana', 'pear', 'orange', 'kiwi', 'grape']
longWords = []

# Get the words longer than 3 characters.
for word in words:
  if len(word) > 3:
    longWords.append(word)

The equivalent expression using list comprehension is:

# Initialize a list with a bunch of words.
words = ['apple', 'banana', 'pear', 'orange', 'kiwi', 'grape']

# Use list comprehension to get the words longer than 3 characters.
longWords = [word for eachWord in words if len(word) > 3]

3. Ternary Operator

The ternary operator provides a shorthand way of writing an if-else statement in a single line of code.

Sample Code

# Check if the number is even.
num = 5
result = ""

if (num % 2 == 0):
  result = "Even"
else:
  result = "Odd"

The equivalent expression using ternary operators is:

# Check if the number is even using ternary operator.
num = 5
result = "Even" if num % 2 == 0 else "Odd"

Conclusion

In conclusion, mastering Pythonic code is an essential skill for any developer who wants to write clean code. By using these shortcuts, you can simplify complex tasks, reduce the number of lines of code, and improve the readability of your codebase.

So, whether you’re a beginner or an experienced developer, take the time to learn these shortcuts and incorporate them into your Python code to write more Pythonic code that’s efficient, readable, and a joy to work with.

If you would like an article that is more advanced in its shortcuts, leave a response and I will be sure to make a second part that is targeted at more seasoned developers.