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Python One Line Ternary

Ternary (from Latin ternarius) is an adjective meaning “composed of three items”. (source) So, literally, the ternary operator in Python is composed of three operands.

Syntax: The three operands are written in an intuitive combination ... if ... else ....

<On True> if <Condition> else <On False>
Operand Description
<On True> The return expression of the operator in case the condition evaluates to True
<Condition> The condition that determines whether to return the <On True> or the <On False> branch.
<On False> The return expression of the operator in case the condition evaluates to False
Operands of the Ternary Operator

Let’s have a look at a minimum example in our interactive code shell:

Exercise: Run the code and input your age. What’s the output? Run the code again and try to change the output!

Let’s dive into the different variants of the Ternary operator in Python!

Python Ternary Examples

Let’s have a quick overview of a few examples on different methods to use the ternary operator:

age = 17 # Method 1: Basic Ternary
print('wtf' if age<20 else 'What?') 'wtf' # Method 2: Ternary Tuple
# (onFalse, onTrue) [condition]
print(('wtf', 'What?') [age<20]) 'What?' # Method 3: Ternary Dictionary
# Use Dictionary True/False values
print({True: 'wtf', False: 'What?'} [age<20]) 'wtf' # Method 4: Ternary Lambda
# Lambda function with 0 arguments
# Execute only one branch expression --> more efficient
print((lambda: 'wtf', lambda:'What?') [age<20]()) 'What?'

Some of them are pretty confusing, right? Stay with me for a moment because you’ll learn about each of those next! 🙂

Python Ternary Tuple

Python Ternary Dictionary

Python Ternary Lambda

Python Ternary Multiple Lines

Python Ternary Elif

Python Ternary Nested

Python Ternary Plot

Python Ternary Diagram

Python Ternary Evaluation Order

Python Ternary Try Except

Python Ternary Tree

Python Ternary in List Comprehension

Python Ternary Pep8 Pythonic

Python Ternary Can’t Assign to Conditional Expression

Python Ternary For Loop

Python Ternary Break

Python Ternary None

Python Ternary Multiple Conditions

Where to Go From Here?

Enough theory, let’s get some practice!

To become successful in coding, you need to get out there and solve real problems for real people. That’s how you can become a six-figure earner easily. And that’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs?

Practice projects is how you sharpen your saw in coding!

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Then become a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.

Join my free webinar “How to Build Your High-Income Skill Python” and watch how I grew my coding business online and how you can, too—from the comfort of your own home.

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Python One-Liners Book

Python programmers will improve their computer science skills with these useful one-liners.

Python One-Liners

Python One-Liners will teach you how to read and write “one-liners”: concise statements of useful functionality packed into a single line of code. You’ll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert.

The book’s five chapters cover tips and tricks, regular expressions, machine learning, core data science topics, and useful algorithms. Detailed explanations of one-liners introduce key computer science concepts and boost your coding and analytical skills. You’ll learn about advanced Python features such as list comprehension, slicing, lambda functions, regular expressions, map and reduce functions, and slice assignments. You’ll also learn how to:

•  Leverage data structures to solve real-world problems, like using Boolean indexing to find cities with above-average pollution
•  Use NumPy basics such as array, shape, axis, type, broadcasting, advanced indexing, slicing, sorting, searching, aggregating, and statistics
•  Calculate basic statistics of multidimensional data arrays and the K-Means algorithms for unsupervised learning
•  Create more advanced regular expressions using grouping and named groups, negative lookaheads, escaped characters, whitespaces, character sets (and negative characters sets), and greedy/nongreedy operators
•  Understand a wide range of computer science topics, including anagrams, palindromes, supersets, permutations, factorials, prime numbers, Fibonacci numbers, obfuscation, searching, and algorithmic sorting

By the end of the book, you’ll know how to write Python at its most refined, and create concise, beautiful pieces of “Python art” in merely a single line.

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