It feels like I’m writing a grocery list, then driving to the store, then putting each item away one by one," Timothy muttered. He was looking at a block of code meant to filter and transform some sensor data.
Timothy’s "Assembly Line" Code:
squares = []
for n in range(10):
if n % 2 == 0:
squares.append(n**2)
Margaret looked over. "That’s because you are doing that. You’re manually managing the list, the loop, the filter, and the storage. It’s an assembly line. But what if you just ordered the finished product?"
The Problem: The Three-Level Deep Append
Margaret pasted Timothy’s code into the Python Structure Viewer.
Python Structure Viewer output:
=== TREE VIEW ===
squares = []
For n in range(10)
If n % 2 == 0
└── squares.append(n ** 2)
...It feels like I’m writing a grocery list, then driving to the store, then putting each item away one by one," Timothy muttered. He was looking at a block of code meant to filter and transform some sensor data.
Timothy’s "Assembly Line" Code:
squares = []
for n in range(10):
if n % 2 == 0:
squares.append(n**2)
Margaret looked over. "That’s because you are doing that. You’re manually managing the list, the loop, the filter, and the storage. It’s an assembly line. But what if you just ordered the finished product?"
The Problem: The Three-Level Deep Append
Margaret pasted Timothy’s code into the Python Structure Viewer.
Python Structure Viewer output:
=== TREE VIEW ===
squares = []
For n in range(10)
If n % 2 == 0
└── squares.append(n ** 2)
=== ENGLISH VIEW ===
Set squares to [].
For each n in range(10):
If n % 2 == 0:
Evaluate squares.append(n ** 2).
"Look at the indentation," Margaret said. "To get to the actual work—the squares.append—you have to go three levels deep. Your logic is scattered. If someone reads this, they have to keep track of an empty list and wait for the loop to finish to see what actually happens to it."
The Solution: Structural Transformation
"Python allows you to collapse that entire process into a single structural unit," Margaret said. "Beyond just looking cleaner, this single-unit structure allows Python to optimize the operation more effectively."
She refactored the code into a List Comprehension.
The Structured Python Snippet:
squares = [n**2 for n in range(10) if n % 2 == 0]
She ran it through the Viewer.
Python Structure Viewer output:
=== TREE VIEW ===
squares =
Comprehension: n ** 2
For n in range(10)
If n % 2 == 0
=== ENGLISH VIEW ===
Set squares to:
List comprehension: n ** 2
For each n in range(10)
If n % 2 == 0
Timothy leaned in. "The Viewer changed how it describes the assignment. It’s not just ‘Set squares to a list’ anymore. It says ‘Set squares to... the result of this whole operation.’"
"Exactly," Margaret nodded. "The assembly line requires you to track the product as it moves and changes. The factory mold is the product’s definition. By moving the ‘If’ and ‘For’ inside the comprehension, you collapse the process into its specification."
The "Factory" Metaphor
"So," Timothy said, "the first version is like building a car by hand on a floor—frame first, then engine, then wheels. But the comprehension is like a factory mold. I define the mold, and the car comes out finished in one piece."
"Perfectly stated," Margaret said. "You’ve reduced the cognitive load because the reader doesn’t have to track a ‘mutating’ list. They just see the definition of the final result."
Timothy looked at his 4-line loop and then back at the single-line comprehension. "It’s not about typing less. It’s about the logic being in one place."
"Now you’re thinking structurally," Margaret smiled.
Analyze Python structure yourself
Download the Python Structure Viewer — a free tool that shows code structure in tree and plain English views. Works offline, no installation required.
Aaron Rose is a software engineer and technology writer at tech-reader.blog and the author of Think Like a Genius.