Use Comprehension Chain

use-comprehension-chain

When to Use

• Transforming sequences (map)
• Filtering sequences
• Building dicts or sets from data
• Combining filter + map
• Creating lookup tables

When NOT to Use

• Complex logic that needs multiple statements
• Side effects needed during iteration
• Code would be unreadable as one-liner

The Pattern

Use comprehensions for concise, readable data transformation.

# List comprehension: map + filter
squares = [x**2 for x in range(10)]
evens = [x for x in numbers if x % 2 == 0]
even_squares = [x**2 for x in numbers if x % 2 == 0]

# Dict comprehension: build lookup tables
word_lengths = {word: len(word) for word in words}
index = {item: i for i, item in enumerate(items)}
inverted = {v: k for k, v in original.items()}

# Set comprehension: unique values
unique_lengths = {len(word) for word in words}

# Nested comprehension: flatten or cross product
flat = [x for row in matrix for x in row]
pairs = [(x, y) for x in xs for y in ys]

# Conditional expression in comprehension
signs = ['pos' if x > 0 else 'neg' if x  1]

Key Principles

1. One line, one transformation: Keep it readable
2. Left to right: [expr for var in seq if cond]
3. Nested = flatten: Inner loop varies fastest
4. Dict for lookups: O(1) access pattern
5. Set for uniqueness: Auto-deduplicate

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: jimmc414
• Source: jimmc414/claude-code-plugin-marketplace
• License: MIT

Install and usage instructions live in the source repository linked above.