8. Comprehensions

Tutorial

Comprehensions are Python's most expressive feature — faster than equivalent for loops and DSA-critical for building grids, frequency tables, and coordinate-compressed arrays.

# ══ LIST COMPREHENSION ═════════════════════════════════════════
squares   = [x**2 for x in range(6)]
evens     = [x for x in range(10) if x % 2 == 0]
doubled   = [x * 2 for x in nums]
filtered  = [x if x > 0 else 0 for x in nums]  # conditional output

# Nested: flatten 2D
flat = [x for row in matrix for x in row]

# Build grid
grid = [[0] * cols for _ in range(rows)]

# ══ DICT COMPREHENSION ═════════════════════════════════════════
sq_map   = {x: x**2 for x in range(5)}
inverted = {v: k for k, v in d.items()}
filtered = {k: v for k, v in d.items() if v > 1}

# Coordinate compression (DSA essential)
vals = [30, 10, 50, 10, 20]
rank = {v: i for i, v in enumerate(sorted(set(vals)))}
compressed = [rank[v] for v in vals]   # [2, 0, 3, 0, 1]

# Build index map
idx_map = {v: i for i, v in enumerate(arr)}   # value → index

# ══ SET COMPREHENSION ══════════════════════════════════════════
unique_lens = {len(w) for w in words}
seen_chars  = {c.lower() for c in s if c.isalpha()}

# ══ GENERATOR EXPRESSIONS ══════════════════════════════════════
# Like list comprehension but lazy — no intermediate list in memory
total = sum(x**2 for x in range(10**6))
has_neg = any(x < 0 for x in nums)
all_pos = all(x > 0 for x in nums)
max_len = max(len(w) for w in words)

Reference

Type	Syntax	Returns
List	[expr for x in it if cond]	list
Dict	{k:v for x in it if cond}	dict
Set	{expr for x in it if cond}	set
Generator	(expr for x in it if cond)	lazy iterator
Nested flatten	[x for row in mat for x in row]	list
2D grid	[[0]*c for _ in range(r)]	list[list]
Conditional output	[a if cond else b for x in it]	list
Coord compress	{v:i for i,v in enumerate(sorted(set(arr)))}	dict

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