Dictionary & Set Comprehensions

Dictionary comprehension pattern

A dictionary comprehension builds a dict in one pass.

python
squares = {n: n * n for n in range(5)}

Filtering in a dict comprehension

You can include only the items that match a condition.

python
scores = {"A": 95, "B": 70, "C": 88}
passed = {k: v for k, v in scores.items() if v >= 80}

Transforming keys or values

You can change keys, values, or both.

python
names = ["Ali", "Mona"]
lengths = {name: len(name) for name in names}

Inverting a dictionary

Swap keys and values carefully.

python
original = {"a": 1, "b": 2}
inverted = {v: k for k, v in original.items()}

If two keys share the same value, the last one wins.

Frequency maps (simple version)

python
text = "banana"
counts = {ch: text.count(ch) for ch in set(text)}

This is fine for small strings. For large data, a loop is faster.

Set comprehensions

Use a set comprehension when you want unique results.

python
words = ["hello", "hi", "world"]
lengths = {len(w) for w in words}

Common mistakes to avoid

• Forgetting to use items() when you need keys and values.
• Inverting a dict without thinking about duplicates.
• Using a list comprehension when you want a dict or set.

What you should understand after this lesson

• How to build dicts and sets with comprehensions.
• How to filter and transform data in one line.
• When a comprehension is helpful and when it is not.