Python Dictionary Comprehensions

Let’s Talk About Building Dictionaries Quickly

We know how to create a dictionary. We write out the key-value pairs.

squares = {1: 1, 2: 4, 3: 9, 4: 16}

That works. But what if we want to build a dictionary from some data? Like a list of numbers? Or from another dictionary?

We could write a loop.

numbers = [1, 2, 3, 4, 5]
squares = {}
for n in numbers:
    squares[n] = n * n
print(squares)

{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

That works. But it takes four lines. And it is a bit repetitive.

Python has a shortcut for this. It is called a dictionary comprehension.

What Is a Dictionary Comprehension in Python?

A dictionary comprehension is a way to create a dictionary in one line. We describe what keys and values we want. And Python builds the dictionary for us.

It is just like a list comprehension, but for dictionaries.

The Basic Syntax of Python Dictionary Comprehension

{key_expression: value_expression for item in iterable}

• key_expression — what we want as the key
• value_expression — what we want as the value
• item — the variable that takes each value from the iterable
• iterable — the sequence we are looping over

Let’s see a simple example.

numbers = [1, 2, 3, 4, 5]
squares = {n: n * n for n in numbers}
print(squares)

{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

One line. Same result. Much cleaner.

Adding a Condition to Python Dictionary Comprehension

We can add an if to filter items. Only items that satisfy the condition are included.

numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_squares = {n: n * n for n in numbers if n % 2 == 0}
print(even_squares)

{2: 4, 4: 16, 6: 36, 8: 64, 10: 100}

Only even numbers are included. The odd ones are skipped.

We can use any condition.

words = ["apple", "banana", "cherry", "date"]
long_words = {w: len(w) for w in words if len(w) > 5}
print(long_words)

{'banana': 6, 'cherry': 6}

If and Else in Python Dictionary Comprehension

We can also use if and else together. But the syntax is a bit different. The if-else goes before the for.

numbers = [1, 2, 3, 4, 5]
labels = {n: ("even" if n % 2 == 0 else "odd") for n in numbers}
print(labels)

{1: 'odd', 2: 'even', 3: 'odd', 4: 'even', 5: 'odd'}

Here, for each number, we choose the label “even” or “odd”. The condition is n % 2 == 0. If true, “even”. If false, “odd”.

That is the ternary operator inside a comprehension. It works, but let’s not make it too complex.

Building a Dictionary from Two Lists in Python

A very common use case is building a dictionary from two lists. One list of keys. One list of values.

keys = ["name", "age", "city"]
values = ["Alex", 25, "London"]

person = {k: v for k, v in zip(keys, values)}
print(person)

{'name': 'Alex', 'age': 25, 'city': 'London'}

The zip() function pairs up the items from both lists. Then the comprehension builds the dictionary.

That is a very handy pattern.

Swapping Keys and Values in Python Dictionary Comprehension

We can swap keys and values in a dictionary.

original = {"a": 1, "b": 2, "c": 3}
swapped = {v: k for k, v in original.items()}
print(swapped)

{1: 'a', 2: 'b', 3: 'c'}

That is a clean way to invert a dictionary. Just let’s be careful if values are not unique. Because keys must be unique.

Filtering a Dictionary in Python

We can filter a dictionary based on conditions.

scores = {"Alex": 85, "Sam": 92, "John": 78, "Emma": 95}
high_scores = {name: score for name, score in scores.items() if score >= 90}
print(high_scores)

{'Sam': 92, 'Emma': 95}

Only the students with scores 90 or above are included.

Transforming Values in Python Dictionary Comprehension

We can transform values while building a new dictionary.

prices = {"apple": 1.50, "banana": 0.75, "cherry": 3.00}
discounted = {item: price * 0.9 for item, price in prices.items()}
print(discounted)

{'apple': 1.35, 'banana': 0.675, 'cherry': 2.7}

Every price is reduced by 10%.

Python Dictionary Comprehension: A Real-Life Example

Let’s say we have a list of words. And we want to build a dictionary where the word is the key and the length is the value. But only for words longer than 3 characters.

words = ["cat", "elephant", "dog", "butterfly", "ant"]
word_lengths = {word: len(word) for word in words if len(word) > 3}
print(word_lengths)

{'elephant': 8, 'butterfly': 9}

That is clean and easy.

Another Example — Counting Characters

text = "hello"
char_count = {char: text.count(char) for char in set(text)}
print(char_count)

{'h': 1, 'e': 1, 'l': 2, 'o': 1}

We use set(text) to get unique characters. Then for each character, we count how many times it appears.

That is a nice one-liner.

Nested Dictionary Comprehension in Python

We can have a dictionary comprehension inside another. But let’s be careful. It can get confusing.

matrix = [[1, 2], [3, 4], [5, 6]]
flat = {i: j for i, row in enumerate(matrix) for j in row}
print(flat)

{0: 2, 1: 4, 2: 6}

Wait. That is not what we might expect. Let me explain.

The enumerate(matrix) gives (0, [1,2]), (1, [3,4]), (2, [5,6]).

For each pair, we loop over row. So for the first row, i=0, and j takes 1 and 2. The dictionary gets 0: 1 then 0: 2. The last one wins. So 0 ends up with 2.

Then i=1, j takes 3 and 4. So 1: 4. And so on.

So the result is {0: 2, 1: 4, 2: 6}. That is probably not what we wanted. But it shows how nested comprehensions work.

For flattening, we would just use a list comprehension. Dictionary comprehensions are for creating dictionaries.

When to Use Dictionary Comprehensions in Python

Use them when:

• We are building a new dictionary from an iterable.
• The logic is simple (one key expression, one value expression, maybe one condition).
• We want cleaner, more readable code.

Do not use them when:

• The logic is complex.
• We need multiple statements.
• The comprehension becomes hard to read.

Readability matters more than shortness. If a loop is clearer, let’s use a loop.

Common Mistakes with Python Dictionary Comprehensions

squares = {n n * n for n in numbers}   # Error!

squares = {n: n * n for n in numbers}

labels = {n: if n % 2 == 0 "even" else "odd" for n in numbers}   # Error!

labels = {n: ("even" if n % 2 == 0 else "odd") for n in numbers}

words = ["apple", "banana", "apple"]
lengths = {w: len(w) for w in words}
print(lengths)

{'apple': 5, 'banana': 6}

result = {k: v for k in list1 for v in list2 if k > 0 if v < 10}