Counting how often items appear in a list is a common programming task.
This challenge asks you to write a function that returns a frequency dictionary, mapping each item to the number of times it occurs.

It’s a simple problem—but one that appears everywhere in real-world code.

Your Task

Write a function that counts how many times each item appears in a list.

Function Signature

def count_items(items: list) -> dict:
…

Rules

1. The input must be a list.
2. Each item in the list must be hashable (so it can be used as a dictionary key).
3. Return a dictionary where:
   • Keys are the unique items
   • Values are the number of times each item appears
4. Return an empty dictionary for an empty list.
5. Raise a TypeError for invalid input.

Examples

count_items([1, 2, 2, 3])
# → {1: 1, 2: 2, 3: 1}
count_items(["a", "b", "a"])
# → {"a": 2, "b": 1}
count_items([])
# → {}

Invalid Input Examples

count_items("abc") # TypeError
count_items(None) # TypeError
count_items([1, [], 2]) # TypeError (unhashable item)

Hints

• Use a dictionary to keep track of counts.
• Check whether an item already exists in the dictionary.
• Increment carefully.

What This Challenge Teaches

• Iterating through lists
• Using dictionaries as counters
• Understanding hashable vs unhashable types
• Writing predictable data-processing functions

Bonus Challenges

• Ignore case when counting strings
• Return items sorted by frequency
• Rebuild the solution using collections.Counter
• Count items across multiple lists

Why This Matters

Counting is one of the most common operations in programming.
Mastering this pattern gives you a reusable tool that applies to text processing, analytics, data validation, and more.

Beginner Track Checkpoint (Important)

With Challenge #12, your Beginner Track is now complete:

1. Strings
2. Lists
3. Validation
4. Conditionals
5. Dictionaries
6. Frequency patterns

This is a solid, real beginner foundation — not fluff.

🔗 View reference solution on GitHub
(After you’ve tried the challenge)

👉Next Challenge →

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