HashMap Basics 10 XP Easy

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A Hash Map (dictionary in Python) is perhaps the MOST important data structure in coding interviews. It gives O(1) average lookup! 🗂️

💡 Think of it like this: Imagine a library where every book has a unique code. Instead of searching every shelf, you type the code into a computer and it tells you the EXACT location instantly. That's a hash map — it maps keys to values in constant time!

# Python dictionary = hash map
phonebook = {
    'Alice': '555-1234',
    'Bob': '555-5678',
    'Charlie': '555-9999'
}

print(phonebook['Alice'])      # '555-1234' — O(1) lookup!
phonebook['Dave'] = '555-0000'  # Add new entry — O(1)
print('Bob' in phonebook)       # True — O(1) check
del phonebook['Charlie']        # Delete — O(1)

Hash Map operations (all O(1) average):

📖 Lookup: d[key] or d.get(key, default)
✏️ Insert/Update: d[key] = value
🗑️ Delete: del d[key]
🔍 Check existence: key in d

The #1 pattern: "Have I seen this before?" — Store things as you go and check for them in O(1):

# Two Sum — the quintessential hashmap problem
def twoSum(nums, target):
    seen = {}  # val → index
    for i, num in enumerate(nums):
        complement = target - num
        if complement in seen:          # Seen before? Match!
            return [seen[complement], i]
        seen[num] = i                    # Remember this number

If you see a problem asking about counting, grouping, finding duplicates, or pairing — think hash map first!

📋 Instructions

Create a dictionary that maps fruit names to their colors: - 'apple' → 'red' - 'banana' → 'yellow' - 'grape' → 'purple' Then print the color of 'banana' using the dictionary.

Create the dictionary with {} syntax, then access with dict['banana']. You've got this — take it step by step!

🧪 Test Cases

Input

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Expected

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Expected program output

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main.py

Hi! I'm Rex 👋

Output

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