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Dictionaries: Power & Speed

In Python, everything is a dictionary. Modules, classes, namespaces—it's all hash maps all the way down. Understanding the Dictionary is understanding Python itself.

A dict (Hash Map) is the most optimized data structure in Python. It maps unique Keys to Values.

Historically, dictionaries were unordered and memory-hungry. But in the Python 3.6+ era, a revolution called the "Compact Dict" changed everything. They are now ordered by insertion and use ~30% less RAM.

What You'll Learn

  • Modern Internals: How "Compact Dicts" work (Indices Array vs Entries Array).
  • Safe Access: Why .get() is better than brackets.
  • Merging: The modern | operator (Python 3.9+).
  • Performance: O(1) average lookup speed.

The Revolution: Compact Dicts

Before Python 3.6, a dictionary was a sparse table with lots of empty space. Now, Python splits simple storage into two parts:

  1. Indices Array: A small table mapping hash-to-index.
  2. Entries Array: A dense list of (hash, key, value) tuples.

This is why d = {"a": 1, "b": 2} remembers that "a" came before "b". It's not just a side effect anymore; it's a language guarantee.

Accessing Patterns: Safe vs Unsafe

The most common error in beginner Python code is KeyError. This happens when you assume data exists when it doesn't.

Avoiding KeyError Crashes
PYTHON
user_data = {"id": 4209, "name": "Rohit"}

# ❌ Unsafe: If 'email' is missing, the program CRASHES
# print(user_data["email"]) 
# Output: KeyError: 'email'

# ✅ Safe: Returns None if missing
email = user_data.get("email") 

# ✅ Safer: Returns a default value
role = user_data.get("role", "Guest")
print(f"Role: {role}")  # Output: Role: Guest

Merging Dictionaries (The Modern Way)

Merging configs or JSON responses is common. Python 3.9 gave us the beautiful Union Operator |.

PYTHON
default_config = {"theme": "dark", "notifications": True}
user_config = {"theme": "light"}

# The RIGHT side overwrites the LEFT side
final_config = default_config | user_config

print(final_config) 
# {'theme': 'light', 'notifications': True}
🕰️
Legacy Code: In older codebases, you will see {**d1, **d2}. This is the "dictionary unpacking" hack. It works, but | is cleaner.

Valid Keys: Hashability Rule

Just like Sets, Dictionary Keys must be immutable (hashable). Values can be anything.

PYTHON
# ✅ Valid
d = {
    (1, 2): "Coordinate",  # Tuple is immutable
    "name": "String"       # String is immutable
}

# ❌ Invalid
d = {
    [1, 2]: "List"         # List is mutable -> CRASH
}

Best Practices & Takeaways

✅ Do

  • Use .get() for optional keys.
  • Use .items() to loop over key-value pairs at once.
  • Use dict | dict to merge.

❌ Don't

  • Don't check if key in d: then access d[key]. Just use d.get()!
  • Don't modify a dict size while looping over it.

Next Steps

You now have the full toolset: Lists, Tuples, Sets, and Dicts. The next chapter explores how to control these structures with advanced flow logic.

Next: Chapter 8 - Control Flow →