Python Dictionaries

Overview

Dictionaries (dict) store key-value pairs with O(1) average lookup time. Keys must be hashable (strings, numbers, tuples of hashables). Dicts preserve insertion order as of Python 3.7+ and are ideal for records, caches, and configuration.

Syntax / Usage

# Create
user = {"name": "Ada", "role": "engineer", "active": True}
empty = {}
from_keys = dict.fromkeys(["a", "b"], 0)

# Access and update
user["name"]           # "Ada"
user.get("email", "n/a")  # safe default
user["email"] = "ada@example.com"

# Iterate
for key in user:
    print(key, user[key])

for key, value in user.items():
    print(key, value)

# Merge (Python 3.9+)
defaults = {"theme": "dark"}
prefs = {"lang": "en"}
merged = defaults | prefs

Examples

Count word frequency in a sentence:

sentence = "the cat sat on the mat"
counts = {}
for word in sentence.split():
    counts[word] = counts.get(word, 0) + 1
# {'the': 2, 'cat': 1, 'sat': 1, 'on': 1, 'mat': 1}

Build a lookup table from a list of records:

users = [{"id": 1, "name": "Ada"}, {"id": 2, "name": "Guido"}]
by_id = {u["id"]: u for u in users}
by_id[1]["name"]  # "Ada"

Common Mistakes

• Using mutable types (lists) as dict keys
• Assuming dict[key] returns None for missing keys—it raises KeyError
• Relying on order before Python 3.7 in older codebases
• Shallow copying nested dicts when a deep copy is needed

See Also

python-tuples python-sets python-list-comprehension