Python Dictionaries: Key-Value Pairs for Efficient Data Storage

Python programming tutorial

Python Dictionaries: Key-Value Pairs for Efficient Data Storage

Beginner

Dictionaries are Python's built-in, unordered, mutable, and indexed data structures. They store data in key-value pairs, offering fast lookups.

Core Concept

A dictionary uses unique keys to access associated values. Keys must be immutable types (strings, numbers, tuples), while values can be of any data type.

Basic Example

Basics.py 

# Creating a dictionary
student = {
    "name": "Alice",
    "age": 20,
    "major": "Computer Science"
}

# Accessing values
print(student["name"])
print(student.get("age"))

# Adding a new key-value pair
student["gpa"] = 3.8
print(student)

# Modifying a value
student["age"] = 21
print(student)

How It Works

Dictionaries use a hash table internally. When you access an item, Python hashes the key to quickly find its corresponding value. This makes retrieval O(1) on average.

Advanced Example

advance.py 

# Dictionary comprehension
squares = {x: x**2 for x in range(1, 6)}
print(squares)

# Iterating through a dictionary
for key, value in student.items():
    print(f"{key}: {value}")

# Nested dictionaries
employee_data = {
    "emp1": {"name": "Bob", "dept": "IT"},
    "emp2": {"name": "Charlie", "dept": "HR"}
}
print(employee_data["emp1"]["name"])

Common Use Cases

  • Representing structured data (e.g., JSON objects).
  • Storing configurations or settings.
  • Implementing caches for fast data retrieval.
  • Counting frequencies of items.

Common Pitfalls

  • Trying to use mutable types (like lists) as keys.
  • Accessing a non-existent key without using `.get()` or checking first (results in `KeyError`).
  • Forgetting that dictionaries are unordered in older Python versions (Python 3.7+ preserves insertion order).

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Python Structural Pattern Matching: The `match` Statement

FAQs

Q: What's the difference between a dictionary and a list?
A: Lists are ordered sequences accessed by integer indices, while dictionaries are unordered collections accessed by unique keys.

Q: Can dictionary values be complex data types?
A: Yes, values can be any Python object, including lists, tuples, and even other dictionaries.

Q: How do I check if a key exists in a dictionary?
A: Use the `in` operator (e.g., 'key' in my_dict) or the `.get()` method which returns `None` if the key is not found.

Conclusion

Dictionaries are indispensable for efficient data handling in Python, providing a flexible way to organize and retrieve information using descriptive keys.

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