PYTHON
Creating Dictionaries with Comprehensions
Efficiently create and transform dictionaries in Python using concise dictionary comprehensions, perfect for processing data and API responses.
# Example 1: Creating a dictionary from a list of items
items = ['apple', 'banana', 'cherry']
item_prices = {item: len(item) * 1.5 for item in items}
# item_prices will be {'apple': 7.5, 'banana': 9.0, 'cherry': 9.0}
# Example 2: Filtering and transforming an existing dictionary
stock_data = {'apple': 100, 'banana': 0, 'orange': 50, 'grape': 200}
available_stock = {fruit: quantity for fruit, quantity in stock_data.items() if quantity > 0}
# available_stock will be {'apple': 100, 'orange': 50, 'grape': 200}
# Example 3: Reversing keys and values (if values are hashable)
status_codes = {200: 'OK', 404: 'Not Found', 500: 'Internal Server Error'}
code_names = {name: code for code, name in status_codes.items()}
# code_names will be {'OK': 200, 'Not Found': 404, 'Internal Server Error': 500}
How it works: Dictionary comprehensions provide a clean and efficient way to create new dictionaries or transform existing ones. They follow the structure `{key_expression: value_expression for item in iterable if condition}`. This syntax is highly readable and performs better than traditional loop-based dictionary construction, making it ideal for data manipulation tasks common in web development, such as processing API payloads or generating structured responses.