Python's Core Structures
Python includes several built-in data structures: lists, dictionaries, sets, and tuples. These structures are flexible, allowing dynamic data storage and manipulation right out of the box.
Lists: More Than Arrays
Python lists are not mere arrays; they are dynamic arrays that can store mixed types. They maintain order, support nested structures, and offer methods for powerful list comprehensions.
Dictionaries: Unordered Collections
Before Python 3.7, dictionaries were unordered. Now, they maintain insertion order. Their underlying implementation uses a hash table, providing O(1) average complexity for lookups.
Sets: Distinct Elements
Python sets store unique elements and are backed by a hashtable. They offer efficient membership testing and are optimized for operations like union, intersection, and difference.
Tuples: Immutable Sequences
Tuples are immutable lists. They can be used as keys in dictionaries or as elements in sets. Their immutability makes them reliable as constant collections of items.
List Comprehensions: Elegant
List comprehensions provide a concise way to create lists. The syntax mirrors natural language, allowing for readable and efficient one-liners that replace multi-line for-loops.
Generators: On-Demand Iteration
Generators yield items one at a time, using the 'yield' keyword. They are memory-efficient because they generate items on-the-fly rather than storing an entire collection in memory at once.
Which Python structure maintains insertion order?
Sets with hashtable backing
Dictionaries since Python 3.7
Lists as dynamic arrays
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