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Module 5
Choose the Right Tool: Mastering Python's Containers
1
Choosing the Right Data Structure
Choose between list, tuple, set, and dict based on semantics (order, uniqueness, immutability) and performance.
2
Counting with `collections.Counter`
Use `collections.Counter` to replace manual logic for counting hashable objects.
Grouping with `defaultdict`
Use `collections.defaultdict` to simplify the logic for grouping items into collections.
4
`deque` for Stacks and Queues
Use `collections.deque` for efficient, thread-safe appends and pops from both ends (stacks and queues).
5
Creating Immutable Data Classes with `@dataclass`
Define clean record types using `@dataclass` with `frozen`, default values, and `__post_init__` validation.
6
`NamedTuple` vs. `@dataclass`: Choosing the Right Data Structure
Choose between `NamedTuple` (for immutable, tuple-like public APIs) and `@dataclass` (for flexible, mutable objects).
7
Mastering Modern Dictionary Operations
Use modern dictionary idioms: views, `.get()`, `.setdefault()`, and merging with `|` or `{**a, **b}`.
Optimizing Collections with `heapq` and `bisect`
Apply specialized containers like `heapq` for priority queues and `bisect` for maintaining sorted lists.
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Advanced Iteration: `itertools` and Expression Power
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Design Elegant Functions: Closures, Decorators, and APIs