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Module 3
Write Fluent Loops: Iteration Idioms and Comprehensions
1
Iterate Directly, Iterate Safely
Replace `range(len(...))` with direct iteration (`for item in xs`) for improved readability and safety.
Iterating with `enumerate()` and `zip()`
Use `enumerate()` for index-and-value access and `zip()` for parallel iteration over multiple sequences.
3
Iteration Control with `reversed()` and `sorted()`
Use `reversed()` and `sorted()` to control iteration order without manual indexing or modifying the original collection.
4
Mastering Comprehensions for Concise Collections
Write list, set, and dict comprehensions to replace verbose collection-building loops.
5
Generator Expressions for Memory-Efficient Data Processing
Use generator expressions `(x for x in ...)` for lazy, memory-efficient processing of large datasets.
Built-in Functions for Efficient Iteration
Use the built-in functions `sum()`, `any()`, `all()`, `min()`, and `max()` to replace manual accumulation and test loops.
7
Tuple Unpacking and Multiple Assignment
Apply tuple unpacking and multiple assignment for readable variable binding and atomic swaps.
Unpacking Sequences with Starred Assignment
Apply starred unpacking (`first, *rest, last`) for variable-length sequence destructuring in assignments.
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Master Python's Data Model: Make Your Objects Feel Native
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Advanced Iteration: `itertools` and Expression Power