Meaning
This generator expression yields (index, value) pairs for each truthy element in a collection, preserving the original order. It helps when you need to process items together with their positions while skipping falsy values. You reach for it when iterating over large sequences where memory efficiency and conditional filtering are required.
Primary Function
Data transformation
Communicative Purpose
Enables lazy iteration over indexed items while filtering out falsy values
Pattern
((index, value) for index, value in enumerate(collection) if value)
Core Structure
((... ) for ... in enumerate(... ) if ...)
Função primária
Data transformation
Propósito comunicativo
Enables lazy iteration over indexed items while filtering out falsy values
Situações de gatilho
Data processing: filtering out empty strings from a list of user inputs; Performance-critical code: iterating over large datasets without materializing intermediate lists; Functional pipelines: feeding indexed pairs into downstream generators
Contextos
Python data pipelines, ETL scripts, analytics notebooks, web scrapers handling optional fields
Padrão
((index, value) for index, value in enumerate(collection) if value)
Estrutura central
((... ) for ... in enumerate(... ) if ...)
Slots de substituição
index: int ≥ 0; value: any object; collection: iterable
Colocados típicos
- enumerate
- if condition
- generator expression
Substituições comuns
- list comprehension `[ (i
- v) for i
- v in enumerate(items) if v ]` – eager evaluation
- using `filter` with `enumerate` – less readable but explicit
Erros comuns
Using `enumerate` on a non-iterable → TypeError; forgetting parentheses around the tuple, resulting in only the index being yielded; filtering with `if value` when legitimate falsy values like 0 should be kept → unintended omission of valid items
Similar / contraste
List comprehension builds a full list in memory, whereas this generator expression is lazy and memory-efficient
Interferências
Coming from JavaScript: assuming `for (i, v) of enumerate(items)` works — Python requires `for i, v in enumerate(items)` and uses a generator expression for laziness
Família do chunk
- generator expressions
- enumerate usage
- lazy filtering
Nuance
1) Do not use when you need random access to the generated pairs after creation; 2) Lazy evaluation saves memory but may defer exceptions until iteration; 3) If the collection is empty, the generator yields nothing, so downstream code must handle an empty sequence
Efeito pragmático
Allows processing of large indexed datasets with minimal memory overhead while automatically skipping irrelevant entries
Dica de memória
Think of a filtered index of a bookshelf: you list only the books that are actually present, together with their shelf numbers.
Nota
Generator expressions are evaluated lazily; any side effects in the iterable or condition occur during iteration, not at definition time
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