{k: v*2 for k, v in my_dict.items()}
Built-in Data Structures

Meaning

This chunk creates a new dictionary by iterating over each key‑value pair of an existing dictionary and multiplying each value by two. It provides a concise way to transform all values while preserving the original keys. It is triggered when you need a derived mapping with modified values without writing an explicit loop.

Primary Function

Data transformation

Communicative Purpose

Enables rapid transformation of dictionary values by applying a uniform operation

Pattern

{key: value * 2 for key, value in source_dict.items()}

Core Structure

{...: ... * 2 for ..., ... in ... .items()}

Função primária

Data transformation

Propósito comunicativo

Enables rapid transformation of dictionary values by applying a uniform operation

Situações de gatilho

Data processing: need to double numeric values in a mapping; Configuration handling: adjust thresholds in a settings dict; Analytics: scale metric values stored in a dict

Contextos

General Python codebases, data‑science scripts, web back‑ends, configuration management modules

Padrão

{key: value * 2 for key, value in source_dict.items()}

Estrutura central

{...: ... * 2 for ..., ... in ... .items()}

Slots de substituição

key: hashable, value: any, source_dict: dict of key to value

Colocados típicos

  • for ... in ...
  • .items()
  • dict comprehension
  • multiplication operator

Substituições comuns

  • use a for‑loop with dict assignment → more verbose
  • use dict.update with a generator expression → similar result but less readable

Erros comuns

Using `*` on non‑numeric values → TypeError; forgetting `.items()` and iterating over keys only → only keys processed; reusing same variable names causing shadowing → unexpected results; omitting colon after key → SyntaxError

Similar / contraste

list comprehension (produces a list, not a dict); set comprehension (creates a set); dict.update (mutates existing dict); map function (returns iterator, not a dict)

Interferências

Coming from JavaScript: may try to use `Object.entries` with a for‑of loop → Python uses `.items()` instead

Família do chunk

  • list comprehension
  • set comprehension
  • dict merging
  • dict update

Nuance

Do not use when values are non‑numeric or when you need to keep the original dict unchanged; creates a new dict in O(n) time and memory, preserving key order as of Python 3.7; large dictionaries may increase memory pressure

Efeito pragmático

Allows concise, readable transformation of all dictionary values, reducing boilerplate and potential bugs

Dica de memória

Dictionary comprehension: like a factory that takes each raw ingredient (key, value) and outputs a packaged product (key, doubled value).

Nota

The comprehension evaluates each expression eagerly; for very large dictionaries consider generator‑based approaches to limit memory usage

Upgrade path

nested dictionary comprehension for transforming nested mappings

Frequência: HighFormulaicidade: Semi-fixedTipo de construção: code_patternPrioridade de aquisição: Active recallPrioridade de output: BothTag de espaçamento: Immediate

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