while retry_count < max_retries: try: operation() break except TemporaryError: retry_count += 1
Iteration Patterns

Meaning

This snippet implements a retry loop that repeatedly calls an operation until it succeeds or a maximum number of attempts is reached. It addresses the pain point of transient failures that can be resolved by retrying the operation. It is triggered when an operation may raise a TemporaryError and you want to limit the number of retries.

Primary Function

Error handling

Communicative Purpose

Ensures that a transient operation is retried up to a limit, aborting on success and giving up after the maximum attempts.

Pattern

while attempt < max_attempts: try: func() break except TemporaryError: attempt += 1

Core Structure

while ... < ...: try: ...() break except ...: ... += 1

Função primária

Error handling

Propósito comunicativo

Ensures that a transient operation is retried up to a limit, aborting on success and giving up after the maximum attempts.

Situações de gatilho

Network request: calling an API that may intermittently fail with TemporaryError; File I/O: reading from a flaky storage device that raises TemporaryError; Database transaction: executing a query that may temporarily lock

Contextos

Python scripts, command‑line tools, services interacting with unreliable external resources, libraries that need retry logic

Padrão

while attempt < max_attempts: try: func() break except TemporaryError: attempt += 1

Estrutura central

while ... < ...: try: ...() break except ...: ... += 1

Slots de substituição

attempt: int ≥ 0; max_attempts: int > 0; func: callable; exception: Exception subclass; increment: int (usually 1)

Colocados típicos

  • time.sleep()
  • logging.warning()
  • exponential backoff
  • retry decorator

Substituições comuns

  • Use a for loop with range(max_attempts) instead of while – simpler but less flexible
  • Wrap retry logic in a decorator (e.g.
  • tenacity) – reusable but adds a dependency
  • Add delay between retries with time.sleep – reduces load but increases latency

Erros comuns

Forgetting to increment the counter → infinite loop; Catching a broad Exception instead of TemporaryError → masks other errors; Placing break outside the try block → loop exits after first iteration regardless of success; Not resetting the counter when reusing the loop in a function → unexpected early termination

Similar / contraste

while‑retry loop vs for‑range retry – for is more concise; manual retry loop vs tenacity.retry decorator – decorator abstracts logic

Interferências

Coming from JavaScript: assuming you can catch errors with try/catch without specifying the error type → Python requires an explicit exception class

Família do chunk

  • retry pattern
  • exception handling loop
  • backoff strategies

Nuance

Do not use when the operation already has built‑in retry logic (e.g., requests library with retries) – redundant; Each retry adds latency and can block the thread, so keep max_attempts low for time‑critical code; If max_attempts is set to 0 the loop never runs, which may hide the operation entirely

Efeito pragmático

Provides resilience against transient failures, preventing crashes and reducing the need for manual error checks throughout the codebase

Dica de memória

A retry loop is like a persistent doorbell that keeps ringing until someone answers, but stops after a set number of rings

Nota

Make sure TemporaryError is defined or imported from the appropriate module; otherwise the except clause will raise a NameError

Upgrade path

Replace the manual retry loop with a retry decorator (e.g., tenacity) that provides configurable backoff, jitter, and retry conditions.

Frequência: HighFormulaicidade: Semi-fixedTipo de construção: loop with exception handlingPrioridade de aquisição: Active recallPrioridade de output: BothTag de espaçamento: Immediate

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