backoff (Python)

Python library for adding retry behavior with exponential backoff, full jitter, and custom wait strategies to functions using decorators. Simple API: @backoff.on_exception(backoff.expo, requests.exceptions.RequestException, max_tries=8) wraps any function with configurable retry logic. Supports sync and async functions, custom predicates, and retry hooks.

Evaluated Mar 06, 2026 (0d ago) v2.x
Homepage ↗ Repo ↗ Developer Tools python retry backoff exponential-backoff decorator resilience rate-limiting api-calls
⚙ Agent Friendliness
68
/ 100
Can an agent use this?
🔒 Security
96
/ 100
Is it safe for agents?
⚡ Reliability
88
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
--
Documentation
88
Error Messages
82
Auth Simplicity
100
Rate Limits
100

🔒 Security

TLS Enforcement
100
Auth Strength
100
Scope Granularity
100
Dep. Hygiene
90
Secret Handling
88

Retry library — no network access. Ensure retried operations don't leak credentials in exception messages.

⚡ Reliability

Uptime/SLA
90
Version Stability
88
Breaking Changes
85
Error Recovery
90
AF Security Reliability

Best When

Adding retry logic to Python API clients with minimal code — one decorator line vs manual retry loops.

Avoid When

You need circuit breakers, bulkheads, or complex resilience patterns — use a full resilience library.

Use Cases

  • Add exponential backoff retries to HTTP API calls that may receive 429 or 503 responses
  • Implement retry logic for database connections or queries that may fail transiently
  • Retry AWS/GCP API calls that hit rate limits with configurable jitter to avoid thundering herd
  • Add conditional retry with @backoff.on_predicate to retry based on return value (not just exceptions)
  • Implement async retry loops for aiohttp or httpx API calls with backoff.on_exception on async functions

Not For

  • Complex retry workflows needing circuit breakers — use pybreaker or resilience4py for circuit breaker patterns
  • Production service-level retry policies — Kubernetes, service meshes (Istio), or load balancers handle infra-level retries better
  • Non-Python languages — language-specific retry libraries exist for Go (retry-go), Rust (backoff), etc.

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
No
SDK
Yes
Webhooks
No

Authentication

Methods: none
OAuth: No Scopes: No

Pure Python library — no auth needed.

Pricing

Model: open_source
Free tier: Yes
Requires CC: No

MIT licensed open source library.

Agent Metadata

Pagination
none
Idempotent
Partial
Retry Guidance
Documented

Known Gotchas

  • backoff retries ALL matching exceptions — ensure only retriable exceptions are listed; retrying non-retriable errors (401 auth) wastes time
  • The decorator wraps the function permanently — all calls to the decorated function will retry; create separate retrying/non-retrying versions if needed
  • max_time is wall clock time from first call, not per-retry timeout — a long first attempt counts against max_time
  • on_backoff and on_giveup hooks receive a details dict with tries, elapsed, wait — use these for logging without modifying retry behavior
  • jitter=backoff.full_jitter is recommended for distributed systems to prevent thundering herd — default behavior may synchronize retries
  • async support requires async decorated functions — backoff detects async functions automatically but mixing sync/async in the same decorator causes issues

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Scores are editorial opinions as of 2026-03-06.

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Packages Evaluated
26151
Need Evaluation
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