structlog

Structured logging library for Python that makes logging output consistent, processable, and observable. Provides a processor pipeline for enriching log events (timestamp, request ID, user context), supports JSON output for log aggregation, context management via bound loggers, and async support. More powerful than loguru for complex structured logging needs in production services.

Evaluated Mar 06, 2026 (0d ago) v24.x
Homepage ↗ Repo ↗ Developer Tools structlog python structured-logging json-logging observability async processors
⚙ Agent Friendliness
68
/ 100
Can an agent use this?
🔒 Security
96
/ 100
Is it safe for agents?
⚡ Reliability
91
/ 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
92
Secret Handling
88

MIT licensed. Structured logging — avoid including sensitive data in log events. Use custom processors to redact sensitive fields.

⚡ Reliability

Uptime/SLA
100
Version Stability
90
Breaking Changes
85
Error Recovery
90
AF Security Reliability

Best When

You're building a production Python service where consistent structured JSON logging with context binding and custom processor pipelines matters for observability.

Avoid When

You want simple, beautiful logging with minimal configuration — use loguru instead. Structlog's power comes with configuration complexity.

Use Cases

  • Add consistent structured JSON logging to Python agent services with automatic context propagation
  • Bind request-scoped metadata (request_id, user_id, trace_id) to agent loggers for correlated logging
  • Build processor pipelines that enrich all log events with service metadata before JSON output
  • Integrate with Python stdlib logging to capture third-party library logs in structured format
  • Implement OpenTelemetry-compatible trace context injection into log events for distributed tracing

Not For

  • Simple logging for scripts — Python's stdlib logging or loguru is simpler for basic use cases
  • Applications where developer experience matters more than structure — loguru has a much simpler API
  • Projects avoiding configuration complexity — structlog requires explicit processor configuration for production setup

Interface

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

Authentication

Methods: none
OAuth: No Scopes: No

Local library — no authentication required. MIT licensed.

Pricing

Model: open_source
Free tier: Yes
Requires CC: No

MIT licensed. Zero cost.

Agent Metadata

Pagination
none
Idempotent
Full
Retry Guidance
Not documented

Known Gotchas

  • Must configure structlog before use — structlog.configure(processors=[...]) sets global pipeline; do this once at app startup before any logging
  • Bound loggers: log = structlog.get_logger().bind(request_id='123') creates logger with bound context — all subsequent log calls include request_id automatically
  • Async support: use structlog.stdlib.AsyncBoundLogger or structlog.contextvars for asyncio context propagation — standard bound loggers aren't async-context-aware
  • Stdlib integration: structlog.stdlib.add_log_level, add_logger_name processors bridge to Python's logging module — needed to capture third-party library logs
  • Development vs production config differs significantly — dev: ConsoleRenderer with colors; prod: JSONRenderer with timestamps and structured fields
  • structlog.contextvars.bind_contextvars(request_id=req_id) for request-scoped context in async code — automatically cleared per contextvars context

Alternatives

Full Evaluation Report

Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for structlog.

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

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